system

Abstract

Provide a system. 【Solution means】Means for receiving user information, Means for storing the user information in a database, Means for processing payments based on the stored user information, Means for notifying the user of the payment result, Means for analyzing the user's expenditure data, Means for notifying the user of the analysis result, Means for generating personalized promotions, Means for providing the generated promotions to the user A system including.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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] Modern diverse payment methods and the accompanying complex payment management are burdensome for many users. In particular, it is difficult to track and effectively manage expenditures when using different settlement methods. Also, it is not easy for users to efficiently manage their budgets by leveraging their individual payment histories and expenditure data. Furthermore, the provision of personalized promotions based on users' purchase histories and preferences has not been adequately addressed in conventional systems. There is a need to provide a smart payment assistant to solve such problems and improve users' payment management and marketing effects.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system including the following components: means for receiving user information and storing it in a database; means for processing payments using a payment API based on the stored user information; means for notifying the user of the payment results; means for analyzing the user's spending data and managing it as a budget; and means for generating alerts when the budget is exceeded. Furthermore, this system includes means for notifying the user of the analysis results, and for generating and providing personalized promotions based on the user's purchase history and preferences. With such a configuration, it is possible to streamline the management of user payments and improve the effectiveness of personalized marketing.

[0006] "User information" refers to information that includes user identification and related attribute data.

[0007] A "database" is a structured data storage system for efficiently storing, managing, and retrieving information.

[0008] "Payment processing" is the process of executing the necessary monetary transactions as payment for a purchase or service.

[0009] A "payment API" is an application programming interface for executing payment processing in conjunction with external services.

[0010] "Payment result" refers to the status of whether the payment processing was successful or unsuccessful, along with any related details.

[0011] "Expenditure data" refers to data that includes information about purchases and payments made by users.

[0012] "Analysis" is the process of organizing data to derive insights, patterns, and conclusions.

[0013] "Budget management" is a means of balancing income and expenses and planning and controlling economic activities.

[0014] An "alert" is a message or signal used to notify a user when certain conditions are met.

[0015] "Personalized promotions" are marketing offers and discounts that are individually customized based on a user's purchase history and preferences.

[0016] "Purchase history" refers to a record of purchases and payments made by a user in the past. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

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

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

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

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0032] 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.

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

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[0039] System configuration and operation

[0040] This system includes the following main components:

[0041] 1. Receiving and storing user information

[0042] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[0043] Specific example: For instance, when a new user signs up for an app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[0044] 2. Payment Processing

[0045] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[0046] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[0047] 3. Analysis of expenditure data and budget management

[0048] The server retrieves the user's past spending data from the database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[0049] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[0050] 4. Payment-related notices

[0051] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[0052] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[0053] 5. Providing personalized promotions

[0054] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[0055] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[0056] These features allow users to efficiently manage their payments and receive personalized promotions. This system is a powerful tool for optimizing the user experience and improving marketing effectiveness.

[0057] The following describes the processing flow.

[0058] User registration process

[0059] Step 1:

[0060] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[0061] Step 2:

[0062] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[0063] Step 3:

[0064] The server executes an SQL query to extract user information from the received request and save it to the database.

[0065] Step 4:

[0066] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[0067] Step 5:

[0068] The server sends the generated response to the terminal.

[0069] Step 6:

[0070] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[0071] Payment processing flow

[0072] Step 1:

[0073] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or PayPay account information).

[0074] Step 2:

[0075] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[0076] Step 3:

[0077] The server extracts the received payment information and uses a payment API client to call an external payment API.

[0078] Step 4:

[0079] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[0080] Step 5:

[0081] The server sends the generated response to the terminal.

[0082] Step 6:

[0083] The terminal receives the response and notifies the user of the payment result.

[0084] Budget management and expenditure analysis process

[0085] Step 1:

[0086] The user accesses the budget management page to check their set budget and spending status.

[0087] Step 2:

[0088] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[0089] Step 3:

[0090] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[0091] Step 4:

[0092] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[0093] Step 5:

[0094] The server generates the budget analysis results as a response in JSON format.

[0095] Step 6:

[0096] The server sends the generated response to the terminal.

[0097] Step 7:

[0098] The device receives the response and displays the analysis results to the user.

[0099] Payment-related notification flow

[0100] Step 1:

[0101] Users set up payment reminders.

[0102] Step 2:

[0103] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[0104] Step 3:

[0105] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[0106] Step 4:

[0107] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[0108] Step 5:

[0109] The server creates the generated notification as a response in JSON format.

[0110] Step 6:

[0111] The server sends the generated response to the terminal.

[0112] Step 7:

[0113] The device receives the response and displays a notification to the user.

[0114] Personalized promotion delivery process

[0115] Step 1:

[0116] Users can set up their preferences to receive personalized promotional information.

[0117] Step 2:

[0118] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[0119] Step 3:

[0120] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[0121] Step 4:

[0122] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[0123] Step 5:

[0124] The server generates the generated promotion as a response in JSON format.

[0125] Step 6:

[0126] The server sends the generated response to the terminal.

[0127] Step 7:

[0128] The device receives the response and displays promotional information to the user.

[0129] The above outlines the specific process flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, and personalized promotional offerings.

[0130] (Example 1)

[0131] 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."

[0132] In today's consumer lifestyle, efficiently managing multiple payments and personalized marketing is extremely difficult. This leads to problems such as missed payments and budget overruns for users, and makes it challenging for businesses to accurately capture user purchasing preferences through marketing. There is a need for systems that can address these challenges.

[0133] 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.

[0134] In this invention, the server includes means for receiving user information, means for storing it in a database, means for processing payments, means for notifying payment results, means for collecting spending data, means for analyzing data, means for notifying analysis results, means for generating personalized promotions, means for providing promotions, means for comparing spending data with a budget and generating alerts if there is a possibility of budget overrun, and means for periodically generating payment reminders and unpaid notifications. This enables users to efficiently manage their payments and allows companies to conduct personalized marketing to users.

[0135] "User information" refers to personally identifiable information such as the user's name, email address, and password.

[0136] A "database" refers to a system used to structure and store user information, spending data, and other similar information.

[0137] "Payment processing" refers to the process of executing payment information received from users through external payment APIs.

[0138] "Payment result" refers to notification information indicating whether the payment process was successful or unsuccessful.

[0139] "Expenditure data" refers to information such as the amount and date of various purchases made by the user.

[0140] An "analysis algorithm" refers to a calculation method used to analyze a user's spending data to determine spending trends and the likelihood of budget overruns.

[0141] "Personalized promotions" refer to discount coupons and exclusive offers that are individually generated based on a user's purchase history and preference data.

[0142] An "alert" refers to a warning or notification issued to a user. For example, it could be a notification informing the user of a potential budget overrun.

[0143] A "payment reminder" refers to a notification that periodically informs the user of the payment deadline.

[0144] An "unpaid notice" refers to a notification informing the user that a specified payment has not yet been completed.

[0145] A "payment API" refers to a programmatic interface for processing payments in conjunction with external payment services.

[0146] "Budget" refers to the upper limit of expenses that a user should spend within a set period of time.

[0147] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[0148] System configuration and operation

[0149] This system includes the following main components:

[0150] 1. Receiving and storing user information

[0151] The terminal provides an interface for the user to enter registration information such as name, email address, and password. When the user enters the information and presses the "Register" button, the terminal sends this information to the server. The server stores the received user information in its database and notifies the terminal of the successful saving.

[0152] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, stores it in its database, and notifies the device that registration is complete.

[0153] 2. Payment Processing

[0154] When a user purchases a product, they enter payment information (credit card number, expiration date, security code, etc.) into the terminal. The terminal sends the payment information to the server. The server calls an external payment API to process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result via the terminal.

[0155] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[0156] 3. Analysis of expenditure data and budget management

[0157] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[0158] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if the budget is exceeded.

[0159] 4. Payment-related notices

[0160] The server collects information based on specific conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[0161] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when payment deadlines are approaching.

[0162] 5. Providing personalized promotions

[0163] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[0164] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[0165] This allows users to efficiently manage their payments and receive personalized, optimized promotions. The system becomes a powerful tool for optimizing the user experience and improving marketing effectiveness.

[0166] Example of a prompt

[0167] 1. "What information do new users need to sign up for the app?"

[0168] 2. "Please explain how to make a payment online using a credit card."

[0169] 3. "How can I set up budget management in the app and receive alerts when the budget is exceeded?"

[0170] 4. "Please explain how to set up recurring payment reminders."

[0171] 5. "How can we offer personalized promotions based on purchase history?"

[0172] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0173] Details of the processing steps

[0174] Step 1: Enter user information

[0175] The device displays a form for the user to enter their name, email address, and password.

[0176] Input: The user enters their name, email address, and password.

[0177] Output: The entered user information is stored on the device.

[0178] Specifically, the user opens the app and enters information into the displayed registration form.

[0179] Step 2: Sending Information

[0180] The terminal sends the entered information to the server.

[0181] Input: User information entered on the terminal.

[0182] Output: User information is sent to the server.

[0183] After the user completes the input and presses the "Register" button, the device sends the user information to the server.

[0184] Step 3: Saving Information

[0185] The server stores the received user information in a database.

[0186] Input: User information sent to the server.

[0187] Output: User information is saved to the database.

[0188] If the save is successful, the server sends a success message to the terminal.

[0189] Step 4: Enter payment information

[0190] The terminal provides an interface for the user to enter payment information.

[0191] Input: The user enters their payment information.

[0192] Output: The entered payment information is stored on the terminal.

[0193] Specifically, the user enters their credit card number and security code on the purchase screen.

[0194] Step 5: Submit payment information

[0195] The device sends payment information to the server.

[0196] Input: Payment information entered on the terminal.

[0197] Output: Payment information is sent to the server.

[0198] When the user presses the "Pay" button, the device sends the payment information to the server.

[0199] Step 6: Execute Payment

[0200] The server processes payments by calling an external payment API.

[0201] Input: Payment information sent to the server.

[0202] Output: Payment result from the payment API.

[0203] The server sends a payment request to the payment API and receives a response from the API.

[0204] Step 7: Notification of payment result

[0205] The server notifies the user of the payment result (success / failure) via the terminal.

[0206] Input: Payment result from the payment API.

[0207] Output: The payment result is notified to the device.

[0208] The server sends a message to the terminal indicating whether the payment was successful or failed, and displays it to the user.

[0209] Step 8: Collecting expenditure data

[0210] The server periodically retrieves user spending data from the database.

[0211] Input: Expense data stored in the database.

[0212] Output: The acquired expenditure data is aggregated on the server.

[0213] The server sets up scheduled tasks to periodically collect expenditure data from the database.

[0214] Step 9: Data Analysis

[0215] The server processes the spending data using an analysis algorithm to calculate the monthly spending situation.

[0216] Input: Aggregated expenditure data.

[0217] Output: Results of the analyzed spending situation.

[0218] The server runs an analysis algorithm to calculate monthly spending trends and abnormal spending.

[0219] Step 10: Check for budget overruns and generate alerts

[0220] The server compares the user's set budget with actual spending and checks for potential budget overruns. If a budget overrun is anticipated, the server generates an alert and notifies the user.

[0221] Input: Analysis results and user-defined budget.

[0222] Output: Alert notifications generated as needed.

[0223] Specifically, if there is a possibility of exceeding the budget at the end of the month, the server generates an alert message such as "You have exceeded your budget" and notifies the user.

[0224] Step 11: Generate payment-related notifications

[0225] The server generates payment reminders and non-payment notifications based on certain conditions.

[0226] Input: Payment due date data and outstanding payment data.

[0227] Output: Generated notification.

[0228] The server periodically generates and sends reminders based on the reminder conditions set by the user.

[0229] Step 12: Generate and notify personalized promotions

[0230] The server generates and notifies users of personalized promotions based on their purchase history and preference data.

[0231] Input: Purchase history data and preference data.

[0232] Output: Generated promotional notification.

[0233] Specifically, if a user frequently purchases products in a particular category, the server generates a discount promotion for those products and notifies the user.

[0234] (Application Example 1)

[0235] 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."

[0236] In modern society, many users struggle to efficiently manage multiple payments. Furthermore, insufficient tracking of expenses and budget management often leads to budget overruns. Additionally, effectively delivering personalized promotions to users remains a challenge. There is a need for a system that solves these problems, streamlining payment management while enhancing marketing effectiveness tailored to individual needs.

[0237] 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.

[0238] In this invention, the server includes means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of payment results, means for analyzing user spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for setting a budget and displaying monthly spending status in real time, means for generating alerts when the budget is exceeded, means for sending regular payment reminders and unpaid notifications to the user, and means for generating and providing discount coupons and limited offers based on purchase history. This enables users to efficiently manage their payments, prevent budget overruns, and receive promotions tailored to them.

[0239] "User information" refers to personal data provided by the user, such as name, email address, and payment information.

[0240] A "database" is a system for efficiently storing and managing data such as user information and payment history.

[0241] "Payment processing" refers to the process by which users complete payment using their payment information when purchasing goods or services.

[0242] "Notifications" are a means of communication used to inform users of payment results, budget overrun alerts, promotional information, and other relevant details.

[0243] "Expense data" refers to a record of payments a user has made in the past.

[0244] "Analysis" is the process of evaluating spending patterns and budget situations through users' spending data.

[0245] "Personalized promotions" refer to special offers and discounts generated based on a user's purchase history and preferences.

[0246] A "budget" is the maximum amount of money a user can spend within a certain period of time.

[0247] An "alert" is a notification that warns a user based on set conditions (e.g., exceeding the budget).

[0248] A "reminder" is a feature that periodically notifies users of payment deadlines or other important dates.

[0249] A "coupon" is a benefit that applies a discount when purchasing specific products or services.

[0250] A "limited offer" is a special deal that is offered to specific users for a limited time only.

[0251] This invention provides a system that streamlines user payment management and offers personalized promotions. The system's configuration and operation are described in detail below.

[0252] System Configuration

[0253] The system mainly consists of the following components:

[0254] 1. Receiving and storing user information

[0255] The device provides the interface, allowing the user to enter their name, email address, password, payment information, etc.

[0256] The server stores the received user information in a database.

[0257] 2. Payment Processing

[0258] When a user purchases a product, they enter their payment information into the device.

[0259] The server uses this payment information to call an external payment API and process the payment.

[0260] 3. Analysis of expenditure data and budget management

[0261] The server retrieves the user's past spending data from the database and uses an analysis algorithm to calculate the monthly spending pattern.

[0262] If a user has a budget set, the server will check for potential budget overruns and generate an alert.

[0263] 4. Payment-related notices

[0264] The server generates and sends periodic payment reminders and overdue payment notifications to the user.

[0265] 5. Providing personalized promotions

[0266] The server generates personalized promotions based on the user's purchase history and preference data, and notifies the user.

[0267] System operation

[0268] Receiving and storing user information

[0269] When a user signs up for the app, the device sends the entered information to the server. The server stores this information in a database and notifies the device that the saving was successful.

[0270] Payment processing

[0271] When a user purchases a product online, they enter their payment information and send it to the server via their device. The server calls an external payment API, executes the payment, and notifies the user of the result.

[0272] Analysis of expenditure data and budget management

[0273] The server analyzes the user's past spending data to calculate monthly spending and generates an alert if the set budget is exceeded. This analysis retrieves data from a database and applies a specific algorithm.

[0274] Payment-related notices

[0275] The server generates and sends regularly scheduled reminders and notifications when payment deadlines are approaching. This allows users to manage important payments without forgetting them.

[0276] Providing personalized promotions

[0277] The server generates and notifies users of personalized promotions, such as discount coupons and limited-time offers, based on their purchase history. These promotions are tailored to each user, improving marketing effectiveness.

[0278] Hardware and software to be used

[0279] Hardware: Smartphones, servers

[0280] Software: Flask (web framework), SQLite (database), external payment API

[0281] Specific example

[0282] For example, when a user newly registers for an app, enters their name, email address, password, and presses the registration button, data is sent from the terminal to the server. The server saves this data in the database and returns an appropriate notification to the user.

[0283] Also, when a user enters credit card information when purchasing a product, the server calls an external payment API and the payment is completed. The expenditure data is automatically recorded, and an alert for exceeding the budget is generated at the end of the month.

[0284] Examples of prompt sentences for the generated AI model

[0285] "I want to set a monthly budget. Can you tell me how to set the budget?"

[0286] "I want to know my spending situation this month. Please tell me how much I've spent."

[0287] "Are there any discount coupons available for my next purchase?"

[0288] In this way, the system of the present invention can improve the user experience by streamlining the user's payment management and providing personalized promotions.

[0289] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0290] Step 1:

[0291] Receiving and saving user information

[0292] The terminal receives name, email address, password, payment information, etc. from the user and sends that information to the server.

[0293] The server saves the received user information to the database. The input consists of personal data entered by the user, and data processing for saving to the database includes format conversion and validation. The output is a notification of successful saving.

[0294] Step 2:

[0295] Payment processing

[0296] When a user purchases goods online, they enter their payment information, which is then transmitted to the server via their device.

[0297] The server uses this payment information to convert the input data into a format suitable for sending to an external payment API. After this conversion and transmission process is complete, it receives the result (success / failure) from the payment API. The received result is processed by the server and notified to the user. Here, the input is the payment information and payment request, and the output is the payment result notification.

[0298] Step 3:

[0299] Analysis of expenditure data and budget management

[0300] The server retrieves the user's past spending data from the database.

[0301] Subsequently, a data analysis algorithm is applied to calculate monthly spending. This calculation aggregates past spending data and analyzes monthly spending patterns. As a result, the calculated spending status is output, and based on this, it is determined whether there is a possibility of budget overrun. The input is past spending data, and the output is spending status and budget overrun alerts.

[0302] Step 4:

[0303] Payment-related notices

[0304] The server generates regular payment reminders and unpaid notices and automatically sends them to users.

[0305] The inputs are the current date and the user's payment schedule data. Based on this, a list of unpaid amounts is generated with an SQL query, and reminder notifications are created based on that list and sent to the user. The output is reminder notifications.

[0306] Step 5:

[0307] Provision of personalized promotions

[0308] The server generates discount coupons and limited offers based on the user's purchase history and preference data.

[0309] The input is the user's past purchase data, which is analyzed to generate promotions for specific products. This promotion is sent to the user as a notification. The generated promotion includes appropriate discounts and offers based on the specified purchase history. The output is a personalized promotion.

[0310] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0311] The present invention combines an emotion engine that recognizes the user's emotions with a system that receives and stores user information, performs payment processing, expenditure analysis, budget management, and provides personalized promotions. This system can dynamically adjust the notification content and promotion content based on the user's emotions. Each processing step in this system will be described below.

