system

Abstract

Provide a system. [Solution] A means for a user to input product information; A means for storing the product information received by the server in a database; means for analyzing the transaction information so that the server can match the transaction information based on specific criteria; means for notifying the user of the matching results generated by the server; a means by which the server records the history of transactions and stores them for future reference; A system including:

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] The used car market faces the challenge of difficult information transfer and matching between sellers and buyers. Transactions do not proceed smoothly, particularly when the information provided by the seller is inaccurate or when a vehicle matching the buyer's desired conditions cannot be found. Furthermore, due to insufficient management of transaction history, it is difficult to refer to past transaction data. These issues reduce the efficiency of transactions in the used car market, and the inability to achieve optimal matching is an issue. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means: A system including a means for a user to input product information is provided. In this system, a server includes a means for storing the received product information in a database. The server further includes a means for analyzing the transaction information to perform matching based on specific criteria. The system also provides a means for notifying the user of the matching results generated by the server, and includes a means for recording and saving the transaction history for future reference. This enables effective information sharing between sellers and buyers and optimal transactions.

[0006] "User" means an individual or corporation that uses the system.

[0007] "Product information" refers to detailed information about items that sellers sell on the Internet.

[0008] A "server" is a computing device that receives, processes, stores, and transmits data.

[0009] A "database" is a system for storing and managing data according to specific rules.

[0010] The "specific criteria" are the conditions and evaluation criteria used when performing matching.

[0011] "Matching" is the process of finding the optimal combination by comparing the product information provided by the seller with the buyer's desired conditions.

[0012] "Deal Desired Information" is detailed condition information provided by a user when he / she wishes to make a transaction.

[0013] "Analysis" is the act of examining data or information in detail to clarify its meaning and significance.

[0014] "Notification" is the act of the server informing the user of information or results.

[0015] A "transaction history" is a detailed record of past transactions.

[0016] "Recording" is the act of accurately recording and preserving facts and events.

[0017] "Preservation" is the act of storing data or information so that it can be reused at a later date.

[0018] A "system" is a collection of multiple elements that work together. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] This invention is a system that streamlines the transmission of information and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history, thereby realizing smooth transactions.

[0041] User Registration

[0042] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[0043] Vehicle information registration

[0044] Next, we will explain the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user that the registration was successful.

[0045] Vehicle information search

[0046] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[0047] Trade Matching

[0048] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. This matching result is generated by the server and notified to the buyer and seller's devices. Both parties can then proceed to the actual transaction.

[0049] Managing transaction history

[0050] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. This allows the user to refer to past transactions and use them as reference for future transactions.

[0051] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches it and notifies both parties. In this way, User A and User B communicate with each other and the transaction is completed. All data during this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[0052] Through these procedures, the present invention realizes improved efficiency and reliability of transactions in the used car market.

[0053] The processing flow will be explained below.

[0054] User Registration

[0055] Step 1:

[0056] The user enters their name, email address, and password in the registration form and clicks the registration button.

[0057] Step 2:

[0058] The terminal transmits the input user information to the server.

[0059] Step 3:

[0060] The server receives the user information sent from the terminal.

[0061] Step 4:

[0062] The server searches its database to see if the entered email address already exists.

[0063] Step 5:

[0064] If the server finds no duplicate email addresses, it saves the new user information in the database.

[0065] Step 6:

[0066] The server generates an authentication token for the newly registered user.

[0067] Step 7:

[0068] The server returns the generated authentication token to the user's device.

[0069] Vehicle information registration

[0070] Step 1:

[0071] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[0072] Step 2:

[0073] The terminal transmits the entered vehicle information and authentication token to the server.

[0074] Step 3:

[0075] The server receives the vehicle information and the authentication token sent from the terminal.

[0076] Step 4:

[0077] The server validates the authentication token and verifies that the user is valid.

[0078] Step 5:

[0079] The server stores the vehicle information in a database.

[0080] Step 6:

[0081] The server notifies the user's terminal of successful registration.

[0082] Vehicle information search

[0083] Step 1:

[0084] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[0085] Step 2:

[0086] The terminal transmits the entered search conditions to the server.

[0087] Step 3:

[0088] The server receives the search conditions sent from the terminal.

[0089] Step 4:

[0090] The server searches the database and retrieves vehicle information that matches the criteria.

[0091] Step 5:

[0092] The server returns the search results to the user's terminal.

[0093] Trade Matching

[0094] Step 1:

[0095] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[0096] Step 2:

[0097] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[0098] Step 3:

[0099] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[0100] Step 4:

[0101] The server notifies the generated matching results to the terminals of the seller and the buyer.

[0102] Managing transaction history

[0103] Step 1:

[0104] A user issues a request to check their transaction history.

[0105] Step 2:

[0106] The terminal sends a request for transaction history to the server.

[0107] Step 3:

[0108] The server receives the request sent from the terminal.

[0109] Step 4:

[0110] The server validates the authentication token and verifies that the user is valid.

[0111] Step 5:

[0112] The server retrieves the user's transaction history from the database.

[0113] Step 6:

[0114] The server returns the acquired transaction history to the user's terminal.

[0115] Example 1

[0116] 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."

[0117] To ensure efficient and reliable transactions between sellers and buyers in the used car market, many processes are involved, including product information registration, search, matching, and transaction history management. Performing these processes manually is extremely time-consuming and prone to errors, so there is a need for a system that automates the transmission of information and optimal transaction matching in the used car market. Additionally, there are problems with duplicate registered information and delayed transaction status updates, which need to be resolved.

[0118] 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.

