System

Abstract

A system is provided.SOLUTION: A system comprising: means for acquiring information on a product; means for generating a quiz based on the acquired product information; means for presenting the generated quiz to a user; means for receiving and verifying a quiz answer of the user; means for generating an authentication token for proceeding with a product purchase procedure when the user gives a correct answer to the quiz; and means for transmitting the authentication token to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] As product resale becomes more prevalent, retailers, individual sellers, and online store operators are seeking effective and easy ways to prevent the resale of products they have sold. Current measures are difficult to completely prevent resale, and consumers often purchase products without knowing the details of the product. Therefore, a method is needed to effectively prevent product resale and encourage customers to make accurate product purchases. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. A system is provided that includes a means for acquiring product information, a means for generating a quiz based on the acquired product information, a means for presenting the generated quiz to a user, a means for accepting and verifying the user's quiz answers, a means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly, and a means for transmitting the authentication token to the user. This allows the user to purchase a product after understanding its details and prevents resale. Furthermore, by further including a means for dynamically adjusting the content and difficulty of the quiz and a means for individually customizing the quiz questions for specific users, the system achieves greater entertainment value and learning effects.

[0006] "Product Information" refers to detailed data about a product, such as its name, features, specifications, instructions for use, and key benefits.

[0007] "Quiz" refers to a question-type question generated based on product information, and refers to a means for users to verify their knowledge by answering the question.

[0008] "User" refers to a consumer or user attempting to purchase a product.

[0009] An "authentication token" is a unique identification code that is generated when a user successfully answers a quiz, and that grants the user permission to proceed with the purchase.

[0010] "Server" refers to a computer system that acquires product information, generates quizzes, verifies answers, and generates authentication tokens.

[0011] "Terminal" refers to the device that a user uses to answer quizzes and complete purchase procedures.

[0012] The "purchase procedure" refers to a series of steps a user takes to finalize the purchase of a product, including inputting payment information and registering shipping address information.

[0013] "Dynamic adjustment of quiz content and difficulty" refers to changing the number of questions and difficulty of a quiz in real time based on the user's progress and answer history.

[0014] "Individual customization of quizzes" refers to changing the questions in a quiz for a specific user based on that user's interests and knowledge level. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The system of the present invention includes the following means, thereby providing a mechanism for preventing resale of products while helping customers deepen their knowledge of the products.

[0037] Quiz Generation Module

[0038] Obtaining product information

[0039] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[0040] Generate a quiz

[0041] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[0042] Quiz Formatting

[0043] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[0044] User Interface

[0045] View Quiz

[0046] The terminal displays the quiz questions sent from the server to the user, and the user interface presents the quiz through, for example, a web page or an application.

[0047] Getting user answers

[0048] The user answers the displayed quiz questions by clicking on the options or by writing the answer.

[0049] Submitting user answers

[0050] The terminal transmits the user's answer to the server. This transmitted data includes the user ID, question ID, selected answer, etc.

[0051] Purchase Management System

[0052] Verifying answers

[0053] The server checks the received user's answers against the correct answers. A list of correct answers is prepared for each question, and the server compares the user's answers with the list to determine whether they are correct or not.

[0054] Generate an authentication token

[0055] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code that is associated with a specific user and the product being purchased.

[0056] Sending an authentication token

[0057] The server then sends the generated authentication token to the user's device. The token is transmitted using a secure communication protocol to ensure authenticity.

[0058] Specific examples

[0059] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[0060] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[0061] This system allows users to understand the details of the product before making a purchase, and effectively prevents resale.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[0065] Step 2:

[0066] The server inputs the acquired product information into the generative AI model and generates quiz questions, such as "What are the features of this product?" along with corresponding options.

[0067] Step 3:

[0068] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[0069] Step 4:

[0070] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[0071] Step 5:

[0072] The user checks the quiz questions displayed on the terminal and selects or inputs an answer, for example, by clicking one of the options.

[0073] Step 6:

[0074] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[0075] Step 7:

[0076] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[0077] Step 8:

[0078] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code used to verify the user's purchasing authority.

[0079] Step 9:

[0080] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[0081] Step 10:

[0082] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[0083] Step 11:

[0084] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[0085] Step 12:

[0086] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[0087] Step 13:

[0088] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[0089] Example 1

[0090] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0091] It is necessary to effectively provide users with detailed product information so that they can proceed with the purchase process while having accurate knowledge about the product, thereby preventing fraudulent resale. However, conventional systems lack a mechanism that integrates the provision of product information, the generation of quizzes, and the confirmation of user knowledge, resulting in low user understanding and insufficient effectiveness in preventing resale.

[0092] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0093] In this invention, the server includes means for acquiring detailed product information from a database, means for generating a quiz based on the acquired product information using a generative AI model, means for formatting the generated quiz into JSON format and presenting it to the user via a user interface, means for accepting the user's answers to the quiz and verifying the answers against a list of correct answers, means for generating a unique authentication token if the user answers all questions correctly, and means for transmitting the authentication token to the user using a secure communication protocol. This allows the user to proceed with the purchase process while having in-depth knowledge of the product, and prevents resale.

[0094] "Means for retrieving detailed information about a product from a database" refers to the process of retrieving data such as the product's name, features, specifications, usage, and main benefits from a designated database.

[0095] "Means of generating quizzes based on acquired product information using a generative AI model" refers to the process of inputting product information into a pre-prepared generative AI model and automatically generating appropriate quiz questions based on that information.

[0096] "Means for formatting the generated quiz into JSON format and presenting it to the user through a user interface" refers to the process of formatting the generated quiz questions into JSON format and displaying them to the user through a user interface such as a web page or application.

[0097] "Means for accepting a user's quiz answers and verifying the answers against a list of correct answers" refers to a process for receiving the answers to a quiz given by a user and comparing them with a list of correct answers to determine whether the answers are correct or not.

[0098] "Means for generating a unique authentication token if the user answers all quiz questions correctly" refers to the process of issuing a unique authentication token associated with a specific user ID after confirming that the user has answered all quiz questions correctly.

[0099] "Means for transmitting the authentication token to the user using a secure communication protocol" refers to the process of securely transmitting the generated authentication token to the user's device via a secure communication protocol (e.g., HTTPS).

[0100] The present invention relates to a system that promotes understanding of a product and prevents fraudulent resale as a user purchases the product while deepening detailed knowledge about the product.

[0101] Hardware and Software Configuration

[0102] server

[0103] The server has the ability to retrieve detailed product information from a database. The database used is often an SQL-based database management system (DBMS). It also has the ability to generate quiz questions based on the retrieved product information using a generative AI model (e.g., OpenAI's GPT-3). It then formats the generated quiz questions in JSON format and sends them to the user's device.

[0104] Terminal

[0105] The device receives the quiz questions in JSON format sent from the server and displays them to the user through a user interface (UI), often a web page or a smartphone application.

[0106] User

[0107] The user answers the quiz questions displayed on the terminal. The user's answers are sent to the server via the terminal, and the server checks the received answers against a list of correct answers to determine whether they are correct or not.

[0108] Generate quiz questions

[0109] The server retrieves detailed product information (for example, in the case of a smartphone, whether it is 5G compatible, has a high-resolution camera, is waterproof, etc.) from a database. Using this information, the server generates quiz questions by providing the following prompt to a generative AI model (such as GPT-3):

[0110] "Explain the features of this new smartphone and generate appropriate quiz questions."

[0111] The generated quiz questions will have the following format:

[0112] "Which of the following features does this smartphone have? A. 5G support B. 4K camera C. Waterproof D. All of them"

[0113] Quiz delivery and answer verification

[0114] The terminal displays quiz questions to the user through a user interface. The user answers the quiz questions and sends the answers to the server through the terminal. The server compares the received answer data with a list of correct answers and determines whether the user's answers are correct. If the user answers all the quiz questions correctly, the server generates a unique authentication token and sends it to the user's terminal using a secure communication protocol (e.g., HTTPS).

[0115] Specific operation example

[0116] When selling a new smartphone, the server first retrieves information about the product's features and advantages (e.g., 5G compatibility, high-resolution camera, waterproof) from a database. Next, it uses a generative AI model to generate a quiz question such as, "What are the features of this smartphone?" and creates the options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," and "D. All of them." The quiz question is displayed to the user through the user interface, and when the user selects "D. All of them," the answer is sent to the server. The server verifies the answer, and if it is confirmed to be correct, it generates a unique authentication token and sends it to the user's device. This allows the user to officially proceed with the product purchase process.

[0117] This system allows users to make purchases after gaining detailed knowledge about the products, while at the same time effectively preventing resale.

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

[0119] Step 1:

[0120] The server retrieves detailed product information from a database, including product name, features, specifications, usage, key benefits, etc. The server queries the database using SQL queries to retrieve the relevant product information. The input is the database query, and the output is a set of product information.

[0121] Step 2:

[0122] The server generates quiz questions using a generative AI model (e.g., GPT-3) based on the acquired product information. The server inputs the prompt "Please generate quiz questions related to this product" into the generative AI model and receives the quiz questions output by the model. The input is the product information and the prompt, and the output is the generated quiz questions.

[0123] Step 3:

[0124] The server formats the generated quiz questions into a format for presenting them to the user. Specifically, the quiz questions are converted into JSON format. For example, if the quiz has multiple-choice options, it formats them into a JSON format that includes the quiz questions and the options. The input is the generated quiz questions, and the output is the formatted JSON quiz data.

[0125] Step 4:

[0126] The server sends the quiz data in formatted JSON to the terminal, transmits the data through an appropriate communication protocol, and presents the quiz to the user via a user interface. The input is the quiz data in formatted JSON, and the output is the quiz data sent to the terminal.

[0127] Step 5:

[0128] The terminal displays quiz questions to the user. It visually displays formatted JSON formatted quiz data through a user interface. The input is the quiz data received from the server, and the output is the display of quiz questions to the user.

[0129] Step 6:

[0130] The user answers the quiz questions displayed on the terminal. The user inputs the answer by clicking on the answer option or by writing it down. The input is the user's answer, and the output is the answer data.

[0131] Step 7:

[0132] The terminal sends the user's answer data to the server. The answer data includes data such as the user ID, question ID, and selected answer. The input is the user's answer data, and the output is the answer data sent to the server.

[0133] Step 8:

[0134] The server verifies the received answer data by checking it against a list of correct answers. The server compares the user's answer with a list of correct answers prepared in advance and determines whether it is correct or not. The input is the user's answer data and the list of correct answers, and the output is the verification result.

[0135] Step 9:

[0136] If the user answers all questions correctly, the server generates a unique authentication token. It issues an authentication token associated with the user ID and the product being purchased. The input is the verification result, and the output is the generated authentication token.

[0137] Step 10:

[0138] The server sends the generated authentication token to the user's device. The token is securely transmitted using a secure communication protocol (e.g., HTTPS). The input is the generated authentication token, and the output is the authentication token sent to the device.

[0139] (Application example 1)

[0140] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0141] Conventional sales systems lack the means to deepen product knowledge and have the problem of rampant resale without proper purchaser authentication. In particular, in physical stores, opportunities to deepen product understanding are limited and effective means to prevent resale are lacking. For this reason, there is a need for a system that allows users to fully understand products and purchase them through legitimate procedures.

[0142] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0143] In this invention, the server includes means for acquiring information about a product, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for accepting and verifying the user's answer to the quiz, means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly, means for transmitting the authentication token to the user, and means for verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure. This allows the user to deepen their understanding of the product while obtaining legitimate authentication and proceeding with the purchase.

[0144] The "means for obtaining information about a product" is a function by which the server obtains detailed information about a specific product (for example, name, features, specifications, usage, advantages, etc.) from a database.

[0145] "Means for generating quizzes based on acquired product information" refers to a function that uses a generative AI model to create quiz questions based on the product information acquired by the server.

[0146] The "means for presenting the generated quiz to the user" is a function for displaying the generated quiz questions and presenting them to the user on the terminal used by the user.

[0147] The "means for accepting and verifying user's quiz answers" is a function in which a user answers a quiz question, sends the answer to the server, and the server checks whether the answer is correct.

[0148] The "means for generating an authentication token to proceed with the product purchase procedure" is a function that generates an authentication token, which is a unique identification code that the server uses to proceed with the purchase procedure, if the user answers all questions in the quiz correctly.

[0149] The "means for transmitting an authentication token to a user" is a function for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[0150] "Means of verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure" refers to a function that scans the user's authentication token on a dedicated terminal installed in a physical store, confirms its legitimacy, and then completes the purchase procedure.

[0151] This invention relates to a quiz-style promotion system for deepening understanding of products in brick-and-mortar stores and preventing resale. This system is implemented by three parties: a server, a terminal, and a user.

[0152] System Configuration

[0153] server

[0154] The server has the following functions:

[0155] 1. Obtaining product information

[0156] The server retrieves information about the products in the physical store from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[0157] 2. Quiz Generation

[0158] The server generates quiz questions from the acquired product information using a generative AI model. Generative AI models such as OpenAI's GPT-3 can be used. The quizzes are formatted as multiple choice or question-and-answer questions.

[0159] 3. Formatting the quiz

[0160] After the quiz questions are generated, the server formats them for presentation to the user by converting them into a data structure such as JSON.

[0161] 4. Verifying the Answer

[0162] The server receives the user's answers to the quiz and compares them with the list of correct answers to determine whether they are correct or incorrect.

[0163] 5. Generate and send authentication token

[0164] If the user answers all the quiz questions correctly, the server generates an authentication token (such as a QR code) and sends it to the user's device via a secure protocol.

[0165] Terminal

[0166] The terminal has the following functions:

[0167] 1. View the quiz

[0168] Users view and answer quiz questions on their devices, which are presented via a smartphone app or web browser.

[0169] 2. Submit your response

[0170] The user's answers to the quiz are sent to the server via a protocol such as an HTTP request.

[0171] 3. Present your authentication

[0172] The authentication token sent from the server is scanned by a dedicated terminal in the physical store, and the user displays the authentication token on the terminal.

[0173] User

[0174] 1. Obtain product information and answer quizzes

[0175] Users scan QR codes attached to products in physical stores with their device to obtain product information and answer quizzes.

[0176] 2. Authentication for Purchase

[0177] After answering all the questions in the quiz correctly, you present the authentication token at a dedicated terminal in the physical store and proceed with the purchase.

[0178] Processing flow

[0179] 1. Product information acquisition stage

[0180] When a user scans a QR code associated with a product in a physical store with their device, the server retrieves detailed information about the product from the database, including the product name, features, and specifications.

[0181] 2. Quiz generation and formatting stage

[0182] The server generates a quiz by inputting a prompt into the AI ​​model based on the acquired product information. For example, a prompt such as "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life" is input into the AI ​​model. The generated quiz questions are then formatted in JSON format.

[0183] 3. Viewing the quiz and submitting answers

[0184] Quiz questions are displayed on the terminal, and the user answers them. The answer data is sent to the server, which checks it against a list of correct answers.

[0185] 4. Authentication token generation and checkout process

[0186] If the user answers all questions correctly, the server generates an authentication token and sends it to the terminal. The user presents this at a dedicated terminal in the physical store to complete the purchase process.

[0187] In this way, users can deepen their understanding of the product and proceed with the purchase after proper authentication. This system is particularly effective in preventing the resale of expensive products.

[0188] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0189] Step 1:

[0190] Obtaining product information

[0191] The server receives the information entered by the user's device reading the QR code attached to the product in the physical store. The device scans the QR code and sends a request to the server, which starts the process.

[0192] The server retrieves detailed information about the relevant product from the database (product name, features, specifications, usage, main benefits) and inputs the results into the server.

[0193] The product information retrieved from the database becomes the output of the server, and the process proceeds to the next step.

[0194] Step 2:

[0195] Generate a quiz

[0196] To use the generative AI model, the server formats the acquired product information into a prompt sentence, which becomes the server's input.

[0197] The server inputs a prompt into the generative AI model (API) and requests the generation of quiz questions. The prompt input is something like, "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life."

[0198] The generative AI model outputs quiz questions, which are received by the server. The quiz question text becomes the server's output.

[0199] Step 3:

[0200] Quiz Formatting

[0201] The server formats the generated quiz questions into a format for presentation to the user.

[0202] The quiz questions are converted into structured data such as JSON and formatted. This is the input and processed data for the server.

[0203] The formatted quiz question data is output from the server and sent to the user's terminal.

[0204] Step 4:

[0205] View Quiz

[0206] The user's terminal receives the formatted quiz data received from the server as input.

[0207] The terminal displays the quiz questions on the user interface, which is the specific operation of the terminal.

[0208] The displayed quiz will be the output of the terminal.

[0209] Step 5:

[0210] Getting user answers

[0211] The user answers the quiz questions displayed on the terminal, and the user's answers become the input.

[0212] The user's response data (clicking on an option or answering in written form) is entered into the terminal.

[0213] The terminal transmits the user's response data to the server, and the request to the server becomes the output of the terminal.

[0214] Step 6:

[0215] Verifying answers

[0216] The server compares the received user answers with the correct answer list. The user's answer data becomes the input for the server.

[0217] The server compares and verifies the user's answer with the correct answer list in the database, and this process involves data calculations.

[0218] The verification result is output by the server. If it is correct, proceed to the next step.

[0219] Step 7:

[0220] Generate and send an authentication token

[0221] After the server confirms that the user has answered all the questions correctly, it generates an authentication token, which is input to the server.

[0222] The server generates an authentication token (e.g., a QR code), which is a unique identification code, and sends it to the user's device via a secure protocol (e.g., HTTPS). Token generation and protocol selection are the server's operations.

[0223] An authentication token is the output of the server and sent to the user's device.

[0224] Step 8:

[0225] Presenting and validating authentication tokens

[0226] The user presents the authentication token at a dedicated terminal in the physical store. The token displayed on the user's terminal is used as input.

[0227] The dedicated terminal scans the presented authentication token and sends it to the server. The terminal's operation is to present and scan the token.

[0228] The server verifies the received authentication token and confirms its validity. The server's input is the token and its output is the verification result. If the verification is successful, the purchase procedure is completed.

[0229] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0230] The system of this invention provides a mechanism for preventing resale of products while deepening users' product knowledge. Furthermore, by providing a system that combines an emotion engine that can recognize users' emotions and dynamically change the content and presentation of quizzes based on those emotions, a more advanced user experience is realized.