[0312] System configuration and operation

[0313] This system includes the following main components:

[0314] 1. Receiving and storing user information

[0315] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[0316] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and press the register button. The device then sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[0317] 2. Payment Processing

[0318] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[0319] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[0320] 3. Analysis of expenditure data and budget management

[0321] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[0322] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[0323] 4. Payment-related notices

[0324] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[0325] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[0326] 5. Providing personalized promotions

[0327] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[0328] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[0329] 6. Integrating an emotion engine

[0330] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app.

[0331] The server receives emotion data sent from the terminal and analyzes the user's current emotional state.

[0332] Specific example: While a user is selecting products or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to a server. The server receives this data and, if the user is experiencing stress, displays a message to simplify the process.

[0333] 7. Adjusting notification content based on emotions

[0334] The server uses data from the emotion engine to adjust the content of the notifications it generates according to the user's emotional state. For example, if the user is feeling stressed, it will generate a more concise and easy-to-understand notification.

[0335] Specific example: If a user fails to make a payment, and the emotion engine recognizes the user's stress or anxiety, the server will send a gentle message such as, "Something went wrong. Please try again."

[0336] 8. Adjusting promotional content based on emotions

[0337] The server adjusts personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases.

[0338] Specific example: If the sentiment engine confirms that the user was satisfied with a previously purchased item, the server will send a discount coupon for a related product.

[0339] This system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the delivery of highly personalized services.

[0340] The following describes the processing flow.

[0341] User registration process

[0342] Step 1:

[0343] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[0344] Step 2:

[0345] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[0346] Step 3:

[0347] The server executes an SQL query to extract user information from the received request and save it to the database.

[0348] Step 4:

[0349] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[0350] Step 5:

[0351] The server sends the generated response to the terminal.

[0352] Step 6:

[0353] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[0354] Payment processing flow

[0355] Step 1:

[0356] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or payment account information).

[0357] Step 2:

[0358] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[0359] Step 3:

[0360] The server extracts the received payment information and uses a payment API client to call an external payment API.

[0361] Step 4:

[0362] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[0363] Step 5:

[0364] The server sends the generated response to the terminal.

[0365] Step 6:

[0366] The terminal receives the response and notifies the user of the payment result.

[0367] Budget management and expenditure analysis process

[0368] Step 1:

[0369] The user accesses the budget management page to check their set budget and spending status.

[0370] Step 2:

[0371] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[0372] Step 3:

[0373] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[0374] Step 4:

[0375] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[0376] Step 5:

[0377] The server generates the budget analysis results as a response in JSON format.

[0378] Step 6:

[0379] The server sends the generated response to the terminal.

[0380] Step 7:

[0381] The device receives the response and displays the analysis results to the user.

[0382] Payment-related notification flow

[0383] Step 1:

[0384] Users set up payment reminders.

[0385] Step 2:

[0386] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[0387] Step 3:

[0388] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[0389] Step 4:

[0390] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[0391] Step 5:

[0392] The server creates the generated notification as a response in JSON format.

[0393] Step 6:

[0394] The server sends the generated response to the terminal.

[0395] Step 7:

[0396] The device receives the response and displays a notification to the user.

[0397] Personalized promotion delivery process

[0398] Step 1:

[0399] Users can set up their preferences to receive personalized promotional information.

[0400] Step 2:

[0401] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[0402] Step 3:

[0403] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[0404] Step 4:

[0405] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[0406] Step 5:

[0407] The server generates the generated promotion as a response in JSON format.

[0408] Step 6:

[0409] The server sends the generated response to the terminal.

[0410] Step 7:

[0411] The device receives the response and displays promotional information to the user.

[0412] The process of integrating and utilizing an emotional engine

[0413] The flow of emotion recognition

[0414] Step 1:

[0415] While the user is using the app, the device's camera captures the user's facial expressions.

[0416] Step 2:

[0417] The device sends captured facial expression data to an emotion engine, which then analyzes the user's emotions.

[0418] Step 3:

[0419] The device sends the analyzed emotion data to the server.

[0420] Adjusting notifications based on emotions

[0421] Step 1:

[0422] The server adjusts the content of the notifications it generates based on the received emotion data, according to the user's emotional state.

[0423] Step 2:

[0424] The server generates the adjusted notification content as a response in JSON format.

[0425] Step 3:

[0426] The server sends the generated response to the terminal.

[0427] Step 4:

[0428] The device receives the response and displays a tailored notification to the user.

[0429] Emotion-based promotion adjustments

[0430] Step 1:

[0431] The server adjusts the promotional content it generates based on the received sentiment data, according to the user's emotional state.

[0432] Step 2:

[0433] The server generates the adjusted promotional content as a response in JSON format.

[0434] Step 3:

[0435] The server sends the generated response to the terminal.

[0436] Step 4:

[0437] The device receives the response and displays the adjusted promotional information to the user.

[0438] The above outlines the specific processing flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, personalized promotional offerings, and the integration of an emotion engine.

[0439] (Example 2)

[0440] 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".

[0441] The objective of this invention is to improve the user experience by streamlining user payment processing and expenditure management while providing flexible responses tailored to user emotions. Specifically, it is required to detect user emotions in real time, adjust notification and promotional content based on those emotions, and provide a more personalized service.

[0442] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0443] In this invention, the server includes means for receiving user information, means for storing the user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment results, means for analyzing the user's spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for detecting the user's emotions using a terminal, means for transmitting the emotion data to the server and analyzing the emotional state, means for adjusting notification content based on the emotional state, and means for adjusting promotion content based on the emotional state. This makes it possible to provide personalized services based on the user's emotions.

[0444] "User information" refers to information such as name, email address, and password that identifies an individual user and is used for authentication and service provision.

[0445] A "database" is a collection of electronically stored data used to efficiently manage user information and spending data.

[0446] "Payment processing" refers to the process of settling payments when a user purchases goods or services, and includes the use of credit card information and external payment APIs.

[0447] "Notifications" refer to information such as messages and alerts sent from the system to the user, including important information such as payment results and budget overruns.

[0448] "Expenditure data" refers to information about amounts and items recorded by users regarding purchases and payments, and is used for budget management and expenditure analysis.

[0449] An "analysis algorithm" is a means of identifying and evaluating specific patterns and trends in data, and is used in the analysis of user spending data.

[0450] A "personalized promotion" is a promotion that provides individual users with benefits and discounts optimized for them, based on their purchase history and preference data.

[0451] A "terminal" is a device used by a user for input and operation, and includes smartphones, personal computers, and other similar devices.

[0452] An "emotion engine" is a system that uses user input data and facial recognition to detect and analyze a user's emotional state.

[0453] "Emotional data" refers to data that indicates a user's emotional state, collected from facial expressions, words, actions, etc., and used for analysis.

[0454] "Adjusting notification content" refers to the process of changing the content and wording of notification messages according to the user's emotional state.

[0455] "Adjusting promotional content" refers to the process of changing the content and benefits of promotional information provided based on users' emotional states and preference data.

[0456] This invention combines a system that receives and stores user information, processes payments, analyzes spending, manages budgets, and provides personalized promotions with an emotion engine that recognizes user emotions. This system can dynamically adjust notification and promotional content based on user emotions. Specific embodiments of this system are described below.

[0457] System Overview

[0458] This system is mainly composed of the following key components:

[0459] Receiving and storing user information

[0460] Payment processing

[0461] Analysis of expenditure data and budget management

[0462] Payment-related notices

[0463] Providing personalized promotions

[0464] Embedding an emotion engine

[0465] Emotion-based notification adjustments

[0466] Adjusting promotional content based on emotions

[0467] Receiving and storing user information

[0468] The terminal provides an interface for users to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving. For example, when a new user enters their name, email address, and password and presses the registration button, the terminal sends that data to the server. The server receives this data, stores it in its database, and displays a registration completion message.

[0469] Payment processing

[0470] When a user purchases a product, they enter their payment information into a terminal. The terminal sends this payment information to a server. The server uses this information to call an external payment API and process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result. For example, when a user purchases a product online, they enter their credit card information and press the payment button, sending that information to the server. The server calls an external payment API to execute the payment and notifies the user of the result.

[0471] Analysis of expenditure data and budget management

[0472] The server retrieves the user's past spending data from a database and uses an analysis algorithm to calculate monthly spending. If the user has set a budget, the server checks for potential budget overruns and generates an alert. For example, if a user sets their own budget within the app and wants to track their monthly spending, the server aggregates the spending data at the end of the month and generates an alert to notify the user if the budget has been exceeded.

[0473] Payment-related notices

[0474] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and overdue payment notices. Specifically, if a user sets up periodic reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[0475] Providing personalized promotions

[0476] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server notifies the user of the generated promotions. For example, if a user frequently purchases products in a particular category, the server will generate and notify the user of discount promotions for products in that category.

[0477] Embedding an emotion engine

[0478] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app. The server receives the emotion data sent from the device and analyzes the user's current emotional state. For example, while the user is selecting a product or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to the server. The server receives this data and, if the user is feeling stressed, displays a message to simplify the process.

[0479] Emotion-based notification adjustments

[0480] The server adjusts the content of notifications it generates based on data from the emotion engine, according to the user's emotional state. For example, if the user is stressed, it generates a more concise and easy-to-understand notification. Specifically, if the emotion engine recognizes the user's stress or anxiety when a payment fails, the server will send a message in a gentler tone, such as "There was a problem. Please try again."

[0481] Adjusting promotional content based on emotions

[0482] The server adjusts the content of personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases. Specifically, if the emotion engine confirms that the user was satisfied with a previously purchased product, the server will send a discount coupon for a related product.

[0483] Examples of prompt statements

[0484] As a concrete example, one could consider inputting the following prompt message into a generative AI model.

[0485] Prompt: "Please explain in detail how to generate personalized promotions based on users' purchase history and sentiment data."

[0486] As described above, this system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the provision of highly personalized services.

[0487] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0488] Step 1: Enter and receive user information

[0489] Input: The user enters their name, email address, and password into the device.

[0490] Specific operation: The terminal provides an input form, the user enters the required information and presses the registration button. The entered information is format-checked, and if there are no problems, it is sent to the server.

[0491] Output: Format check results and user information sent to the server if correct.

[0492] Step 2: Saving User Information

[0493] Input: User information sent from the device.

[0494] Specific operation: The server saves the received user information to the database. It returns the success or failure of the save to the terminal.

[0495] Output: User information saved in the database and notification of successful saving.

[0496] Step 3: Enter and receive payment information

[0497] Input: The user enters their credit card information into the device.

[0498] Specific operation: The terminal provides a form for entering payment information, the user enters the information and presses the payment button. The entered information is sent to the server.

[0499] Output: Payment information sent to the server.

[0500] Step 4: Payment Processing

[0501] Input: Payment information sent from the device.

[0502] Specific operation: The server sends the received payment information to an external payment API and executes the payment. The payment result is returned from the API, and the server notifies the user of the result.

[0503] Output: The result of the payment (success or failure) and the notification thereof.

[0504] Step 5: Collect and store spending data

[0505] Input: Payment processing result data.

[0506] Specific operation: If the payment processing is successful, the server saves the expenditure data to the database. If it fails, it is recorded as an error log.

[0507] Output: Expenditure data stored in the database, or error logs.

[0508] Step 6: Analysis of monthly expenses

[0509] Input: User spending data stored in the database.

[0510] Specific operation: At the end of the month, the server retrieves expenditure data from the database and uses an analysis algorithm to calculate the monthly expenditure status. If a budget is set, it also checks for the possibility of budget overrun.

[0511] Output: Monthly spending report and budget overrun alerts.

[0512] Step 7: Generate payment-related notifications

[0513] Input: Expense data and user settings stored in the database.

[0514] Specific operation: The server periodically collects user payment due dates and outstanding payment information, and generates reminders and notifications.

[0515] Output: Payment reminders and non-payment notifications to users.

[0516] Step 8: Generating Personalized Promotions

[0517] Input: User purchase history and preference data.

[0518] Specific operation: The server analyzes this data and generates personalized promotions that are best suited to the user.

[0519] Output: Personalized promotional information notified to the user.

[0520] Step 9: Collecting emotional data

[0521] Input: User's facial recognition data and input data.

[0522] Specific operation: The device's camera captures the user's facial expressions, the emotion engine analyzes this data to generate emotion data, and sends it to the server.

[0523] Output: User sentiment data sent to the server.

[0524] Step 10: Analyzing emotional data

[0525] Input: Emotional data sent from the device.

[0526] Specific operation: The server analyzes the received emotion data to identify the user's current emotional state.

[0527] Output: Emotional state data.

[0528] Step 11: Adjusting notification content based on emotions

[0529] Input: Emotional state data.

[0530] Specific operation: The server adjusts the notification content based on the user's emotional state. For example, if the user is feeling stressed, the notification will be concise and expressed in a gentle tone.

[0531] Output: Notification content adjusted based on emotions.

[0532] Step 12: Adjusting promotional content based on emotions

[0533] Input: Emotional state data and promotional information.

[0534] Specific operation: The server adjusts promotional content based on the user's emotional state. For example, if the user is in a good mood, it will offer promotions that further encourage purchases.

[0535] Output: Promotional information tailored based on emotions.

[0536] (Application Example 2)

[0537] 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".

[0538] Traditional electronic payment systems and spending management applications have a problem in that they do not take into account the user's emotional state, and therefore do not adequately optimize the user experience or reduce stress. Furthermore, personalized promotional offerings also have the problem of not being able to respond flexibly based on the user's real-time emotional changes.

[0539] 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 means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment result, means for analyzing the user's spending data, means for notifying the user of the analysis result, means for generating personalized promotions, means for providing the generated promotions to the user, means for acquiring emotional data and analyzing the user's emotional state, and means for adjusting notification content and payment processing methods based on the user's emotional state. This makes it possible to simplify payment processing according to the user's emotional state and to provide personalized notifications and promotions.

[0540] "User information" refers to the collective term for personal identification information such as the user's name, email address, and password, as well as transaction history data.

[0541] A "database" is an electronic storage location for systematically organizing, saving, and managing received user information.

[0542] "Payment processing" refers to a series of procedures that use payment information provided by the user to settle the payment for goods or services.

[0543] A "notification" is a message sent from the system to the user, such as payment results, analysis results, or promotional information.

[0544] "Expenditure data" refers to records of various payments and transactions made by the user.

[0545] "Analysis" is the process of evaluating and calculating users' consumption trends and budget management status based on collected spending data and other user information.

[0546] "Personalized promotions" refer to the provision of discounts and benefits optimized for each user, based on their individual purchase history and preference data.

[0547] "Emotional data" refers to digital data that indicates a user's emotional state, obtained from their facial expressions and behavior.

[0548] "Emotional state" refers to the user's current mental and psychological state, as analyzed from emotional data.

[0549] "Simplification" is the act of reducing complexity in order to make operating procedures and processes intuitive and easy to understand in accordance with the user's emotional state.

[0550] This invention provides technical means for realizing a smartphone application that dynamically adjusts payment processing and notification content while taking into account the user's emotional state. Here, the configuration and operation of each component of this system are described in detail.

[0551] System Configuration

[0552] The main hardware components of this system include a smartphone (with a built-in camera). The main software components include an emotion recognition library (e.g., emotion_recognition), an HTTP request library (e.g., requests), and an external payment API wrapper (e.g., payment_api).

[0553] Receiving and storing user information

[0554] The terminal provides an interface for the user to enter information such as their name, email address, and password. Once the user enters the required information, the terminal sends that information to the server for storage in a database. The server stores the received data in the database and notifies the terminal of the successful storage.

[0555] Acquisition and analysis of emotional data

[0556] The device's built-in camera is used to capture an image of the user's face, and this image is analyzed using an emotion recognition library. The emotion data is sent to the server as numerical data representing the user's current emotional state (e.g., stress, happiness). Based on this data, the server evaluates the user's emotional state and takes appropriate action.

[0557] Adjustment of payment processing and notification content

[0558] When a user purchases goods or services, the device receives payment information from the user and sends it to a server. The server calls an external payment API to execute the payment. If the user's emotional state indicates high stress, a method is provided to simplify the payment process. The payment result is notified to the user in an appropriate tone according to their emotional state.

[0559] Providing personalized promotions

[0560] The server generates personalized promotions optimized for the user based on their purchase history and emotional data. For example, if a user is in a good mood, it offers discounts to encourage further purchases; if they are stressed, it presents promotions for relaxation products, etc.

[0561] Data and calculations to be used

[0562] The server aggregates user information, sentiment data, payment information, and purchase history data, and uses this information to simplify payment processing and adjust notification content. The data is processed through sentiment analysis libraries and external payment APIs to provide users with optimized advice and promotions.

[0563] Specific processing examples

[0564] For example, if a user's facial image is analyzed and indicates high stress levels, the server will send a gentle message such as, "An error occurred. Please try again." Also, if a user has previously purchased relaxation products and been satisfied, they may be offered related new promotions.

[0565] Example of a prompt

[0566] The following are specific examples of prompt messages to send to a generative AI model:

[0567] A user has registered for the app and entered their email address and password. Write code to retrieve the user's emotion recognition data and suggest appropriate notifications and payment methods based on their different emotional states.

[0568] This will enable simplified payment processing based on the user's emotional state, as well as the delivery of personalized notifications and promotions.

[0569] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0570] Step 1: Register User Information

[0571] The terminal provides an interface for the user to enter information such as their name, email address, and password. Once the user enters the information, the data is sent to the server. The server stores the received information in a database and sends a message back to the terminal confirming that the data was successfully saved.

[0572] Input: Information entered by the user, such as name, email address, and password.

[0573] Data processing: none

[0574] Calculation: none

[0575] Output: Message indicating successful save

[0576] Step 2: Acquiring emotional data

[0577] The device uses its built-in camera to acquire an image of the user's face. This image is input into an emotion recognition library to generate emotion data. This data is sent to a server. The server stores the received emotion data and makes it available for processing.

[0578] Input: Face image

[0579] Data processing: Convert facial expression information into numerical data and then into emotional data.

[0580] Calculation: Generation of emotion data using emotion recognition algorithms

[0581] Output: Sentiment data

[0582] Step 3: Execute payment processing

[0583] The user enters payment information (e.g., credit card information) for the goods or services they wish to purchase into the terminal. The terminal sends this payment information to the server. The server calls an external payment API to execute the payment. If the user's emotional data indicates high stress, the process is simplified. The payment result is adjusted based on the emotional data and communicated to the user.

[0584] Input: Payment information, sentiment data

[0585] Data processing: Converting payment information into the appropriate format.