[0119] In this invention, the server includes means for a user to input product information, means for the server to store the received product information in a database, means for the server to check for the existence of duplicate accounts, means for the server to generate a unique identification code for each new account, means for a seller to input vehicle information and for the server to check the relevance of the data, means for the server to analyze the trade request information based on specific criteria, means for the server to perform matching using a generated AI model, means for the server to notify the user of the matching results generated by the server, and means for the server to record the transaction history and store it for future reference, thereby realizing efficient and reliable transactions in the used car market and enabling the checking of duplicate product information and real-time updates of transaction status.

[0120] "User" refers to an individual or corporation that uses the system to input product information and conduct sales.

[0121] "Product information" refers to detailed data entered by the user regarding the used car to be sold or bought.

[0122] "Server" refers to a computer system that processes, stores, and analyzes information received from users and sends necessary notifications.

[0123] "Database" means a collection of information managed by a server that stores product information, transaction history, etc.

[0124] "Identification Code" means a unique token or ID generated by the server when registering a new account.

[0125] "AI Model" means the artificial intelligence algorithm and its implementation used by the Server for transaction matching and data analysis.

[0126] "Token" refers to a unique identification code generated for authentication and security purposes.

[0127] A "seller" refers to a user who wishes to sell a used car and registers vehicle information in the system.

[0128] "Buyer" refers to a user who wishes to purchase a used car and searches for vehicle information in the system.

[0129] "Matching" refers to the process in which the server uses an AI model to analyze the seller's vehicle information and the buyer's desired conditions and propose the optimal deal.

[0130] "Transaction History" means a detailed record of completed transactions for future reference and analysis.

[0131] "Real-time updates" refers to a process in which the status of a transaction is reflected immediately and users are notified immediately.

[0132] This invention is a system for improving the efficiency and reliability of transactions in the used car market. This system allows users to input product information, and the server stores, analyzes, and matches the received information, notifies the results, and manages transaction history to ensure smooth transactions.

[0133] Configuration requirements

[0134] Hardware and Software

[0135] Server: The main computer system that processes, stores, and analyzes information.

[0136] Usage example: Server OS (Linux (registered trademark)), Web server (Apache (registered trademark))

[0137] Terminal: Device operated by the user (PC, smartphone, etc.)

[0138] Example of use: Web browser (Chrome, Firefox)

[0139] Database: Where information is stored

[0140] Usage example: MySQL(registered trademark)

[0141] AI model: Artificial intelligence model used for information analysis and matching

[0142] Usage examples: TENSORFLOW (registered trademark), Scikit-learn

[0143] Main processing flow

[0144] User Registration

[0145] overview

[0146] The user completes the registration process by entering their name, email address, and password and pressing the register button. The server receives this information and stores it in a database. It also checks for duplicate accounts and generates a unique identification code (token) for new accounts. This token is used for future user authentication.

[0147] Specific examples

[0148] The user enters the following information:

[0149] Name: Yamada Taro

[0150] Email address: taro@example.com

[0151] Password: password123

[0152] When the user presses the register button, the device sends this information to the server. The server receives the data and executes an "INSERT" query in the database to store the information. It then checks for duplicate accounts using an SQL query. A unique token is generated using a UUID library and sent back to the user.

[0153] Example prompt sentence:

[0154] What happens when a user enters their name, email address, and password and clicks the register button?

[0155] Vehicle information registration

[0156] overview

[0157] The seller enters the information of the vehicle they are selling (make, model, year, price, mileage, etc.) and presses the register button. The server receives this information, verifies the token, and saves it in the database. Once saved, the user is notified that registration was successful.

[0158] Specific examples

[0159] The seller enters the following vehicle information:

[0160] Manufacturer: Toyota

[0161] Model: Corolla

[0162] Year: 2015

[0163] Price: 1.5 million yen

[0164] Mileage: 50,000 km

[0165] When the user presses the registration button, the device sends this information and the token to the server. The server receives the data and verifies the token. It then executes an "INSERT" query in the database to save the data. After saving is complete, the server sends a notification to the user that registration is complete.

[0166] Example prompt sentence:

[0167] When a seller registers their vehicle information, how does the server process it?

[0168] Vehicle information search

[0169] overview

[0170] A buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives the request and searches the database for vehicle information that matches the conditions. The results are then sent back to the buyer's terminal.

[0171] Specific examples

[0172] Buyer enters the following search criteria:

[0173] Manufacturer: Toyota

[0174] Model: Corolla

[0175] Price: Under 2 million yen

[0176] Year: 2010 onwards

[0177] When a buyer presses the search button, the terminal sends the search criteria to the server. The server receives the search criteria and executes a "SELECT" query on the database. The results are returned to the terminal in JSON format, and the buyer can check the results on the terminal.

[0178] Example prompt sentence:

[0179] When a buyer searches for a desired vehicle, how does the system handle it?

[0180] Trade Matching

[0181] overview

[0182] The server uses AI to analyze the vehicle information registered by the seller and the buyer's desired conditions to perform optimal matching, and the generated matching results are sent to the buyer and seller's devices.

[0183] Specific examples

[0184] The server uses the AI ​​model to analyze:

[0185] Seller's vehicle information: Toyota Corolla 2015 model, 1.5 million yen, 50,000 km

[0186] Buyer's desired conditions: Toyota Corolla, under 2 million yen, 2010 or later

[0187] The AI ​​model calculates the optimal matching score, the server notifies the buyer and seller of the results, and the buyer and seller can proceed with the transaction.

[0188] Example prompt sentence:

[0189] What is the procedure for AI-based trade matching?