[0231] Quiz Generation Module

[0232] Obtaining product information

[0233] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[0234] Generate a quiz

[0235] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[0236] Quiz Formatting

[0237] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[0238] Emotion Engine

[0239] emotion recognition

[0240] The device recognizes the user's emotional state by inputting the user's facial expressions and tone of voice into an emotion engine via sensors such as a camera and microphone. Emotional states are classified into multiple categories, such as joy, anger, sadness, and surprise.

[0241] Sentiment Data Analysis

[0242] The server analyzes the recognized emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if a user is feeling anxious or stressed, the server can set the quiz to present easier questions first.

[0243] User Interface

[0244] View Quiz

[0245] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. The display content is dynamically adjusted according to the user's emotional state.

[0246] Getting user answers

[0247] The user checks the quiz questions displayed on the device and selects or enters an answer by clicking on an option or writing an answer.

[0248] Submitting user answers

[0249] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[0250] Purchase Management System

[0251] Verifying answers

[0252] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[0253] Generate an authentication token

[0254] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[0255] Sending an authentication token

[0256] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[0257] Specific examples

[0258] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[0259] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[0260] Furthermore, if the device's camera detects the user's facial expressions and detects that the user is feeling anxious about the quiz, the server can make the next quiz a little easier or add additional explanations, allowing the user to relax and take the quiz, gaining accurate knowledge as they proceed through the purchasing process.

[0261] The processing flow will be explained below.

[0262] Step 1:

[0263] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[0264] Step 2:

[0265] The server uses a generative AI model to generate quiz questions based on the acquired product information. For example, it creates a question such as "What are the features of this product?" along with corresponding options.

[0266] Step 3:

[0267] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[0268] Step 4:

[0269] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[0270] Step 5:

[0271] The device uses sensors such as a built-in camera and microphone to input the user's facial expressions and tone of voice into the emotion engine.

[0272] Step 6:

[0273] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their current emotional state (joy, anger, sadness, surprise, etc.).

[0274] Step 7:

[0275] The emotion engine sends the recognized emotion data to the server.

[0276] Step 8:

[0277] The server analyzes the received emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if the user is feeling anxious, it will present easier questions first.

[0278] Step 9:

[0279] The device then displays the adjusted quiz questions to the user again, with the content and presentation method taking into consideration the user's emotional state.

[0280] Step 10:

[0281] The user answers the displayed quiz questions by clicking on the answer options or by writing a response.

[0282] Step 11:

[0283] The terminal sends the user's answer to the server. This sent data includes the user ID, question ID, selected answer, etc.

[0284] Step 12:

[0285] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[0286] Step 13:

[0287] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[0288] Step 14:

[0289] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[0290] Step 15:

[0291] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[0292] Step 16:

[0293] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[0294] Step 17:

[0295] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[0296] Step 18:

[0297] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[0298] Example 2

[0299] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0300] In modern online shopping, preventing product resale and improving the user's purchasing experience are important issues. Especially for high-priced or limited-edition products, it is necessary to prevent purchases for resale purposes while also enabling users to gain sufficient information about the product before purchasing. However, conventional systems lack a mechanism for dynamically adjusting the content and difficulty of quizzes based on the user's emotional state, resulting in a uniform user experience.

[0301] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0302] In this invention, the server includes: [means for acquiring information about a product;] [means for generating a quiz using a generative AI model based on the acquired product information;] [means for formatting the generated quiz into a format for presentation to the user;] [means for recognizing the user's emotional state;] [means for dynamically adjusting the content and difficulty of the quiz based on the recognized emotional state;] [means for displaying the quiz to the user;] [means for accepting and verifying the user's quiz answers; [means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly; and] [means for sending the authentication token to the user. This allows the user to gain sufficient knowledge about the product while taking a quiz that is appropriate to their situation and emotions at the time, preventing resale and improving the user experience.

[0303] "Means for obtaining information about products" refers to technical means for obtaining detailed information about products from a database.

[0304] "Means for generating a quiz using a generative AI model based on acquired product information" refers to means for creating a quiz using a generative AI model based on acquired product information.

[0305] The "means for formatting the generated quiz into a format for presenting to the user" refers to a means for formatting data and converting it into an appropriate format such as JSON or HTML in order to properly present the generated quiz questions to the user.

[0306] The "means for recognizing the user's emotional state" is a means for detecting the user's facial expression, tone of voice, etc. using sensors such as a camera or microphone on the device, and recognizing the emotional state using an emotion engine.

[0307] "Means for dynamically adjusting the content and difficulty of a quiz based on a recognized emotional state" refers to means for dynamically adjusting the content, difficulty, and presentation order of a quiz based on the recognized emotional state of the user.

[0308] "Means for displaying a quiz to a user" refers to the technical means for displaying the quiz questions sent from the server to a user, and includes web browser forms, application screens, and the like.

[0309] The "means for receiving and verifying a user's quiz answer" refers to a means for receiving an answer selected or entered by a user to a quiz and verifying the answer by checking it against a list of correct answers.

[0310] The "means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly" refers to a means for generating an authentication token, which is a unique identification code for the purchase procedure, if the user answers all the quizzes correctly.

[0311] The "means for transmitting an authentication token to a user" refers to a means for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[0312] MODE FOR CARRYING OUT THE INVENTION

[0313] This embodiment of the present invention provides a system that prevents resale of products while deepening users' product knowledge. In addition, by combining it with an emotion engine that recognizes the user's emotions and dynamically changes the content and difficulty of the quiz based on those emotions, a more advanced user experience is realized. A specific implementation method is described below.

[0314] 1. Obtaining product information

[0315] The server retrieves detailed information about the product being bought and sold from a database, including the product name, features, specifications, instructions for use, key benefits, etc. The server executes SQL queries to retrieve the required information from the database and loads it into memory.

[0316] 2. Quiz Generation

[0317] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. For example, a prompt such as "What are the features of this smartphone?" is input into the generative AI model, which then generates options such as "A. 5G compatible," "B. 4K camera," "C. Waterproof," and "D. All." A common open-source natural language processing (NLP) model can be used as the generative AI model.

[0318] 3. Formatting the quiz

[0319] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and saved in the file system.

[0320] 4. Emotional Recognition

[0321] The device inputs the user's facial expressions and tone of voice into the emotion engine via sensors such as a camera and microphone. This allows the user's emotional state to be recognized. Emotional states are classified as joy, anger, sadness, surprise, etc. The emotion engine uses image recognition and voice analysis technology.

[0322] 5. Emotional Data Analysis

[0323] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quizzes based on the user's emotional state. For example, if the user is feeling anxious, the server will set the next quiz to an easier one.

[0324] 6. View the quiz

[0325] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. Based on the JSON format data received from the server, the device generates HTML and CSS to display the quiz.

[0326] 7. Obtaining User Answers

[0327] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. Specifically, the user selects option D (all). The user's input is acquired by the terminal as form data.

[0328] 8. Submitting User Answers

[0329] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID. The data is sent using a secure protocol.

[0330] 9. Verifying the Answer

[0331] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[0332] 10. Generate an authentication token

[0333] If the user answers all the quiz questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code stored in a secure data store.

[0334] 11. Sending Authentication Tokens

[0335] The server sends the generated authentication token to the user's device using a secure communication protocol.

[0336] Specific examples

[0337] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[0338] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[0339] An example of a prompt is:

[0340] "Generate a quiz about selling a new smartphone. Create multiple-choice questions that include the product's features and benefits, and use a corresponding emotion recognition system to dynamically adjust the quiz based on the user's emotions. Specific examples of prompts might include, 'What are the features of this smartphone?' and 'What is the balance between style and performance?'"

[0341] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0342] Step 1:

[0343] The server retrieves detailed information about the product being sold from a database, using search criteria such as the product ID as input. The output is detailed product information such as the product name, features, specifications, instructions for use, and key benefits.

[0344] Specific operation: The server executes an SQL query such as "SELECT FROM product_info WHERE product_id = '12345'" and reads the retrieved data into memory.

[0345] Step 2:

[0346] The server generates quiz questions using a generative AI model based on the acquired product information. The acquired product information is used as input, and the generated quiz questions are obtained as output.

[0347] Specific operation: The server sends a prompt to the generation AI model saying, "Please generate quiz questions about the features of the new smartphone," and the AI ​​model returns the quiz questions.

[0348] Step 3:

[0349] The server formats the generated quiz questions into a format for presentation to the user. The generated quiz questions are used as input. As output, the formatted quiz questions are converted into a data structure such as JSON format.

[0350] Specific operation: The server converts the generated quiz questions into the "quiz_questions.json" format and saves the formatted data in the file system.

[0351] Step 4:

[0352] The device inputs the user's facial expressions and tone of voice to the emotion engine through sensors such as a camera and microphone. The input uses data on the user's facial expressions and voice. The output is a recognized emotional state.

[0353] Specific operation: The device captures the user's facial expression with a camera and sends the image data to the emotion engine, which analyzes the image data and determines the user's emotional state.

[0354] Step 5:

[0355] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quiz based on the user's emotional state. The recognized emotion data is used as input, and the adjusted quiz questions are obtained as output.

[0356] Specific operation: The server receives the emotion data of "anxiety" and reconfigures the list of quiz questions to prioritize displaying easy questions.

[0357] Step 6:

[0358] The terminal displays the quiz questions sent from the server to the user. The input is the quiz question data received from the server. The output is the quiz displayed on the screen.

[0359] Specific operation: The device downloads "quiz_questions.json" from the server and generates HTML and CSS to display the quiz questions on the UI.

[0360] Step 7:

[0361] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. The input is the user's answer. The output is the selected or input answer.

[0362] Specific behavior: The user clicks or enters options using the mouse or keyboard, and the input data is captured as a form.

[0363] Step 8:

[0364] The terminal transmits the answer selected or input by the user to the server. The input includes the user's answer data. The output is the transmitted answer data.

[0365] Specific operation: The device generates "user_answer.json" and posts the user's selected answer to the server.

[0366] Step 9:

[0367] The server compares the received user's answer with the correct answer list and determines whether the answer is correct. The input is the user's answer data and the correct answer list. The output is the verification result.

[0368] Specific operation: The server receives "user_answer.json" and checks the answer against the correct answer list.

[0369] Step 10:

[0370] The server generates an authentication token to allow the user to proceed with the purchase process if the user answers all the quiz questions correctly. The input is the verification results of all the quiz questions. The output is the generated authentication token.

[0371] Specific operation: If the server determines that all questions are answered correctly, it generates an "auth_token" and stores it in a secure data store.

[0372] Step 11:

[0373] The server sends the generated authentication token to the user's device. The input is the generated authentication token. The output is the authentication token sent to the user's device.

[0374] Specific operation: The server generates "auth_token.json" and sends it to the user's device via a secure protocol.

[0375] (Application example 2)

[0376] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0377] Today, there is a demand for systems to improve the customer experience in brick-and-mortar stores. However, there is a lack of ways for customers to deepen their knowledge about products while increasing their purchasing motivation. Furthermore, because content cannot be provided that takes into account customer emotions, customers may feel anxious or stressed, and the purchasing process may not proceed smoothly. Therefore, the challenge is to develop a system that provides an optimal purchasing experience based on the customer's emotional state by using a dynamic quiz adjustment function that includes emotion recognition.

[0378] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information about products, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for acquiring emotional data using sensors such as a camera and a microphone to recognize the user's emotional state, and means for dynamically adjusting the difficulty and content of the quiz based on the emotional data. This enables customers to deepen their knowledge about products in a physical store while taking on quizzes that correspond to their emotional state, thereby reducing customer stress and anxiety and allowing the purchasing process to proceed smoothly.

[0379] "Means for obtaining information about products" refers to a function for obtaining detailed information such as product features, specifications, and advantages from a database or external information source.

[0380] "Means for generating quizzes based on acquired product information" refers to a function that automatically creates quiz questions using a generative AI model based on acquired product information.

[0381] The "means for presenting the generated quiz to the user" is a function that provides an interface for displaying the generated quiz questions to the user.

[0382] The "means for accepting and verifying the user's quiz answers" is a function for receiving the quiz answers entered by the user and determining whether they are correct or incorrect.

[0383] The "means for generating an authentication token to proceed with the product purchase process when the user answers the quiz correctly" is a function that generates a unique authentication code to prove the user's authority to purchase a product when the user answers all the quizzes correctly.

[0384] The "means for transmitting an authentication token to a user" is a function for transmitting a generated authentication token to a user using a secure communication protocol.

[0385] "Means for acquiring emotional data using sensors such as a camera or microphone in order to recognize the user's emotional state" refers to a function that uses a camera or microphone to analyze the user's facial expressions and tone of voice and recognize the user's emotional state.

[0386] The "means for dynamically adjusting the difficulty and content of the quiz based on emotion data" is a function for changing the difficulty and content of the quiz in real time according to the recognized emotion of the user.

[0387] The system of this invention allows customers in physical stores to deepen their product knowledge while smoothly progressing through the purchasing process. The system mainly consists of the following components: a server, a terminal, and sensors such as a camera and a microphone.

[0388] Server Roles

[0389] The server retrieves product information from the database and generates a quiz based on that information. A generative AI model is used in this quiz generation process. The generated quiz is then formatted appropriately to be presented to the user. The server also has the function of accepting and verifying the user's quiz answers and generating authentication tokens. Furthermore, the server analyzes the user's emotional state data and dynamically adjusts the content and difficulty of the quiz.

[0390] Device Role

[0391] The terminal displays product information and quizzes sent from the server to the user. Devices such as smartphones and smart glasses are used. The terminal is equipped with a camera and microphone, and these sensors are used to recognize the user's emotional state in real time. The user's emotional data is sent to the server, which then adjusts the content and difficulty of the quiz.

[0392] User Experience

[0393] Users answer quizzes through their device, and if they answer all of them correctly, they receive an authentication token. This token is used to proceed with the product purchase process. While taking the quiz, the user's emotions are sensed via a camera and microphone. For example, if the user is feeling anxious or stressed, the server will adjust the next quiz to be easier.

[0394] Software and hardware used

[0395] The server requires a database management system (DBMS) and the computing resources to run the generative AI model, specifically, to analyze emotion data using OpenCV and the EmotionRecognition library.

[0396] The devices used are smartphones or smart glasses equipped with cameras and microphones, and the user interface is a web browser or dedicated application.

[0397] Specific examples

[0398] For example, let's say this system is used in a physical store selling new smartphones. The server retrieves information about the smartphone's features and advantages from a database (e.g., 5G compatibility, high-resolution camera, large-capacity battery). Based on this information, the generative AI model generates a quiz and sends it to the device. If the device is a smartphone, the user answers the quiz through the camera, and their facial expressions are analyzed during the process. If the user feels unsure, the server can easily adjust the next quiz to be presented. Furthermore, if the user answers all the quizzes correctly, the server issues an authentication token and sends it to the device. Using this token, the user can smoothly proceed through the purchase process.

[0399] Prompt Sentence Examples

[0400] Product information: {"Product name": "New smartphone", "Features": "5G compatible, high-resolution camera, large-capacity battery, OLED display"}.

[0401] Generate a quiz about this product.

[0402] This system configuration enriches the customer experience in physical stores, allowing customers to make purchases in a relaxed manner.

[0403] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0404] Step 1: Get product information

[0405] The server retrieves product information from the database, including product name, features, specifications, key benefits, etc. For example, it retrieves the features and benefits of a new smartphone (5G compatibility, high-resolution camera, large battery, etc.).

[0406] Input: Product ID

[0407] Output: Product data (product name, features, specifications, benefits)

[0408] Step 2: Generate the quiz

[0409] The server creates a prompt based on the acquired product information and sends it to the generative AI model, which then generates multiple quiz questions based on this prompt.

[0410] Input: Product data

[0411] Output: Quiz question set

[0412] Step 3: Formatting Quiz Questions

[0413] The server formats the generated quiz questions in an appropriate format (e.g., JSON) for presentation to the user, which is then sent to the user interface.

[0414] Input: Quiz question set

[0415] Output: Formatted quiz data

[0416] Step 4: Present the quiz

[0417] The terminal receives the formatted quiz data sent from the server and displays it to the user. The user interface uses the application screen of a smartphone or smart glasses.

[0418] Input: Formatted quiz data

[0419] Output: Quiz questions displayed

[0420] Step 5: Obtaining emotion data

[0421] The device captures the user's facial expressions and tone of voice through a camera and microphone, and sends the emotion data to the emotion engine, which then analyzes the user's emotional state.

[0422] Input: User facial expression images, voice data

[0423] Output: Emotional state data (happiness, anxiety, stress, etc.)

[0424] Step 6: Dynamically adjust the quiz

[0425] The server dynamically adjusts the difficulty and content of the quiz based on the emotional state data, for example, lowering the difficulty of the quiz if the user is in an anxious state.

[0426] Input: Emotional state data, formatted quiz data

[0427] Output: Reconciled quiz data

[0428] Step 7: Accept quiz responses

[0429] The user answers the quiz questions displayed on the terminal, and the terminal accepts the answers and transmits them to the server.

[0430] Input: User's answer

[0431] Output: Accepted response data

[0432] Step 8: Verify your answers

[0433] The server checks the user's answer against a list of correct answers to determine whether the answer is correct.

[0434] Input: User response data, correct answer list

[0435] Output: Correctness of answer

[0436] Step 9: Generate an Auth Token

[0437] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code, that allows the user to proceed with the purchase process.

[0438] Input: Correct answer result

[0439] Output: Authentication token

[0440] Step 10: Sending an authentication token

[0441] The server sends the generated authentication token to the terminal, which displays it to the user, allowing the user to proceed with the purchase.

[0442] Input: Authentication Token

[0443] Output: Displayed authentication token

[0444] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0445] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0446] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0447] [Second embodiment]

[0448] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0449] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0450] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0451] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0452] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0453] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0454] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0455] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0456] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0457] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0458] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0459] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0460] The system of the present invention includes the following means, thereby providing a mechanism for preventing resale of products while helping customers deepen their knowledge of the products.

[0461] Quiz Generation Module

[0462] Obtaining product information

[0463] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[0464] Generate a quiz

[0465] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[0466] Quiz Formatting

[0467] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[0468] User Interface

[0469] View Quiz

[0470] The terminal displays the quiz questions sent from the server to the user, and the user interface presents the quiz through, for example, a web page or an application.