[0586] Calculation: Payment API call and retrieval of payment results

[0587] Output: Payment result notification

[0588] Step 4: Spending Log Analysis

[0589] The server retrieves the user's past spending data from the database and calculates their monthly spending. It uses an analytical algorithm to aggregate the spending data and generates an alert if the user's budget is exceeded.

[0590] Input: Past spending data

[0591] Data processing: Aggregation of monthly expenditure data

[0592] Calculation: Use an analytical algorithm to calculate spending patterns.

[0593] Output: Expenditure analysis results, budget overrun alerts

[0594] Step 5: Adjusting notification content

[0595] The server evaluates the user's current emotional state based on emotional data and optimizes the notification content accordingly. For example, if the user is feeling stressed, it generates a concise and easy-to-understand notification.

[0596] Input: Sentiment data, analysis results

[0597] Data processing: Generating notification messages

[0598] Calculation: Optimization of notification content based on emotional state

[0599] Output: Notification message

[0600] Step 6: Offer personalized promotions

[0601] The server generates personalized promotions based on the user's purchase history and emotional data. Based on emotional data, it provides promotions that encourage purchases when the user is in a good mood, and promotions for relaxation products, etc., when the user is feeling stressed.

[0602] Input: Purchase history, sentiment data

[0603] Data processing: Customization of promotional content

[0604] Calculation: Generating promotions based on purchase history and sentiment data

[0605] Output: Promotion message

[0606] This series of processing steps enables flexible responses tailored to the user's emotional state, optimizing the user experience.

[0607] 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.

[0608] 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.

[0609] 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.

[0610] [Second Embodiment]

[0611] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0612] 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.

[0613] 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).

[0614] 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.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] 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".

[0623] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[0624] System configuration and operation

[0625] This system includes the following main components:

[0626] 1. Receiving and storing user information

[0627] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[0628] Specific example: For instance, when a new user signs up for an app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[0629] 2. Payment Processing

[0630] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[0631] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[0632] 3. Analysis of expenditure data and budget management

[0633] The server retrieves the user's past spending data from the database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[0634] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[0635] 4. Payment-related notices

[0636] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[0637] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[0638] 5. Providing personalized promotions

[0639] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[0640] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[0641] These features allow users to efficiently manage their payments and receive personalized promotions. This system is a powerful tool for optimizing the user experience and improving marketing effectiveness.

[0642] The following describes the processing flow.

[0643] User registration process

[0644] Step 1:

[0645] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[0646] Step 2:

[0647] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[0648] Step 3:

[0649] The server executes an SQL query to extract user information from the received request and save it to the database.

[0650] Step 4:

[0651] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[0652] Step 5:

[0653] The server sends the generated response to the terminal.

[0654] Step 6:

[0655] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[0656] Payment processing flow

[0657] Step 1:

[0658] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or PayPay account information).

[0659] Step 2:

[0660] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[0661] Step 3:

[0662] The server extracts the received payment information and uses a payment API client to call an external payment API.

[0663] Step 4:

[0664] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[0665] Step 5:

[0666] The server sends the generated response to the terminal.

[0667] Step 6:

[0668] The terminal receives the response and notifies the user of the payment result.

[0669] Budget management and expenditure analysis process

[0670] Step 1:

[0671] The user accesses the budget management page to check their set budget and spending status.

[0672] Step 2:

[0673] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[0674] Step 3:

[0675] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[0676] Step 4:

[0677] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[0678] Step 5:

[0679] The server generates the budget analysis results as a response in JSON format.

[0680] Step 6:

[0681] The server sends the generated response to the terminal.

[0682] Step 7:

[0683] The device receives the response and displays the analysis results to the user.

[0684] Payment-related notification flow

[0685] Step 1:

[0686] Users set up payment reminders.

[0687] Step 2:

[0688] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[0689] Step 3:

[0690] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[0691] Step 4:

[0692] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[0693] Step 5:

[0694] The server creates the generated notification as a response in JSON format.

[0695] Step 6:

[0696] The server sends the generated response to the terminal.

[0697] Step 7:

[0698] The device receives the response and displays a notification to the user.

[0699] Personalized promotion delivery process

[0700] Step 1:

[0701] Users can set up their preferences to receive personalized promotional information.

[0702] Step 2:

[0703] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[0704] Step 3:

[0705] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[0706] Step 4:

[0707] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[0708] Step 5:

[0709] The server generates the generated promotion as a response in JSON format.

[0710] Step 6:

[0711] The server sends the generated response to the terminal.

[0712] Step 7:

[0713] The device receives the response and displays promotional information to the user.

[0714] The above outlines the specific process flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, and personalized promotional offerings.

[0715] (Example 1)

[0716] 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."

[0717] In today's consumer lifestyle, efficiently managing multiple payments and personalized marketing is extremely difficult. This leads to problems such as missed payments and budget overruns for users, and makes it challenging for businesses to accurately capture user purchasing preferences through marketing. There is a need for systems that can address these challenges.

[0718] 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.

[0719] In this invention, the server includes means for receiving user information, means for storing it in a database, means for processing payments, means for notifying payment results, means for collecting spending data, means for analyzing data, means for notifying analysis results, means for generating personalized promotions, means for providing promotions, means for comparing spending data with a budget and generating alerts if there is a possibility of budget overrun, and means for periodically generating payment reminders and unpaid notifications. This enables users to efficiently manage their payments and allows companies to conduct personalized marketing to users.

[0720] "User information" refers to personally identifiable information such as the user's name, email address, and password.

[0721] A "database" refers to a system used to structure and store user information, spending data, and other similar information.

[0722] "Payment processing" refers to the process of executing payment information received from users through external payment APIs.

[0723] "Payment result" refers to notification information indicating whether the payment process was successful or unsuccessful.

[0724] "Expenditure data" refers to information such as the amount and date of various purchases made by the user.

[0725] An "analysis algorithm" refers to a calculation method used to analyze a user's spending data to determine spending trends and the likelihood of budget overruns.

[0726] "Personalized promotions" refer to discount coupons and exclusive offers that are individually generated based on a user's purchase history and preference data.

[0727] An "alert" refers to a warning or notification issued to a user. For example, it could be a notification informing the user of a potential budget overrun.

[0728] A "payment reminder" refers to a notification that periodically informs the user of the payment deadline.

[0729] An "unpaid notice" refers to a notification informing the user that a specified payment has not yet been completed.

[0730] A "payment API" refers to a programmatic interface for processing payments in conjunction with external payment services.

[0731] "Budget" refers to the upper limit of expenses that a user should spend within a set period of time.

[0732] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[0733] System configuration and operation

[0734] This system includes the following main components:

[0735] 1. Receiving and storing user information

[0736] The terminal provides an interface for the user to enter registration information such as name, email address, and password. When the user enters the information and presses the "Register" button, the terminal sends this information to the server. The server stores the received user information in its database and notifies the terminal of the successful saving.

[0737] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, stores it in its database, and notifies the device that registration is complete.

[0738] 2. Payment Processing

[0739] When a user purchases a product, they enter payment information (credit card number, expiration date, security code, etc.) into the terminal. The terminal sends the payment information to the server. The server calls an external payment API to process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result via the terminal.

[0740] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[0741] 3. Analysis of expenditure data and budget management

[0742] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[0743] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if the budget is exceeded.

[0744] 4. Payment-related notices

[0745] The server collects information based on specific conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[0746] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when payment deadlines are approaching.

[0747] 5. Providing personalized promotions

[0748] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[0749] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[0750] This allows users to efficiently manage their payments and receive personalized, optimized promotions. The system becomes a powerful tool for optimizing the user experience and improving marketing effectiveness.

[0751] Example of a prompt

[0752] 1. "What information do new users need to sign up for the app?"

[0753] 2. "Please explain how to make a payment online using a credit card."

[0754] 3. "How can I set up budget management in the app and receive alerts when the budget is exceeded?"

[0755] 4. "Please explain how to set up recurring payment reminders."

[0756] 5. "How can we offer personalized promotions based on purchase history?"

[0757] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0758] Details of the processing steps

[0759] Step 1: Enter user information

[0760] The device displays a form for the user to enter their name, email address, and password.

[0761] Input: The user enters their name, email address, and password.

[0762] Output: The entered user information is stored on the device.

[0763] Specifically, the user opens the app and enters information into the displayed registration form.

[0764] Step 2: Sending Information

[0765] The terminal sends the entered information to the server.

[0766] Input: User information entered on the terminal.

[0767] Output: User information is sent to the server.

[0768] After the user completes the input and presses the "Register" button, the device sends the user information to the server.

[0769] Step 3: Saving Information

[0770] The server stores the received user information in a database.

[0771] Input: User information sent to the server.

[0772] Output: User information is saved to the database.

[0773] If the save is successful, the server sends a success message to the terminal.

[0774] Step 4: Enter payment information

[0775] The terminal provides an interface for the user to enter payment information.

[0776] Input: The user enters their payment information.

[0777] Output: The entered payment information is stored on the terminal.

[0778] Specifically, the user enters their credit card number and security code on the purchase screen.

[0779] Step 5: Submit payment information

[0780] The device sends payment information to the server.

[0781] Input: Payment information entered on the terminal.

[0782] Output: Payment information is sent to the server.

[0783] When the user presses the "Pay" button, the device sends the payment information to the server.

[0784] Step 6: Execute Payment

[0785] The server processes payments by calling an external payment API.

[0786] Input: Payment information sent to the server.

[0787] Output: Payment result from the payment API.

[0788] The server sends a payment request to the payment API and receives a response from the API.

[0789] Step 7: Notification of payment result

[0790] The server notifies the user of the payment result (success / failure) via the terminal.

[0791] Input: Payment result from the payment API.

[0792] Output: The payment result is notified to the device.

[0793] The server sends a message to the terminal indicating whether the payment was successful or failed, and displays it to the user.

[0794] Step 8: Collecting expenditure data

[0795] The server periodically retrieves user spending data from the database.

[0796] Input: Expense data stored in the database.

[0797] Output: The acquired expenditure data is aggregated on the server.

[0798] The server sets up scheduled tasks to periodically collect expenditure data from the database.

[0799] Step 9: Data Analysis

[0800] The server processes the spending data using an analysis algorithm to calculate the monthly spending situation.

[0801] Input: Aggregated expenditure data.

[0802] Output: Results of the analyzed spending situation.

[0803] The server runs an analysis algorithm to calculate monthly spending trends and abnormal spending.

[0804] Step 10: Check for budget overruns and generate alerts

[0805] The server compares the user's set budget with actual spending and checks for potential budget overruns. If a budget overrun is anticipated, the server generates an alert and notifies the user.

[0806] Input: Analysis results and user-defined budget.

[0807] Output: Alert notifications generated as needed.

[0808] Specifically, if there is a possibility of exceeding the budget at the end of the month, the server generates an alert message such as "You have exceeded your budget" and notifies the user.

[0809] Step 11: Generate payment-related notifications

[0810] The server generates payment reminders and non-payment notifications based on certain conditions.

[0811] Input: Payment due date data and outstanding payment data.

[0812] Output: Generated notification.

[0813] The server periodically generates and sends reminders based on the reminder conditions set by the user.

[0814] Step 12: Generate and notify personalized promotions

[0815] The server generates and notifies users of personalized promotions based on their purchase history and preference data.

[0816] Input: Purchase history data and preference data.

[0817] Output: Generated promotional notification.

[0818] Specifically, if a user frequently purchases products in a particular category, the server generates a discount promotion for those products and notifies the user.

[0819] (Application Example 1)

[0820] 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."

[0821] In modern society, many users struggle to efficiently manage multiple payments. Furthermore, insufficient tracking of expenses and budget management often leads to budget overruns. Additionally, effectively delivering personalized promotions to users remains a challenge. There is a need for a system that solves these problems, streamlining payment management while enhancing marketing effectiveness tailored to individual needs.

[0822] 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.

[0823] In this invention, the server includes means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of payment results, means for analyzing user spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for setting a budget and displaying monthly spending status in real time, means for generating alerts when the budget is exceeded, means for sending regular payment reminders and unpaid notifications to the user, and means for generating and providing discount coupons and limited offers based on purchase history. This enables users to efficiently manage their payments, prevent budget overruns, and receive promotions tailored to them.

[0824] "User information" refers to personal data provided by the user, such as name, email address, and payment information.

[0825] A "database" is a system for efficiently storing and managing data such as user information and payment history.

[0826] "Payment processing" refers to the process by which users complete payment using their payment information when purchasing goods or services.

[0827] "Notifications" are a means of communication used to inform users of payment results, budget overrun alerts, promotional information, and other relevant details.

[0828] "Expense data" refers to a record of payments a user has made in the past.

[0829] "Analysis" is the process of evaluating spending patterns and budget situations through users' spending data.

[0830] "Personalized promotions" refer to special offers and discounts generated based on a user's purchase history and preferences.

[0831] A "budget" is the maximum amount of money a user can spend within a certain period of time.

[0832] An "alert" is a notification that warns a user based on set conditions (e.g., exceeding the budget).

[0833] A "reminder" is a feature that periodically notifies users of payment deadlines or other important dates.

[0834] A "coupon" is a benefit that applies a discount when purchasing specific products or services.

[0835] A "limited offer" is a special deal that is offered to specific users for a limited time only.

[0836] This invention provides a system that streamlines user payment management and offers personalized promotions. The system's configuration and operation are described in detail below.

[0837] System Configuration

[0838] The system mainly consists of the following components:

[0839] 1. Receiving and storing user information

[0840] The device provides the interface, allowing the user to enter their name, email address, password, payment information, etc.

[0841] The server stores the received user information in a database.

[0842] 2. Payment Processing

[0843] When a user purchases a product, they enter their payment information into the device.

[0844] The server uses this payment information to call an external payment API and process the payment.

[0845] 3. Analysis of expenditure data and budget management

[0846] The server retrieves the user's past spending data from the database and uses an analysis algorithm to calculate the monthly spending pattern.

[0847] If a user has a budget set, the server will check for potential budget overruns and generate an alert.

[0848] 4. Payment-related notices

[0849] The server generates and sends periodic payment reminders and overdue payment notifications to the user.

[0850] 5. Providing personalized promotions

[0851] The server generates personalized promotions based on the user's purchase history and preference data, and notifies the user.

[0852] System operation

[0853] Receiving and storing user information

[0854] When a user signs up for the app, the device sends the entered information to the server. The server stores this information in a database and notifies the device that the saving was successful.

[0855] Payment processing

[0856] When a user purchases a product online, they enter their payment information and send it to the server via their device. The server calls an external payment API, executes the payment, and notifies the user of the result.

[0857] Analysis of expenditure data and budget management

[0858] The server analyzes the user's past spending data to calculate monthly spending and generates an alert if the set budget is exceeded. This analysis retrieves data from a database and applies a specific algorithm.

[0859] Payment-related notices

[0860] The server generates and sends regularly scheduled reminders and notifications when payment deadlines are approaching. This allows users to manage important payments without forgetting them.

[0861] Providing personalized promotions

[0862] The server generates and notifies users of personalized promotions, such as discount coupons and limited-time offers, based on their purchase history. These promotions are tailored to each user, improving marketing effectiveness.

[0863] Hardware and software to be used

[0864] Hardware: Smartphones, servers

[0865] Software: Flask (web framework), SQLite (database), external payment API

[0866] Specific example

[0867] For example, when a user registers for the app, they enter their name, email address, and password, and then press the registration button. This data is sent from the device to the server. The server stores this data in a database and sends an appropriate notification to the user.

[0868] Furthermore, when a user enters their credit card information to purchase a product, the server calls an external payment API to complete the payment. Spending data is automatically recorded, and an alert is generated at the end of the month if the budget is exceeded.

[0869] Examples of prompts for generative AI models

[0870] "I want to set a monthly budget. Can you tell me how to set a budget?"

[0871] "I'd like to know about this month's spending. Please tell me how much you spent."

[0872] "Do you have any discount coupons I can use for my next purchase?"

[0873] Thus, the system of the present invention can improve the user experience by streamlining user payment management and providing personalized promotions.

[0874] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0875] Step 1:

[0876] Receiving and storing user information

[0877] The device receives information such as the user's name, email address, password, and payment information, and sends that information to the server.

[0878] The server saves the received user information to the database. The input consists of personal data entered by the user, and data processing for saving to the database includes format conversion and validation. The output is a notification of successful saving.

[0879] Step 2:

[0880] Payment processing

[0881] When a user purchases goods online, they enter their payment information, which is then transmitted to the server via their device.

[0882] The server uses this payment information to convert the input data into a format suitable for sending to an external payment API. After this conversion and transmission process is complete, it receives the result (success / failure) from the payment API. The received result is processed by the server and notified to the user. Here, the input is the payment information and payment request, and the output is the payment result notification.

[0883] Step 3:

[0884] Analysis of expenditure data and budget management

[0885] The server retrieves the user's past spending data from the database.

[0886] Subsequently, a data analysis algorithm is applied to calculate monthly spending. This calculation aggregates past spending data and analyzes monthly spending patterns. As a result, the calculated spending status is output, and based on this, it is determined whether there is a possibility of budget overrun. The input is past spending data, and the output is spending status and budget overrun alerts.

[0887] Step 4:

[0888] Payment-related notices

[0889] The server generates and automatically sends periodic payment reminders and overdue payment notifications to users.

[0890] The inputs are the current date and the user's payment schedule data. Based on this, an SQL query is used to generate a list of unpaid items, and a reminder notification is created and sent to the user based on that list. The output is the reminder notification.

[0891] Step 5:

[0892] Providing personalized promotions

[0893] The server generates discount coupons and exclusive offers based on the user's purchase history and preference data.

[0894] The input is the user's past purchase data, which is analyzed to generate promotions for specific products. These promotions are sent to the user as notifications. The generated promotions include appropriate discounts and offers based on the specified purchase history. The output is a personalized promotion.

[0895] 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.

[0896] This invention combines a system that receives and stores user information, processes payments, analyzes spending, manages budgets, and provides personalized promotions with an emotion engine that recognizes user emotions. This system can dynamically adjust notification and promotional content based on user emotions. Each processing step in this system is described below.

[0897] System configuration and operation

[0898] This system includes the following main components:

[0899] 1. Receiving and storing user information

[0900] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[0901] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and press the register button. The device then sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[0902] 2. Payment Processing

[0903] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[0904] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[0905] 3. Analysis of expenditure data and budget management

[0906] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[0907] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[0908] 4. Payment-related notices

[0909] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[0910] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[0911] 5. Providing personalized promotions

[0912] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[0913] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[0914] 6. Integrating an emotion engine

[0915] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app.