[0190] Managing transaction history

[0191] overview

[0192] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can send a request to check the transaction history, and the server retrieves the relevant transaction history from the database and sends it back to the terminal.

[0193] Specific examples

[0194] A transaction is completed and the server records the transaction details as follows:

[0195] Seller: User A

[0196] Buyer: User B

[0197] Vehicle traded: Toyota Corolla

[0198] Transaction amount: 1.5 million yen

[0199] Transaction Date: October 1, 2023

[0200] When a user sends a request to check their transaction history, the server retrieves the relevant transaction history from the database and returns it to the terminal.

[0201] Example prompt sentence:

[0202] How does the system work when it comes to managing transaction history?

[0203] Through these specific procedures and techniques, the present invention provides a system that improves the efficiency and reliability of transactions in the used car market.

[0204] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0205] Step 1: User Registration

[0206] 1.1 The user enters their name, email address, and password and presses the registration button.

[0207] Input: Name, Email Address, Password

[0208] Output: Sending input data

[0209] What happens: The device correctly formats the input data and sends it to the server.

[0210] 1.2 The server receives the data and checks the database for duplicate accounts.

[0211] Input: Received data (name, email address, password)

[0212] Output: Results of duplicate check

[0213] What happens: The server runs a "SELECT" query against the database to check for duplicate information.

[0214] 1.3 The server stores the new account in its database and generates a unique identification code.

[0215] Enter your new account information

[0216] Output: A unique identifier (token)

[0217] What happens: The server uses a UUID library to generate a unique token and executes an "INSERT" query against the database.

[0218] 1.4 The server generates a token and sends a notification back to the user.

[0219] Input: Token

[0220] Output: Token sent notification

[0221] Specific operation: The server sends a notification message containing the generated token to the device.

[0222] Step 2: Register your vehicle information

[0223] 2.1 The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and presses the registration button.

[0224] Input: Make, Model, Year, Price, Mileage

[0225] Output: Sending input data

[0226] What happens: The device correctly formats the input data, adds a token, and sends it to the server.

[0227] 2.2 The server checks the token in the received data.

[0228] Input: Vehicle information with token

[0229] Output: Token verification result

[0230] What happens: The server runs a "SELECT" query to check the validity of the token against the database.

[0231] 2.3 The server stores the vehicle information in a database.

[0232] Input: Vehicle information (make, model, year, price, mileage)

[0233] Output: Vehicle information saved

[0234] Specific behavior: The server executes an "INSERT" query on the database and saves the data.

[0235] 2.4 The server notifies the user of successful registration.

[0236] Input: Registration success status

[0237] Output: Registration successful notification

[0238] Specific operation: The server sends a registration completion status to the device.

[0239] Step 3: Find vehicle information

[0240] 3.1 The buyer enters the desired vehicle conditions into the terminal and presses the search button.

[0241] Input: Search criteria (make, model, price, year, etc.)

[0242] Output: Sending input data

[0243] What happens: The device correctly formats the search criteria and sends them to the server.

[0244] 3.2 The server receives the request and searches the database for vehicle information that matches the relevant criteria.

[0245] Input: Search criteria

[0246] Output: Search results

[0247] Specific operation: The server executes a "SELECT" query against the database to retrieve vehicle information that matches the search criteria.

[0248] 3.3 The server returns the search results to the device.

[0249] Input: Search results

[0250] Output: Send search results

[0251] Specific operation: The server generates search results in JSON format and sends them to the device.

[0252] 3.4 The buyer checks the vehicle list displayed as a result and presses the Show Details button.

[0253] Input: Search results

[0254] Output: Verbose

[0255] Specific behavior: The device displays the search results it receives and waits for the user's action.

[0256] Step 4: Deal Matching

[0257] 4.1 The server analyzes the seller's vehicle information and the buyer's desired conditions based on AI.

[0258] Input: Seller's vehicle information, Buyer's desired conditions

[0259] Output: Analysis results

[0260] How it works: The server analyzes this information using a generative AI model and generates a matching score.

[0261] 4.2 The server uses AI to find the best match.

[0262] Input: Parsed data

[0263] Output: Matching results

[0264] Specific behavior: The server determines the best matching pair based on the matching score.

[0265] 4.3 The server notifies the buyer and seller of the matching results.

[0266] Input: Matching results

[0267] Output: Matching notification

[0268] Specific operation: The server sends a notification message containing the matching result to the device.

[0269] 4.4 The buyer and seller will contact each other to proceed with the specific transaction.

[0270] Input: Matching results

[0271] Output: Transaction contact

[0272] Specific operation: The terminal provides the means of communication and the user proceeds with the transaction.

[0273] Step 5: Manage your transaction history

[0274] 5.1 Once the transaction is complete, the terminal notifies the server that the transaction is complete.

[0275] Input: Transaction Completion Status

[0276] Output: Notification of transaction completion

[0277] Specific operation: The terminal sends the transaction completion status to the server.

[0278] 5.2 The server records the transaction details and stores them in a database.

[0279] Enter: Transaction Details

[0280] Output: Saved results

[0281] What happens: The server executes an "INSERT" query against the database to store the transaction details.

[0282] 5.3 The user sends a request from the terminal to check past transaction history.

[0283] Input: User request

[0284] Output: Transaction history request

[0285] Specific operation: The terminal sends a request for transaction history to the server.

[0286] 5.4 The server retrieves the transaction history from the database and returns it to the terminal.

[0287] Input: User request

[0288] Output: Transaction history

[0289] Specific operation: The server executes a "SELECT" query on the database to retrieve the transaction history and send it to the terminal.

[0290] 5.5 The user checks the transaction history on the terminal.