[0471] Getting user answers

[0472] The user answers the displayed quiz questions by clicking on the options or by writing the answer.

[0473] Submitting user answers

[0474] The terminal transmits the user's answer to the server. This transmitted data includes the user ID, question ID, selected answer, etc.

[0475] Purchase Management System

[0476] Verifying answers

[0477] The server checks the received user's answers against the correct answers. A list of correct answers is prepared for each question, and the server compares the user's answers with the list to determine whether they are correct or not.

[0478] Generate an authentication token

[0479] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code that is associated with a specific user and the product being purchased.

[0480] Sending an authentication token

[0481] The server then sends the generated authentication token to the user's device. The token is transmitted using a secure communication protocol to ensure authenticity.

[0482] Specific examples

[0483] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[0484] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[0485] This system allows users to understand the details of the product before making a purchase, and effectively prevents resale.

[0486] The processing flow will be explained below.

[0487] Step 1:

[0488] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[0489] Step 2:

[0490] The server inputs the acquired product information into the generative AI model and generates quiz questions, such as "What are the features of this product?" along with corresponding options.

[0491] Step 3:

[0492] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[0493] Step 4:

[0494] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[0495] Step 5:

[0496] The user checks the quiz questions displayed on the terminal and selects or inputs an answer, for example, by clicking one of the options.

[0497] Step 6:

[0498] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[0499] Step 7:

[0500] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[0501] Step 8:

[0502] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code used to verify the user's purchasing authority.

[0503] Step 9:

[0504] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[0505] Step 10:

[0506] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[0507] Step 11:

[0508] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[0509] Step 12:

[0510] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[0511] Step 13:

[0512] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[0513] Example 1

[0514] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0515] It is necessary to effectively provide users with detailed product information so that they can proceed with the purchase process while having accurate knowledge about the product, thereby preventing fraudulent resale. However, conventional systems lack a mechanism that integrates the provision of product information, the generation of quizzes, and the confirmation of user knowledge, resulting in low user understanding and insufficient effectiveness in preventing resale.

[0516] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0517] In this invention, the server includes means for acquiring detailed product information from a database, means for generating a quiz based on the acquired product information using a generative AI model, means for formatting the generated quiz into JSON format and presenting it to the user via a user interface, means for accepting the user's answers to the quiz and verifying the answers against a list of correct answers, means for generating a unique authentication token if the user answers all questions correctly, and means for transmitting the authentication token to the user using a secure communication protocol. This allows the user to proceed with the purchase process while having in-depth knowledge of the product, and prevents resale.

[0518] "Means for retrieving detailed information about a product from a database" refers to the process of retrieving data such as the product's name, features, specifications, usage, and main benefits from a designated database.

[0519] "Means of generating quizzes based on acquired product information using a generative AI model" refers to the process of inputting product information into a pre-prepared generative AI model and automatically generating appropriate quiz questions based on that information.

[0520] "Means for formatting the generated quiz into JSON format and presenting it to the user through a user interface" refers to the process of formatting the generated quiz questions into JSON format and displaying them to the user through a user interface such as a web page or application.

[0521] "Means for accepting a user's quiz answers and verifying the answers against a list of correct answers" refers to a process for receiving the answers to a quiz given by a user and comparing them with a list of correct answers to determine whether the answers are correct or not.

[0522] "Means for generating a unique authentication token if the user answers all quiz questions correctly" refers to the process of issuing a unique authentication token associated with a specific user ID after confirming that the user has answered all quiz questions correctly.

[0523] "Means for transmitting the authentication token to the user using a secure communication protocol" refers to the process of securely transmitting the generated authentication token to the user's device via a secure communication protocol (e.g., HTTPS).

[0524] The present invention relates to a system that promotes understanding of a product and prevents fraudulent resale as a user purchases the product while deepening detailed knowledge about the product.

[0525] Hardware and Software Configuration

[0526] server

[0527] The server has the ability to retrieve detailed product information from a database. The database used is often an SQL-based database management system (DBMS). It also has the ability to generate quiz questions based on the retrieved product information using a generative AI model (e.g., OpenAI's GPT-3). It then formats the generated quiz questions in JSON format and sends them to the user's device.

[0528] Terminal

[0529] The device receives the quiz questions in JSON format sent from the server and displays them to the user through a user interface (UI), often a web page or a smartphone application.

[0530] User

[0531] The user answers the quiz questions displayed on the terminal. The user's answers are sent to the server via the terminal, and the server checks the received answers against a list of correct answers to determine whether they are correct or not.

[0532] Generate quiz questions

[0533] The server retrieves detailed product information (for example, in the case of a smartphone, whether it is 5G compatible, has a high-resolution camera, is waterproof, etc.) from a database. Using this information, the server generates quiz questions by providing the following prompt to a generative AI model (such as GPT-3):

[0534] "Explain the features of this new smartphone and generate appropriate quiz questions."

[0535] The generated quiz questions will have the following format:

[0536] "Which of the following features does this smartphone have? A. 5G support B. 4K camera C. Waterproof D. All of them"

[0537] Quiz delivery and answer verification

[0538] The terminal displays quiz questions to the user through a user interface. The user answers the quiz questions and sends the answers to the server through the terminal. The server compares the received answer data with a list of correct answers and determines whether the user's answers are correct. If the user answers all the quiz questions correctly, the server generates a unique authentication token and sends it to the user's terminal using a secure communication protocol (e.g., HTTPS).

[0539] Specific operation example

[0540] When selling a new smartphone, the server first retrieves information about the product's features and advantages (e.g., 5G compatibility, high-resolution camera, waterproof) from a database. Next, it uses a generative AI model to generate a quiz question such as, "What are the features of this smartphone?" and creates the options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," and "D. All of them." The quiz question is displayed to the user through the user interface, and when the user selects "D. All of them," the answer is sent to the server. The server verifies the answer, and if it is confirmed to be correct, it generates a unique authentication token and sends it to the user's device. This allows the user to officially proceed with the product purchase process.

[0541] This system allows users to make purchases after gaining detailed knowledge about the products, while at the same time effectively preventing resale.

[0542] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0543] Step 1:

[0544] The server retrieves detailed product information from a database, including product name, features, specifications, usage, key benefits, etc. The server queries the database using SQL queries to retrieve the relevant product information. The input is the database query, and the output is a set of product information.

[0545] Step 2:

[0546] The server generates quiz questions using a generative AI model (e.g., GPT-3) based on the acquired product information. The server inputs the prompt "Please generate quiz questions related to this product" into the generative AI model and receives the quiz questions output by the model. The input is the product information and the prompt, and the output is the generated quiz questions.

[0547] Step 3:

[0548] The server formats the generated quiz questions into a format for presenting them to the user. Specifically, the quiz questions are converted into JSON format. For example, if the quiz has multiple-choice options, it formats them into a JSON format that includes the quiz questions and the options. The input is the generated quiz questions, and the output is the formatted JSON quiz data.

[0549] Step 4:

[0550] The server sends the quiz data in formatted JSON to the terminal, transmits the data through an appropriate communication protocol, and presents the quiz to the user via a user interface. The input is the quiz data in formatted JSON, and the output is the quiz data sent to the terminal.

[0551] Step 5:

[0552] The terminal displays quiz questions to the user. It visually displays formatted JSON formatted quiz data through a user interface. The input is the quiz data received from the server, and the output is the display of quiz questions to the user.

[0553] Step 6:

[0554] The user answers the quiz questions displayed on the terminal. The user inputs the answer by clicking on the answer option or by writing it down. The input is the user's answer, and the output is the answer data.

[0555] Step 7:

[0556] The terminal sends the user's answer data to the server. The answer data includes data such as the user ID, question ID, and selected answer. The input is the user's answer data, and the output is the answer data sent to the server.

[0557] Step 8:

[0558] The server verifies the received answer data by checking it against a list of correct answers. The server compares the user's answer with a list of correct answers prepared in advance and determines whether it is correct or not. The input is the user's answer data and the list of correct answers, and the output is the verification result.

[0559] Step 9:

[0560] If the user answers all questions correctly, the server generates a unique authentication token. It issues an authentication token associated with the user ID and the product being purchased. The input is the verification result, and the output is the generated authentication token.

[0561] Step 10:

[0562] The server sends the generated authentication token to the user's device. The token is securely transmitted using a secure communication protocol (e.g., HTTPS). The input is the generated authentication token, and the output is the authentication token sent to the device.

[0563] (Application example 1)

[0564] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0565] Conventional sales systems lack the means to deepen product knowledge and have the problem of rampant resale without proper purchaser authentication. In particular, in physical stores, opportunities to deepen product understanding are limited and effective means to prevent resale are lacking. For this reason, there is a need for a system that allows users to fully understand products and purchase them through legitimate procedures.

[0566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0567] In this invention, the server includes means for acquiring information about a product, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for accepting and verifying the user's answer to the quiz, means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly, means for transmitting the authentication token to the user, and means for verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure. This allows the user to deepen their understanding of the product while obtaining legitimate authentication and proceeding with the purchase.

[0568] The "means for obtaining information about a product" is a function by which the server obtains detailed information about a specific product (for example, name, features, specifications, usage, advantages, etc.) from a database.

[0569] "Means for generating quizzes based on acquired product information" refers to a function that uses a generative AI model to create quiz questions based on the product information acquired by the server.

[0570] The "means for presenting the generated quiz to the user" is a function for displaying the generated quiz questions and presenting them to the user on the terminal used by the user.

[0571] The "means for accepting and verifying user's quiz answers" is a function in which a user answers a quiz question, sends the answer to the server, and the server checks whether the answer is correct.

[0572] The "means for generating an authentication token to proceed with the product purchase procedure" is a function that generates an authentication token, which is a unique identification code that the server uses to proceed with the purchase procedure, if the user answers all questions in the quiz correctly.

[0573] The "means for transmitting an authentication token to a user" is a function for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[0574] "Means of verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure" refers to a function that scans the user's authentication token on a dedicated terminal installed in a physical store, confirms its legitimacy, and then completes the purchase procedure.

[0575] This invention relates to a quiz-style promotion system for deepening understanding of products in brick-and-mortar stores and preventing resale. This system is implemented by three parties: a server, a terminal, and a user.

[0576] System Configuration

[0577] server

[0578] The server has the following functions:

[0579] 1. Obtaining product information

[0580] The server retrieves information about the products in the physical store from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[0581] 2. Quiz Generation

[0582] The server generates quiz questions from the acquired product information using a generative AI model. Generative AI models such as OpenAI's GPT-3 can be used. The quizzes are formatted as multiple choice or question-and-answer questions.

[0583] 3. Formatting the quiz

[0584] After the quiz questions are generated, the server formats them for presentation to the user by converting them into a data structure such as JSON.

[0585] 4. Verifying the Answer

[0586] The server receives the user's answers to the quiz and compares them with the list of correct answers to determine whether they are correct or incorrect.

[0587] 5. Generate and send authentication token

[0588] If the user answers all the quiz questions correctly, the server generates an authentication token (such as a QR code) and sends it to the user's device via a secure protocol.

[0589] Terminal

[0590] The terminal has the following functions:

[0591] 1. View the quiz

[0592] Users view and answer quiz questions on their devices, which are presented via a smartphone app or web browser.

[0593] 2. Submit your response

[0594] The user's answers to the quiz are sent to the server via a protocol such as an HTTP request.

[0595] 3. Present your authentication

[0596] The authentication token sent from the server is scanned by a dedicated terminal in the physical store, and the user displays the authentication token on the terminal.

[0597] User

[0598] 1. Obtain product information and answer quizzes

[0599] Users scan QR codes attached to products in physical stores with their device to obtain product information and answer quizzes.

[0600] 2. Authentication for Purchase

[0601] After answering all the questions in the quiz correctly, you present the authentication token at a dedicated terminal in the physical store and proceed with the purchase.

[0602] Processing flow

[0603] 1. Product information acquisition stage

[0604] When a user scans a QR code associated with a product in a physical store with their device, the server retrieves detailed information about the product from the database, including the product name, features, and specifications.

[0605] 2. Quiz generation and formatting stage

[0606] The server generates a quiz by inputting a prompt into the AI ​​model based on the acquired product information. For example, a prompt such as "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life" is input into the AI ​​model. The generated quiz questions are then formatted in JSON format.

[0607] 3. Viewing the quiz and submitting answers

[0608] Quiz questions are displayed on the terminal, and the user answers them. The answer data is sent to the server, which checks it against a list of correct answers.

[0609] 4. Authentication token generation and checkout process

[0610] If the user answers all questions correctly, the server generates an authentication token and sends it to the terminal. The user presents this at a dedicated terminal in the physical store to complete the purchase process.

[0611] In this way, users can deepen their understanding of the product and proceed with the purchase after proper authentication. This system is particularly effective in preventing the resale of expensive products.

[0612] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0613] Step 1:

[0614] Obtaining product information

[0615] The server receives the information entered by the user's device reading the QR code attached to the product in the physical store. The device scans the QR code and sends a request to the server, which starts the process.

[0616] The server retrieves detailed information about the relevant product from the database (product name, features, specifications, usage, main benefits) and inputs the results into the server.

[0617] The product information retrieved from the database becomes the output of the server, and the process proceeds to the next step.

[0618] Step 2:

[0619] Generate a quiz

[0620] To use the generative AI model, the server formats the acquired product information into a prompt sentence, which becomes the server's input.

[0621] The server inputs a prompt into the generative AI model (API) and requests the generation of quiz questions. The prompt input is something like, "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life."

[0622] The generative AI model outputs quiz questions, which are received by the server. The quiz question text becomes the server's output.

[0623] Step 3:

[0624] Quiz Formatting

[0625] The server formats the generated quiz questions into a format for presentation to the user.

[0626] The quiz questions are converted into structured data such as JSON and formatted. This is the input and processed data for the server.

[0627] The formatted quiz question data is output from the server and sent to the user's terminal.

[0628] Step 4:

[0629] View Quiz

[0630] The user's terminal receives the formatted quiz data received from the server as input.

[0631] The terminal displays the quiz questions on the user interface, which is the specific operation of the terminal.

[0632] The displayed quiz will be the output of the terminal.

[0633] Step 5:

[0634] Getting user answers

[0635] The user answers the quiz questions displayed on the terminal, and the user's answers become the input.

[0636] The user's response data (clicking on an option or answering in written form) is entered into the terminal.

[0637] The terminal transmits the user's response data to the server, and the request to the server becomes the output of the terminal.

[0638] Step 6:

[0639] Verifying answers

[0640] The server compares the received user answers with the correct answer list. The user's answer data becomes the input for the server.

[0641] The server compares and verifies the user's answer with the correct answer list in the database, and this process involves data calculations.

[0642] The verification result is output by the server. If it is correct, proceed to the next step.

[0643] Step 7:

[0644] Generate and send an authentication token

[0645] After the server confirms that the user has answered all the questions correctly, it generates an authentication token, which is input to the server.

[0646] The server generates an authentication token (e.g., a QR code), which is a unique identification code, and sends it to the user's device via a secure protocol (e.g., HTTPS). Token generation and protocol selection are the server's operations.

[0647] An authentication token is the output of the server and sent to the user's device.

[0648] Step 8:

[0649] Presenting and validating authentication tokens

[0650] The user presents the authentication token at a dedicated terminal in the physical store. The token displayed on the user's terminal is used as input.

[0651] The dedicated terminal scans the presented authentication token and sends it to the server. The terminal's operation is to present and scan the token.

[0652] The server verifies the received authentication token and confirms its validity. The server's input is the token and its output is the verification result. If the verification is successful, the purchase procedure is completed.

[0653] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0654] The system of this invention provides a mechanism for preventing resale of products while deepening users' product knowledge. Furthermore, by providing a system that combines an emotion engine that can recognize users' emotions and dynamically change the content and presentation of quizzes based on those emotions, a more advanced user experience is realized.

[0655] Quiz Generation Module

[0656] Obtaining product information

[0657] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[0658] Generate a quiz

[0659] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[0660] Quiz Formatting

[0661] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[0662] Emotion Engine

[0663] emotion recognition

[0664] The device recognizes the user's emotional state by inputting the user's facial expressions and tone of voice into an emotion engine via sensors such as a camera and microphone. Emotional states are classified into multiple categories, such as joy, anger, sadness, and surprise.

[0665] Sentiment Data Analysis

[0666] The server analyzes the recognized emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if a user is feeling anxious or stressed, the server can set the quiz to present easier questions first.

[0667] User Interface

[0668] View Quiz

[0669] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. The display content is dynamically adjusted according to the user's emotional state.

[0670] Getting user answers

[0671] The user checks the quiz questions displayed on the device and selects or enters an answer by clicking on an option or writing an answer.

[0672] Submitting user answers

[0673] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[0674] Purchase Management System

[0675] Verifying answers

[0676] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[0677] Generate an authentication token

[0678] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[0679] Sending an authentication token

[0680] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[0681] Specific examples

[0682] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[0683] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[0684] Furthermore, if the device's camera detects the user's facial expressions and detects that the user is feeling anxious about the quiz, the server can make the next quiz a little easier or add additional explanations, allowing the user to relax and take the quiz, gaining accurate knowledge as they proceed through the purchasing process.

[0685] The processing flow will be explained below.

[0686] Step 1:

[0687] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[0688] Step 2:

[0689] The server uses a generative AI model to generate quiz questions based on the acquired product information. For example, it creates a question such as "What are the features of this product?" along with corresponding options.

[0690] Step 3:

[0691] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[0692] Step 4:

[0693] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[0694] Step 5:

[0695] The device uses sensors such as a built-in camera and microphone to input the user's facial expressions and tone of voice into the emotion engine.

[0696] Step 6:

[0697] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their current emotional state (joy, anger, sadness, surprise, etc.).

[0698] Step 7:

[0699] The emotion engine sends the recognized emotion data to the server.

[0700] Step 8:

[0701] The server analyzes the received emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if the user is feeling anxious, it will present easier questions first.

[0702] Step 9:

[0703] The device then displays the adjusted quiz questions to the user again, with the content and presentation method taking into consideration the user's emotional state.

[0704] Step 10:

[0705] The user answers the displayed quiz questions by clicking on the answer options or by writing a response.