[0916] The server receives emotion data sent from the terminal and analyzes the user's current emotional state.

[0917] Specific example: While a user is selecting products or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to a server. The server receives this data and, if the user is experiencing stress, displays a message to simplify the process.

[0918] 7. Adjusting notification content based on emotions

[0919] The server uses data from the emotion engine to adjust the content of the notifications it generates according to the user's emotional state. For example, if the user is feeling stressed, it will generate a more concise and easy-to-understand notification.

[0920] Specific example: If a user fails to make a payment, and the emotion engine recognizes the user's stress or anxiety, the server will send a gentle message such as, "Something went wrong. Please try again."

[0921] 8. Adjusting promotional content based on emotions

[0922] The server adjusts personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases.

[0923] Specific example: If the sentiment engine confirms that the user was satisfied with a previously purchased item, the server will send a discount coupon for a related product.

[0924] This system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the delivery of highly personalized services.

[0925] The following describes the processing flow.

[0926] User registration process

[0927] Step 1:

[0928] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[0929] Step 2:

[0930] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[0931] Step 3:

[0932] The server executes an SQL query to extract user information from the received request and save it to the database.

[0933] Step 4:

[0934] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[0935] Step 5:

[0936] The server sends the generated response to the terminal.

[0937] Step 6:

[0938] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[0939] Payment processing flow

[0940] Step 1:

[0941] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or payment account information).

[0942] Step 2:

[0943] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[0944] Step 3:

[0945] The server extracts the received payment information and uses a payment API client to call an external payment API.

[0946] Step 4:

[0947] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[0948] Step 5:

[0949] The server sends the generated response to the terminal.

[0950] Step 6:

[0951] The terminal receives the response and notifies the user of the payment result.

[0952] Budget management and expenditure analysis process

[0953] Step 1:

[0954] The user accesses the budget management page to check their set budget and spending status.

[0955] Step 2:

[0956] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[0957] Step 3:

[0958] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[0959] Step 4:

[0960] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[0961] Step 5:

[0962] The server generates the budget analysis results as a response in JSON format.

[0963] Step 6:

[0964] The server sends the generated response to the terminal.

[0965] Step 7:

[0966] The device receives the response and displays the analysis results to the user.

[0967] Payment-related notification flow

[0968] Step 1:

[0969] Users set up payment reminders.

[0970] Step 2:

[0971] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[0972] Step 3:

[0973] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[0974] Step 4:

[0975] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[0976] Step 5:

[0977] The server creates the generated notification as a response in JSON format.

[0978] Step 6:

[0979] The server sends the generated response to the terminal.

[0980] Step 7:

[0981] The device receives the response and displays a notification to the user.

[0982] Personalized promotion delivery process

[0983] Step 1:

[0984] Users can set up their preferences to receive personalized promotional information.

[0985] Step 2:

[0986] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[0987] Step 3:

[0988] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[0989] Step 4:

[0990] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[0991] Step 5:

[0992] The server generates the generated promotion as a response in JSON format.

[0993] Step 6:

[0994] The server sends the generated response to the terminal.

[0995] Step 7:

[0996] The device receives the response and displays promotional information to the user.

[0997] The process of integrating and utilizing an emotional engine

[0998] The flow of emotion recognition

[0999] Step 1:

[1000] While the user is using the app, the device's camera captures the user's facial expressions.

[1001] Step 2:

[1002] The device sends captured facial expression data to an emotion engine, which then analyzes the user's emotions.

[1003] Step 3:

[1004] The device sends the analyzed emotion data to the server.

[1005] Adjusting notifications based on emotions

[1006] Step 1:

[1007] The server adjusts the content of the notifications it generates based on the received emotion data, according to the user's emotional state.

[1008] Step 2:

[1009] The server generates the adjusted notification content as a response in JSON format.

[1010] Step 3:

[1011] The server sends the generated response to the terminal.

[1012] Step 4:

[1013] The device receives the response and displays a tailored notification to the user.

[1014] Emotion-based promotion adjustments

[1015] Step 1:

[1016] The server adjusts the promotional content it generates based on the received sentiment data, according to the user's emotional state.

[1017] Step 2:

[1018] The server generates the adjusted promotional content as a response in JSON format.

[1019] Step 3:

[1020] The server sends the generated response to the terminal.

[1021] Step 4:

[1022] The device receives the response and displays the adjusted promotional information to the user.

[1023] The above outlines the specific processing flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, personalized promotional offerings, and the integration of an emotion engine.

[1024] (Example 2)

[1025] 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".

[1026] The objective of this invention is to improve the user experience by streamlining user payment processing and expenditure management while providing flexible responses tailored to user emotions. Specifically, it is required to detect user emotions in real time, adjust notification and promotional content based on those emotions, and provide a more personalized service.

[1027] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1028] In this invention, the server includes means for receiving user information, means for storing the user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment results, means for analyzing the user's spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for detecting the user's emotions using a terminal, means for transmitting the emotion data to the server and analyzing the emotional state, means for adjusting notification content based on the emotional state, and means for adjusting promotion content based on the emotional state. This makes it possible to provide personalized services based on the user's emotions.

[1029] "User information" refers to information such as name, email address, and password that identifies an individual user and is used for authentication and service provision.

[1030] A "database" is a collection of electronically stored data used to efficiently manage user information and spending data.

[1031] "Payment processing" refers to the process of settling payments when a user purchases goods or services, and includes the use of credit card information and external payment APIs.

[1032] "Notifications" refer to information such as messages and alerts sent from the system to the user, including important information such as payment results and budget overruns.

[1033] "Expenditure data" refers to information about amounts and items recorded by users regarding purchases and payments, and is used for budget management and expenditure analysis.

[1034] An "analysis algorithm" is a means of identifying and evaluating specific patterns and trends in data, and is used in the analysis of user spending data.

[1035] A "personalized promotion" is a promotion that provides individual users with benefits and discounts optimized for them, based on their purchase history and preference data.

[1036] A "terminal" is a device used by a user for input and operation, and includes smartphones, personal computers, and other similar devices.

[1037] An "emotion engine" is a system that uses user input data and facial recognition to detect and analyze a user's emotional state.

[1038] "Emotional data" refers to data that indicates a user's emotional state, collected from facial expressions, words, actions, etc., and used for analysis.

[1039] "Adjusting notification content" refers to the process of changing the content and wording of notification messages according to the user's emotional state.

[1040] "Adjusting promotional content" refers to the process of changing the content and benefits of promotional information provided based on users' emotional states and preference data.

[1041] This invention combines a system that receives and stores user information, processes payments, analyzes spending, manages budgets, and provides personalized promotions with an emotion engine that recognizes user emotions. This system can dynamically adjust notification and promotional content based on user emotions. Specific embodiments of this system are described below.

[1042] System Overview

[1043] This system is mainly composed of the following key components:

[1044] Receiving and storing user information

[1045] Payment processing

[1046] Analysis of expenditure data and budget management

[1047] Payment-related notices

[1048] Providing personalized promotions

[1049] Embedding an emotion engine

[1050] Emotion-based notification adjustments

[1051] Adjusting promotional content based on emotions

[1052] Receiving and storing user information

[1053] The terminal provides an interface for users to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving. For example, when a new user enters their name, email address, and password and presses the registration button, the terminal sends that data to the server. The server receives this data, stores it in its database, and displays a registration completion message.

[1054] Payment processing

[1055] When a user purchases a product, they enter their payment information into a terminal. The terminal sends this payment information to a server. The server uses this information to call an external payment API and process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result. For example, when a user purchases a product online, they enter their credit card information and press the payment button, sending that information to the server. The server calls an external payment API to execute the payment and notifies the user of the result.

[1056] Analysis of expenditure data and budget management

[1057] The server retrieves the user's past spending data from a database and uses an analysis algorithm to calculate monthly spending. If the user has set a budget, the server checks for potential budget overruns and generates an alert. For example, if a user sets their own budget within the app and wants to track their monthly spending, the server aggregates the spending data at the end of the month and generates an alert to notify the user if the budget has been exceeded.

[1058] Payment-related notices

[1059] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and overdue payment notices. Specifically, if a user sets up periodic reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[1060] Providing personalized promotions

[1061] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server notifies the user of the generated promotions. For example, if a user frequently purchases products in a particular category, the server will generate and notify the user of discount promotions for products in that category.

[1062] Embedding an emotion engine

[1063] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app. The server receives the emotion data sent from the device and analyzes the user's current emotional state. For example, while the user is selecting a product or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to the server. The server receives this data and, if the user is feeling stressed, displays a message to simplify the process.

[1064] Emotion-based notification adjustments

[1065] The server adjusts the content of notifications it generates based on data from the emotion engine, according to the user's emotional state. For example, if the user is stressed, it generates a more concise and easy-to-understand notification. Specifically, if the emotion engine recognizes the user's stress or anxiety when a payment fails, the server will send a message in a gentler tone, such as "There was a problem. Please try again."

[1066] Adjusting promotional content based on emotions

[1067] The server adjusts the content of personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases. Specifically, if the emotion engine confirms that the user was satisfied with a previously purchased product, the server will send a discount coupon for a related product.

[1068] Examples of prompt statements

[1069] As a concrete example, one could consider inputting the following prompt message into a generative AI model.

[1070] Prompt: "Please explain in detail how to generate personalized promotions based on users' purchase history and sentiment data."

[1071] As described above, this system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the provision of highly personalized services.

[1072] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1073] Step 1: Enter and receive user information

[1074] Input: The user enters their name, email address, and password into the device.

[1075] Specific operation: The terminal provides an input form, the user enters the required information and presses the registration button. The entered information is format-checked, and if there are no problems, it is sent to the server.

[1076] Output: Format check results and user information sent to the server if correct.

[1077] Step 2: Saving User Information

[1078] Input: User information sent from the device.

[1079] Specific operation: The server saves the received user information to the database. It returns the success or failure of the save to the terminal.

[1080] Output: User information saved in the database and notification of successful saving.

[1081] Step 3: Enter and receive payment information

[1082] Input: The user enters their credit card information into the device.

[1083] Specific operation: The terminal provides a form for entering payment information, the user enters the information and presses the payment button. The entered information is sent to the server.

[1084] Output: Payment information sent to the server.

[1085] Step 4: Payment Processing

[1086] Input: Payment information sent from the device.

[1087] Specific operation: The server sends the received payment information to an external payment API and executes the payment. The payment result is returned from the API, and the server notifies the user of the result.

[1088] Output: The result of the payment (success or failure) and the notification thereof.

[1089] Step 5: Collect and store spending data

[1090] Input: Payment processing result data.

[1091] Specific operation: If the payment processing is successful, the server saves the expenditure data to the database. If it fails, it is recorded as an error log.

[1092] Output: Expenditure data stored in the database, or error logs.

[1093] Step 6: Analysis of monthly expenses

[1094] Input: User spending data stored in the database.

[1095] Specific operation: At the end of the month, the server retrieves expenditure data from the database and uses an analysis algorithm to calculate the monthly expenditure status. If a budget is set, it also checks for the possibility of budget overrun.

[1096] Output: Monthly spending report and budget overrun alerts.

[1097] Step 7: Generate payment-related notifications

[1098] Input: Expense data and user settings stored in the database.

[1099] Specific operation: The server periodically collects user payment due dates and outstanding payment information, and generates reminders and notifications.

[1100] Output: Payment reminders and non-payment notifications to users.

[1101] Step 8: Generating Personalized Promotions

[1102] Input: User purchase history and preference data.

[1103] Specific operation: The server analyzes this data and generates personalized promotions that are best suited to the user.

[1104] Output: Personalized promotional information notified to the user.

[1105] Step 9: Collecting emotional data

[1106] Input: User's facial recognition data and input data.

[1107] Specific operation: The device's camera captures the user's facial expressions, the emotion engine analyzes this data to generate emotion data, and sends it to the server.

[1108] Output: User sentiment data sent to the server.

[1109] Step 10: Analyzing emotional data

[1110] Input: Emotional data sent from the device.

[1111] Specific operation: The server analyzes the received emotion data to identify the user's current emotional state.

[1112] Output: Emotional state data.

[1113] Step 11: Adjusting notification content based on emotions

[1114] Input: Emotional state data.

[1115] Specific operation: The server adjusts the notification content based on the user's emotional state. For example, if the user is feeling stressed, the notification will be concise and expressed in a gentle tone.

[1116] Output: Notification content adjusted based on emotions.

[1117] Step 12: Adjusting promotional content based on emotions

[1118] Input: Emotional state data and promotional information.

[1119] Specific operation: The server adjusts promotional content based on the user's emotional state. For example, if the user is in a good mood, it will offer promotions that further encourage purchases.

[1120] Output: Promotional information tailored based on emotions.

[1121] (Application Example 2)

[1122] 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."

[1123] Traditional electronic payment systems and spending management applications have a problem in that they do not take into account the user's emotional state, and therefore do not adequately optimize the user experience or reduce stress. Furthermore, personalized promotional offerings also have the problem of not being able to respond flexibly based on the user's real-time emotional changes.

[1124] 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 means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment result, means for analyzing the user's spending data, means for notifying the user of the analysis result, means for generating personalized promotions, means for providing the generated promotions to the user, means for acquiring emotional data and analyzing the user's emotional state, and means for adjusting notification content and payment processing methods based on the user's emotional state. This makes it possible to simplify payment processing according to the user's emotional state and to provide personalized notifications and promotions.

[1125] "User information" refers to the collective term for personal identification information such as the user's name, email address, and password, as well as transaction history data.

[1126] A "database" is an electronic storage location for systematically organizing, saving, and managing received user information.

[1127] "Payment processing" refers to a series of procedures that use payment information provided by the user to settle the payment for goods or services.

[1128] A "notification" is a message sent from the system to the user, such as payment results, analysis results, or promotional information.

[1129] "Expenditure data" refers to records of various payments and transactions made by the user.

[1130] "Analysis" is the process of evaluating and calculating users' consumption trends and budget management status based on collected spending data and other user information.

[1131] "Personalized promotions" refer to the provision of discounts and benefits optimized for each user, based on their individual purchase history and preference data.

[1132] "Emotional data" refers to digital data that indicates a user's emotional state, obtained from their facial expressions and behavior.

[1133] "Emotional state" refers to the user's current mental and psychological state, as analyzed from emotional data.

[1134] "Simplification" is the act of reducing complexity in order to make operating procedures and processes intuitive and easy to understand in accordance with the user's emotional state.

[1135] This invention provides technical means for realizing a smartphone application that dynamically adjusts payment processing and notification content while taking into account the user's emotional state. Here, the configuration and operation of each component of this system are described in detail.

[1136] System Configuration

[1137] The main hardware components of this system include a smartphone (with a built-in camera). The main software components include an emotion recognition library (e.g., emotion_recognition), an HTTP request library (e.g., requests), and an external payment API wrapper (e.g., payment_api).

[1138] Receiving and storing user information

[1139] The terminal provides an interface for the user to enter information such as their name, email address, and password. Once the user enters the required information, the terminal sends that information to the server for storage in a database. The server stores the received data in the database and notifies the terminal of the successful storage.

[1140] Acquisition and analysis of emotional data

[1141] The device's built-in camera is used to capture an image of the user's face, and this image is analyzed using an emotion recognition library. The emotion data is sent to the server as numerical data representing the user's current emotional state (e.g., stress, happiness). Based on this data, the server evaluates the user's emotional state and takes appropriate action.

[1142] Adjustment of payment processing and notification content

[1143] When a user purchases goods or services, the device receives payment information from the user and sends it to a server. The server calls an external payment API to execute the payment. If the user's emotional state indicates high stress, a method is provided to simplify the payment process. The payment result is notified to the user in an appropriate tone according to their emotional state.

[1144] Providing personalized promotions

[1145] The server generates personalized promotions optimized for the user based on their purchase history and emotional data. For example, if a user is in a good mood, it offers discounts to encourage further purchases; if they are stressed, it presents promotions for relaxation products, etc.

[1146] Data and calculations to be used

[1147] The server aggregates user information, sentiment data, payment information, and purchase history data, and uses this information to simplify payment processing and adjust notification content. The data is processed through sentiment analysis libraries and external payment APIs to provide users with optimized advice and promotions.

[1148] Specific processing examples

[1149] For example, if a user's facial image is analyzed and indicates high stress levels, the server will send a gentle message such as, "An error occurred. Please try again." Also, if a user has previously purchased relaxation products and been satisfied, they may be offered related new promotions.

[1150] Example of a prompt

[1151] The following are specific examples of prompt messages to send to a generative AI model:

[1152] A user has registered for the app and entered their email address and password. Write code to retrieve the user's emotion recognition data and suggest appropriate notifications and payment methods based on their different emotional states.

[1153] This will enable simplified payment processing based on the user's emotional state, as well as the delivery of personalized notifications and promotions.

[1154] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1155] Step 1: Register User Information

[1156] The terminal provides an interface for the user to enter information such as their name, email address, and password. Once the user enters the information, the data is sent to the server. The server stores the received information in a database and sends a message back to the terminal confirming that the data was successfully saved.

[1157] Input: Information entered by the user, such as name, email address, and password.

[1158] Data processing: none

[1159] Calculation: none

[1160] Output: Message indicating successful save

[1161] Step 2: Acquiring emotional data

[1162] The device uses its built-in camera to acquire an image of the user's face. This image is input into an emotion recognition library to generate emotion data. This data is sent to a server. The server stores the received emotion data and makes it available for processing.

[1163] Input: Face image

[1164] Data processing: Convert facial expression information into numerical data and then into emotional data.

[1165] Calculation: Generation of emotion data using emotion recognition algorithms

[1166] Output: Sentiment data

[1167] Step 3: Execute payment processing

[1168] The user enters payment information (e.g., credit card information) for the goods or services they wish to purchase into the terminal. The terminal sends this payment information to the server. The server calls an external payment API to execute the payment. If the user's emotional data indicates high stress, the process is simplified. The payment result is adjusted based on the emotional data and communicated to the user.

[1169] Input: Payment information, sentiment data

[1170] Data processing: Converting payment information into the appropriate format.

[1171] Calculation: Payment API call and retrieval of payment results

[1172] Output: Payment result notification

[1173] Step 4: Spending Log Analysis

[1174] The server retrieves the user's past spending data from the database and calculates their monthly spending. It uses an analytical algorithm to aggregate the spending data and generates an alert if the user's budget is exceeded.

[1175] Input: Past spending data

[1176] Data processing: Aggregation of monthly expenditure data

[1177] Calculation: Use an analytical algorithm to calculate spending patterns.