[0291] Input: Transaction History

[0292] Output: History display

[0293] Specific operation: The terminal displays the received transaction history and the user confirms it.

[0294] (Application example 1)

[0295] 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."

[0296] In the used car trading market, achieving efficient and fast matching between sellers and buyers is a challenge. Conventional systems require complicated information input, search, and matching processes, resulting in a lack of reliability and efficiency in transactions. Furthermore, few systems allow users to check the transaction status in real time, making it difficult to keep track of the transaction progress in a timely manner.

[0297] 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.

[0298] In this invention, the server includes: a means for a user to input product information; a means for storing the received product information in a database; a means for the server to analyze transaction request information to perform matching based on specific criteria; a means for notifying the user of the matching results generated by the server; a means for the server to record transaction history and store it for future reference; a means for a user to input and confirm transaction information using a mobile device; a means for the server to analyze the information obtained from the mobile device and use a generative AI model to provide optimal matching; a means for updating the transaction status in real time based on transaction conditions and notifying the user; and a means for analyzing the requirements obtained from the user using prompt sentences and presenting optimal product information based on the analysis results, thereby enabling efficient and fast matching between sellers and buyers and improving the reliability and efficiency of transactions.

[0299] "User" refers to a general user of the system.

[0300] "Product Information" refers to detailed data relating to the products that are the subject of a transaction.

[0301] "Server" refers to the central processing unit that receives, stores, analyzes, and matches product information.

[0302] "Database" refers to a structured collection of information for storing data such as product information and transaction history.

[0303] "Matching" refers to the process of analyzing the conditions of the seller and buyer and optimally connecting the two.

[0304] "Desired transaction information" refers to the requests and conditions regarding the transaction entered by the user.

[0305] "Transaction history" refers to a detailed record of past transactions.

[0306] "Mobile terminal" refers to a portable information and communication device such as a smartphone or tablet.

[0307] A "generative AI model" refers to an artificial intelligence algorithm that generates optimal results based on large amounts of data.

[0308] A "prompt sentence" refers to an instruction sentence for accurately obtaining the user's requests or conditions.

[0309] This invention provides a system that aims to improve the efficiency and reliability of transactions in the used car market. A means is provided for users to input product information, and the server receives the information and stores it in a database. Specific embodiments of this system are described below.

[0310] First, a user accesses the system using a mobile device (e.g., smartphone, tablet). The user enters product information (manufacturer, model, year, price, mileage, etc.) and sends it to the system. This information is received by the server and stored in a database.

[0311] The server analyzes the information provided by each user and checks for duplicate product information, preventing the same product from being registered multiple times. The server also searches for information in its database based on the entered conditions and finds the best match based on the specified criteria.

[0312] In the matching process, the server uses a generative AI model that analyzes the user's desired transaction information to generate the optimal match. For example, if a user desires a "2015 Toyota Corolla," the server searches and analyzes the corresponding vehicle information to find the best match.

[0313] The generated matching results are notified to the user's mobile device. The user can then receive the notification and proceed with the transaction. Once the transaction is completed, the server records the transaction history in a database and saves it for future reference. Furthermore, the server updates the transaction status in real time based on the transaction conditions and notifies the user.

[0314] As a concrete example, suppose a user uses the system to search for "Toyota Corolla 2015 model." In this case, the server uses the generative AI model to analyze the user's prompt, "Toyota Corolla 2015 model," and searches for related information in the database. If a suitable vehicle is found, the server notifies the user of the matching results and allows the user to proceed with the specific transaction.

[0315] In this process, the server uses a Python-based back-end system and PostgreSQL or MongoDB as the database. The front-end is built using HTML, CSS, and JavaScript (registered trademark). This system configuration improves the efficiency and reliability of used car transactions.

[0316] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0317] Step 1:

[0318] The user enters product information.

[0319] Input: Vehicle information such as make, model, year, price, mileage, etc.

[0320] Specific operation: The user enters product information into the input form on the mobile device and presses the "Submit" button.

[0321] Output: The entered vehicle information is sent to the server.

[0322] Step 2:

[0323] The server stores the received product information in a database.

[0324] Input: Vehicle information sent by the user

[0325] What happens: The server receives the input information and saves it to the database. The Python code saves it to the database.

[0326] Output: Vehicle information stored in the database

[0327] Step 3:

[0328] The server checks for duplicate product information.

[0329] Input: Vehicle information stored in the database

[0330] What happens: The server compares the new data with existing data in the database to see if there are any duplicates.

[0331] Output: Whether there are any duplicates. If there are any duplicates, an error message is displayed to the user.

[0332] Step 4:

[0333] The user inputs desired transaction information.

[0334] Input: Desired vehicle conditions (make, model, year, price range, etc.)

[0335] Specific operation: The user inputs the desired vehicle conditions on the mobile terminal and presses the "Search" button.

[0336] Output: The entered transaction request information is sent to the server.

[0337] Step 5:

[0338] The server analyzes the desired transaction information and searches the database for matching vehicle information.

[0339] Input: Transaction request information sent by the user, vehicle information in the database

[0340] Specific operation: The server uses the generative AI model to analyze the input information and search the database for matching vehicle information. Data analysis is performed using the generative AI model.

[0341] Output: List of matching vehicle information

[0342] Step 6:

[0343] The server generates the matching results and notifies the user.

[0344] Input: List of matching vehicle information

[0345] Specific operation: The server compiles matching vehicle information as a matching result and notifies the user's mobile device.

[0346] Output: Matching results displayed on the user's mobile device

[0347] Step 7:

[0348] The user proceeds with the transaction and enters and confirms the required information.