[0706] Step 11:

[0707] The terminal sends the user's answer to the server. This sent data includes the user ID, question ID, selected answer, etc.

[0708] Step 12:

[0709] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[0710] Step 13:

[0711] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[0712] Step 14:

[0713] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[0714] Step 15:

[0715] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[0716] Step 16:

[0717] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[0718] Step 17:

[0719] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[0720] Step 18:

[0721] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[0722] Example 2

[0723] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0724] In modern online shopping, preventing product resale and improving the user's purchasing experience are important issues. Especially for high-priced or limited-edition products, it is necessary to prevent purchases for resale purposes while also enabling users to gain sufficient information about the product before purchasing. However, conventional systems lack a mechanism for dynamically adjusting the content and difficulty of quizzes based on the user's emotional state, resulting in a uniform user experience.

[0725] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0726] In this invention, the server includes: [means for acquiring information about a product;] [means for generating a quiz using a generative AI model based on the acquired product information;] [means for formatting the generated quiz into a format for presentation to the user;] [means for recognizing the user's emotional state;] [means for dynamically adjusting the content and difficulty of the quiz based on the recognized emotional state;] [means for displaying the quiz to the user;] [means for accepting and verifying the user's quiz answers; [means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly; and] [means for sending the authentication token to the user. This allows the user to gain sufficient knowledge about the product while taking a quiz that is appropriate to their situation and emotions at the time, preventing resale and improving the user experience.

[0727] "Means for obtaining information about products" refers to technical means for obtaining detailed information about products from a database.

[0728] "Means for generating a quiz using a generative AI model based on acquired product information" refers to means for creating a quiz using a generative AI model based on acquired product information.

[0729] The "means for formatting the generated quiz into a format for presenting to the user" refers to a means for formatting data and converting it into an appropriate format such as JSON or HTML in order to properly present the generated quiz questions to the user.

[0730] The "means for recognizing the user's emotional state" is a means for detecting the user's facial expression, tone of voice, etc. using sensors such as a camera or microphone on the device, and recognizing the emotional state using an emotion engine.

[0731] "Means for dynamically adjusting the content and difficulty of a quiz based on a recognized emotional state" refers to means for dynamically adjusting the content, difficulty, and presentation order of a quiz based on the recognized emotional state of the user.

[0732] "Means for displaying a quiz to a user" refers to the technical means for displaying the quiz questions sent from the server to a user, and includes web browser forms, application screens, and the like.

[0733] The "means for receiving and verifying a user's quiz answer" refers to a means for receiving an answer selected or entered by a user to a quiz and verifying the answer by checking it against a list of correct answers.

[0734] The "means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly" refers to a means for generating an authentication token, which is a unique identification code for the purchase procedure, if the user answers all the quizzes correctly.

[0735] The "means for transmitting an authentication token to a user" refers to a means for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[0736] MODE FOR CARRYING OUT THE INVENTION

[0737] This embodiment of the present invention provides a system that prevents resale of products while deepening users' product knowledge. In addition, by combining it with an emotion engine that recognizes the user's emotions and dynamically changes the content and difficulty of the quiz based on those emotions, a more advanced user experience is realized. A specific implementation method is described below.

[0738] 1. Obtaining product information

[0739] The server retrieves detailed information about the product being bought and sold from a database, including the product name, features, specifications, instructions for use, key benefits, etc. The server executes SQL queries to retrieve the required information from the database and loads it into memory.

[0740] 2. Quiz Generation

[0741] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. For example, a prompt such as "What are the features of this smartphone?" is input into the generative AI model, which then generates options such as "A. 5G compatible," "B. 4K camera," "C. Waterproof," and "D. All." A common open-source natural language processing (NLP) model can be used as the generative AI model.

[0742] 3. Formatting the quiz

[0743] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and saved in the file system.

[0744] 4. Emotional Recognition

[0745] The device inputs the user's facial expressions and tone of voice into the emotion engine via sensors such as a camera and microphone. This allows the user's emotional state to be recognized. Emotional states are classified as joy, anger, sadness, surprise, etc. The emotion engine uses image recognition and voice analysis technology.

[0746] 5. Emotional Data Analysis

[0747] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quizzes based on the user's emotional state. For example, if the user is feeling anxious, the server will set the next quiz to an easier one.

[0748] 6. View the quiz

[0749] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. Based on the JSON format data received from the server, the device generates HTML and CSS to display the quiz.

[0750] 7. Obtaining User Answers

[0751] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. Specifically, the user selects option D (all). The user's input is acquired by the terminal as form data.

[0752] 8. Submitting User Answers

[0753] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID. The data is sent using a secure protocol.

[0754] 9. Verifying the Answer

[0755] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[0756] 10. Generate an authentication token

[0757] If the user answers all the quiz questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code stored in a secure data store.

[0758] 11. Sending Authentication Tokens

[0759] The server sends the generated authentication token to the user's device using a secure communication protocol.

[0760] Specific examples

[0761] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[0762] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[0763] An example of a prompt is:

[0764] "Generate a quiz about selling a new smartphone. Create multiple-choice questions that include the product's features and benefits, and use a corresponding emotion recognition system to dynamically adjust the quiz based on the user's emotions. Specific examples of prompts might include, 'What are the features of this smartphone?' and 'What is the balance between style and performance?'"

[0765] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0766] Step 1:

[0767] The server retrieves detailed information about the product being sold from a database, using search criteria such as the product ID as input. The output is detailed product information such as the product name, features, specifications, instructions for use, and key benefits.

[0768] Specific operation: The server executes an SQL query such as "SELECT FROM product_info WHERE product_id = '12345'" and reads the retrieved data into memory.

[0769] Step 2:

[0770] The server generates quiz questions using a generative AI model based on the acquired product information. The acquired product information is used as input, and the generated quiz questions are obtained as output.

[0771] Specific operation: The server sends a prompt to the generation AI model saying, "Please generate quiz questions about the features of the new smartphone," and the AI ​​model returns the quiz questions.

[0772] Step 3:

[0773] The server formats the generated quiz questions into a format for presentation to the user. The generated quiz questions are used as input. As output, the formatted quiz questions are converted into a data structure such as JSON format.

[0774] Specific operation: The server converts the generated quiz questions into the "quiz_questions.json" format and saves the formatted data in the file system.

[0775] Step 4:

[0776] The device inputs the user's facial expressions and tone of voice to the emotion engine through sensors such as a camera and microphone. The input uses data on the user's facial expressions and voice. The output is a recognized emotional state.

[0777] Specific operation: The device captures the user's facial expression with a camera and sends the image data to the emotion engine, which analyzes the image data and determines the user's emotional state.

[0778] Step 5:

[0779] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quiz based on the user's emotional state. The recognized emotion data is used as input, and the adjusted quiz questions are obtained as output.

[0780] Specific operation: The server receives the emotion data of "anxiety" and reconfigures the list of quiz questions to prioritize displaying easy questions.

[0781] Step 6:

[0782] The terminal displays the quiz questions sent from the server to the user. The input is the quiz question data received from the server. The output is the quiz displayed on the screen.

[0783] Specific operation: The device downloads "quiz_questions.json" from the server and generates HTML and CSS to display the quiz questions on the UI.

[0784] Step 7:

[0785] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. The input is the user's answer. The output is the selected or input answer.

[0786] Specific behavior: The user clicks or enters options using the mouse or keyboard, and the input data is captured as a form.

[0787] Step 8:

[0788] The terminal transmits the answer selected or input by the user to the server. The input includes the user's answer data. The output is the transmitted answer data.

[0789] Specific operation: The device generates "user_answer.json" and posts the user's selected answer to the server.

[0790] Step 9:

[0791] The server compares the received user's answer with the correct answer list and determines whether the answer is correct. The input is the user's answer data and the correct answer list. The output is the verification result.

[0792] Specific operation: The server receives "user_answer.json" and checks the answer against the correct answer list.

[0793] Step 10:

[0794] The server generates an authentication token to allow the user to proceed with the purchase process if the user answers all the quiz questions correctly. The input is the verification results of all the quiz questions. The output is the generated authentication token.

[0795] Specific operation: If the server determines that all questions are answered correctly, it generates an "auth_token" and stores it in a secure data store.

[0796] Step 11:

[0797] The server sends the generated authentication token to the user's device. The input is the generated authentication token. The output is the authentication token sent to the user's device.

[0798] Specific operation: The server generates "auth_token.json" and sends it to the user's device via a secure protocol.

[0799] (Application example 2)

[0800] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0801] Today, there is a demand for systems to improve the customer experience in brick-and-mortar stores. However, there is a lack of ways for customers to deepen their knowledge about products while increasing their purchasing motivation. Furthermore, because content cannot be provided that takes into account customer emotions, customers may feel anxious or stressed, and the purchasing process may not proceed smoothly. Therefore, the challenge is to develop a system that provides an optimal purchasing experience based on the customer's emotional state by using a dynamic quiz adjustment function that includes emotion recognition.

[0802] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information about products, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for acquiring emotional data using sensors such as a camera and a microphone to recognize the user's emotional state, and means for dynamically adjusting the difficulty and content of the quiz based on the emotional data. This enables customers to deepen their knowledge about products in a physical store while taking on quizzes that correspond to their emotional state, thereby reducing customer stress and anxiety and allowing the purchasing process to proceed smoothly.

[0803] "Means for obtaining information about products" refers to a function for obtaining detailed information such as product features, specifications, and advantages from a database or external information source.

[0804] "Means for generating quizzes based on acquired product information" refers to a function that automatically creates quiz questions using a generative AI model based on acquired product information.

[0805] The "means for presenting the generated quiz to the user" is a function that provides an interface for displaying the generated quiz questions to the user.

[0806] The "means for accepting and verifying the user's quiz answers" is a function for receiving the quiz answers entered by the user and determining whether they are correct or incorrect.

[0807] The "means for generating an authentication token to proceed with the product purchase process when the user answers the quiz correctly" is a function that generates a unique authentication code to prove the user's authority to purchase a product when the user answers all the quizzes correctly.

[0808] The "means for transmitting an authentication token to a user" is a function for transmitting a generated authentication token to a user using a secure communication protocol.

[0809] "Means for acquiring emotional data using sensors such as a camera or microphone in order to recognize the user's emotional state" refers to a function that uses a camera or microphone to analyze the user's facial expressions and tone of voice and recognize the user's emotional state.

[0810] The "means for dynamically adjusting the difficulty and content of the quiz based on emotion data" is a function for changing the difficulty and content of the quiz in real time according to the recognized emotion of the user.

[0811] The system of this invention allows customers in physical stores to deepen their product knowledge while smoothly progressing through the purchasing process. The system mainly consists of the following components: a server, a terminal, and sensors such as a camera and a microphone.

[0812] Server Roles

[0813] The server retrieves product information from the database and generates a quiz based on that information. A generative AI model is used in this quiz generation process. The generated quiz is then formatted appropriately to be presented to the user. The server also has the function of accepting and verifying the user's quiz answers and generating authentication tokens. Furthermore, the server analyzes the user's emotional state data and dynamically adjusts the content and difficulty of the quiz.

[0814] Device Role

[0815] The terminal displays product information and quizzes sent from the server to the user. Devices such as smartphones and smart glasses are used. The terminal is equipped with a camera and microphone, and these sensors are used to recognize the user's emotional state in real time. The user's emotional data is sent to the server, which then adjusts the content and difficulty of the quiz.

[0816] User Experience

[0817] Users answer quizzes through their device, and if they answer all of them correctly, they receive an authentication token. This token is used to proceed with the product purchase process. While taking the quiz, the user's emotions are sensed via a camera and microphone. For example, if the user is feeling anxious or stressed, the server will adjust the next quiz to be easier.

[0818] Software and hardware used

[0819] The server requires a database management system (DBMS) and the computing resources to run the generative AI model, specifically, to analyze emotion data using OpenCV and the EmotionRecognition library.

[0820] The devices used are smartphones or smart glasses equipped with cameras and microphones, and the user interface is a web browser or dedicated application.

[0821] Specific examples

[0822] For example, let's say this system is used in a physical store selling new smartphones. The server retrieves information about the smartphone's features and advantages from a database (e.g., 5G compatibility, high-resolution camera, large-capacity battery). Based on this information, the generative AI model generates a quiz and sends it to the device. If the device is a smartphone, the user answers the quiz through the camera, and their facial expressions are analyzed during the process. If the user feels unsure, the server can easily adjust the next quiz to be presented. Furthermore, if the user answers all the quizzes correctly, the server issues an authentication token and sends it to the device. Using this token, the user can smoothly proceed through the purchase process.

[0823] Prompt Sentence Examples

[0824] Product information: {"Product name": "New smartphone", "Features": "5G compatible, high-resolution camera, large-capacity battery, OLED display"}.

[0825] Generate a quiz about this product.

[0826] This system configuration enriches the customer experience in physical stores, allowing customers to make purchases in a relaxed manner.

[0827] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0828] Step 1: Get product information

[0829] The server retrieves product information from the database, including product name, features, specifications, key benefits, etc. For example, it retrieves the features and benefits of a new smartphone (5G compatibility, high-resolution camera, large battery, etc.).

[0830] Input: Product ID

[0831] Output: Product data (product name, features, specifications, benefits)

[0832] Step 2: Generate the quiz

[0833] The server creates a prompt based on the acquired product information and sends it to the generative AI model, which then generates multiple quiz questions based on this prompt.

[0834] Input: Product data

[0835] Output: Quiz question set

[0836] Step 3: Formatting Quiz Questions

[0837] The server formats the generated quiz questions in an appropriate format (e.g., JSON) for presentation to the user, which is then sent to the user interface.

[0838] Input: Quiz question set

[0839] Output: Formatted quiz data

[0840] Step 4: Present the quiz

[0841] The terminal receives the formatted quiz data sent from the server and displays it to the user. The user interface uses the application screen of a smartphone or smart glasses.

[0842] Input: Formatted quiz data

[0843] Output: Quiz questions displayed

[0844] Step 5: Obtaining emotion data

[0845] The device captures the user's facial expressions and tone of voice through a camera and microphone, and sends the emotion data to the emotion engine, which then analyzes the user's emotional state.

[0846] Input: User facial expression images, voice data

[0847] Output: Emotional state data (happiness, anxiety, stress, etc.)

[0848] Step 6: Dynamically adjust the quiz

[0849] The server dynamically adjusts the difficulty and content of the quiz based on the emotional state data, for example, lowering the difficulty of the quiz if the user is in an anxious state.

[0850] Input: Emotional state data, formatted quiz data

[0851] Output: Reconciled quiz data

[0852] Step 7: Accept quiz responses

[0853] The user answers the quiz questions displayed on the terminal, and the terminal accepts the answers and transmits them to the server.

[0854] Input: User's answer

[0855] Output: Accepted response data

[0856] Step 8: Verify your answers

[0857] The server checks the user's answer against a list of correct answers to determine whether the answer is correct.

[0858] Input: User response data, correct answer list

[0859] Output: Correctness of answer

[0860] Step 9: Generate an Auth Token

[0861] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code, that allows the user to proceed with the purchase process.

[0862] Input: Correct answer result

[0863] Output: Authentication token

[0864] Step 10: Sending an authentication token

[0865] The server sends the generated authentication token to the terminal, which displays it to the user, allowing the user to proceed with the purchase.

[0866] Input: Authentication Token

[0867] Output: Displayed authentication token

[0868] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0869] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0870] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0871] [Third embodiment]

[0872] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0873] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0874] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0875] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0876] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0877] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0878] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0879] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0880] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0881] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0882] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0883] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0884] The system of the present invention includes the following means, thereby providing a mechanism for preventing resale of products while helping customers deepen their knowledge of the products.

[0885] Quiz Generation Module

[0886] Obtaining product information

[0887] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[0888] Generate a quiz

[0889] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[0890] Quiz Formatting

[0891] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[0892] User Interface

[0893] View Quiz

[0894] The terminal displays the quiz questions sent from the server to the user, and the user interface presents the quiz through, for example, a web page or an application.

[0895] Getting user answers

[0896] The user answers the displayed quiz questions by clicking on the options or by writing the answer.

[0897] Submitting user answers

[0898] The terminal transmits the user's answer to the server. This transmitted data includes the user ID, question ID, selected answer, etc.

[0899] Purchase Management System

[0900] Verifying answers

[0901] The server checks the received user's answers against the correct answers. A list of correct answers is prepared for each question, and the server compares the user's answers with the list to determine whether they are correct or not.

[0902] Generate an authentication token

[0903] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code that is associated with a specific user and the product being purchased.

[0904] Sending an authentication token

[0905] The server then sends the generated authentication token to the user's device. The token is transmitted using a secure communication protocol to ensure authenticity.

[0906] Specific examples

[0907] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[0908] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[0909] This system allows users to understand the details of the product before making a purchase, and effectively prevents resale.

[0910] The processing flow will be explained below.

[0911] Step 1:

[0912] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[0913] Step 2:

[0914] The server inputs the acquired product information into the generative AI model and generates quiz questions, such as "What are the features of this product?" along with corresponding options.

[0915] Step 3:

[0916] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[0917] Step 4:

[0918] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[0919] Step 5:

[0920] The user checks the quiz questions displayed on the terminal and selects or inputs an answer, for example, by clicking one of the options.

[0921] Step 6:

[0922] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[0923] Step 7:

[0924] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[0925] Step 8:

[0926] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code used to verify the user's purchasing authority.

[0927] Step 9:

[0928] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[0929] Step 10:

[0930] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[0931] Step 11:

[0932] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[0933] Step 12:

[0934] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[0935] Step 13:

[0936] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[0937] Example 1

[0938] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0939] It is necessary to effectively provide users with detailed product information so that they can proceed with the purchase process while having accurate knowledge about the product, thereby preventing fraudulent resale. However, conventional systems lack a mechanism that integrates the provision of product information, the generation of quizzes, and the confirmation of user knowledge, resulting in low user understanding and insufficient effectiveness in preventing resale.

[0940] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0941] In this invention, the server includes means for acquiring detailed product information from a database, means for generating a quiz based on the acquired product information using a generative AI model, means for formatting the generated quiz into JSON format and presenting it to the user via a user interface, means for accepting the user's answers to the quiz and verifying the answers against a list of correct answers, means for generating a unique authentication token if the user answers all questions correctly, and means for transmitting the authentication token to the user using a secure communication protocol. This allows the user to proceed with the purchase process while having in-depth knowledge of the product, and prevents resale.