[1178] Output: Expenditure analysis results, budget overrun alerts

[1179] Step 5: Adjusting notification content

[1180] The server evaluates the user's current emotional state based on emotional data and optimizes the notification content accordingly. For example, if the user is feeling stressed, it generates a concise and easy-to-understand notification.

[1181] Input: Sentiment data, analysis results

[1182] Data processing: Generating notification messages

[1183] Calculation: Optimization of notification content based on emotional state

[1184] Output: Notification message

[1185] Step 6: Offer personalized promotions

[1186] The server generates personalized promotions based on the user's purchase history and emotional data. Based on emotional data, it provides promotions that encourage purchases when the user is in a good mood, and promotions for relaxation products, etc., when the user is feeling stressed.

[1187] Input: Purchase history, sentiment data

[1188] Data processing: Customization of promotional content

[1189] Calculation: Generating promotions based on purchase history and sentiment data

[1190] Output: Promotion message

[1191] This series of processing steps enables flexible responses tailored to the user's emotional state, optimizing the user experience.

[1192] 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.

[1193] 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.

[1194] 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.

[1195] [Third Embodiment]

[1196] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1197] 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.

[1198] 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).

[1199] 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.

[1200] 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.

[1201] 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).

[1202] 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.

[1203] 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.

[1204] 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.

[1205] 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.

[1206] 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.

[1207] 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".

[1208] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[1209] System configuration and operation

[1210] This system includes the following main components:

[1211] 1. Receiving and storing user information

[1212] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[1213] Specific example: For instance, when a new user signs up for an app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[1214] 2. Payment Processing

[1215] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[1216] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[1217] 3. Analysis of expenditure data and budget management

[1218] The server retrieves the user's past spending data from the database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[1219] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[1220] 4. Payment-related notices

[1221] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[1222] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[1223] 5. Providing personalized promotions

[1224] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[1225] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[1226] These features allow users to efficiently manage their payments and receive personalized promotions. This system is a powerful tool for optimizing the user experience and improving marketing effectiveness.

[1227] The following describes the processing flow.

[1228] User registration process

[1229] Step 1:

[1230] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[1231] Step 2:

[1232] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[1233] Step 3:

[1234] The server executes an SQL query to extract user information from the received request and save it to the database.

[1235] Step 4:

[1236] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[1237] Step 5:

[1238] The server sends the generated response to the terminal.

[1239] Step 6:

[1240] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[1241] Payment processing flow

[1242] Step 1:

[1243] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or PayPay account information).

[1244] Step 2:

[1245] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[1246] Step 3:

[1247] The server extracts the received payment information and uses a payment API client to call an external payment API.

[1248] Step 4:

[1249] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[1250] Step 5:

[1251] The server sends the generated response to the terminal.

[1252] Step 6:

[1253] The terminal receives the response and notifies the user of the payment result.

[1254] Budget management and expenditure analysis process

[1255] Step 1:

[1256] The user accesses the budget management page to check their set budget and spending status.

[1257] Step 2:

[1258] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[1259] Step 3:

[1260] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[1261] Step 4:

[1262] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[1263] Step 5:

[1264] The server generates the budget analysis results as a response in JSON format.

[1265] Step 6:

[1266] The server sends the generated response to the terminal.

[1267] Step 7:

[1268] The device receives the response and displays the analysis results to the user.

[1269] Payment-related notification flow

[1270] Step 1:

[1271] Users set up payment reminders.

[1272] Step 2:

[1273] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[1274] Step 3:

[1275] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[1276] Step 4:

[1277] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[1278] Step 5:

[1279] The server creates the generated notification as a response in JSON format.

[1280] Step 6:

[1281] The server sends the generated response to the terminal.

[1282] Step 7:

[1283] The device receives the response and displays a notification to the user.

[1284] Personalized promotion delivery process

[1285] Step 1:

[1286] Users can set up their preferences to receive personalized promotional information.

[1287] Step 2:

[1288] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[1289] Step 3:

[1290] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[1291] Step 4:

[1292] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[1293] Step 5:

[1294] The server generates the generated promotion as a response in JSON format.

[1295] Step 6:

[1296] The server sends the generated response to the terminal.

[1297] Step 7:

[1298] The device receives the response and displays promotional information to the user.

[1299] The above outlines the specific process flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, and personalized promotional offerings.

[1300] (Example 1)

[1301] 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."

[1302] In today's consumer lifestyle, efficiently managing multiple payments and personalized marketing is extremely difficult. This leads to problems such as missed payments and budget overruns for users, and makes it challenging for businesses to accurately capture user purchasing preferences through marketing. There is a need for systems that can address these challenges.

[1303] 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.

[1304] In this invention, the server includes means for receiving user information, means for storing it in a database, means for processing payments, means for notifying payment results, means for collecting spending data, means for analyzing data, means for notifying analysis results, means for generating personalized promotions, means for providing promotions, means for comparing spending data with a budget and generating alerts if there is a possibility of budget overrun, and means for periodically generating payment reminders and unpaid notifications. This enables users to efficiently manage their payments and allows companies to conduct personalized marketing to users.

[1305] "User information" refers to personally identifiable information such as the user's name, email address, and password.

[1306] A "database" refers to a system used to structure and store user information, spending data, and other similar information.

[1307] "Payment processing" refers to the process of executing payment information received from users through external payment APIs.

[1308] "Payment result" refers to notification information indicating whether the payment process was successful or unsuccessful.

[1309] "Expenditure data" refers to information such as the amount and date of various purchases made by the user.

[1310] An "analysis algorithm" refers to a calculation method used to analyze a user's spending data to determine spending trends and the likelihood of budget overruns.

[1311] "Personalized promotions" refer to discount coupons and exclusive offers that are individually generated based on a user's purchase history and preference data.

[1312] An "alert" refers to a warning or notification issued to a user. For example, it could be a notification informing the user of a potential budget overrun.

[1313] A "payment reminder" refers to a notification that periodically informs the user of the payment deadline.

[1314] An "unpaid notice" refers to a notification informing the user that a specified payment has not yet been completed.

[1315] A "payment API" refers to a programmatic interface for processing payments in conjunction with external payment services.

[1316] "Budget" refers to the upper limit of expenses that a user should spend within a set period of time.

[1317] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[1318] System configuration and operation

[1319] This system includes the following main components:

[1320] 1. Receiving and storing user information

[1321] The terminal provides an interface for the user to enter registration information such as name, email address, and password. When the user enters the information and presses the "Register" button, the terminal sends this information to the server. The server stores the received user information in its database and notifies the terminal of the successful saving.

[1322] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, stores it in its database, and notifies the device that registration is complete.

[1323] 2. Payment Processing

[1324] When a user purchases a product, they enter payment information (credit card number, expiration date, security code, etc.) into the terminal. The terminal sends the payment information to the server. The server calls an external payment API to process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result via the terminal.

[1325] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[1326] 3. Analysis of expenditure data and budget management

[1327] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[1328] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if the budget is exceeded.

[1329] 4. Payment-related notices

[1330] The server collects information based on specific conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[1331] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when payment deadlines are approaching.

[1332] 5. Providing personalized promotions

[1333] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[1334] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[1335] This allows users to efficiently manage their payments and receive personalized, optimized promotions. The system becomes a powerful tool for optimizing the user experience and improving marketing effectiveness.

[1336] Example of a prompt

[1337] 1. "What information do new users need to sign up for the app?"

[1338] 2. "Please explain how to make a payment online using a credit card."

[1339] 3. "How can I set up budget management in the app and receive alerts when the budget is exceeded?"

[1340] 4. "Please explain how to set up recurring payment reminders."

[1341] 5. "How can we offer personalized promotions based on purchase history?"

[1342] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1343] Details of the processing steps

[1344] Step 1: Enter user information

[1345] The device displays a form for the user to enter their name, email address, and password.

[1346] Input: The user enters their name, email address, and password.

[1347] Output: The entered user information is stored on the device.

[1348] Specifically, the user opens the app and enters information into the displayed registration form.

[1349] Step 2: Sending Information

[1350] The terminal sends the entered information to the server.

[1351] Input: User information entered on the terminal.

[1352] Output: User information is sent to the server.

[1353] After the user completes the input and presses the "Register" button, the device sends the user information to the server.

[1354] Step 3: Saving Information

[1355] The server stores the received user information in a database.

[1356] Input: User information sent to the server.

[1357] Output: User information is saved to the database.

[1358] If the save is successful, the server sends a success message to the terminal.

[1359] Step 4: Enter payment information

[1360] The terminal provides an interface for the user to enter payment information.

[1361] Input: The user enters their payment information.

[1362] Output: The entered payment information is stored on the terminal.

[1363] Specifically, the user enters their credit card number and security code on the purchase screen.

[1364] Step 5: Submit payment information

[1365] The device sends payment information to the server.

[1366] Input: Payment information entered on the terminal.

[1367] Output: Payment information is sent to the server.

[1368] When the user presses the "Pay" button, the device sends the payment information to the server.

[1369] Step 6: Execute Payment

[1370] The server processes payments by calling an external payment API.

[1371] Input: Payment information sent to the server.

[1372] Output: Payment result from the payment API.

[1373] The server sends a payment request to the payment API and receives a response from the API.

[1374] Step 7: Notification of payment result

[1375] The server notifies the user of the payment result (success / failure) via the terminal.

[1376] Input: Payment result from the payment API.

[1377] Output: The payment result is notified to the device.

[1378] The server sends a message to the terminal indicating whether the payment was successful or failed, and displays it to the user.

[1379] Step 8: Collecting expenditure data

[1380] The server periodically retrieves user spending data from the database.

[1381] Input: Expense data stored in the database.

[1382] Output: The acquired expenditure data is aggregated on the server.

[1383] The server sets up scheduled tasks to periodically collect expenditure data from the database.

[1384] Step 9: Data Analysis

[1385] The server processes the spending data using an analysis algorithm to calculate the monthly spending situation.

[1386] Input: Aggregated expenditure data.

[1387] Output: Results of the analyzed spending situation.

[1388] The server runs an analysis algorithm to calculate monthly spending trends and abnormal spending.

[1389] Step 10: Check for budget overruns and generate alerts

[1390] The server compares the user's set budget with actual spending and checks for potential budget overruns. If a budget overrun is anticipated, the server generates an alert and notifies the user.

[1391] Input: Analysis results and user-defined budget.

[1392] Output: Alert notifications generated as needed.

[1393] Specifically, if there is a possibility of exceeding the budget at the end of the month, the server generates an alert message such as "You have exceeded your budget" and notifies the user.

[1394] Step 11: Generate payment-related notifications

[1395] The server generates payment reminders and non-payment notifications based on certain conditions.

[1396] Input: Payment due date data and outstanding payment data.

[1397] Output: Generated notification.

[1398] The server periodically generates and sends reminders based on the reminder conditions set by the user.

[1399] Step 12: Generate and notify personalized promotions

[1400] The server generates and notifies users of personalized promotions based on their purchase history and preference data.

[1401] Input: Purchase history data and preference data.

[1402] Output: Generated promotional notification.

[1403] Specifically, if a user frequently purchases products in a particular category, the server generates a discount promotion for those products and notifies the user.

[1404] (Application Example 1)

[1405] 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."

[1406] In modern society, many users struggle to efficiently manage multiple payments. Furthermore, insufficient tracking of expenses and budget management often leads to budget overruns. Additionally, effectively delivering personalized promotions to users remains a challenge. There is a need for a system that solves these problems, streamlining payment management while enhancing marketing effectiveness tailored to individual needs.

[1407] 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.

[1408] In this invention, the server includes means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of payment results, means for analyzing user spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for setting a budget and displaying monthly spending status in real time, means for generating alerts when the budget is exceeded, means for sending regular payment reminders and unpaid notifications to the user, and means for generating and providing discount coupons and limited offers based on purchase history. This enables users to efficiently manage their payments, prevent budget overruns, and receive promotions tailored to them.

[1409] "User information" refers to personal data provided by the user, such as name, email address, and payment information.

[1410] A "database" is a system for efficiently storing and managing data such as user information and payment history.

[1411] "Payment processing" refers to the process by which users complete payment using their payment information when purchasing goods or services.

[1412] "Notifications" are a means of communication used to inform users of payment results, budget overrun alerts, promotional information, and other relevant details.

[1413] "Expense data" refers to a record of payments a user has made in the past.

[1414] "Analysis" is the process of evaluating spending patterns and budget situations through users' spending data.

[1415] "Personalized promotions" refer to special offers and discounts generated based on a user's purchase history and preferences.

[1416] A "budget" is the maximum amount of money a user can spend within a certain period of time.

[1417] An "alert" is a notification that warns a user based on set conditions (e.g., exceeding the budget).

[1418] A "reminder" is a feature that periodically notifies users of payment deadlines or other important dates.

[1419] A "coupon" is a benefit that applies a discount when purchasing specific products or services.

[1420] A "limited offer" is a special deal that is offered to specific users for a limited time only.

[1421] This invention provides a system that streamlines user payment management and offers personalized promotions. The system's configuration and operation are described in detail below.

[1422] System Configuration

[1423] The system mainly consists of the following components:

[1424] 1. Receiving and storing user information

[1425] The device provides the interface, allowing the user to enter their name, email address, password, payment information, etc.

[1426] The server stores the received user information in a database.

[1427] 2. Payment Processing

[1428] When a user purchases a product, they enter their payment information into the device.

[1429] The server uses this payment information to call an external payment API and process the payment.

[1430] 3. Analysis of expenditure data and budget management

[1431] The server retrieves the user's past spending data from the database and uses an analysis algorithm to calculate the monthly spending pattern.

[1432] If a user has a budget set, the server will check for potential budget overruns and generate an alert.

[1433] 4. Payment-related notices

[1434] The server generates and sends periodic payment reminders and overdue payment notifications to the user.

[1435] 5. Providing personalized promotions

[1436] The server generates personalized promotions based on the user's purchase history and preference data, and notifies the user.

[1437] System operation

[1438] Receiving and storing user information

[1439] When a user signs up for the app, the device sends the entered information to the server. The server stores this information in a database and notifies the device that the saving was successful.

[1440] Payment processing

[1441] When a user purchases a product online, they enter their payment information and send it to the server via their device. The server calls an external payment API, executes the payment, and notifies the user of the result.

[1442] Analysis of expenditure data and budget management

[1443] The server analyzes the user's past spending data to calculate monthly spending and generates an alert if the set budget is exceeded. This analysis retrieves data from a database and applies a specific algorithm.

[1444] Payment-related notices

[1445] The server generates and sends regularly scheduled reminders and notifications when payment deadlines are approaching. This allows users to manage important payments without forgetting them.

[1446] Providing personalized promotions

[1447] The server generates and notifies users of personalized promotions, such as discount coupons and limited-time offers, based on their purchase history. These promotions are tailored to each user, improving marketing effectiveness.

[1448] Hardware and software to be used

[1449] Hardware: Smartphones, servers

[1450] Software: Flask (web framework), SQLite (database), external payment API

[1451] Specific example

[1452] For example, when a user registers for the app, they enter their name, email address, and password, and then press the registration button. This data is sent from the device to the server. The server stores this data in a database and sends an appropriate notification to the user.

[1453] Furthermore, when a user enters their credit card information to purchase a product, the server calls an external payment API to complete the payment. Spending data is automatically recorded, and an alert is generated at the end of the month if the budget is exceeded.

[1454] Examples of prompts for generative AI models

[1455] "I want to set a monthly budget. Can you tell me how to set a budget?"

[1456] "I'd like to know about this month's spending. Please tell me how much you spent."

[1457] "Do you have any discount coupons I can use for my next purchase?"

[1458] Thus, the system of the present invention can improve the user experience by streamlining user payment management and providing personalized promotions.

[1459] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1460] Step 1:

[1461] Receiving and storing user information

[1462] The device receives information such as the user's name, email address, password, and payment information, and sends that information to the server.

[1463] The server saves the received user information to the database. The input consists of personal data entered by the user, and data processing for saving to the database includes format conversion and validation. The output is a notification of successful saving.

[1464] Step 2:

[1465] Payment processing

[1466] When a user purchases goods online, they enter their payment information, which is then transmitted to the server via their device.

[1467] The server uses this payment information to convert the input data into a format suitable for sending to an external payment API. After this conversion and transmission process is complete, it receives the result (success / failure) from the payment API. The received result is processed by the server and notified to the user. Here, the input is the payment information and payment request, and the output is the payment result notification.

[1468] Step 3:

[1469] Analysis of expenditure data and budget management

[1470] The server retrieves the user's past spending data from the database.

[1471] Subsequently, a data analysis algorithm is applied to calculate monthly spending. This calculation aggregates past spending data and analyzes monthly spending patterns. As a result, the calculated spending status is output, and based on this, it is determined whether there is a possibility of budget overrun. The input is past spending data, and the output is spending status and budget overrun alerts.

[1472] Step 4:

[1473] Payment-related notices

[1474] The server generates and automatically sends periodic payment reminders and overdue payment notifications to users.

[1475] The inputs are the current date and the user's payment schedule data. Based on this, an SQL query is used to generate a list of unpaid items, and a reminder notification is created and sent to the user based on that list. The output is the reminder notification.

[1476] Step 5:

[1477] Providing personalized promotions

[1478] The server generates discount coupons and exclusive offers based on the user's purchase history and preference data.

[1479] The input is the user's past purchase data, which is analyzed to generate promotions for specific products. These promotions are sent to the user as notifications. The generated promotions include appropriate discounts and offers based on the specified purchase history. The output is a personalized promotion.

[1480] 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.

[1481] This invention combines a system that receives and stores user information, processes payments, analyzes spending, manages budgets, and provides personalized promotions with an emotion engine that recognizes user emotions. This system can dynamically adjust notification and promotional content based on user emotions. Each processing step in this system is described below.

[1482] System configuration and operation

[1483] This system includes the following main components:

[1484] 1. Receiving and storing user information

[1485] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[1486] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and press the register button. The device then sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[1487] 2. Payment Processing

[1488] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[1489] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[1490] 3. Analysis of expenditure data and budget management

[1491] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[1492] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[1493] 4. Payment-related notices

[1494] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[1495] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[1496] 5. Providing personalized promotions

[1497] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[1498] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[1499] 6. Integrating an emotion engine

[1500] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app.

[1501] The server receives emotion data sent from the terminal and analyzes the user's current emotional state.

[1502] Specific example: While a user is selecting products or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to a server. The server receives this data and, if the user is experiencing stress, displays a message to simplify the process.

[1503] 7. Adjusting notification content based on emotions

[1504] The server uses data from the emotion engine to adjust the content of the notifications it generates according to the user's emotional state. For example, if the user is feeling stressed, it will generate a more concise and easy-to-understand notification.