[0349] Input: Vehicle information and additional information included in the matching results

[0350] Specific operations: A user uses a mobile device to enter and confirm transaction information.

[0351] Output: The progress of the transaction is sent to the server.

[0352] Step 8:

[0353] The server records the transaction history and stores it for future reference.

[0354] Input: Detailed information after transaction completion

[0355] What happens: The server receives the final transaction information and saves it to the database. This is done using Python code.

[0356] Output: Transaction history stored in a database

[0357] Step 9:

[0358] The server updates the transaction status in real time based on the transaction conditions and notifies the user.

[0359] Input: In-progress transaction status information

[0360] Specific operation: The server monitors the transaction status in real time and notifies the user according to changes in conditions and progress.

[0361] Output: Real-time transaction status displayed on the user's mobile device

[0362] Step 10:

[0363] The system analyzes the required specifications obtained from the user using prompt statements and presents optimal product information based on the analysis results.

[0364] Input: Prompt from the user

[0365] Specific operation: The server inputs the prompt sentence into the generative AI model, obtains the analysis results, and presents the most suitable product information to the user based on the analysis results.

[0366] Output: The best product information presented to the user

[0367] 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.

[0368] This invention improves the trading experience in the used car market by combining an emotion engine with a system that streamlines the transmission of information and transaction matching between sellers and buyers. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. It also includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[0369] User Registration

[0370] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[0371] Vehicle information registration

[0372] This section explains the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user's device that the registration was successful.

[0373] Vehicle information search

[0374] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[0375] Trade Matching

[0376] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. The matching results are generated by the server and notified to the buyer and seller's devices. Furthermore, an emotion engine analyzes the user's reactions and provides feedback based on emotional data, improving the quality of the transaction.

[0377] Emotion Engine Operation

[0378] The emotion engine analyzes the user's facial expressions, tone of voice, and text message content during input and operation to detect emotions in real time. For example, when a user is browsing vehicle information, the emotion engine detects interest and satisfaction from the user's facial expressions. This information is sent to the server and reflected in the matching results.

[0379] Managing transaction history

[0380] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. The emotion data obtained by the emotion engine is also stored as history and can be used as a reference for future transactions. This allows users to refer to past transactions and make better decisions for future transactions.

[0381] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches them and notifies both parties. At this time, the emotion engine analyzes User B's reaction and confirms that the match is satisfactory. In this way, User A and User B communicate and the transaction is completed. All data from this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[0382] Through these procedures, the present invention realizes efficient transactions, improved reliability, and an improved trading experience in the used car market.

[0383] The processing flow will be explained below.

[0384] User Registration

[0385] Step 1:

[0386] The user enters their name, email address, and password in the registration form and clicks the registration button.

[0387] Step 2:

[0388] The terminal transmits the input user information to the server.

[0389] Step 3:

[0390] The server receives the user information sent from the terminal.

[0391] Step 4:

[0392] The server searches its database to see if the entered email address already exists.

[0393] Step 5:

[0394] If the server finds no duplicate email addresses, it saves the new user information in the database.

[0395] Step 6:

[0396] The server generates an authentication token for the newly registered user.

[0397] Step 7:

[0398] The server returns the generated authentication token to the user's device.

[0399] Vehicle information registration

[0400] Step 1:

[0401] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[0402] Step 2:

[0403] The terminal transmits the entered vehicle information and authentication token to the server.

[0404] Step 3:

[0405] The server receives the vehicle information and the authentication token sent from the terminal.

[0406] Step 4:

[0407] The server validates the authentication token and verifies that the user is valid.

[0408] Step 5:

[0409] The server stores the vehicle information in a database.

[0410] Step 6:

[0411] The server notifies the user's terminal of successful registration.

[0412] Vehicle information search

[0413] Step 1:

[0414] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[0415] Step 2:

[0416] The terminal transmits the entered search conditions to the server.

[0417] Step 3:

[0418] The server receives the search conditions sent from the terminal.

[0419] Step 4:

[0420] The server searches the database and retrieves vehicle information that matches the criteria.

[0421] Step 5:

[0422] The server returns the search results to the user's terminal.

[0423] Trade Matching

[0424] Step 1:

[0425] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[0426] Step 2:

[0427] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[0428] Step 3:

[0429] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[0430] Step 4:

[0431] The server notifies the generated matching results to the terminals of the seller and the buyer.

[0432] Step 5:

[0433] The emotion engine analyzes the user's facial expressions, tone of voice, and text messages when performing operations or inputting text to detect the user's emotions.

[0434] Step 6:

[0435] The server receives the emotion data from the emotion engine and reflects it in the matching results.

[0436] Step 7:

[0437] The server notifies the seller and buyer terminals of the feedback based on the emotion.

[0438] Managing transaction history

[0439] Step 1:

[0440] A user issues a request to check their transaction history.

[0441] Step 2:

[0442] The terminal sends a request for transaction history to the server.

[0443] Step 3:

[0444] The server receives the request sent from the terminal.

[0445] Step 4:

[0446] The server validates the authentication token and verifies that the user is valid.

[0447] Step 5:

[0448] The server retrieves the user's transaction history from the database.

[0449] Step 6:

[0450] The server returns the acquired transaction history to the user's terminal.

[0451] Step 7:

[0452] Emotion data obtained by the emotion engine is also saved as history and used as a reference for future transactions.

[0453] As a result, the present invention improves the efficiency and reliability of transactions in the used car market, and improves the trading experience.

[0454] Example 2

[0455] 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."