[0942] "Means for retrieving detailed information about a product from a database" refers to the process of retrieving data such as the product's name, features, specifications, usage, and main benefits from a designated database.

[0943] "Means of generating quizzes based on acquired product information using a generative AI model" refers to the process of inputting product information into a pre-prepared generative AI model and automatically generating appropriate quiz questions based on that information.

[0944] "Means for formatting the generated quiz into JSON format and presenting it to the user through a user interface" refers to the process of formatting the generated quiz questions into JSON format and displaying them to the user through a user interface such as a web page or application.

[0945] "Means for accepting a user's quiz answers and verifying the answers against a list of correct answers" refers to a process for receiving the answers to a quiz given by a user and comparing them with a list of correct answers to determine whether the answers are correct or not.

[0946] "Means for generating a unique authentication token if the user answers all quiz questions correctly" refers to the process of issuing a unique authentication token associated with a specific user ID after confirming that the user has answered all quiz questions correctly.

[0947] "Means for transmitting the authentication token to the user using a secure communication protocol" refers to the process of securely transmitting the generated authentication token to the user's device via a secure communication protocol (e.g., HTTPS).

[0948] The present invention relates to a system that promotes understanding of a product and prevents fraudulent resale as a user purchases the product while deepening detailed knowledge about the product.

[0949] Hardware and Software Configuration

[0950] server

[0951] The server has the ability to retrieve detailed product information from a database. The database used is often an SQL-based database management system (DBMS). It also has the ability to generate quiz questions based on the retrieved product information using a generative AI model (e.g., OpenAI's GPT-3). It then formats the generated quiz questions in JSON format and sends them to the user's device.

[0952] Terminal

[0953] The device receives the quiz questions in JSON format sent from the server and displays them to the user through a user interface (UI), often a web page or a smartphone application.

[0954] User

[0955] The user answers the quiz questions displayed on the terminal. The user's answers are sent to the server via the terminal, and the server checks the received answers against a list of correct answers to determine whether they are correct or not.

[0956] Generate quiz questions

[0957] The server retrieves detailed product information (for example, in the case of a smartphone, whether it is 5G compatible, has a high-resolution camera, is waterproof, etc.) from a database. Using this information, the server generates quiz questions by providing the following prompt to a generative AI model (such as GPT-3):

[0958] "Explain the features of this new smartphone and generate appropriate quiz questions."

[0959] The generated quiz questions will have the following format:

[0960] "Which of the following features does this smartphone have? A. 5G support B. 4K camera C. Waterproof D. All of them"

[0961] Quiz delivery and answer verification

[0962] The terminal displays quiz questions to the user through a user interface. The user answers the quiz questions and sends the answers to the server through the terminal. The server compares the received answer data with a list of correct answers and determines whether the user's answers are correct. If the user answers all the quiz questions correctly, the server generates a unique authentication token and sends it to the user's terminal using a secure communication protocol (e.g., HTTPS).

[0963] Specific operation example

[0964] When selling a new smartphone, the server first retrieves information about the product's features and advantages (e.g., 5G compatibility, high-resolution camera, waterproof) from a database. Next, it uses a generative AI model to generate a quiz question such as, "What are the features of this smartphone?" and creates the options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," and "D. All of them." The quiz question is displayed to the user through the user interface, and when the user selects "D. All of them," the answer is sent to the server. The server verifies the answer, and if it is confirmed to be correct, it generates a unique authentication token and sends it to the user's device. This allows the user to officially proceed with the product purchase process.

[0965] This system allows users to make purchases after gaining detailed knowledge about the products, while at the same time effectively preventing resale.

[0966] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0967] Step 1:

[0968] The server retrieves detailed product information from a database, including product name, features, specifications, usage, key benefits, etc. The server queries the database using SQL queries to retrieve the relevant product information. The input is the database query, and the output is a set of product information.

[0969] Step 2:

[0970] The server generates quiz questions using a generative AI model (e.g., GPT-3) based on the acquired product information. The server inputs the prompt "Please generate quiz questions related to this product" into the generative AI model and receives the quiz questions output by the model. The input is the product information and the prompt, and the output is the generated quiz questions.

[0971] Step 3:

[0972] The server formats the generated quiz questions into a format for presenting them to the user. Specifically, the quiz questions are converted into JSON format. For example, if the quiz has multiple-choice options, it formats them into a JSON format that includes the quiz questions and the options. The input is the generated quiz questions, and the output is the formatted JSON quiz data.

[0973] Step 4:

[0974] The server sends the quiz data in formatted JSON to the terminal, transmits the data through an appropriate communication protocol, and presents the quiz to the user via a user interface. The input is the quiz data in formatted JSON, and the output is the quiz data sent to the terminal.

[0975] Step 5:

[0976] The terminal displays quiz questions to the user. It visually displays formatted JSON formatted quiz data through a user interface. The input is the quiz data received from the server, and the output is the display of quiz questions to the user.

[0977] Step 6:

[0978] The user answers the quiz questions displayed on the terminal. The user inputs the answer by clicking on the answer option or by writing it down. The input is the user's answer, and the output is the answer data.

[0979] Step 7:

[0980] The terminal sends the user's answer data to the server. The answer data includes data such as the user ID, question ID, and selected answer. The input is the user's answer data, and the output is the answer data sent to the server.

[0981] Step 8:

[0982] The server verifies the received answer data by checking it against a list of correct answers. The server compares the user's answer with a list of correct answers prepared in advance and determines whether it is correct or not. The input is the user's answer data and the list of correct answers, and the output is the verification result.

[0983] Step 9:

[0984] If the user answers all questions correctly, the server generates a unique authentication token. It issues an authentication token associated with the user ID and the product being purchased. The input is the verification result, and the output is the generated authentication token.

[0985] Step 10:

[0986] The server sends the generated authentication token to the user's device. The token is securely transmitted using a secure communication protocol (e.g., HTTPS). The input is the generated authentication token, and the output is the authentication token sent to the device.

[0987] (Application example 1)

[0988] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0989] Conventional sales systems lack the means to deepen product knowledge and have the problem of rampant resale without proper purchaser authentication. In particular, in physical stores, opportunities to deepen product understanding are limited and effective means to prevent resale are lacking. For this reason, there is a need for a system that allows users to fully understand products and purchase them through legitimate procedures.

[0990] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0991] In this invention, the server includes means for acquiring information about a product, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for accepting and verifying the user's answer to the quiz, means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly, means for transmitting the authentication token to the user, and means for verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure. This allows the user to deepen their understanding of the product while obtaining legitimate authentication and proceeding with the purchase.

[0992] The "means for obtaining information about a product" is a function by which the server obtains detailed information about a specific product (for example, name, features, specifications, usage, advantages, etc.) from a database.

[0993] "Means for generating quizzes based on acquired product information" refers to a function that uses a generative AI model to create quiz questions based on the product information acquired by the server.

[0994] The "means for presenting the generated quiz to the user" is a function for displaying the generated quiz questions and presenting them to the user on the terminal used by the user.

[0995] The "means for accepting and verifying user's quiz answers" is a function in which a user answers a quiz question, sends the answer to the server, and the server checks whether the answer is correct.

[0996] The "means for generating an authentication token to proceed with the product purchase procedure" is a function that generates an authentication token, which is a unique identification code that the server uses to proceed with the purchase procedure, if the user answers all questions in the quiz correctly.

[0997] The "means for transmitting an authentication token to a user" is a function for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[0998] "Means of verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure" refers to a function that scans the user's authentication token on a dedicated terminal installed in a physical store, confirms its legitimacy, and then completes the purchase procedure.

[0999] This invention relates to a quiz-style promotion system for deepening understanding of products in brick-and-mortar stores and preventing resale. This system is implemented by three parties: a server, a terminal, and a user.

[1000] System Configuration

[1001] server

[1002] The server has the following functions:

[1003] 1. Obtaining product information

[1004] The server retrieves information about the products in the physical store from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[1005] 2. Quiz Generation

[1006] The server generates quiz questions from the acquired product information using a generative AI model. Generative AI models such as OpenAI's GPT-3 can be used. The quizzes are formatted as multiple choice or question-and-answer questions.

[1007] 3. Formatting the quiz

[1008] After the quiz questions are generated, the server formats them for presentation to the user by converting them into a data structure such as JSON.

[1009] 4. Verifying the Answer

[1010] The server receives the user's answers to the quiz and compares them with the list of correct answers to determine whether they are correct or incorrect.

[1011] 5. Generate and send authentication token

[1012] If the user answers all the quiz questions correctly, the server generates an authentication token (such as a QR code) and sends it to the user's device via a secure protocol.

[1013] Terminal

[1014] The terminal has the following functions:

[1015] 1. View the quiz

[1016] Users view and answer quiz questions on their devices, which are presented via a smartphone app or web browser.

[1017] 2. Submit your response

[1018] The user's answers to the quiz are sent to the server via a protocol such as an HTTP request.

[1019] 3. Present your authentication

[1020] The authentication token sent from the server is scanned by a dedicated terminal in the physical store, and the user displays the authentication token on the terminal.

[1021] User

[1022] 1. Obtain product information and answer quizzes

[1023] Users scan QR codes attached to products in physical stores with their device to obtain product information and answer quizzes.

[1024] 2. Authentication for Purchase

[1025] After answering all the questions in the quiz correctly, you present the authentication token at a dedicated terminal in the physical store and proceed with the purchase.

[1026] Processing flow

[1027] 1. Product information acquisition stage

[1028] When a user scans a QR code associated with a product in a physical store with their device, the server retrieves detailed information about the product from the database, including the product name, features, and specifications.

[1029] 2. Quiz generation and formatting stage

[1030] The server generates a quiz by inputting a prompt into the AI ​​model based on the acquired product information. For example, a prompt such as "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life" is input into the AI ​​model. The generated quiz questions are then formatted in JSON format.

[1031] 3. Viewing the quiz and submitting answers

[1032] Quiz questions are displayed on the terminal, and the user answers them. The answer data is sent to the server, which checks it against a list of correct answers.

[1033] 4. Authentication token generation and checkout process

[1034] If the user answers all questions correctly, the server generates an authentication token and sends it to the terminal. The user presents this at a dedicated terminal in the physical store to complete the purchase process.

[1035] In this way, users can deepen their understanding of the product and proceed with the purchase after proper authentication. This system is particularly effective in preventing the resale of expensive products.

[1036] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1037] Step 1:

[1038] Obtaining product information

[1039] The server receives the information entered by the user's device reading the QR code attached to the product in the physical store. The device scans the QR code and sends a request to the server, which starts the process.

[1040] The server retrieves detailed information about the relevant product from the database (product name, features, specifications, usage, main benefits) and inputs the results into the server.

[1041] The product information retrieved from the database becomes the output of the server, and the process proceeds to the next step.

[1042] Step 2:

[1043] Generate a quiz

[1044] To use the generative AI model, the server formats the acquired product information into a prompt sentence, which becomes the server's input.

[1045] The server inputs a prompt into the generative AI model (API) and requests the generation of quiz questions. The prompt input is something like, "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life."

[1046] The generative AI model outputs quiz questions, which are received by the server. The quiz question text becomes the server's output.

[1047] Step 3:

[1048] Quiz Formatting

[1049] The server formats the generated quiz questions into a format for presentation to the user.

[1050] The quiz questions are converted into structured data such as JSON and formatted. This is the input and processed data for the server.

[1051] The formatted quiz question data is output from the server and sent to the user's terminal.

[1052] Step 4:

[1053] View Quiz

[1054] The user's terminal receives the formatted quiz data received from the server as input.

[1055] The terminal displays the quiz questions on the user interface, which is the specific operation of the terminal.

[1056] The displayed quiz will be the output of the terminal.

[1057] Step 5:

[1058] Getting user answers

[1059] The user answers the quiz questions displayed on the terminal, and the user's answers become the input.

[1060] The user's response data (clicking on an option or answering in written form) is entered into the terminal.

[1061] The terminal transmits the user's response data to the server, and the request to the server becomes the output of the terminal.

[1062] Step 6:

[1063] Verifying answers

[1064] The server compares the received user answers with the correct answer list. The user's answer data becomes the input for the server.

[1065] The server compares and verifies the user's answer with the correct answer list in the database, and this process involves data calculations.

[1066] The verification result is output by the server. If it is correct, proceed to the next step.

[1067] Step 7:

[1068] Generate and send an authentication token

[1069] After the server confirms that the user has answered all the questions correctly, it generates an authentication token, which is input to the server.

[1070] The server generates an authentication token (e.g., a QR code), which is a unique identification code, and sends it to the user's device via a secure protocol (e.g., HTTPS). Token generation and protocol selection are the server's operations.

[1071] An authentication token is the output of the server and sent to the user's device.

[1072] Step 8:

[1073] Presenting and validating authentication tokens

[1074] The user presents the authentication token at a dedicated terminal in the physical store. The token displayed on the user's terminal is used as input.

[1075] The dedicated terminal scans the presented authentication token and sends it to the server. The terminal's operation is to present and scan the token.

[1076] The server verifies the received authentication token and confirms its validity. The server's input is the token and its output is the verification result. If the verification is successful, the purchase procedure is completed.

[1077] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1078] The system of this invention provides a mechanism for preventing resale of products while deepening users' product knowledge. Furthermore, by providing a system that combines an emotion engine that can recognize users' emotions and dynamically change the content and presentation of quizzes based on those emotions, a more advanced user experience is realized.

[1079] Quiz Generation Module

[1080] Obtaining product information

[1081] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[1082] Generate a quiz

[1083] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[1084] Quiz Formatting

[1085] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[1086] Emotion Engine

[1087] emotion recognition

[1088] The device recognizes the user's emotional state by inputting the user's facial expressions and tone of voice into an emotion engine via sensors such as a camera and microphone. Emotional states are classified into multiple categories, such as joy, anger, sadness, and surprise.

[1089] Sentiment Data Analysis

[1090] The server analyzes the recognized emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if a user is feeling anxious or stressed, the server can set the quiz to present easier questions first.

[1091] User Interface

[1092] View Quiz

[1093] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. The display content is dynamically adjusted according to the user's emotional state.

[1094] Getting user answers

[1095] The user checks the quiz questions displayed on the device and selects or enters an answer by clicking on an option or writing an answer.

[1096] Submitting user answers

[1097] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[1098] Purchase Management System

[1099] Verifying answers

[1100] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[1101] Generate an authentication token

[1102] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[1103] Sending an authentication token

[1104] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[1105] Specific examples

[1106] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[1107] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[1108] Furthermore, if the device's camera detects the user's facial expressions and detects that the user is feeling anxious about the quiz, the server can make the next quiz a little easier or add additional explanations, allowing the user to relax and take the quiz, gaining accurate knowledge as they proceed through the purchasing process.

[1109] The processing flow will be explained below.

[1110] Step 1:

[1111] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[1112] Step 2:

[1113] The server uses a generative AI model to generate quiz questions based on the acquired product information. For example, it creates a question such as "What are the features of this product?" along with corresponding options.

[1114] Step 3:

[1115] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[1116] Step 4:

[1117] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[1118] Step 5:

[1119] The device uses sensors such as a built-in camera and microphone to input the user's facial expressions and tone of voice into the emotion engine.

[1120] Step 6:

[1121] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their current emotional state (joy, anger, sadness, surprise, etc.).

[1122] Step 7:

[1123] The emotion engine sends the recognized emotion data to the server.

[1124] Step 8:

[1125] The server analyzes the received emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if the user is feeling anxious, it will present easier questions first.

[1126] Step 9:

[1127] The device then displays the adjusted quiz questions to the user again, with the content and presentation method taking into consideration the user's emotional state.

[1128] Step 10:

[1129] The user answers the displayed quiz questions by clicking on the answer options or by writing a response.

[1130] Step 11:

[1131] The terminal sends the user's answer to the server. This sent data includes the user ID, question ID, selected answer, etc.

[1132] Step 12:

[1133] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[1134] Step 13:

[1135] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[1136] Step 14:

[1137] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[1138] Step 15:

[1139] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[1140] Step 16:

[1141] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[1142] Step 17:

[1143] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[1144] Step 18:

[1145] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[1146] Example 2

[1147] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1148] In modern online shopping, preventing product resale and improving the user's purchasing experience are important issues. Especially for high-priced or limited-edition products, it is necessary to prevent purchases for resale purposes while also enabling users to gain sufficient information about the product before purchasing. However, conventional systems lack a mechanism for dynamically adjusting the content and difficulty of quizzes based on the user's emotional state, resulting in a uniform user experience.

[1149] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1150] In this invention, the server includes: [means for acquiring information about a product;] [means for generating a quiz using a generative AI model based on the acquired product information;] [means for formatting the generated quiz into a format for presentation to the user;] [means for recognizing the user's emotional state;] [means for dynamically adjusting the content and difficulty of the quiz based on the recognized emotional state;] [means for displaying the quiz to the user;] [means for accepting and verifying the user's quiz answers; [means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly; and] [means for sending the authentication token to the user. This allows the user to gain sufficient knowledge about the product while taking a quiz that is appropriate to their situation and emotions at the time, preventing resale and improving the user experience.

[1151] "Means for obtaining information about products" refers to technical means for obtaining detailed information about products from a database.

[1152] "Means for generating a quiz using a generative AI model based on acquired product information" refers to means for creating a quiz using a generative AI model based on acquired product information.

[1153] The "means for formatting the generated quiz into a format for presenting to the user" refers to a means for formatting data and converting it into an appropriate format such as JSON or HTML in order to properly present the generated quiz questions to the user.

[1154] The "means for recognizing the user's emotional state" is a means for detecting the user's facial expression, tone of voice, etc. using sensors such as a camera or microphone on the device, and recognizing the emotional state using an emotion engine.

[1155] "Means for dynamically adjusting the content and difficulty of a quiz based on a recognized emotional state" refers to means for dynamically adjusting the content, difficulty, and presentation order of a quiz based on the recognized emotional state of the user.

[1156] "Means for displaying a quiz to a user" refers to the technical means for displaying the quiz questions sent from the server to a user, and includes web browser forms, application screens, and the like.

[1157] The "means for receiving and verifying a user's quiz answer" refers to a means for receiving an answer selected or entered by a user to a quiz and verifying the answer by checking it against a list of correct answers.