[1505] Specific example: If a user fails to make a payment, and the emotion engine recognizes the user's stress or anxiety, the server will send a gentle message such as, "Something went wrong. Please try again."

[1506] 8. Adjusting promotional content based on emotions

[1507] The server adjusts personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases.

[1508] Specific example: If the sentiment engine confirms that the user was satisfied with a previously purchased item, the server will send a discount coupon for a related product.

[1509] This system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the delivery of highly personalized services.

[1510] The following describes the processing flow.

[1511] User registration process

[1512] Step 1:

[1513] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[1514] Step 2:

[1515] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[1516] Step 3:

[1517] The server executes an SQL query to extract user information from the received request and save it to the database.

[1518] Step 4:

[1519] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[1520] Step 5:

[1521] The server sends the generated response to the terminal.

[1522] Step 6:

[1523] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[1524] Payment processing flow

[1525] Step 1:

[1526] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or payment account information).

[1527] Step 2:

[1528] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[1529] Step 3:

[1530] The server extracts the received payment information and uses a payment API client to call an external payment API.

[1531] Step 4:

[1532] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[1533] Step 5:

[1534] The server sends the generated response to the terminal.

[1535] Step 6:

[1536] The terminal receives the response and notifies the user of the payment result.

[1537] Budget management and expenditure analysis process

[1538] Step 1:

[1539] The user accesses the budget management page to check their set budget and spending status.

[1540] Step 2:

[1541] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[1542] Step 3:

[1543] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[1544] Step 4:

[1545] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[1546] Step 5:

[1547] The server generates the budget analysis results as a response in JSON format.

[1548] Step 6:

[1549] The server sends the generated response to the terminal.

[1550] Step 7:

[1551] The device receives the response and displays the analysis results to the user.

[1552] Payment-related notification flow

[1553] Step 1:

[1554] Users set up payment reminders.

[1555] Step 2:

[1556] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[1557] Step 3:

[1558] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[1559] Step 4:

[1560] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[1561] Step 5:

[1562] The server creates the generated notification as a response in JSON format.

[1563] Step 6:

[1564] The server sends the generated response to the terminal.

[1565] Step 7:

[1566] The device receives the response and displays a notification to the user.

[1567] Personalized promotion delivery process

[1568] Step 1:

[1569] Users can set up their preferences to receive personalized promotional information.

[1570] Step 2:

[1571] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[1572] Step 3:

[1573] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[1574] Step 4:

[1575] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[1576] Step 5:

[1577] The server generates the generated promotion as a response in JSON format.

[1578] Step 6:

[1579] The server sends the generated response to the terminal.

[1580] Step 7:

[1581] The device receives the response and displays promotional information to the user.

[1582] The process of integrating and utilizing an emotional engine

[1583] The flow of emotion recognition

[1584] Step 1:

[1585] While the user is using the app, the device's camera captures the user's facial expressions.

[1586] Step 2:

[1587] The device sends captured facial expression data to an emotion engine, which then analyzes the user's emotions.

[1588] Step 3:

[1589] The device sends the analyzed emotion data to the server.

[1590] Adjusting notifications based on emotions

[1591] Step 1:

[1592] The server adjusts the content of the notifications it generates based on the received emotion data, according to the user's emotional state.

[1593] Step 2:

[1594] The server generates the adjusted notification content as a response in JSON format.

[1595] Step 3:

[1596] The server sends the generated response to the terminal.

[1597] Step 4:

[1598] The device receives the response and displays a tailored notification to the user.

[1599] Emotion-based promotion adjustments

[1600] Step 1:

[1601] The server adjusts the promotional content it generates based on the received sentiment data, according to the user's emotional state.

[1602] Step 2:

[1603] The server generates the adjusted promotional content as a response in JSON format.

[1604] Step 3:

[1605] The server sends the generated response to the terminal.

[1606] Step 4:

[1607] The device receives the response and displays the adjusted promotional information to the user.

[1608] The above outlines the specific processing flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, personalized promotional offerings, and the integration of an emotion engine.

[1609] (Example 2)

[1610] 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."

[1611] The objective of this invention is to improve the user experience by streamlining user payment processing and expenditure management while providing flexible responses tailored to user emotions. Specifically, it is required to detect user emotions in real time, adjust notification and promotional content based on those emotions, and provide a more personalized service.

[1612] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1613] In this invention, the server includes means for receiving user information, means for storing the user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment results, means for analyzing the user's spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for detecting the user's emotions using a terminal, means for transmitting the emotion data to the server and analyzing the emotional state, means for adjusting notification content based on the emotional state, and means for adjusting promotion content based on the emotional state. This makes it possible to provide personalized services based on the user's emotions.

[1614] "User information" refers to information such as name, email address, and password that identifies an individual user and is used for authentication and service provision.

[1615] A "database" is a collection of electronically stored data used to efficiently manage user information and spending data.

[1616] "Payment processing" refers to the process of settling payments when a user purchases goods or services, and includes the use of credit card information and external payment APIs.

[1617] "Notifications" refer to information such as messages and alerts sent from the system to the user, including important information such as payment results and budget overruns.

[1618] "Expenditure data" refers to information about amounts and items recorded by users regarding purchases and payments, and is used for budget management and expenditure analysis.

[1619] An "analysis algorithm" is a means of identifying and evaluating specific patterns and trends in data, and is used in the analysis of user spending data.

[1620] A "personalized promotion" is a promotion that provides individual users with benefits and discounts optimized for them, based on their purchase history and preference data.

[1621] A "terminal" is a device used by a user for input and operation, and includes smartphones, personal computers, and other similar devices.

[1622] An "emotion engine" is a system that uses user input data and facial recognition to detect and analyze a user's emotional state.

[1623] "Emotional data" refers to data that indicates a user's emotional state, collected from facial expressions, words, actions, etc., and used for analysis.

[1624] "Adjusting notification content" refers to the process of changing the content and wording of notification messages according to the user's emotional state.

[1625] "Adjusting promotional content" refers to the process of changing the content and benefits of promotional information provided based on users' emotional states and preference data.

[1626] This invention combines a system that receives and stores user information, processes payments, analyzes spending, manages budgets, and provides personalized promotions with an emotion engine that recognizes user emotions. This system can dynamically adjust notification and promotional content based on user emotions. Specific embodiments of this system are described below.

[1627] System Overview

[1628] This system is mainly composed of the following key components:

[1629] Receiving and storing user information

[1630] Payment processing

[1631] Analysis of expenditure data and budget management

[1632] Payment-related notices

[1633] Providing personalized promotions

[1634] Embedding an emotion engine

[1635] Emotion-based notification adjustments

[1636] Adjusting promotional content based on emotions

[1637] Receiving and storing user information

[1638] The terminal provides an interface for users to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving. For example, when a new user enters their name, email address, and password and presses the registration button, the terminal sends that data to the server. The server receives this data, stores it in its database, and displays a registration completion message.

[1639] Payment processing

[1640] When a user purchases a product, they enter their payment information into a terminal. The terminal sends this payment information to a server. The server uses this information to call an external payment API and process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result. For example, when a user purchases a product online, they enter their credit card information and press the payment button, sending that information to the server. The server calls an external payment API to execute the payment and notifies the user of the result.

[1641] Analysis of expenditure data and budget management

[1642] The server retrieves the user's past spending data from a database and uses an analysis algorithm to calculate monthly spending. If the user has set a budget, the server checks for potential budget overruns and generates an alert. For example, if a user sets their own budget within the app and wants to track their monthly spending, the server aggregates the spending data at the end of the month and generates an alert to notify the user if the budget has been exceeded.

[1643] Payment-related notices

[1644] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and overdue payment notices. Specifically, if a user sets up periodic reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[1645] Providing personalized promotions

[1646] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server notifies the user of the generated promotions. For example, if a user frequently purchases products in a particular category, the server will generate and notify the user of discount promotions for products in that category.

[1647] Embedding an emotion engine

[1648] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app. The server receives the emotion data sent from the device and analyzes the user's current emotional state. For example, while the user is selecting a product or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to the server. The server receives this data and, if the user is feeling stressed, displays a message to simplify the process.

[1649] Emotion-based notification adjustments

[1650] The server adjusts the content of notifications it generates based on data from the emotion engine, according to the user's emotional state. For example, if the user is stressed, it generates a more concise and easy-to-understand notification. Specifically, if the emotion engine recognizes the user's stress or anxiety when a payment fails, the server will send a message in a gentler tone, such as "There was a problem. Please try again."

[1651] Adjusting promotional content based on emotions

[1652] The server adjusts the content of personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases. Specifically, if the emotion engine confirms that the user was satisfied with a previously purchased product, the server will send a discount coupon for a related product.

[1653] Examples of prompt statements

[1654] As a concrete example, one could consider inputting the following prompt message into a generative AI model.

[1655] Prompt: "Please explain in detail how to generate personalized promotions based on users' purchase history and sentiment data."

[1656] As described above, this system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the provision of highly personalized services.

[1657] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1658] Step 1: Enter and receive user information

[1659] Input: The user enters their name, email address, and password into the device.

[1660] Specific operation: The terminal provides an input form, the user enters the required information and presses the registration button. The entered information is format-checked, and if there are no problems, it is sent to the server.

[1661] Output: Format check results and user information sent to the server if correct.

[1662] Step 2: Saving User Information

[1663] Input: User information sent from the device.

[1664] Specific operation: The server saves the received user information to the database. It returns the success or failure of the save to the terminal.

[1665] Output: User information saved in the database and notification of successful saving.

[1666] Step 3: Enter and receive payment information

[1667] Input: The user enters their credit card information into the device.

[1668] Specific operation: The terminal provides a form for entering payment information, the user enters the information and presses the payment button. The entered information is sent to the server.

[1669] Output: Payment information sent to the server.

[1670] Step 4: Payment Processing

[1671] Input: Payment information sent from the device.

[1672] Specific operation: The server sends the received payment information to an external payment API and executes the payment. The payment result is returned from the API, and the server notifies the user of the result.

[1673] Output: The result of the payment (success or failure) and the notification thereof.

[1674] Step 5: Collect and store spending data

[1675] Input: Payment processing result data.

[1676] Specific operation: If the payment processing is successful, the server saves the expenditure data to the database. If it fails, it is recorded as an error log.

[1677] Output: Expenditure data stored in the database, or error logs.

[1678] Step 6: Analysis of monthly expenses

[1679] Input: User spending data stored in the database.

[1680] Specific operation: At the end of the month, the server retrieves expenditure data from the database and uses an analysis algorithm to calculate the monthly expenditure status. If a budget is set, it also checks for the possibility of budget overrun.

[1681] Output: Monthly spending report and budget overrun alerts.

[1682] Step 7: Generate payment-related notifications

[1683] Input: Expense data and user settings stored in the database.

[1684] Specific operation: The server periodically collects user payment due dates and outstanding payment information, and generates reminders and notifications.

[1685] Output: Payment reminders and non-payment notifications to users.

[1686] Step 8: Generating Personalized Promotions

[1687] Input: User purchase history and preference data.

[1688] Specific operation: The server analyzes this data and generates personalized promotions that are best suited to the user.

[1689] Output: Personalized promotional information notified to the user.

[1690] Step 9: Collecting emotional data

[1691] Input: User's facial recognition data and input data.

[1692] Specific operation: The device's camera captures the user's facial expressions, the emotion engine analyzes this data to generate emotion data, and sends it to the server.

[1693] Output: User sentiment data sent to the server.

[1694] Step 10: Analyzing emotional data

[1695] Input: Emotional data sent from the device.

[1696] Specific operation: The server analyzes the received emotion data to identify the user's current emotional state.

[1697] Output: Emotional state data.

[1698] Step 11: Adjusting notification content based on emotions

[1699] Input: Emotional state data.

[1700] Specific operation: The server adjusts the notification content based on the user's emotional state. For example, if the user is feeling stressed, the notification will be concise and expressed in a gentle tone.

[1701] Output: Notification content adjusted based on emotions.

[1702] Step 12: Adjusting promotional content based on emotions

[1703] Input: Emotional state data and promotional information.

[1704] Specific operation: The server adjusts promotional content based on the user's emotional state. For example, if the user is in a good mood, it will offer promotions that further encourage purchases.

[1705] Output: Promotional information tailored based on emotions.

[1706] (Application Example 2)

[1707] 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."

[1708] Traditional electronic payment systems and spending management applications have a problem in that they do not take into account the user's emotional state, and therefore do not adequately optimize the user experience or reduce stress. Furthermore, personalized promotional offerings also have the problem of not being able to respond flexibly based on the user's real-time emotional changes.

[1709] 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 means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment result, means for analyzing the user's spending data, means for notifying the user of the analysis result, means for generating personalized promotions, means for providing the generated promotions to the user, means for acquiring emotional data and analyzing the user's emotional state, and means for adjusting notification content and payment processing methods based on the user's emotional state. This makes it possible to simplify payment processing according to the user's emotional state and to provide personalized notifications and promotions.

[1710] "User information" refers to the collective term for personal identification information such as the user's name, email address, and password, as well as transaction history data.

[1711] A "database" is an electronic storage location for systematically organizing, saving, and managing received user information.

[1712] "Payment processing" refers to a series of procedures that use payment information provided by the user to settle the payment for goods or services.

[1713] A "notification" is a message sent from the system to the user, such as payment results, analysis results, or promotional information.

[1714] "Expenditure data" refers to records of various payments and transactions made by the user.

[1715] "Analysis" is the process of evaluating and calculating users' consumption trends and budget management status based on collected spending data and other user information.

[1716] "Personalized promotions" refer to the provision of discounts and benefits optimized for each user, based on their individual purchase history and preference data.

[1717] "Emotional data" refers to digital data that indicates a user's emotional state, obtained from their facial expressions and behavior.

[1718] "Emotional state" refers to the user's current mental and psychological state, as analyzed from emotional data.

[1719] "Simplification" is the act of reducing complexity in order to make operating procedures and processes intuitive and easy to understand in accordance with the user's emotional state.

[1720] This invention provides technical means for realizing a smartphone application that dynamically adjusts payment processing and notification content while taking into account the user's emotional state. Here, the configuration and operation of each component of this system are described in detail.

[1721] System Configuration

[1722] The main hardware components of this system include a smartphone (with a built-in camera). The main software components include an emotion recognition library (e.g., emotion_recognition), an HTTP request library (e.g., requests), and an external payment API wrapper (e.g., payment_api).

[1723] Receiving and storing user information

[1724] The terminal provides an interface for the user to enter information such as their name, email address, and password. Once the user enters the required information, the terminal sends that information to the server for storage in a database. The server stores the received data in the database and notifies the terminal of the successful storage.

[1725] Acquisition and analysis of emotional data

[1726] The device's built-in camera is used to capture an image of the user's face, and this image is analyzed using an emotion recognition library. The emotion data is sent to the server as numerical data representing the user's current emotional state (e.g., stress, happiness). Based on this data, the server evaluates the user's emotional state and takes appropriate action.

[1727] Adjustment of payment processing and notification content

[1728] When a user purchases goods or services, the device receives payment information from the user and sends it to a server. The server calls an external payment API to execute the payment. If the user's emotional state indicates high stress, a method is provided to simplify the payment process. The payment result is notified to the user in an appropriate tone according to their emotional state.

[1729] Providing personalized promotions

[1730] The server generates personalized promotions optimized for the user based on their purchase history and emotional data. For example, if a user is in a good mood, it offers discounts to encourage further purchases; if they are stressed, it presents promotions for relaxation products, etc.

[1731] Data and calculations to be used

[1732] The server aggregates user information, sentiment data, payment information, and purchase history data, and uses this information to simplify payment processing and adjust notification content. The data is processed through sentiment analysis libraries and external payment APIs to provide users with optimized advice and promotions.

[1733] Specific processing examples

[1734] For example, if a user's facial image is analyzed and indicates high stress levels, the server will send a gentle message such as, "An error occurred. Please try again." Also, if a user has previously purchased relaxation products and been satisfied, they may be offered related new promotions.

[1735] Example of a prompt

[1736] The following are specific examples of prompt messages to send to a generative AI model:

[1737] A user has registered for the app and entered their email address and password. Write code to retrieve the user's emotion recognition data and suggest appropriate notifications and payment methods based on their different emotional states.

[1738] This will enable simplified payment processing based on the user's emotional state, as well as the delivery of personalized notifications and promotions.

[1739] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1740] Step 1: Register User Information

[1741] The terminal provides an interface for the user to enter information such as their name, email address, and password. Once the user enters the information, the data is sent to the server. The server stores the received information in a database and sends a message back to the terminal confirming that the data was successfully saved.

[1742] Input: Information entered by the user, such as name, email address, and password.

[1743] Data processing: none

[1744] Calculation: none

[1745] Output: Message indicating successful save

[1746] Step 2: Acquiring emotional data

[1747] The device uses its built-in camera to acquire an image of the user's face. This image is input into an emotion recognition library to generate emotion data. This data is sent to a server. The server stores the received emotion data and makes it available for processing.

[1748] Input: Face image

[1749] Data processing: Convert facial expression information into numerical data and then into emotional data.

[1750] Calculation: Generation of emotion data using emotion recognition algorithms

[1751] Output: Sentiment data

[1752] Step 3: Execute payment processing

[1753] The user enters payment information (e.g., credit card information) for the goods or services they wish to purchase into the terminal. The terminal sends this payment information to the server. The server calls an external payment API to execute the payment. If the user's emotional data indicates high stress, the process is simplified. The payment result is adjusted based on the emotional data and communicated to the user.

[1754] Input: Payment information, sentiment data

[1755] Data processing: Converting payment information into the appropriate format.

[1756] Calculation: Payment API call and retrieval of payment results

[1757] Output: Payment result notification

[1758] Step 4: Spending Log Analysis

[1759] The server retrieves the user's past spending data from the database and calculates their monthly spending. It uses an analytical algorithm to aggregate the spending data and generates an alert if the user's budget is exceeded.

[1760] Input: Past spending data

[1761] Data processing: Aggregation of monthly expenditure data

[1762] Calculation: Use an analytical algorithm to calculate spending patterns.

[1763] Output: Expenditure analysis results, budget overrun alerts

[1764] Step 5: Adjusting notification content

[1765] The server evaluates the user's current emotional state based on emotional data and optimizes the notification content accordingly. For example, if the user is feeling stressed, it generates a concise and easy-to-understand notification.

[1766] Input: Sentiment data, analysis results

[1767] Data processing: Generating notification messages

[1768] Calculation: Optimization of notification content based on emotional state

[1769] Output: Notification message

[1770] Step 6: Offer personalized promotions

[1771] The server generates personalized promotions based on the user's purchase history and emotional data. Based on emotional data, it provides promotions that encourage purchases when the user is in a good mood, and promotions for relaxation products, etc., when the user is feeling stressed.