[0456] In traditional used car markets, information matching between sellers and buyers is often inefficient, resulting in problems such as insufficient improvement of transaction reliability and user experience. Furthermore, the quality of transactions can decline because users' feelings are not taken into consideration during transactions. Furthermore, transaction history management is inadequate, limiting its use as reference information for future transactions.

[0457] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input product information, a means for the server to store the received product information in a database, a means for the server to analyze transaction request information to perform matching based on specific criteria, a means for the server to notify the user of the matching results generated by the server, a means for the server to detect the user's emotions and provide feedback to improve the quality of the transaction based on the detected emotions, and a means for the server to record the transaction history and store it for future reference. This enables more efficient transactions, improved reliability, and an improved trading experience.

[0458] "Product information" refers to specific information about the product being traded (e.g., vehicle manufacturer, model, year, price, mileage, etc.).

[0459] "Server" refers to a computer system that manages and processes data over a network and responds to user requests.

[0460] A "database" refers to an information system that enables efficient storage, retrieval, and updating of large amounts of data.

[0461] "Deal Desired Information" refers to the transaction conditions desired by the user (e.g., price range, product characteristics, etc.).

[0462] "Matching" refers to the process of analyzing information on sellers and buyers to find the optimal combination.

[0463] An "emotion engine" refers to a system that detects emotions by analyzing a user's facial expressions, voice, and text messages.

[0464] "Feedback" refers to information provided for improvement or adjustment based on a user's behavior and feelings.

[0465] "Transaction history" refers to detailed information about past transactions (e.g., transaction date and time, price, participant information, etc.).

[0466] "Token" refers to a unique identifier used for user authentication and data protection.

[0467] "Duplicate checking" refers to the process of checking whether newly entered information already exists by comparing it with existing data.

[0468] This invention improves the trading experience by combining an emotion engine with a system that streamlines information transmission and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. Furthermore, it includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[0469] Hardware and software used

[0470] The system is implemented using the following hardware and software:

[0471] Server: A high-performance server machine for processing and managing data.

[0472] Database: Use a relational database system such as MySQL or PostgreSQL.

[0473] Emotion Engine: An emotion analysis system using OpenCV and TensorFlow.

[0474] User Interface: Web application using HTML, CSS, and JavaScript.

[0475] Specific operation of the system

[0476] The system operates as follows:

[0477] 1. User Registration:

[0478] A user enters their name, email address, and password into a web form and clicks the Register button. The server receives this information and stores it in a MySQL database using an INSERT statement. The server checks for duplicate accounts and generates a unique token that is emailed back to the user.

[0479] 2. Product information registration:

[0480] The seller enters information such as the make, model, year, price, and mileage, and clicks the register button. The server receives this information, verifies the seller's token, and saves it in the MySQL database using an INSERT statement. Once saved, the server sends a registration success message to the user's device via an AJAX request.

[0481] 3. Product Information Search:

[0482] The buyer enters the desired vehicle conditions (e.g. price range, model year, mileage) and clicks the search button. The server receives the request and performs a SELECT statement from the MySQL database based on the conditions. The results are compiled in JSON format and displayed in the buyer's browser via an AJAX request.

[0483] 4. Trade Matching:

[0484] The server receives the seller's vehicle information and the buyer's conditions and analyzes them using a Python AI library (e.g., scikit-learn). It performs the best match and generates the results in JSON format. The server notifies the user of the results using AJAX. The emotion engine captures and analyzes the user's facial expressions and voice using the webcam and microphone, and the server receives the emotion data and provides feedback.

[0485] 5. Emotion Engine in Action:

[0486] When a user browses vehicle information, their facial expressions and voice are captured in real time via a webcam and microphone. The emotion engine analyzes the data using OpenCV and TensorFlow to detect their interests and satisfaction. The emotion data is sent to the server and reflected in the matching results.

[0487] 6. Transaction History Management:

[0488] When a transaction is completed, the server records the details of the transaction (e.g., seller / buyer information, transaction date and time, transaction price). The recorded information is saved in a MySQL database using an INSERT statement. When a user sends a request to check the history, the server retrieves the transaction history from the database using a SELECT statement and returns it to the user in JSON format. Emotion data generated by the emotion engine is also saved as history and used as reference information for the next transaction.

[0489] Specific examples

[0490] For example, consider the case where User A registers vehicle information in the system and User B performs a search based on that information. The vehicle information entered by User A is saved on the server, and User B enters search criteria and presses the search button. The server searches for vehicle information that matches the criteria, compiles the results, and displays them on the buyer's browser. The AI ​​generates the optimal matching results, and the emotion engine analyzes User B's reaction to determine his or her satisfaction level. Ultimately, User A and User B complete a transaction.

[0491] Prompt Sentence Examples

[0492] The following can be used as an example of an input prompt for a generative AI model:

[0493] "We are considering a system that efficiently matches information between sellers and buyers in the used car market. In particular, the system will have the function of optimally combining the seller's vehicle information with the buyer's desired conditions and providing feedback based on the user's emotional data. Please provide a detailed explanation in natural language of the specific hardware and software, processing details, and operation of the emotion engine."

[0494] This allows you to understand the specific operation of the entire system and the technical details associated with it.

[0495] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0496] Step 1:

[0497] A user fills in a web form with their name, email address, and password and clicks the Register button.

[0498] Input: The user enters their name, email address, and password.

[0499] Specific operation: The terminal sends input data to the server.

[0500] Output: The server receives the input data.

[0501] Step 2:

[0502] The server processes the received registration information and stores it in a database.

[0503] Input: The server receives the user's name, email address, and password.

[0504] Specific operation: The server saves this data in the MySQL database using an INSERT statement.

[0505] Output: User information is saved to a database and checked for duplicate accounts.