[1158] The "means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly" refers to a means for generating an authentication token, which is a unique identification code for the purchase procedure, if the user answers all the quizzes correctly.

[1159] The "means for transmitting an authentication token to a user" refers to a means for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[1160] MODE FOR CARRYING OUT THE INVENTION

[1161] This embodiment of the present invention provides a system that prevents resale of products while deepening users' product knowledge. In addition, by combining it with an emotion engine that recognizes the user's emotions and dynamically changes the content and difficulty of the quiz based on those emotions, a more advanced user experience is realized. A specific implementation method is described below.

[1162] 1. Obtaining product information

[1163] The server retrieves detailed information about the product being bought and sold from a database, including the product name, features, specifications, instructions for use, key benefits, etc. The server executes SQL queries to retrieve the required information from the database and loads it into memory.

[1164] 2. Quiz Generation

[1165] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. For example, a prompt such as "What are the features of this smartphone?" is input into the generative AI model, which then generates options such as "A. 5G compatible," "B. 4K camera," "C. Waterproof," and "D. All." A common open-source natural language processing (NLP) model can be used as the generative AI model.

[1166] 3. Formatting the quiz

[1167] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and saved in the file system.

[1168] 4. Emotional Recognition

[1169] The device inputs the user's facial expressions and tone of voice into the emotion engine via sensors such as a camera and microphone. This allows the user's emotional state to be recognized. Emotional states are classified as joy, anger, sadness, surprise, etc. The emotion engine uses image recognition and voice analysis technology.

[1170] 5. Emotional Data Analysis

[1171] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quizzes based on the user's emotional state. For example, if the user is feeling anxious, the server will set the next quiz to an easier one.

[1172] 6. View the quiz

[1173] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. Based on the JSON format data received from the server, the device generates HTML and CSS to display the quiz.

[1174] 7. Obtaining User Answers

[1175] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. Specifically, the user selects option D (all). The user's input is acquired by the terminal as form data.

[1176] 8. Submitting User Answers

[1177] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID. The data is sent using a secure protocol.

[1178] 9. Verifying the Answer

[1179] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[1180] 10. Generate an authentication token

[1181] If the user answers all the quiz questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code stored in a secure data store.

[1182] 11. Sending Authentication Tokens

[1183] The server sends the generated authentication token to the user's device using a secure communication protocol.

[1184] Specific examples

[1185] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[1186] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[1187] An example of a prompt is:

[1188] "Generate a quiz about selling a new smartphone. Create multiple-choice questions that include the product's features and benefits, and use a corresponding emotion recognition system to dynamically adjust the quiz based on the user's emotions. Specific examples of prompts might include, 'What are the features of this smartphone?' and 'What is the balance between style and performance?'"

[1189] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1190] Step 1:

[1191] The server retrieves detailed information about the product being sold from a database, using search criteria such as the product ID as input. The output is detailed product information such as the product name, features, specifications, instructions for use, and key benefits.

[1192] Specific operation: The server executes an SQL query such as "SELECT FROM product_info WHERE product_id = '12345'" and reads the retrieved data into memory.

[1193] Step 2:

[1194] The server generates quiz questions using a generative AI model based on the acquired product information. The acquired product information is used as input, and the generated quiz questions are obtained as output.

[1195] Specific operation: The server sends a prompt to the generation AI model saying, "Please generate quiz questions about the features of the new smartphone," and the AI ​​model returns the quiz questions.

[1196] Step 3:

[1197] The server formats the generated quiz questions into a format for presentation to the user. The generated quiz questions are used as input. As output, the formatted quiz questions are converted into a data structure such as JSON format.

[1198] Specific operation: The server converts the generated quiz questions into the "quiz_questions.json" format and saves the formatted data in the file system.

[1199] Step 4:

[1200] The device inputs the user's facial expressions and tone of voice to the emotion engine through sensors such as a camera and microphone. The input uses data on the user's facial expressions and voice. The output is a recognized emotional state.

[1201] Specific operation: The device captures the user's facial expression with a camera and sends the image data to the emotion engine, which analyzes the image data and determines the user's emotional state.

[1202] Step 5:

[1203] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quiz based on the user's emotional state. The recognized emotion data is used as input, and the adjusted quiz questions are obtained as output.

[1204] Specific operation: The server receives the emotion data of "anxiety" and reconfigures the list of quiz questions to prioritize displaying easy questions.

[1205] Step 6:

[1206] The terminal displays the quiz questions sent from the server to the user. The input is the quiz question data received from the server. The output is the quiz displayed on the screen.

[1207] Specific operation: The device downloads "quiz_questions.json" from the server and generates HTML and CSS to display the quiz questions on the UI.

[1208] Step 7:

[1209] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. The input is the user's answer. The output is the selected or input answer.

[1210] Specific behavior: The user clicks or enters options using the mouse or keyboard, and the input data is captured as a form.

[1211] Step 8:

[1212] The terminal transmits the answer selected or input by the user to the server. The input includes the user's answer data. The output is the transmitted answer data.

[1213] Specific operation: The device generates "user_answer.json" and posts the user's selected answer to the server.

[1214] Step 9:

[1215] The server compares the received user's answer with the correct answer list and determines whether the answer is correct. The input is the user's answer data and the correct answer list. The output is the verification result.

[1216] Specific operation: The server receives "user_answer.json" and checks the answer against the correct answer list.

[1217] Step 10:

[1218] The server generates an authentication token to allow the user to proceed with the purchase process if the user answers all the quiz questions correctly. The input is the verification results of all the quiz questions. The output is the generated authentication token.

[1219] Specific operation: If the server determines that all questions are answered correctly, it generates an "auth_token" and stores it in a secure data store.

[1220] Step 11:

[1221] The server sends the generated authentication token to the user's device. The input is the generated authentication token. The output is the authentication token sent to the user's device.

[1222] Specific operation: The server generates "auth_token.json" and sends it to the user's device via a secure protocol.

[1223] (Application example 2)

[1224] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1225] Today, there is a demand for systems to improve the customer experience in brick-and-mortar stores. However, there is a lack of ways for customers to deepen their knowledge about products while increasing their purchasing motivation. Furthermore, because content cannot be provided that takes into account customer emotions, customers may feel anxious or stressed, and the purchasing process may not proceed smoothly. Therefore, the challenge is to develop a system that provides an optimal purchasing experience based on the customer's emotional state by using a dynamic quiz adjustment function that includes emotion recognition.

[1226] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information about products, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for acquiring emotional data using sensors such as a camera and a microphone to recognize the user's emotional state, and means for dynamically adjusting the difficulty and content of the quiz based on the emotional data. This enables customers to deepen their knowledge about products in a physical store while taking on quizzes that correspond to their emotional state, thereby reducing customer stress and anxiety and allowing the purchasing process to proceed smoothly.

[1227] "Means for obtaining information about products" refers to a function for obtaining detailed information such as product features, specifications, and advantages from a database or external information source.

[1228] "Means for generating quizzes based on acquired product information" refers to a function that automatically creates quiz questions using a generative AI model based on acquired product information.

[1229] The "means for presenting the generated quiz to the user" is a function that provides an interface for displaying the generated quiz questions to the user.

[1230] The "means for accepting and verifying the user's quiz answers" is a function for receiving the quiz answers entered by the user and determining whether they are correct or incorrect.

[1231] The "means for generating an authentication token to proceed with the product purchase process when the user answers the quiz correctly" is a function that generates a unique authentication code to prove the user's authority to purchase a product when the user answers all the quizzes correctly.

[1232] The "means for transmitting an authentication token to a user" is a function for transmitting a generated authentication token to a user using a secure communication protocol.

[1233] "Means for acquiring emotional data using sensors such as a camera or microphone in order to recognize the user's emotional state" refers to a function that uses a camera or microphone to analyze the user's facial expressions and tone of voice and recognize the user's emotional state.

[1234] The "means for dynamically adjusting the difficulty and content of the quiz based on emotion data" is a function for changing the difficulty and content of the quiz in real time according to the recognized emotion of the user.

[1235] The system of this invention allows customers in physical stores to deepen their product knowledge while smoothly progressing through the purchasing process. The system mainly consists of the following components: a server, a terminal, and sensors such as a camera and a microphone.

[1236] Server Roles

[1237] The server retrieves product information from the database and generates a quiz based on that information. A generative AI model is used in this quiz generation process. The generated quiz is then formatted appropriately to be presented to the user. The server also has the function of accepting and verifying the user's quiz answers and generating authentication tokens. Furthermore, the server analyzes the user's emotional state data and dynamically adjusts the content and difficulty of the quiz.

[1238] Device Role

[1239] The terminal displays product information and quizzes sent from the server to the user. Devices such as smartphones and smart glasses are used. The terminal is equipped with a camera and microphone, and these sensors are used to recognize the user's emotional state in real time. The user's emotional data is sent to the server, which then adjusts the content and difficulty of the quiz.

[1240] User Experience

[1241] Users answer quizzes through their device, and if they answer all of them correctly, they receive an authentication token. This token is used to proceed with the product purchase process. While taking the quiz, the user's emotions are sensed via a camera and microphone. For example, if the user is feeling anxious or stressed, the server will adjust the next quiz to be easier.

[1242] Software and hardware used

[1243] The server requires a database management system (DBMS) and the computing resources to run the generative AI model, specifically, to analyze emotion data using OpenCV and the EmotionRecognition library.

[1244] The devices used are smartphones or smart glasses equipped with cameras and microphones, and the user interface is a web browser or dedicated application.

[1245] Specific examples

[1246] For example, let's say this system is used in a physical store selling new smartphones. The server retrieves information about the smartphone's features and advantages from a database (e.g., 5G compatibility, high-resolution camera, large-capacity battery). Based on this information, the generative AI model generates a quiz and sends it to the device. If the device is a smartphone, the user answers the quiz through the camera, and their facial expressions are analyzed during the process. If the user feels unsure, the server can easily adjust the next quiz to be presented. Furthermore, if the user answers all the quizzes correctly, the server issues an authentication token and sends it to the device. Using this token, the user can smoothly proceed through the purchase process.

[1247] Prompt Sentence Examples

[1248] Product information: {"Product name": "New smartphone", "Features": "5G compatible, high-resolution camera, large-capacity battery, OLED display"}.

[1249] Generate a quiz about this product.

[1250] This system configuration enriches the customer experience in physical stores, allowing customers to make purchases in a relaxed manner.

[1251] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1252] Step 1: Get product information

[1253] The server retrieves product information from the database, including product name, features, specifications, key benefits, etc. For example, it retrieves the features and benefits of a new smartphone (5G compatibility, high-resolution camera, large battery, etc.).

[1254] Input: Product ID

[1255] Output: Product data (product name, features, specifications, benefits)

[1256] Step 2: Generate the quiz

[1257] The server creates a prompt based on the acquired product information and sends it to the generative AI model, which then generates multiple quiz questions based on this prompt.

[1258] Input: Product data

[1259] Output: Quiz question set

[1260] Step 3: Formatting Quiz Questions

[1261] The server formats the generated quiz questions in an appropriate format (e.g., JSON) for presentation to the user, which is then sent to the user interface.

[1262] Input: Quiz question set

[1263] Output: Formatted quiz data

[1264] Step 4: Present the quiz

[1265] The terminal receives the formatted quiz data sent from the server and displays it to the user. The user interface uses the application screen of a smartphone or smart glasses.

[1266] Input: Formatted quiz data

[1267] Output: Quiz questions displayed

[1268] Step 5: Obtaining emotion data

[1269] The device captures the user's facial expressions and tone of voice through a camera and microphone, and sends the emotion data to the emotion engine, which then analyzes the user's emotional state.

[1270] Input: User facial expression images, voice data

[1271] Output: Emotional state data (happiness, anxiety, stress, etc.)

[1272] Step 6: Dynamically adjust the quiz

[1273] The server dynamically adjusts the difficulty and content of the quiz based on the emotional state data, for example, lowering the difficulty of the quiz if the user is in an anxious state.

[1274] Input: Emotional state data, formatted quiz data

[1275] Output: Reconciled quiz data

[1276] Step 7: Accept quiz responses

[1277] The user answers the quiz questions displayed on the terminal, and the terminal accepts the answers and transmits them to the server.

[1278] Input: User's answer

[1279] Output: Accepted response data

[1280] Step 8: Verify your answers

[1281] The server checks the user's answer against a list of correct answers to determine whether the answer is correct.

[1282] Input: User response data, correct answer list

[1283] Output: Correctness of answer

[1284] Step 9: Generate an Auth Token

[1285] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code, that allows the user to proceed with the purchase process.

[1286] Input: Correct answer result

[1287] Output: Authentication token

[1288] Step 10: Sending an authentication token

[1289] The server sends the generated authentication token to the terminal, which displays it to the user, allowing the user to proceed with the purchase.

[1290] Input: Authentication Token

[1291] Output: Displayed authentication token

[1292] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1293] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1294] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1295] [Fourth embodiment]

[1296] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1297] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1298] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1299] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1300] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1301] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1302] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1303] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1304] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1305] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1306] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1307] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1308] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1309] The system of the present invention includes the following means, thereby providing a mechanism for preventing resale of products while helping customers deepen their knowledge of the products.

[1310] Quiz Generation Module

[1311] Obtaining product information

[1312] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[1313] Generate a quiz

[1314] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[1315] Quiz Formatting

[1316] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[1317] User Interface

[1318] View Quiz

[1319] The terminal displays the quiz questions sent from the server to the user, and the user interface presents the quiz through, for example, a web page or an application.

[1320] Getting user answers

[1321] The user answers the displayed quiz questions by clicking on the options or by writing the answer.

[1322] Submitting user answers

[1323] The terminal transmits the user's answer to the server. This transmitted data includes the user ID, question ID, selected answer, etc.

[1324] Purchase Management System

[1325] Verifying answers

[1326] The server checks the received user's answers against the correct answers. A list of correct answers is prepared for each question, and the server compares the user's answers with the list to determine whether they are correct or not.

[1327] Generate an authentication token

[1328] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code that is associated with a specific user and the product being purchased.

[1329] Sending an authentication token

[1330] The server then sends the generated authentication token to the user's device. The token is transmitted using a secure communication protocol to ensure authenticity.

[1331] Specific examples

[1332] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[1333] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[1334] This system allows users to understand the details of the product before making a purchase, and effectively prevents resale.

[1335] The processing flow will be explained below.

[1336] Step 1:

[1337] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[1338] Step 2:

[1339] The server inputs the acquired product information into the generative AI model and generates quiz questions, such as "What are the features of this product?" along with corresponding options.

[1340] Step 3:

[1341] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[1342] Step 4:

[1343] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[1344] Step 5:

[1345] The user checks the quiz questions displayed on the terminal and selects or inputs an answer, for example, by clicking one of the options.

[1346] Step 6:

[1347] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[1348] Step 7:

[1349] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[1350] Step 8:

[1351] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code used to verify the user's purchasing authority.

[1352] Step 9:

[1353] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[1354] Step 10:

[1355] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[1356] Step 11:

[1357] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[1358] Step 12:

[1359] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[1360] Step 13:

[1361] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[1362] Example 1

[1363] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1364] It is necessary to effectively provide users with detailed product information so that they can proceed with the purchase process while having accurate knowledge about the product, thereby preventing fraudulent resale. However, conventional systems lack a mechanism that integrates the provision of product information, the generation of quizzes, and the confirmation of user knowledge, resulting in low user understanding and insufficient effectiveness in preventing resale.

[1365] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1366] In this invention, the server includes means for acquiring detailed product information from a database, means for generating a quiz based on the acquired product information using a generative AI model, means for formatting the generated quiz into JSON format and presenting it to the user via a user interface, means for accepting the user's answers to the quiz and verifying the answers against a list of correct answers, means for generating a unique authentication token if the user answers all questions correctly, and means for transmitting the authentication token to the user using a secure communication protocol. This allows the user to proceed with the purchase process while having in-depth knowledge of the product, and prevents resale.

[1367] "Means for retrieving detailed information about a product from a database" refers to the process of retrieving data such as the product's name, features, specifications, usage, and main benefits from a designated database.

[1368] "Means of generating quizzes based on acquired product information using a generative AI model" refers to the process of inputting product information into a pre-prepared generative AI model and automatically generating appropriate quiz questions based on that information.

[1369] "Means for formatting the generated quiz into JSON format and presenting it to the user through a user interface" refers to the process of formatting the generated quiz questions into JSON format and displaying them to the user through a user interface such as a web page or application.

[1370] "Means for accepting a user's quiz answers and verifying the answers against a list of correct answers" refers to a process for receiving the answers to a quiz given by a user and comparing them with a list of correct answers to determine whether the answers are correct or not.

[1371] "Means for generating a unique authentication token if the user answers all quiz questions correctly" refers to the process of issuing a unique authentication token associated with a specific user ID after confirming that the user has answered all quiz questions correctly.

[1372] "Means for transmitting the authentication token to the user using a secure communication protocol" refers to the process of securely transmitting the generated authentication token to the user's device via a secure communication protocol (e.g., HTTPS).

[1373] The present invention relates to a system that promotes understanding of a product and prevents fraudulent resale as a user purchases the product while deepening detailed knowledge about the product.

[1374] Hardware and Software Configuration

[1375] server

[1376] The server has the ability to retrieve detailed product information from a database. The database used is often an SQL-based database management system (DBMS). It also has the ability to generate quiz questions based on the retrieved product information using a generative AI model (e.g., OpenAI's GPT-3). It then formats the generated quiz questions in JSON format and sends them to the user's device.

[1377] Terminal

[1378] The device receives the quiz questions in JSON format sent from the server and displays them to the user through a user interface (UI), often a web page or a smartphone application.

[1379] User

[1380] The user answers the quiz questions displayed on the terminal. The user's answers are sent to the server via the terminal, and the server checks the received answers against a list of correct answers to determine whether they are correct or not.

[1381] Generate quiz questions

[1382] The server retrieves detailed product information (for example, in the case of a smartphone, whether it is 5G compatible, has a high-resolution camera, is waterproof, etc.) from a database. Using this information, the server generates quiz questions by providing the following prompt to a generative AI model (such as GPT-3):

[1383] "Explain the features of this new smartphone and generate appropriate quiz questions."