[1772] Input: Purchase history, sentiment data

[1773] Data processing: Customization of promotional content

[1774] Calculation: Generating promotions based on purchase history and sentiment data

[1775] Output: Promotion message

[1776] This series of processing steps enables flexible responses tailored to the user's emotional state, optimizing the user experience.

[1777] 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.

[1778] 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.

[1779] 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.

[1780] [Fourth Embodiment]

[1781] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1782] 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.

[1783] 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).

[1784] 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.

[1785] 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.

[1786] 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).

[1787] 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.

[1788] 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.

[1789] 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.

[1790] 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.

[1791] 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.

[1792] 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.

[1793] 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".

[1794] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[1795] System configuration and operation

[1796] This system includes the following main components:

[1797] 1. Receiving and storing user information

[1798] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[1799] Specific example: For instance, when a new user signs up for an app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[1800] 2. Payment Processing

[1801] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[1802] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[1803] 3. Analysis of expenditure data and budget management

[1804] The server retrieves the user's past spending data from the database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[1805] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[1806] 4. Payment-related notices

[1807] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[1808] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[1809] 5. Providing personalized promotions

[1810] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[1811] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[1812] These features allow users to efficiently manage their payments and receive personalized promotions. This system is a powerful tool for optimizing the user experience and improving marketing effectiveness.

[1813] The following describes the processing flow.

[1814] User registration process

[1815] Step 1:

[1816] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[1817] Step 2:

[1818] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[1819] Step 3:

[1820] The server executes an SQL query to extract user information from the received request and save it to the database.

[1821] Step 4:

[1822] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[1823] Step 5:

[1824] The server sends the generated response to the terminal.

[1825] Step 6:

[1826] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[1827] Payment processing flow

[1828] Step 1:

[1829] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or PayPay account information).

[1830] Step 2:

[1831] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[1832] Step 3:

[1833] The server extracts the received payment information and uses a payment API client to call an external payment API.

[1834] Step 4:

[1835] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[1836] Step 5:

[1837] The server sends the generated response to the terminal.

[1838] Step 6:

[1839] The terminal receives the response and notifies the user of the payment result.

[1840] Budget management and expenditure analysis process

[1841] Step 1:

[1842] The user accesses the budget management page to check their set budget and spending status.

[1843] Step 2:

[1844] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[1845] Step 3:

[1846] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[1847] Step 4:

[1848] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[1849] Step 5:

[1850] The server generates the budget analysis results as a response in JSON format.

[1851] Step 6:

[1852] The server sends the generated response to the terminal.

[1853] Step 7:

[1854] The device receives the response and displays the analysis results to the user.

[1855] Payment-related notification flow

[1856] Step 1:

[1857] Users set up payment reminders.

[1858] Step 2:

[1859] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[1860] Step 3:

[1861] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[1862] Step 4:

[1863] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[1864] Step 5:

[1865] The server creates the generated notification as a response in JSON format.

[1866] Step 6:

[1867] The server sends the generated response to the terminal.

[1868] Step 7:

[1869] The device receives the response and displays a notification to the user.

[1870] Personalized promotion delivery process

[1871] Step 1:

[1872] Users can set up their preferences to receive personalized promotional information.

[1873] Step 2:

[1874] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[1875] Step 3:

[1876] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[1877] Step 4:

[1878] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[1879] Step 5:

[1880] The server generates the generated promotion as a response in JSON format.

[1881] Step 6:

[1882] The server sends the generated response to the terminal.

[1883] Step 7:

[1884] The device receives the response and displays promotional information to the user.

[1885] The above outlines the specific process flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, and personalized promotional offerings.

[1886] (Example 1)

[1887] 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".

[1888] In today's consumer lifestyle, efficiently managing multiple payments and personalized marketing is extremely difficult. This leads to problems such as missed payments and budget overruns for users, and makes it challenging for businesses to accurately capture user purchasing preferences through marketing. There is a need for systems that can address these challenges.

[1889] 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.

[1890] In this invention, the server includes means for receiving user information, means for storing it in a database, means for processing payments, means for notifying payment results, means for collecting spending data, means for analyzing data, means for notifying analysis results, means for generating personalized promotions, means for providing promotions, means for comparing spending data with a budget and generating alerts if there is a possibility of budget overrun, and means for periodically generating payment reminders and unpaid notifications. This enables users to efficiently manage their payments and allows companies to conduct personalized marketing to users.

[1891] "User information" refers to personally identifiable information such as the user's name, email address, and password.

[1892] A "database" refers to a system used to structure and store user information, spending data, and other similar information.

[1893] "Payment processing" refers to the process of executing payment information received from users through external payment APIs.

[1894] "Payment result" refers to notification information indicating whether the payment process was successful or unsuccessful.

[1895] "Expenditure data" refers to information such as the amount and date of various purchases made by the user.

[1896] An "analysis algorithm" refers to a calculation method used to analyze a user's spending data to determine spending trends and the likelihood of budget overruns.

[1897] "Personalized promotions" refer to discount coupons and exclusive offers that are individually generated based on a user's purchase history and preference data.

[1898] An "alert" refers to a warning or notification issued to a user. For example, it could be a notification informing the user of a potential budget overrun.

[1899] A "payment reminder" refers to a notification that periodically informs the user of the payment deadline.

[1900] An "unpaid notice" refers to a notification informing the user that a specified payment has not yet been completed.

[1901] A "payment API" refers to a programmatic interface for processing payments in conjunction with external payment services.

[1902] "Budget" refers to the upper limit of expenses that a user should spend within a set period of time.

[1903] This invention provides a system that streamlines user payment management and improves the effectiveness of personalized marketing. The system includes means for receiving and storing user information, processing payments, analyzing spending, generating alerts, and providing personalized promotions.

[1904] System configuration and operation

[1905] This system includes the following main components:

[1906] 1. Receiving and storing user information

[1907] The terminal provides an interface for the user to enter registration information such as name, email address, and password. When the user enters the information and presses the "Register" button, the terminal sends this information to the server. The server stores the received user information in its database and notifies the terminal of the successful saving.

[1908] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and then press the register button. The device sends this data to the server. The server receives this data, stores it in its database, and notifies the device that registration is complete.

[1909] 2. Payment Processing

[1910] When a user purchases a product, they enter payment information (credit card number, expiration date, security code, etc.) into the terminal. The terminal sends the payment information to the server. The server calls an external payment API to process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result via the terminal.

[1911] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[1912] 3. Analysis of expenditure data and budget management

[1913] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[1914] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if the budget is exceeded.

[1915] 4. Payment-related notices

[1916] The server collects information based on specific conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[1917] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when payment deadlines are approaching.

[1918] 5. Providing personalized promotions

[1919] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[1920] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[1921] This allows users to efficiently manage their payments and receive personalized, optimized promotions. The system becomes a powerful tool for optimizing the user experience and improving marketing effectiveness.

[1922] Example of a prompt

[1923] 1. "What information do new users need to sign up for the app?"

[1924] 2. "Please explain how to make a payment online using a credit card."

[1925] 3. "How can I set up budget management in the app and receive alerts when the budget is exceeded?"

[1926] 4. "Please explain how to set up recurring payment reminders."

[1927] 5. "How can we offer personalized promotions based on purchase history?"

[1928] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1929] Details of the processing steps

[1930] Step 1: Enter user information

[1931] The device displays a form for the user to enter their name, email address, and password.

[1932] Input: The user enters their name, email address, and password.

[1933] Output: The entered user information is stored on the device.

[1934] Specifically, the user opens the app and enters information into the displayed registration form.

[1935] Step 2: Sending Information

[1936] The terminal sends the entered information to the server.

[1937] Input: User information entered on the terminal.

[1938] Output: User information is sent to the server.

[1939] After the user completes the input and presses the "Register" button, the device sends the user information to the server.

[1940] Step 3: Saving Information

[1941] The server stores the received user information in a database.

[1942] Input: User information sent to the server.

[1943] Output: User information is saved to the database.

[1944] If the save is successful, the server sends a success message to the terminal.

[1945] Step 4: Enter payment information

[1946] The terminal provides an interface for the user to enter payment information.

[1947] Input: The user enters their payment information.

[1948] Output: The entered payment information is stored on the terminal.

[1949] Specifically, the user enters their credit card number and security code on the purchase screen.

[1950] Step 5: Submit payment information

[1951] The device sends payment information to the server.

[1952] Input: Payment information entered on the terminal.

[1953] Output: Payment information is sent to the server.

[1954] When the user presses the "Pay" button, the device sends the payment information to the server.

[1955] Step 6: Execute Payment

[1956] The server processes payments by calling an external payment API.

[1957] Input: Payment information sent to the server.

[1958] Output: Payment result from the payment API.

[1959] The server sends a payment request to the payment API and receives a response from the API.

[1960] Step 7: Notification of payment result

[1961] The server notifies the user of the payment result (success / failure) via the terminal.

[1962] Input: Payment result from the payment API.

[1963] Output: The payment result is notified to the device.

[1964] The server sends a message to the terminal indicating whether the payment was successful or failed, and displays it to the user.

[1965] Step 8: Collecting expenditure data

[1966] The server periodically retrieves user spending data from the database.

[1967] Input: Expense data stored in the database.

[1968] Output: The acquired expenditure data is aggregated on the server.

[1969] The server sets up scheduled tasks to periodically collect expenditure data from the database.

[1970] Step 9: Data Analysis

[1971] The server processes the spending data using an analysis algorithm to calculate the monthly spending situation.

[1972] Input: Aggregated expenditure data.

[1973] Output: Results of the analyzed spending situation.

[1974] The server runs an analysis algorithm to calculate monthly spending trends and abnormal spending.

[1975] Step 10: Check for budget overruns and generate alerts

[1976] The server compares the user's set budget with actual spending and checks for potential budget overruns. If a budget overrun is anticipated, the server generates an alert and notifies the user.

[1977] Input: Analysis results and user-defined budget.

[1978] Output: Alert notifications generated as needed.

[1979] Specifically, if there is a possibility of exceeding the budget at the end of the month, the server generates an alert message such as "You have exceeded your budget" and notifies the user.

[1980] Step 11: Generate payment-related notifications

[1981] The server generates payment reminders and non-payment notifications based on certain conditions.

[1982] Input: Payment due date data and outstanding payment data.

[1983] Output: Generated notification.

[1984] The server periodically generates and sends reminders based on the reminder conditions set by the user.

[1985] Step 12: Generate and notify personalized promotions

[1986] The server generates and notifies users of personalized promotions based on their purchase history and preference data.

[1987] Input: Purchase history data and preference data.

[1988] Output: Generated promotional notification.

[1989] Specifically, if a user frequently purchases products in a particular category, the server generates a discount promotion for those products and notifies the user.

[1990] (Application Example 1)

[1991] 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".

[1992] In modern society, many users struggle to efficiently manage multiple payments. Furthermore, insufficient tracking of expenses and budget management often leads to budget overruns. Additionally, effectively delivering personalized promotions to users remains a challenge. There is a need for a system that solves these problems, streamlining payment management while enhancing marketing effectiveness tailored to individual needs.

[1993] 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.

[1994] In this invention, the server includes means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of payment results, means for analyzing user spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for setting a budget and displaying monthly spending status in real time, means for generating alerts when the budget is exceeded, means for sending regular payment reminders and unpaid notifications to the user, and means for generating and providing discount coupons and limited offers based on purchase history. This enables users to efficiently manage their payments, prevent budget overruns, and receive promotions tailored to them.

[1995] "User information" refers to personal data provided by the user, such as name, email address, and payment information.

[1996] A "database" is a system for efficiently storing and managing data such as user information and payment history.

[1997] "Payment processing" refers to the process by which users complete payment using their payment information when purchasing goods or services.

[1998] "Notifications" are a means of communication used to inform users of payment results, budget overrun alerts, promotional information, and other relevant details.

[1999] "Expense data" refers to a record of payments a user has made in the past.

[2000] "Analysis" is the process of evaluating spending patterns and budget situations through users' spending data.

[2001] "Personalized promotions" refer to special offers and discounts generated based on a user's purchase history and preferences.

[2002] A "budget" is the maximum amount of money a user can spend within a certain period of time.

[2003] An "alert" is a notification that warns a user based on set conditions (e.g., exceeding the budget).

[2004] A "reminder" is a feature that periodically notifies users of payment deadlines or other important dates.

[2005] A "coupon" is a benefit that applies a discount when purchasing specific products or services.

[2006] A "limited offer" is a special deal that is offered to specific users for a limited time only.

[2007] This invention provides a system that streamlines user payment management and offers personalized promotions. The system's configuration and operation are described in detail below.

[2008] System Configuration

[2009] The system mainly consists of the following components:

[2010] 1. Receiving and storing user information

[2011] The device provides the interface, allowing the user to enter their name, email address, password, payment information, etc.

[2012] The server stores the received user information in a database.

[2013] 2. Payment Processing

[2014] When a user purchases a product, they enter their payment information into the device.

[2015] The server uses this payment information to call an external payment API and process the payment.

[2016] 3. Analysis of expenditure data and budget management

[2017] The server retrieves the user's past spending data from the database and uses an analysis algorithm to calculate the monthly spending pattern.

[2018] If a user has a budget set, the server will check for potential budget overruns and generate an alert.

[2019] 4. Payment-related notices

[2020] The server generates and sends periodic payment reminders and overdue payment notifications to the user.

[2021] 5. Providing personalized promotions

[2022] The server generates personalized promotions based on the user's purchase history and preference data, and notifies the user.

[2023] System operation

[2024] Receiving and storing user information

[2025] When a user signs up for the app, the device sends the entered information to the server. The server stores this information in a database and notifies the device that the saving was successful.

[2026] Payment processing

[2027] When a user purchases a product online, they enter their payment information and send it to the server via their device. The server calls an external payment API, executes the payment, and notifies the user of the result.

[2028] Analysis of expenditure data and budget management

[2029] The server analyzes the user's past spending data to calculate monthly spending and generates an alert if the set budget is exceeded. This analysis retrieves data from a database and applies a specific algorithm.

[2030] Payment-related notices

[2031] The server generates and sends regularly scheduled reminders and notifications when payment deadlines are approaching. This allows users to manage important payments without forgetting them.

[2032] Providing personalized promotions

[2033] The server generates and notifies users of personalized promotions, such as discount coupons and limited-time offers, based on their purchase history. These promotions are tailored to each user, improving marketing effectiveness.

[2034] Hardware and software to be used

[2035] Hardware: Smartphones, servers

[2036] Software: Flask (web framework), SQLite (database), external payment API

[2037] Specific example

[2038] For example, when a user registers for the app, they enter their name, email address, and password, and then press the registration button. This data is sent from the device to the server. The server stores this data in a database and sends an appropriate notification to the user.

[2039] Furthermore, when a user enters their credit card information to purchase a product, the server calls an external payment API to complete the payment. Spending data is automatically recorded, and an alert is generated at the end of the month if the budget is exceeded.

[2040] Examples of prompts for generative AI models

[2041] "I want to set a monthly budget. Can you tell me how to set a budget?"

[2042] "I'd like to know about this month's spending. Please tell me how much you spent."

[2043] "Do you have any discount coupons I can use for my next purchase?"

[2044] Thus, the system of the present invention can improve the user experience by streamlining user payment management and providing personalized promotions.

[2045] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2046] Step 1:

[2047] Receiving and storing user information

[2048] The device receives information such as the user's name, email address, password, and payment information, and sends that information to the server.

[2049] The server saves the received user information to the database. The input consists of personal data entered by the user, and data processing for saving to the database includes format conversion and validation. The output is a notification of successful saving.

[2050] Step 2:

[2051] Payment processing

[2052] When a user purchases goods online, they enter their payment information, which is then transmitted to the server via their device.

[2053] The server uses this payment information to convert the input data into a format suitable for sending to an external payment API. After this conversion and transmission process is complete, it receives the result (success / failure) from the payment API. The received result is processed by the server and notified to the user. Here, the input is the payment information and payment request, and the output is the payment result notification.

[2054] Step 3:

[2055] Analysis of expenditure data and budget management

[2056] The server retrieves the user's past spending data from the database.

[2057] Subsequently, a data analysis algorithm is applied to calculate monthly spending. This calculation aggregates past spending data and analyzes monthly spending patterns. As a result, the calculated spending status is output, and based on this, it is determined whether there is a possibility of budget overrun. The input is past spending data, and the output is spending status and budget overrun alerts.

[2058] Step 4:

[2059] Payment-related notices

[2060] The server generates and automatically sends periodic payment reminders and overdue payment notifications to users.

[2061] The inputs are the current date and the user's payment schedule data. Based on this, an SQL query is used to generate a list of unpaid items, and a reminder notification is created and sent to the user based on that list. The output is the reminder notification.

[2062] Step 5:

[2063] Providing personalized promotions

[2064] The server generates discount coupons and exclusive offers based on the user's purchase history and preference data.

[2065] The input is the user's past purchase data, which is analyzed to generate promotions for specific products. These promotions are sent to the user as notifications. The generated promotions include appropriate discounts and offers based on the specified purchase history. The output is a personalized promotion.

[2066] 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.

[2067] This invention combines a system that receives and stores user information, processes payments, analyzes spending, manages budgets, and provides personalized promotions with an emotion engine that recognizes user emotions. This system can dynamically adjust notification and promotional content based on user emotions. Each processing step in this system is described below.

[2068] System configuration and operation

[2069] This system includes the following main components:

[2070] 1. Receiving and storing user information

[2071] The terminal provides an interface for the user to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving.

[2072] Specific example: When a new user signs up for the app, they enter their name, email address, and password, and press the register button. The device then sends this data to the server. The server receives this data, saves it to its database, and displays a message indicating that registration is complete.

[2073] 2. Payment Processing

[2074] When a user purchases a product, they enter their payment information into the terminal. The terminal sends the payment information to the server. The server uses the payment information to call an external payment API and processes the payment. After the payment result (success / failure) is returned, the server notifies the user of the result.

[2075] Specific example: When a user purchases a product online, they enter their credit card information and press the payment button. The device then sends this information to a server. The server calls an external payment API to execute the payment and notifies the user of the result.

[2076] 3. Analysis of expenditure data and budget management

[2077] The server retrieves the user's past spending data from a database and uses an analytical algorithm to calculate monthly spending patterns. If the user has a budget set, the server checks for potential budget overruns and generates alerts.