[0506] Step 3:

[0507] The server checks for unique email addresses and generates a token for new registrations.

[0508] Input: The server retrieves a list of registered email addresses.

[0509] What happens: The server runs a SELECT statement to check for duplicate email addresses. If there are no duplicates, it uses the UUID library to generate a new token.

[0510] Output: A unique token is generated and sent back to the user.

[0511] Step 4:

[0512] The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and clicks the registration button.

[0513] Input: The seller enters vehicle information (make, model, year, price, mileage).

[0514] Specific operation: The terminal sends input data to the server.

[0515] Output: The server receives the input data.

[0516] Step 5:

[0517] The server processes the received vehicle information and stores it in a database.

[0518] Input: The server receives the seller's vehicle information.

[0519] Specific operation: The server verifies the user token and then saves the vehicle information to the MySQL database using an INSERT statement.

[0520] Output: Vehicle information is saved in the database.

[0521] Step 6:

[0522] The server notifies the user's terminal of successful registration.

[0523] Input: The server determines that the vehicle information has been saved.

[0524] Specific operation: The server uses JavaScript to display a registration success message in the user's browser via an AJAX request.

[0525] Output: A notification of successful registration is displayed on the user's device.

[0526] Step 7:

[0527] The buyer enters the vehicle conditions they desire and clicks the search button.

[0528] Input: The buyer enters their desired conditions (price range, model year, mileage, etc.).

[0529] Specific operation: The terminal sends search criteria to the server.

[0530] Output: The server receives the search criteria.

[0531] Step 8:

[0532] The server searches the database for vehicle information based on the received search criteria.

[0533] Input: The server receives the purchase request terms.

[0534] Specific operation: The server executes the SELECT statement and retrieves vehicle information that matches the conditions from the database.

[0535] Output: A list of vehicles that match the criteria is generated.

[0536] Step 9:

[0537] The server returns the search results to the buyer's terminal for display.

[0538] Input: The server has a list of vehicles that match the criteria.

[0539] Specific operation: The server sends the search results in JSON format to the buyer's browser via an AJAX request.

[0540] Output: The vehicle list is displayed on the buyer's terminal.

[0541] Step 10:

[0542] The server analyzes the information of the seller and buyer and makes the best match.

[0543] Input: The server receives the seller's vehicle information and the buyer's desired conditions.

[0544] Specific operation: The server analyzes the information using a Python AI library (e.g., scikit-learn).

[0545] Output: The best matching result is generated.

[0546] Step 11:

[0547] The server notifies the seller and buyer of the matching results.

[0548] Input: The server has the generated matching results.

[0549] Specific operation: The server uses AJAX to send the matching results in JSON format to the user.

[0550] Output: The matching results are displayed on the user's device.

[0551] Step 12:

[0552] The emotion engine analyzes emotions from user input and operations and sends the data to the server.

[0553] Input: Capture real-time facial expressions and voice while the user is viewing vehicle information.

[0554] Specific operation: The emotion engine analyzes facial expression and voice data using OpenCV and TensorFlow.

[0555] Output: The analyzed emotion data is sent to the server.

[0556] Step 13:

[0557] The server analyzes the received emotion data and provides feedback.

[0558] Input: The server receives the user's emotion data.

[0559] Specific operation: The server analyzes the emotional data and reflects it in the matching results or provides it to the user as feedback.

[0560] Output: Feedback is displayed on the user's terminal, improving the quality of the transaction.

[0561] Step 14:

[0562] If the transaction is completed, the server records the transaction details and stores them in a database.

[0563] Input: The server receives the transaction completion information.

[0564] Specific operation: The server saves the transaction details (e.g., seller / buyer information, transaction date and time, transaction price) into the MySQL database using an INSERT statement.

[0565] Output: Transaction details stored in database.

[0566] Step 15:

[0567] The user sends a request to the server to check the transaction history.

[0568] Input: A user submits a request for transaction history.

[0569] Specific operation: The terminal sends a transaction history request to the server.

[0570] Output: The server receives the request.

[0571] Step 16:

[0572] The server retrieves the relevant transaction history from the database and returns it to the user's terminal.

[0573] Input: The server receives a transaction history request.

[0574] Specific operation: The server executes the SELECT statement and retrieves the relevant transaction history.

[0575] Output: The transaction history is sent to the user's device in JSON format.

[0576] Step 17:

[0577] Emotional data generated by the emotion engine is also stored in the transaction history and used as a reference for future transactions.

[0578] Input: The server has emotion data at the time of the transaction.

[0579] Specific operation: The emotion engine saves the emotion data collected during the transaction into the database using an INSERT statement.

[0580] Output: The sentiment data is included in the trading history and used as reference for the next trade.

[0581] (Application example 2)

[0582] 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."

[0583] The main functions of conventional trading systems in the used car market were matching sellers and buyers and managing transaction information, but there was no mechanism to improve the quality of transactions by taking user emotions and satisfaction into consideration.In addition, there was a lack of a way to improve the user experience through real-time emotional feedback during transactions, making improving user satisfaction a challenge.

[0584] The specification process by the specification 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 a means for a user to input product information, a means for the server to store the received product information in a database, a means for the server to analyze transaction request information to perform matching based on specific criteria, a means for the server to notify the user of the matching results generated by the server, a means for the server to record transaction history and store it for future reference, and a means for analyzing user emotions in real time and providing feedback to improve the quality of transactions. This enables more efficient transactions, improved user satisfaction, and an improved quality of the trading experience.

[0585] "Means for users to input product information" refers to an interface that allows users to input information about the products to be traded in text or other formats.