[1384] The generated quiz questions will have the following format:

[1385] "Which of the following features does this smartphone have? A. 5G support B. 4K camera C. Waterproof D. All of them"

[1386] Quiz delivery and answer verification

[1387] The terminal displays quiz questions to the user through a user interface. The user answers the quiz questions and sends the answers to the server through the terminal. The server compares the received answer data with a list of correct answers and determines whether the user's answers are correct. If the user answers all the quiz questions correctly, the server generates a unique authentication token and sends it to the user's terminal using a secure communication protocol (e.g., HTTPS).

[1388] Specific operation example

[1389] When selling a new smartphone, the server first retrieves information about the product's features and advantages (e.g., 5G compatibility, high-resolution camera, waterproof) from a database. Next, it uses a generative AI model to generate a quiz question such as, "What are the features of this smartphone?" and creates the options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," and "D. All of them." The quiz question is displayed to the user through the user interface, and when the user selects "D. All of them," the answer is sent to the server. The server verifies the answer, and if it is confirmed to be correct, it generates a unique authentication token and sends it to the user's device. This allows the user to officially proceed with the product purchase process.

[1390] This system allows users to make purchases after gaining detailed knowledge about the products, while at the same time effectively preventing resale.

[1391] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1392] Step 1:

[1393] The server retrieves detailed product information from a database, including product name, features, specifications, usage, key benefits, etc. The server queries the database using SQL queries to retrieve the relevant product information. The input is the database query, and the output is a set of product information.

[1394] Step 2:

[1395] The server generates quiz questions using a generative AI model (e.g., GPT-3) based on the acquired product information. The server inputs the prompt "Please generate quiz questions related to this product" into the generative AI model and receives the quiz questions output by the model. The input is the product information and the prompt, and the output is the generated quiz questions.

[1396] Step 3:

[1397] The server formats the generated quiz questions into a format for presenting them to the user. Specifically, the quiz questions are converted into JSON format. For example, if the quiz has multiple-choice options, it formats them into a JSON format that includes the quiz questions and the options. The input is the generated quiz questions, and the output is the formatted JSON quiz data.

[1398] Step 4:

[1399] The server sends the quiz data in formatted JSON to the terminal, transmits the data through an appropriate communication protocol, and presents the quiz to the user via a user interface. The input is the quiz data in formatted JSON, and the output is the quiz data sent to the terminal.

[1400] Step 5:

[1401] The terminal displays quiz questions to the user. It visually displays formatted JSON formatted quiz data through a user interface. The input is the quiz data received from the server, and the output is the display of quiz questions to the user.

[1402] Step 6:

[1403] The user answers the quiz questions displayed on the terminal. The user inputs the answer by clicking on the answer option or by writing it down. The input is the user's answer, and the output is the answer data.

[1404] Step 7:

[1405] The terminal sends the user's answer data to the server. The answer data includes data such as the user ID, question ID, and selected answer. The input is the user's answer data, and the output is the answer data sent to the server.

[1406] Step 8:

[1407] The server verifies the received answer data by checking it against a list of correct answers. The server compares the user's answer with a list of correct answers prepared in advance and determines whether it is correct or not. The input is the user's answer data and the list of correct answers, and the output is the verification result.

[1408] Step 9:

[1409] If the user answers all questions correctly, the server generates a unique authentication token. It issues an authentication token associated with the user ID and the product being purchased. The input is the verification result, and the output is the generated authentication token.

[1410] Step 10:

[1411] The server sends the generated authentication token to the user's device. The token is securely transmitted using a secure communication protocol (e.g., HTTPS). The input is the generated authentication token, and the output is the authentication token sent to the device.

[1412] (Application example 1)

[1413] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1414] Conventional sales systems lack the means to deepen product knowledge and have the problem of rampant resale without proper purchaser authentication. In particular, in physical stores, opportunities to deepen product understanding are limited and effective means to prevent resale are lacking. For this reason, there is a need for a system that allows users to fully understand products and purchase them through legitimate procedures.

[1415] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1416] In this invention, the server includes means for acquiring information about a product, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for accepting and verifying the user's answer to the quiz, means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly, means for transmitting the authentication token to the user, and means for verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure. This allows the user to deepen their understanding of the product while obtaining legitimate authentication and proceeding with the purchase.

[1417] The "means for obtaining information about a product" is a function by which the server obtains detailed information about a specific product (for example, name, features, specifications, usage, advantages, etc.) from a database.

[1418] "Means for generating quizzes based on acquired product information" refers to a function that uses a generative AI model to create quiz questions based on the product information acquired by the server.

[1419] The "means for presenting the generated quiz to the user" is a function for displaying the generated quiz questions and presenting them to the user on the terminal used by the user.

[1420] The "means for accepting and verifying user's quiz answers" is a function in which a user answers a quiz question, sends the answer to the server, and the server checks whether the answer is correct.

[1421] The "means for generating an authentication token to proceed with the product purchase procedure" is a function that generates an authentication token, which is a unique identification code that the server uses to proceed with the purchase procedure, if the user answers all questions in the quiz correctly.

[1422] The "means for transmitting an authentication token to a user" is a function for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[1423] "Means of verifying the authentication token on a dedicated terminal in a physical store and completing the purchase procedure" refers to a function that scans the user's authentication token on a dedicated terminal installed in a physical store, confirms its legitimacy, and then completes the purchase procedure.

[1424] This invention relates to a quiz-style promotion system for deepening understanding of products in brick-and-mortar stores and preventing resale. This system is implemented by three parties: a server, a terminal, and a user.

[1425] System Configuration

[1426] server

[1427] The server has the following functions:

[1428] 1. Obtaining product information

[1429] The server retrieves information about the products in the physical store from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[1430] 2. Quiz Generation

[1431] The server generates quiz questions from the acquired product information using a generative AI model. Generative AI models such as OpenAI's GPT-3 can be used. The quizzes are formatted as multiple choice or question-and-answer questions.

[1432] 3. Formatting the quiz

[1433] After the quiz questions are generated, the server formats them for presentation to the user by converting them into a data structure such as JSON.

[1434] 4. Verifying the Answer

[1435] The server receives the user's answers to the quiz and compares them with the list of correct answers to determine whether they are correct or incorrect.

[1436] 5. Generate and send authentication token

[1437] If the user answers all the quiz questions correctly, the server generates an authentication token (such as a QR code) and sends it to the user's device via a secure protocol.

[1438] Terminal

[1439] The terminal has the following functions:

[1440] 1. View the quiz

[1441] Users view and answer quiz questions on their devices, which are presented via a smartphone app or web browser.

[1442] 2. Submit your response

[1443] The user's answers to the quiz are sent to the server via a protocol such as an HTTP request.

[1444] 3. Present your authentication

[1445] The authentication token sent from the server is scanned by a dedicated terminal in the physical store, and the user displays the authentication token on the terminal.

[1446] User

[1447] 1. Obtain product information and answer quizzes

[1448] Users scan QR codes attached to products in physical stores with their device to obtain product information and answer quizzes.

[1449] 2. Authentication for Purchase

[1450] After answering all the questions in the quiz correctly, you present the authentication token at a dedicated terminal in the physical store and proceed with the purchase.

[1451] Processing flow

[1452] 1. Product information acquisition stage

[1453] When a user scans a QR code associated with a product in a physical store with their device, the server retrieves detailed information about the product from the database, including the product name, features, and specifications.

[1454] 2. Quiz generation and formatting stage

[1455] The server generates a quiz by inputting a prompt into the AI ​​model based on the acquired product information. For example, a prompt such as "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life" is input into the AI ​​model. The generated quiz questions are then formatted in JSON format.

[1456] 3. Viewing the quiz and submitting answers

[1457] Quiz questions are displayed on the terminal, and the user answers them. The answer data is sent to the server, which checks it against a list of correct answers.

[1458] 4. Authentication token generation and checkout process

[1459] If the user answers all questions correctly, the server generates an authentication token and sends it to the terminal. The user presents this at a dedicated terminal in the physical store to complete the purchase process.

[1460] In this way, users can deepen their understanding of the product and proceed with the purchase after proper authentication. This system is particularly effective in preventing the resale of expensive products.

[1461] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1462] Step 1:

[1463] Obtaining product information

[1464] The server receives the information entered by the user's device reading the QR code attached to the product in the physical store. The device scans the QR code and sends a request to the server, which starts the process.

[1465] The server retrieves detailed information about the relevant product from the database (product name, features, specifications, usage, main benefits) and inputs the results into the server.

[1466] The product information retrieved from the database becomes the output of the server, and the process proceeds to the next step.

[1467] Step 2:

[1468] Generate a quiz

[1469] To use the generative AI model, the server formats the acquired product information into a prompt sentence, which becomes the server's input.

[1470] The server inputs a prompt into the generative AI model (API) and requests the generation of quiz questions. The prompt input is something like, "Please generate a quiz based on the following information: Product name: New smartphone, Features: 5G compatible, high-resolution camera, waterproof, long battery life."

[1471] The generative AI model outputs quiz questions, which are received by the server. The quiz question text becomes the server's output.

[1472] Step 3:

[1473] Quiz Formatting

[1474] The server formats the generated quiz questions into a format for presentation to the user.

[1475] The quiz questions are converted into structured data such as JSON and formatted. This is the input and processed data for the server.

[1476] The formatted quiz question data is output from the server and sent to the user's terminal.

[1477] Step 4:

[1478] View Quiz

[1479] The user's terminal receives the formatted quiz data received from the server as input.

[1480] The terminal displays the quiz questions on the user interface, which is the specific operation of the terminal.

[1481] The displayed quiz will be the output of the terminal.

[1482] Step 5:

[1483] Getting user answers

[1484] The user answers the quiz questions displayed on the terminal, and the user's answers become the input.

[1485] The user's response data (clicking on an option or answering in written form) is entered into the terminal.

[1486] The terminal transmits the user's response data to the server, and the request to the server becomes the output of the terminal.

[1487] Step 6:

[1488] Verifying answers

[1489] The server compares the received user answers with the correct answer list. The user's answer data becomes the input for the server.

[1490] The server compares and verifies the user's answer with the correct answer list in the database, and this process involves data calculations.

[1491] The verification result is output by the server. If it is correct, proceed to the next step.

[1492] Step 7:

[1493] Generate and send an authentication token

[1494] After the server confirms that the user has answered all the questions correctly, it generates an authentication token, which is input to the server.

[1495] The server generates an authentication token (e.g., a QR code), which is a unique identification code, and sends it to the user's device via a secure protocol (e.g., HTTPS). Token generation and protocol selection are the server's operations.

[1496] An authentication token is the output of the server and sent to the user's device.

[1497] Step 8:

[1498] Presenting and validating authentication tokens

[1499] The user presents the authentication token at a dedicated terminal in the physical store. The token displayed on the user's terminal is used as input.

[1500] The dedicated terminal scans the presented authentication token and sends it to the server. The terminal's operation is to present and scan the token.

[1501] The server verifies the received authentication token and confirms its validity. The server's input is the token and its output is the verification result. If the verification is successful, the purchase procedure is completed.

[1502] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1503] The system of this invention provides a mechanism for preventing resale of products while deepening users' product knowledge. Furthermore, by providing a system that combines an emotion engine that can recognize users' emotions and dynamically change the content and presentation of quizzes based on those emotions, a more advanced user experience is realized.

[1504] Quiz Generation Module

[1505] Obtaining product information

[1506] The server retrieves detailed information about the product being sold from a database, including product name, features, specifications, instructions for use, key benefits, etc.

[1507] Generate a quiz

[1508] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. These quizzes are, for example, multiple choice or question-and-answer format.

[1509] Quiz Formatting

[1510] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and stored in an appropriate format.

[1511] Emotion Engine

[1512] emotion recognition

[1513] The device recognizes the user's emotional state by inputting the user's facial expressions and tone of voice into an emotion engine via sensors such as a camera and microphone. Emotional states are classified into multiple categories, such as joy, anger, sadness, and surprise.

[1514] Sentiment Data Analysis

[1515] The server analyzes the recognized emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if a user is feeling anxious or stressed, the server can set the quiz to present easier questions first.

[1516] User Interface

[1517] View Quiz

[1518] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. The display content is dynamically adjusted according to the user's emotional state.

[1519] Getting user answers

[1520] The user checks the quiz questions displayed on the device and selects or enters an answer by clicking on an option or writing an answer.

[1521] Submitting user answers

[1522] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID.

[1523] Purchase Management System

[1524] Verifying answers

[1525] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[1526] Generate an authentication token

[1527] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[1528] Sending an authentication token

[1529] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[1530] Specific examples

[1531] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[1532] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[1533] Furthermore, if the device's camera detects the user's facial expressions and detects that the user is feeling anxious about the quiz, the server can make the next quiz a little easier or add additional explanations, allowing the user to relax and take the quiz, gaining accurate knowledge as they proceed through the purchasing process.

[1534] The processing flow will be explained below.

[1535] Step 1:

[1536] The server retrieves detailed product information (such as product name, features, specifications, usage, and key benefits) from a database.

[1537] Step 2:

[1538] The server uses a generative AI model to generate quiz questions based on the acquired product information. For example, it creates a question such as "What are the features of this product?" along with corresponding options.

[1539] Step 3:

[1540] The server converts the generated quiz questions into an appropriate data structure, such as JSON format, and sends them to the user interface.

[1541] Step 4:

[1542] The terminal displays the quiz questions received from the server to the user, possibly in the form of a web browser form or an application screen.

[1543] Step 5:

[1544] The device uses sensors such as a built-in camera and microphone to input the user's facial expressions and tone of voice into the emotion engine.

[1545] Step 6:

[1546] The emotion engine analyzes the user's facial expressions and tone of voice to recognize their current emotional state (joy, anger, sadness, surprise, etc.).

[1547] Step 7:

[1548] The emotion engine sends the recognized emotion data to the server.

[1549] Step 8:

[1550] The server analyzes the received emotional data and dynamically adjusts the difficulty, content, and presentation order of the quiz based on the user's emotional state. For example, if the user is feeling anxious, it will present easier questions first.

[1551] Step 9:

[1552] The device then displays the adjusted quiz questions to the user again, with the content and presentation method taking into consideration the user's emotional state.

[1553] Step 10:

[1554] The user answers the displayed quiz questions by clicking on the answer options or by writing a response.

[1555] Step 11:

[1556] The terminal sends the user's answer to the server. This sent data includes the user ID, question ID, selected answer, etc.

[1557] Step 12:

[1558] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If it is correct, it proceeds to the next processing step.

[1559] Step 13:

[1560] If the user answers all the questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code used to verify the user's purchasing authority.

[1561] Step 14:

[1562] The server then sends the generated authentication token to the user's device. The token is sent using a secure communication protocol to ensure authenticity.

[1563] Step 15:

[1564] The terminal uses the received authentication token to initiate the purchase process, displaying a screen on the user interface requesting the entry of shipping and payment information.

[1565] Step 16:

[1566] The user enters the required information (such as shipping address and payment information) and completes the purchase process.

[1567] Step 17:

[1568] The server confirms that the purchase has been completed successfully and sends a notification of the purchase to the user's device. If necessary, a receipt and / or order confirmation email will also be sent.

[1569] Step 18:

[1570] If the user answers the quiz incorrectly, the server sends a message to the terminal inviting the user to try again, allowing the user to try the quiz again.

[1571] Example 2

[1572] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1573] In modern online shopping, preventing product resale and improving the user's purchasing experience are important issues. Especially for high-priced or limited-edition products, it is necessary to prevent purchases for resale purposes while also enabling users to gain sufficient information about the product before purchasing. However, conventional systems lack a mechanism for dynamically adjusting the content and difficulty of quizzes based on the user's emotional state, resulting in a uniform user experience.

[1574] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1575] In this invention, the server includes: [means for acquiring information about a product;] [means for generating a quiz using a generative AI model based on the acquired product information;] [means for formatting the generated quiz into a format for presentation to the user;] [means for recognizing the user's emotional state;] [means for dynamically adjusting the content and difficulty of the quiz based on the recognized emotional state;] [means for displaying the quiz to the user;] [means for accepting and verifying the user's quiz answers; [means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly; and] [means for sending the authentication token to the user. This allows the user to gain sufficient knowledge about the product while taking a quiz that is appropriate to their situation and emotions at the time, preventing resale and improving the user experience.

[1576] "Means for obtaining information about products" refers to technical means for obtaining detailed information about products from a database.

[1577] "Means for generating a quiz using a generative AI model based on acquired product information" refers to means for creating a quiz using a generative AI model based on acquired product information.

[1578] The "means for formatting the generated quiz into a format for presenting to the user" refers to a means for formatting data and converting it into an appropriate format such as JSON or HTML in order to properly present the generated quiz questions to the user.

[1579] The "means for recognizing the user's emotional state" is a means for detecting the user's facial expression, tone of voice, etc. using sensors such as a camera or microphone on the device, and recognizing the emotional state using an emotion engine.

[1580] "Means for dynamically adjusting the content and difficulty of a quiz based on a recognized emotional state" refers to means for dynamically adjusting the content, difficulty, and presentation order of a quiz based on the recognized emotional state of the user.

[1581] "Means for displaying a quiz to a user" refers to the technical means for displaying the quiz questions sent from the server to a user, and includes web browser forms, application screens, and the like.

[1582] The "means for receiving and verifying a user's quiz answer" refers to a means for receiving an answer selected or entered by a user to a quiz and verifying the answer by checking it against a list of correct answers.

[1583] The "means for generating an authentication token for proceeding with the product purchase procedure if the user answers the quiz correctly" refers to a means for generating an authentication token, which is a unique identification code for the purchase procedure, if the user answers all the quizzes correctly.

[1584] The "means for transmitting an authentication token to a user" refers to a means for transmitting the generated authentication token to the user's terminal using a secure communication protocol.

[1585] MODE FOR CARRYING OUT THE INVENTION

[1586] This embodiment of the present invention provides a system that prevents resale of products while deepening users' product knowledge. In addition, by combining it with an emotion engine that recognizes the user's emotions and dynamically changes the content and difficulty of the quiz based on those emotions, a more advanced user experience is realized. A specific implementation method is described below.

[1587] 1. Obtaining product information

[1588] The server retrieves detailed information about the product being bought and sold from a database, including the product name, features, specifications, instructions for use, key benefits, etc. The server executes SQL queries to retrieve the required information from the database and loads it into memory.