[2078] Specific example: If a user wants to set a budget within the app and track their monthly spending, the server will aggregate the spending data at the end of the month and generate an alert to notify the user if they have exceeded their budget.

[2079] 4. Payment-related notices

[2080] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and unpaid notices.

[2081] Specific example: If a user sets up recurring reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[2082] 5. Providing personalized promotions

[2083] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server then notifies the user of the generated promotions.

[2084] Specific example: If a user frequently purchases products in a particular category, the server generates discount promotions for those products and notifies the user.

[2085] 6. Integrating an emotion engine

[2086] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app.

[2087] The server receives emotion data sent from the terminal and analyzes the user's current emotional state.

[2088] Specific example: While a user is selecting products or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to a server. The server receives this data and, if the user is experiencing stress, displays a message to simplify the process.

[2089] 7. Adjusting notification content based on emotions

[2090] The server uses data from the emotion engine to adjust the content of the notifications it generates according to the user's emotional state. For example, if the user is feeling stressed, it will generate a more concise and easy-to-understand notification.

[2091] Specific example: If a user fails to make a payment, and the emotion engine recognizes the user's stress or anxiety, the server will send a gentle message such as, "Something went wrong. Please try again."

[2092] 8. Adjusting promotional content based on emotions

[2093] The server adjusts personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases.

[2094] Specific example: If the sentiment engine confirms that the user was satisfied with a previously purchased item, the server will send a discount coupon for a related product.

[2095] This system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the delivery of highly personalized services.

[2096] The following describes the processing flow.

[2097] User registration process

[2098] Step 1:

[2099] The user accesses the device registration screen. The user enters the required information, such as their name, email address, and password.

[2100] Step 2:

[2101] The terminal converts the entered user information into JSON format and sends it to the / register_user endpoint as an HTTP POST request.

[2102] Step 3:

[2103] The server executes an SQL query to extract user information from the received request and save it to the database.

[2104] Step 4:

[2105] The server verifies that the user information has been correctly saved to the database and generates a response indicating that the saving was successful.

[2106] Step 5:

[2107] The server sends the generated response to the terminal.

[2108] Step 6:

[2109] The device receives the response and displays a message on the screen indicating that registration was successful for the user.

[2110] Payment processing flow

[2111] Step 1:

[2112] The user accesses the payment screen, selects the product they wish to purchase, and then enters their payment information (e.g., credit card information or payment account information).

[2113] Step 2:

[2114] The terminal converts the entered payment information into JSON format and sends it to the / make_payment endpoint as an HTTP POST request.

[2115] Step 3:

[2116] The server extracts the received payment information and uses a payment API client to call an external payment API.

[2117] Step 4:

[2118] The server receives the payment result (success / failure) returned from the payment API and generates a response indicating the payment result.

[2119] Step 5:

[2120] The server sends the generated response to the terminal.

[2121] Step 6:

[2122] The terminal receives the response and notifies the user of the payment result.

[2123] Budget management and expenditure analysis process

[2124] Step 1:

[2125] The user accesses the budget management page to check their set budget and spending status.

[2126] Step 2:

[2127] The device sends an HTTP GET request containing the user ID to the / budget_analysis endpoint.

[2128] Step 3:

[2129] The server executes an SQL query to retrieve the user's spending data from the database based on the received user ID.

[2130] Step 4:

[2131] The server performs budget analysis based on the acquired expenditure data. If a budget overrun occurs, it records that fact.

[2132] Step 5:

[2133] The server generates the budget analysis results as a response in JSON format.

[2134] Step 6:

[2135] The server sends the generated response to the terminal.

[2136] Step 7:

[2137] The device receives the response and displays the analysis results to the user.

[2138] Payment-related notification flow

[2139] Step 1:

[2140] Users set up payment reminders.

[2141] Step 2:

[2142] The device sends an HTTP GET request to the / payment_notifications endpoint, which includes the user ID and reminder settings.

[2143] Step 3:

[2144] The server retrieves information stored in the database based on the received user ID and reminder setting data.

[2145] Step 4:

[2146] The server executes the reminder generation logic and generates the necessary payment reminders for the user.

[2147] Step 5:

[2148] The server creates the generated notification as a response in JSON format.

[2149] Step 6:

[2150] The server sends the generated response to the terminal.

[2151] Step 7:

[2152] The device receives the response and displays a notification to the user.

[2153] Personalized promotion delivery process

[2154] Step 1:

[2155] Users can set up their preferences to receive personalized promotional information.

[2156] Step 2:

[2157] The device sends an HTTP GET request containing the user ID to the / personal_promotions endpoint.

[2158] Step 3:

[2159] The server executes an SQL query from the database to retrieve the user's purchase history based on the received user ID.

[2160] Step 4:

[2161] The server executes an algorithm to generate personalized promotions based on the acquired purchase history data.

[2162] Step 5:

[2163] The server generates the generated promotion as a response in JSON format.

[2164] Step 6:

[2165] The server sends the generated response to the terminal.

[2166] Step 7:

[2167] The device receives the response and displays promotional information to the user.

[2168] The process of integrating and utilizing an emotional engine

[2169] The flow of emotion recognition

[2170] Step 1:

[2171] While the user is using the app, the device's camera captures the user's facial expressions.

[2172] Step 2:

[2173] The device sends captured facial expression data to an emotion engine, which then analyzes the user's emotions.

[2174] Step 3:

[2175] The device sends the analyzed emotion data to the server.

[2176] Adjusting notifications based on emotions

[2177] Step 1:

[2178] The server adjusts the content of the notifications it generates based on the received emotion data, according to the user's emotional state.

[2179] Step 2:

[2180] The server generates the adjusted notification content as a response in JSON format.

[2181] Step 3:

[2182] The server sends the generated response to the terminal.

[2183] Step 4:

[2184] The device receives the response and displays a tailored notification to the user.

[2185] Emotion-based promotion adjustments

[2186] Step 1:

[2187] The server adjusts the promotional content it generates based on the received sentiment data, according to the user's emotional state.

[2188] Step 2:

[2189] The server generates the adjusted promotional content as a response in JSON format.

[2190] Step 3:

[2191] The server sends the generated response to the terminal.

[2192] Step 4:

[2193] The device receives the response and displays the adjusted promotional information to the user.

[2194] The above outlines the specific processing flow for user registration, payment processing, budget management and spending analysis, payment-related notifications, personalized promotional offerings, and the integration of an emotion engine.

[2195] (Example 2)

[2196] 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".

[2197] The objective of this invention is to improve the user experience by streamlining user payment processing and expenditure management while providing flexible responses tailored to user emotions. Specifically, it is required to detect user emotions in real time, adjust notification and promotional content based on those emotions, and provide a more personalized service.

[2198] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[2199] In this invention, the server includes means for receiving user information, means for storing the user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment results, means for analyzing the user's spending data, means for notifying the user of the analysis results, means for generating personalized promotions, means for providing the generated promotions to the user, means for detecting the user's emotions using a terminal, means for transmitting the emotion data to the server and analyzing the emotional state, means for adjusting notification content based on the emotional state, and means for adjusting promotion content based on the emotional state. This makes it possible to provide personalized services based on the user's emotions.

[2200] "User information" refers to information such as name, email address, and password that identifies an individual user and is used for authentication and service provision.

[2201] A "database" is a collection of electronically stored data used to efficiently manage user information and spending data.

[2202] "Payment processing" refers to the process of settling payments when a user purchases goods or services, and includes the use of credit card information and external payment APIs.

[2203] "Notifications" refer to information such as messages and alerts sent from the system to the user, including important information such as payment results and budget overruns.

[2204] "Expenditure data" refers to information about amounts and items recorded by users regarding purchases and payments, and is used for budget management and expenditure analysis.

[2205] An "analysis algorithm" is a means of identifying and evaluating specific patterns and trends in data, and is used in the analysis of user spending data.

[2206] A "personalized promotion" is a promotion that provides individual users with benefits and discounts optimized for them, based on their purchase history and preference data.

[2207] A "terminal" is a device used by a user for input and operation, and includes smartphones, personal computers, and other similar devices.

[2208] An "emotion engine" is a system that uses user input data and facial recognition to detect and analyze a user's emotional state.

[2209] "Emotional data" refers to data that indicates a user's emotional state, collected from facial expressions, words, actions, etc., and used for analysis.

[2210] "Adjusting notification content" refers to the process of changing the content and wording of notification messages according to the user's emotional state.

[2211] "Adjusting promotional content" refers to the process of changing the content and benefits of promotional information provided based on users' emotional states and preference data.

[2212] This invention combines a system that receives and stores user information, processes payments, analyzes spending, manages budgets, and provides personalized promotions with an emotion engine that recognizes user emotions. This system can dynamically adjust notification and promotional content based on user emotions. Specific embodiments of this system are described below.

[2213] System Overview

[2214] This system is mainly composed of the following key components:

[2215] Receiving and storing user information

[2216] Payment processing

[2217] Analysis of expenditure data and budget management

[2218] Payment-related notices

[2219] Providing personalized promotions

[2220] Embedding an emotion engine

[2221] Emotion-based notification adjustments

[2222] Adjusting promotional content based on emotions

[2223] Receiving and storing user information

[2224] The terminal provides an interface for users to enter registration information (name, email address, password, etc.). Once the user enters the information, the terminal sends this information to the server. The server stores the received user information in a database and notifies the terminal of the successful saving. For example, when a new user enters their name, email address, and password and presses the registration button, the terminal sends that data to the server. The server receives this data, stores it in its database, and displays a registration completion message.

[2225] Payment processing

[2226] When a user purchases a product, they enter their payment information into a terminal. The terminal sends this payment information to a server. The server uses this information to call an external payment API and process the payment. After the payment result (success / failure) is returned, the server notifies the user of the result. For example, when a user purchases a product online, they enter their credit card information and press the payment button, sending that information to the server. The server calls an external payment API to execute the payment and notifies the user of the result.

[2227] Analysis of expenditure data and budget management

[2228] The server retrieves the user's past spending data from a database and uses an analysis algorithm to calculate monthly spending. If the user has set a budget, the server checks for potential budget overruns and generates an alert. For example, if a user sets their own budget within the app and wants to track their monthly spending, the server aggregates the spending data at the end of the month and generates an alert to notify the user if the budget has been exceeded.

[2229] Payment-related notices

[2230] The server collects information based on certain conditions in order to generate payment-related notifications for users. For example, it generates and notifies users of periodic payment reminders and overdue payment notices. Specifically, if a user sets up periodic reminders, the server will periodically generate reminders and notify the user when the payment deadline approaches.

[2231] Providing personalized promotions

[2232] The server generates personalized promotions based on the user's purchase history and preference data. This includes discount coupons and limited-time offers for specific products. The server notifies the user of the generated promotions. For example, if a user frequently purchases products in a particular category, the server will generate and notify the user of discount promotions for products in that category.

[2233] Embedding an emotion engine

[2234] The device detects the user's emotions using facial recognition and input data. This information is collected while the user is using the app. The server receives the emotion data sent from the device and analyzes the user's current emotional state. For example, while the user is selecting a product or going through the payment process, the device's camera recognizes the user's facial expressions and sends emotion data to the server. The server receives this data and, if the user is feeling stressed, displays a message to simplify the process.

[2235] Emotion-based notification adjustments

[2236] The server adjusts the content of notifications it generates based on data from the emotion engine, according to the user's emotional state. For example, if the user is stressed, it generates a more concise and easy-to-understand notification. Specifically, if the emotion engine recognizes the user's stress or anxiety when a payment fails, the server will send a message in a gentler tone, such as "There was a problem. Please try again."

[2237] Adjusting promotional content based on emotions

[2238] The server adjusts the content of personalized promotions based on data from the emotion engine. For example, if a user is in a good mood, it will offer promotions that encourage further purchases. Specifically, if the emotion engine confirms that the user was satisfied with a previously purchased product, the server will send a discount coupon for a related product.

[2239] Examples of prompt statements

[2240] As a concrete example, one could consider inputting the following prompt message into a generative AI model.

[2241] Prompt: "Please explain in detail how to generate personalized promotions based on users' purchase history and sentiment data."

[2242] As described above, this system is a powerful tool for optimizing the user experience and improving marketing effectiveness. By incorporating an emotion engine, it becomes possible to respond flexibly to the user's emotional state, enabling the provision of highly personalized services.

[2243] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2244] Step 1: Enter and receive user information

[2245] Input: The user enters their name, email address, and password into the device.

[2246] Specific operation: The terminal provides an input form, the user enters the required information and presses the registration button. The entered information is format-checked, and if there are no problems, it is sent to the server.

[2247] Output: Format check results and user information sent to the server if correct.

[2248] Step 2: Saving User Information

[2249] Input: User information sent from the device.

[2250] Specific operation: The server saves the received user information to the database. It returns the success or failure of the save to the terminal.

[2251] Output: User information saved in the database and notification of successful saving.

[2252] Step 3: Enter and receive payment information

[2253] Input: The user enters their credit card information into the device.

[2254] Specific operation: The terminal provides a form for entering payment information, the user enters the information and presses the payment button. The entered information is sent to the server.

[2255] Output: Payment information sent to the server.

[2256] Step 4: Payment Processing

[2257] Input: Payment information sent from the device.

[2258] Specific operation: The server sends the received payment information to an external payment API and executes the payment. The payment result is returned from the API, and the server notifies the user of the result.

[2259] Output: The result of the payment (success or failure) and the notification thereof.

[2260] Step 5: Collect and store spending data

[2261] Input: Payment processing result data.

[2262] Specific operation: If the payment processing is successful, the server saves the expenditure data to the database. If it fails, it is recorded as an error log.

[2263] Output: Expenditure data stored in the database, or error logs.

[2264] Step 6: Analysis of monthly expenses

[2265] Input: User spending data stored in the database.

[2266] Specific operation: At the end of the month, the server retrieves expenditure data from the database and uses an analysis algorithm to calculate the monthly expenditure status. If a budget is set, it also checks for the possibility of budget overrun.

[2267] Output: Monthly spending report and budget overrun alerts.

[2268] Step 7: Generate payment-related notifications

[2269] Input: Expense data and user settings stored in the database.

[2270] Specific operation: The server periodically collects user payment due dates and outstanding payment information, and generates reminders and notifications.

[2271] Output: Payment reminders and non-payment notifications to users.

[2272] Step 8: Generating Personalized Promotions

[2273] Input: User purchase history and preference data.

[2274] Specific operation: The server analyzes this data and generates personalized promotions that are best suited to the user.

[2275] Output: Personalized promotional information notified to the user.

[2276] Step 9: Collecting emotional data

[2277] Input: User's facial recognition data and input data.

[2278] Specific operation: The device's camera captures the user's facial expressions, the emotion engine analyzes this data to generate emotion data, and sends it to the server.

[2279] Output: User sentiment data sent to the server.

[2280] Step 10: Analyzing emotional data

[2281] Input: Emotional data sent from the device.

[2282] Specific operation: The server analyzes the received emotion data to identify the user's current emotional state.

[2283] Output: Emotional state data.

[2284] Step 11: Adjusting notification content based on emotions

[2285] Input: Emotional state data.

[2286] Specific operation: The server adjusts the notification content based on the user's emotional state. For example, if the user is feeling stressed, the notification will be concise and expressed in a gentle tone.

[2287] Output: Notification content adjusted based on emotions.

[2288] Step 12: Adjusting promotional content based on emotions

[2289] Input: Emotional state data and promotional information.

[2290] Specific operation: The server adjusts promotional content based on the user's emotional state. For example, if the user is in a good mood, it will offer promotions that further encourage purchases.

[2291] Output: Promotional information tailored based on emotions.

[2292] (Application Example 2)

[2293] 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".

[2294] Traditional electronic payment systems and spending management applications have a problem in that they do not take into account the user's emotional state, and therefore do not adequately optimize the user experience or reduce stress. Furthermore, personalized promotional offerings also have the problem of not being able to respond flexibly based on the user's real-time emotional changes.

[2295] 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 means for receiving user information, means for storing user information in a database, means for processing payments based on the stored user information, means for notifying the user of the payment result, means for analyzing the user's spending data, means for notifying the user of the analysis result, means for generating personalized promotions, means for providing the generated promotions to the user, means for acquiring emotional data and analyzing the user's emotional state, and means for adjusting notification content and payment processing methods based on the user's emotional state. This makes it possible to simplify payment processing according to the user's emotional state and to provide personalized notifications and promotions.

[2296] "User information" refers to the collective term for personal identification information such as the user's name, email address, and password, as well as transaction history data.

[2297] A "database" is an electronic storage location for systematically organizing, saving, and managing received user information.

[2298] "Payment processing" refers to a series of procedures that use payment information provided by the user to settle the payment for goods or services.

[2299] A "notification" is a message sent from the system to the user, such as payment results, analysis results, or promotional information.

[2300] "Expenditure data" refers to records of various payments and transactions made by the user.

[2301] "Analysis" is the process of evaluating and calculating users' consumption trends and budget management status based on collected spending data and other user information.

[2302] "Personalized promotions" refer to the provision of discounts and benefits optimized for each user, based on their individual purchase history and preference data.

[2303] "Emotional data" refers to digital data that indicates a user's emotional state, obtained from their facial expressions and behavior.

[2304] "Emotional state" refers to the user's current mental and psychological state, as analyzed from emotional data.

[2305] "Simplification" is the act of reducing complexity in order to make operating procedures and processes intuitive and easy to understand in accordance with the user's emotional state.

[2306] This invention provides technical means for realizing a smartphone application that dynamically adjusts payment processing and notification content while taking into account the user's emotional state. Here, the configuration and operation of each component of this system are described in detail.

[2307] System Configuration

[2308] The main hardware components of this system include a smartphone (with a built-in camera). The main software components include an emotion recognition library (e.g., emotion_recognition), an HTTP request library (e.g., requests), and an external payment API wrapper (e.g., payment_api).

[2309] Receiving and storing user information

[2310] The terminal provides an interface for the user to enter information such as their name, email address, and password. Once the user enters the required information, the terminal sends that information to the server for storage in a database. The server stores the received data in the database and notifies the terminal of the successful storage.

[2311] Acquisition and analysis of emotional data

[2312] The device's built-...

Claims

1. Means for receiving user information, Means for storing the aforementioned user information in a database, A means of processing payments based on saved user information, A means of notifying the user of the payment result, Methods for analyzing user spending data, A means of notifying the user of the analysis results, Means for generating personalized promotions, A means of providing generated promotions to users. A system that includes this.

2. The system according to claim 1, wherein the payment processing means executes the payment using an external payment API.

3. The system according to claim 1, comprising means for managing user spending data as a budget and generating an alert when the budget is exceeded.

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