[1589] 2. Quiz Generation

[1590] The server uses a generative AI model to generate multiple quiz questions based on the acquired product information. For example, a prompt such as "What are the features of this smartphone?" is input into the generative AI model, which then generates options such as "A. 5G compatible," "B. 4K camera," "C. Waterproof," and "D. All." A common open-source natural language processing (NLP) model can be used as the generative AI model.

[1591] 3. Formatting the quiz

[1592] The server formats the generated quiz questions into a format suitable for presentation to the user. The formatted quiz questions are converted into a data structure such as JSON and saved in the file system.

[1593] 4. Emotional Recognition

[1594] The device inputs the user's facial expressions and tone of voice into the emotion engine via sensors such as a camera and microphone. This allows the user's emotional state to be recognized. Emotional states are classified as joy, anger, sadness, surprise, etc. The emotion engine uses image recognition and voice analysis technology.

[1595] 5. Emotional Data Analysis

[1596] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quizzes based on the user's emotional state. For example, if the user is feeling anxious, the server will set the next quiz to an easier one.

[1597] 6. View the quiz

[1598] The device displays the quiz questions sent from the server to the user. The display format can be a form on a web browser or an application screen. Based on the JSON format data received from the server, the device generates HTML and CSS to display the quiz.

[1599] 7. Obtaining User Answers

[1600] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. Specifically, the user selects option D (all). The user's input is acquired by the terminal as form data.

[1601] 8. Submitting User Answers

[1602] The terminal sends the answer selected or entered by the user to the server, along with the user ID and question ID. The data is sent using a secure protocol.

[1603] 9. Verifying the Answer

[1604] The server checks the received user's answer against the list of correct answers to determine whether the answer is correct. If so, the server proceeds to the next processing step.

[1605] 10. Generate an authentication token

[1606] If the user answers all the quiz questions correctly, the server generates an authentication token to proceed with the purchase. This authentication token is a unique identification code stored in a secure data store.

[1607] 11. Sending Authentication Tokens

[1608] The server sends the generated authentication token to the user's device using a secure communication protocol.

[1609] Specific examples

[1610] For example, consider the implementation of this system in the sale of a new smartphone. First, the server retrieves information about the features and advantages of the new smartphone (for example, 5G compatibility or high-resolution camera) from a database. Using this information, a generative AI model is used to generate a quiz question such as, "What are the features of this smartphone?", and provides the following options: "A. 5G compatibility," "B. 4K camera," "C. Waterproof," or "D. All of these."

[1611] The quiz questions are displayed to the user on the device, and the user selects option D (all answers). The device sends the answer to the server, which verifies the answer and confirms that it is correct. If the answer is correct, the server generates and sends an authentication token, and the user can then proceed with the official purchase process via the device.

[1612] An example of a prompt is:

[1613] "Generate a quiz about selling a new smartphone. Create multiple-choice questions that include the product's features and benefits, and use a corresponding emotion recognition system to dynamically adjust the quiz based on the user's emotions. Specific examples of prompts might include, 'What are the features of this smartphone?' and 'What is the balance between style and performance?'"

[1614] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1615] Step 1:

[1616] The server retrieves detailed information about the product being sold from a database, using search criteria such as the product ID as input. The output is detailed product information such as the product name, features, specifications, instructions for use, and key benefits.

[1617] Specific operation: The server executes an SQL query such as "SELECT FROM product_info WHERE product_id = '12345'" and reads the retrieved data into memory.

[1618] Step 2:

[1619] The server generates quiz questions using a generative AI model based on the acquired product information. The acquired product information is used as input, and the generated quiz questions are obtained as output.

[1620] Specific operation: The server sends a prompt to the generation AI model saying, "Please generate quiz questions about the features of the new smartphone," and the AI ​​model returns the quiz questions.

[1621] Step 3:

[1622] The server formats the generated quiz questions into a format for presentation to the user. The generated quiz questions are used as input. As output, the formatted quiz questions are converted into a data structure such as JSON format.

[1623] Specific operation: The server converts the generated quiz questions into the "quiz_questions.json" format and saves the formatted data in the file system.

[1624] Step 4:

[1625] The device inputs the user's facial expressions and tone of voice to the emotion engine through sensors such as a camera and microphone. The input uses data on the user's facial expressions and voice. The output is a recognized emotional state.

[1626] Specific operation: The device captures the user's facial expression with a camera and sends the image data to the emotion engine, which analyzes the image data and determines the user's emotional state.

[1627] Step 5:

[1628] The server analyzes the recognized emotion data and dynamically adjusts the content, difficulty, and presentation order of the quiz based on the user's emotional state. The recognized emotion data is used as input, and the adjusted quiz questions are obtained as output.

[1629] Specific operation: The server receives the emotion data of "anxiety" and reconfigures the list of quiz questions to prioritize displaying easy questions.

[1630] Step 6:

[1631] The terminal displays the quiz questions sent from the server to the user. The input is the quiz question data received from the server. The output is the quiz displayed on the screen.

[1632] Specific operation: The device downloads "quiz_questions.json" from the server and generates HTML and CSS to display the quiz questions on the UI.

[1633] Step 7:

[1634] The user checks the quiz questions displayed on the terminal and selects or inputs an answer. The input is the user's answer. The output is the selected or input answer.

[1635] Specific behavior: The user clicks or enters options using the mouse or keyboard, and the input data is captured as a form.

[1636] Step 8:

[1637] The terminal transmits the answer selected or input by the user to the server. The input includes the user's answer data. The output is the transmitted answer data.

[1638] Specific operation: The device generates "user_answer.json" and posts the user's selected answer to the server.

[1639] Step 9:

[1640] The server compares the received user's answer with the correct answer list and determines whether the answer is correct. The input is the user's answer data and the correct answer list. The output is the verification result.

[1641] Specific operation: The server receives "user_answer.json" and checks the answer against the correct answer list.

[1642] Step 10:

[1643] The server generates an authentication token to allow the user to proceed with the purchase process if the user answers all the quiz questions correctly. The input is the verification results of all the quiz questions. The output is the generated authentication token.

[1644] Specific operation: If the server determines that all questions are answered correctly, it generates an "auth_token" and stores it in a secure data store.

[1645] Step 11:

[1646] The server sends the generated authentication token to the user's device. The input is the generated authentication token. The output is the authentication token sent to the user's device.

[1647] Specific operation: The server generates "auth_token.json" and sends it to the user's device via a secure protocol.

[1648] (Application example 2)

[1649] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1650] Today, there is a demand for systems to improve the customer experience in brick-and-mortar stores. However, there is a lack of ways for customers to deepen their knowledge about products while increasing their purchasing motivation. Furthermore, because content cannot be provided that takes into account customer emotions, customers may feel anxious or stressed, and the purchasing process may not proceed smoothly. Therefore, the challenge is to develop a system that provides an optimal purchasing experience based on the customer's emotional state by using a dynamic quiz adjustment function that includes emotion recognition.

[1651] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring information about products, means for generating a quiz based on the acquired product information, means for presenting the generated quiz to the user, means for acquiring emotional data using sensors such as a camera and a microphone to recognize the user's emotional state, and means for dynamically adjusting the difficulty and content of the quiz based on the emotional data. This enables customers to deepen their knowledge about products in a physical store while taking on quizzes that correspond to their emotional state, thereby reducing customer stress and anxiety and allowing the purchasing process to proceed smoothly.

[1652] "Means for obtaining information about products" refers to a function for obtaining detailed information such as product features, specifications, and advantages from a database or external information source.

[1653] "Means for generating quizzes based on acquired product information" refers to a function that automatically creates quiz questions using a generative AI model based on acquired product information.

[1654] The "means for presenting the generated quiz to the user" is a function that provides an interface for displaying the generated quiz questions to the user.

[1655] The "means for accepting and verifying the user's quiz answers" is a function for receiving the quiz answers entered by the user and determining whether they are correct or incorrect.

[1656] The "means for generating an authentication token to proceed with the product purchase process when the user answers the quiz correctly" is a function that generates a unique authentication code to prove the user's authority to purchase a product when the user answers all the quizzes correctly.

[1657] The "means for transmitting an authentication token to a user" is a function for transmitting a generated authentication token to a user using a secure communication protocol.

[1658] "Means for acquiring emotional data using sensors such as a camera or microphone in order to recognize the user's emotional state" refers to a function that uses a camera or microphone to analyze the user's facial expressions and tone of voice and recognize the user's emotional state.

[1659] The "means for dynamically adjusting the difficulty and content of the quiz based on emotion data" is a function for changing the difficulty and content of the quiz in real time according to the recognized emotion of the user.

[1660] The system of this invention allows customers in physical stores to deepen their product knowledge while smoothly progressing through the purchasing process. The system mainly consists of the following components: a server, a terminal, and sensors such as a camera and a microphone.

[1661] Server Roles

[1662] The server retrieves product information from the database and generates a quiz based on that information. A generative AI model is used in this quiz generation process. The generated quiz is then formatted appropriately to be presented to the user. The server also has the function of accepting and verifying the user's quiz answers and generating authentication tokens. Furthermore, the server analyzes the user's emotional state data and dynamically adjusts the content and difficulty of the quiz.

[1663] Device Role

[1664] The terminal displays product information and quizzes sent from the server to the user. Devices such as smartphones and smart glasses are used. The terminal is equipped with a camera and microphone, and these sensors are used to recognize the user's emotional state in real time. The user's emotional data is sent to the server, which then adjusts the content and difficulty of the quiz.

[1665] User Experience

[1666] Users answer quizzes through their device, and if they answer all of them correctly, they receive an authentication token. This token is used to proceed with the product purchase process. While taking the quiz, the user's emotions are sensed via a camera and microphone. For example, if the user is feeling anxious or stressed, the server will adjust the next quiz to be easier.

[1667] Software and hardware used

[1668] The server requires a database management system (DBMS) and the computing resources to run the generative AI model, specifically, to analyze emotion data using OpenCV and the EmotionRecognition library.

[1669] The devices used are smartphones or smart glasses equipped with cameras and microphones, and the user interface is a web browser or dedicated application.

[1670] Specific examples

[1671] For example, let's say this system is used in a physical store selling new smartphones. The server retrieves information about the smartphone's features and advantages from a database (e.g., 5G compatibility, high-resolution camera, large-capacity battery). Based on this information, the generative AI model generates a quiz and sends it to the device. If the device is a smartphone, the user answers the quiz through the camera, and their facial expressions are analyzed during the process. If the user feels unsure, the server can easily adjust the next quiz to be presented. Furthermore, if the user answers all the quizzes correctly, the server issues an authentication token and sends it to the device. Using this token, the user can smoothly proceed through the purchase process.

[1672] Prompt Sentence Examples

[1673] Product information: {"Product name": "New smartphone", "Features": "5G compatible, high-resolution camera, large-capacity battery, OLED display"}.

[1674] Generate a quiz about this product.

[1675] This system configuration enriches the customer experience in physical stores, allowing customers to make purchases in a relaxed manner.

[1676] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1677] Step 1: Get product information

[1678] The server retrieves product information from the database, including product name, features, specifications, key benefits, etc. For example, it retrieves the features and benefits of a new smartphone (5G compatibility, high-resolution camera, large battery, etc.).

[1679] Input: Product ID

[1680] Output: Product data (product name, features, specifications, benefits)

[1681] Step 2: Generate the quiz

[1682] The server creates a prompt based on the acquired product information and sends it to the generative AI model, which then generates multiple quiz questions based on this prompt.

[1683] Input: Product data

[1684] Output: Quiz question set

[1685] Step 3: Formatting Quiz Questions

[1686] The server formats the generated quiz questions in an appropriate format (e.g., JSON) for presentation to the user, which is then sent to the user interface.

[1687] Input: Quiz question set

[1688] Output: Formatted quiz data

[1689] Step 4: Present the quiz

[1690] The terminal receives the formatted quiz data sent from the server and displays it to the user. The user interface uses the application screen of a smartphone or smart glasses.

[1691] Input: Formatted quiz data

[1692] Output: Quiz questions displayed

[1693] Step 5: Obtaining emotion data

[1694] The device captures the user's facial expressions and tone of voice through a camera and microphone, and sends the emotion data to the emotion engine, which then analyzes the user's emotional state.

[1695] Input: User facial expression images, voice data

[1696] Output: Emotional state data (happiness, anxiety, stress, etc.)

[1697] Step 6: Dynamically adjust the quiz

[1698] The server dynamically adjusts the difficulty and content of the quiz based on the emotional state data, for example, lowering the difficulty of the quiz if the user is in an anxious state.

[1699] Input: Emotional state data, formatted quiz data

[1700] Output: Reconciled quiz data

[1701] Step 7: Accept quiz responses

[1702] The user answers the quiz questions displayed on the terminal, and the terminal accepts the answers and transmits them to the server.

[1703] Input: User's answer

[1704] Output: Accepted response data

[1705] Step 8: Verify your answers

[1706] The server checks the user's answer against a list of correct answers to determine whether the answer is correct.

[1707] Input: User response data, correct answer list

[1708] Output: Correctness of answer

[1709] Step 9: Generate an Auth Token

[1710] If the user answers all the quiz questions correctly, the server generates an authentication token, which is a unique identification code, that allows the user to proceed with the purchase process.

[1711] Input: Correct answer result

[1712] Output: Authentication token

[1713] Step 10: Sending an authentication token

[1714] The server sends the generated authentication token to the terminal, which displays it to the user, allowing the user to proceed with the purchase.

[1715] Input: Authentication Token

[1716] Output: Displayed authentication token

[1717] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1718] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1719] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1720] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1721] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1722] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1723] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1724] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1725] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1726] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1727] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1728] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1729] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1730] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1731] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1732] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1733] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1734] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1735] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1736] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1737] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1738] The following is further disclosed regarding the above embodiment.

[1739] (Claim 1)

[1740] [Means for obtaining information about the product;

[1741] [Means for generating quizzes based on acquired product information;

[1742] [Means for presenting the generated quiz to a user;

[1743] [means for accepting and validating user quiz responses;

[1744] [Means for generating an authentication token to proceed with the purchase of the product if the user answers the quiz correctly;

[1745] [Method for sending authentication token to user

[1746] A system including:

[1747] (Claim 2)

[1748] The system of claim 1, further comprising means for dynamically adjusting the content and difficulty of the quiz.

[1749] (Claim 3)

[1750] The system of claim 1, further comprising means for individually customizing quiz questions for a particular user.

[1751] "Example 1"

[1752] (Claim 1)

[1753] [Means of retrieving detailed product information from a database;

[1754] [Means for generating quizzes based on acquired product information using a generative AI model;

[1755] [Means to format the generated quiz in JSON format and present it to the user through a user interface,

[1756] [means for accepting user quiz responses and validating the responses against a list of correct answers;

[1757] [Means for generating a unique authentication token if the user answers all questions correctly on the quiz;

[1758] [Means of sending authentication tokens to users using secure communication protocols

[1759] A system including:

[1760] (Claim 2)

[1761] [The system of claim 1, which dynamically adjusts the content and difficulty of the quiz.

[1762] (Claim 3)

[1763] [The system of claim 1, wherein quiz questions are individually customized for a particular user.

[1764] "Application Example 1"

[1765] (Claim 1)

[1766] [Means for obtaining information about the product;

[1767] [Means for generating quizzes based on acquired product information;

[1768] [Means for presenting the generated quiz to a user;

[1769] [means for accepting and validating user quiz responses;

[1770] [Means for generating an authentication token to proceed with the purchase of the product if the user answers the quiz correctly;

[1771] [Means for sending an authentication token to a user;

[1772] [A system that includes a means to verify the authentication token at a dedicated terminal in a physical store and complete the purchase process.

[1773] (Claim 2)

[1774] The system of claim 1, further comprising means for dynamically adjusting the content and difficulty of the quiz.

[1775] (Claim 3)

[1776] The system of claim 1, further comprising means for individually customizing quiz questions for a particular user.

[1777] "Example 2: Combining Emotion Engines"

[1778] (Claim 1)

[1779] [Means for obtaining information about the product;

[1780] [Means for generating quizzes using a generative AI model based on acquired product information;

[1781] [Means for formatting the generated quiz into a format for presentation to a user;

[1782] [means for recognizing the emotional state of a user;

[1783] [Means for dynamically adjusting the content and difficulty of the quiz based on the perceived emotional state; and

[1784] [Means for displaying the quiz to the user;

[1785] [means for accepting and validating user quiz responses;

[1786] [Means for generating an authentication token to proceed with the purchase of the product if the user answers the quiz correctly;

[1787] [Method for sending authentication token to user

[1788] A system including:

[1789] (Claim 2)

[1790] [The system of claim 1, wherein the content and order of the quizzes are dynamically adjusted according to the user's emotional state.

[1791] (Claim 3)

[1792] [The system according to claim 1, wherein the acquired user emotion data is analyzed to customize the quiz.

[1793] "Application example 2 when combining emotion engines"

[1794] (Claim 1)

[1795] [Means for obtaining information about the product;

[1796] [Means for generating quizzes based on acquired product information;

[1797] [Means for presenting the generated quiz to a user;

[1798] [means for accepting and validating user quiz responses;

[1799] [Means for generating an authentication token to proceed with the purchase of the product if the user answers the quiz correctly;

[1800] [Means for sending an authentication token to a user;

[1801] [Means for acquiring emotional data using sensors such as a camera and a microphone in order to recognize the emotional state of a user;

[1802] [Means to dynamically adjust the difficulty and content of quizzes based on emotional data]

[1803] A system including:

[1804] (Claim 2)

[1805] [The system of claim 1, which dynamically adjusts the content and difficulty of the quiz.

[1806] (Claim 3)

[1807] [The system of claim 1, wherein quiz questions are individually customized for a particular user. [Explanation of symbols]

[1808] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for obtaining information about the product; A means for generating a quiz based on the acquired product information; means for presenting the generated quiz to a user; means for accepting and validating user quiz answers; means for generating an authentication token for proceeding with a purchase of a product if the user answers the quiz correctly; A means of sending authentication tokens to users A system including:

2. The system of claim 1 , further comprising means for dynamically adjusting the content and difficulty of the quiz.

3. The system of claim 1 further comprising means for individually customizing quiz questions for a particular user.

Images