[0586] The term "means for storing the product information received by the server in a database" refers to a process and mechanism for the server to store the product-related data received from the user in a database.

[0587] "Means for the server to analyze transaction request information in order to perform matching based on specific criteria" refers to a mechanism in which the server analyzes the desired information of sellers and buyers based on pre-set criteria and matches the optimal transaction.

[0588] "Means for notifying the user of the matching results generated by the server" refers to a communication mechanism by which the server generates the matching results and notifies the user of them in real time or at an appropriate timing.

[0589] "Means by which the server records transaction history and stores it for future reference" refers to a mechanism by which the server records the content and results of transactions in a database and stores them for future reference and analysis.

[0590] "Means for analyzing user emotions in real time and providing feedback to improve the quality of trading" refers to a mechanism for analyzing emotions from users' facial expressions, voice, text messages, etc., and providing feedback in real time to improve the user's trading experience based on the results.

[0591] The present invention is a system for streamlining transactions and improving user experience in the used car market. The system allows users to input product information, receives it from a server, stores it in a database, analyzes the desired trade information based on specific criteria, notifies users of matching results, and records and saves transaction history for future reference. The system also includes a function for analyzing users' sentiment in real time and providing feedback to improve the quality of transactions.

[0592] User Registration

[0593] A user registers with the system by entering their name, email address, and password. The server receives this information, stores it in a database, and checks for duplicate accounts. Upon registration, a unique token is generated and returned to the user, which is used for future user authentication.

[0594] Registering product information

[0595] The user enters information about the used car they want to sell, such as the manufacturer, model, year, price, and mileage, and then presses the register button. The server receives this, verifies the user's token, and saves it in the database. Once the save is complete, the server notifies the user that the registration was successful.

[0596] Search for product information

[0597] The user enters the desired vehicle conditions and presses the search button. The server then receives the request and searches the database for vehicles that match the conditions. The results are compiled and notified to the user. The user can then check the details from the displayed list of vehicles and select the vehicle they wish to trade.

[0598] Trade Matching

[0599] The server analyzes product information and transaction request information to find the best match between the two. This analysis is performed using a machine learning algorithm. Matching results are generated and notified to the user. At the same time, an emotion engine analyzes the user's reactions in real time and provides feedback to the user.

[0600] Emotion Engine Operation

[0601] The emotion engine analyzes users' input text, voice data, facial expressions, etc. to detect emotions in real time. For example, when a user is browsing a specific vehicle, the engine analyzes their facial expressions and tone of voice to determine their level of satisfaction and interest. This information is sent to the server and reflected in matching results and transaction history.

[0602] Managing transaction history

[0603] Once a transaction is completed, the server records the transaction details and stores them in a database. Users can then send a request to check their transaction history. At this time, emotional data is also stored as a history and used as a reference for future transactions. This allows users to refer to past transactions and make better decisions.

[0604] Hardware and software used

[0605] Hardware: User's smartphone (iOS or ANDROID)

[0606] Software: Python, sentiment analysis API (e.g., Emotion Detection API)

[0607] Specific examples of processing steps

[0608] If a user inputs information about the "2018 Toyota Corolla" and expresses an interest in the vehicle, the emotion engine analyzes that interest and sends it to the server. Based on this information, the server can make suggestions that will provide a high level of satisfaction.

[0609] Example prompt sentence:

[0610] "When searching for a vehicle on a used car website and selecting the car you want to buy, analyze the user's sentiment towards the description text that appears and suggest the next step action. The user entered the following information: 'Toyota Corolla 2018 model. Price: 1.5 million yen.' Also, the user's sentiment text is 'I really like this car!'"

[0611] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0612] Step 1: User Registration

[0613] The user enters their name, email address, and password. The server receives this information and checks whether there are any duplicate accounts. After checking, the server generates a unique token and stores the information in a database. After the user authentication information is saved, the server returns a success notification to the user.

[0614] Input: Name, Email Address, Password

[0615] Output: Token, save successful message

[0616] Specific operation: The server receives the input data, checks it against existing data in the database to confirm it is a duplicate, then registers the user as a new user in the database, generates an authentication token, and returns it.

[0617] Step 2: Register your product information

[0618] The user enters information about the vehicle they are selling (make, model, year, price, mileage, etc.) into the system. The server receives this information, verifies the user token, and saves it in the database. Once saved, the server sends a notification of successful registration to the user's device.

[0619] Input: Vehicle information such as make, model, year, price, mileage, etc.

[0620] Output: Registration successful message

[0621] Specific operation: The server receives the product information and token, verifies the token, saves the information to the database, and notifies the user after the save is successful.

[0622] Step 3: Search for product information

[0623] The user enters search criteria for the desired vehicle (e.g., manufacturer, model, year, price range, etc.) and presses the search button. The server receives the search criteria and searches the database for vehicle information that matches the criteria. The search results are returned to the user's terminal.

[0624] Input: Search criteria (make, model, year, price range, etc.)

[0625] Output: Search result vehicle list

[0626] Specific operation: The server receives the search criteria, queries the database to extract matching vehicle information, and returns the results to the user device.

[0627] Step 4: Deal Matching

[0628] The server analyzes registered product information and user transaction preferences to find the best match. It uses machine learning algorithms to compare the seller and buyer's desired conditions and find the best combination. The matching results are then notified to the user.

[0629] Input: Product information, transaction request information

[0630] Output: Matching results

[0631] What it does: The server uses machine learning algorithms to analyze the information, calculate the best matches, and notify the user of the generated matches.

[0632] Step 5: Sentiment Analysis and Feedback

[0633] The server uses an emotion engine to analyze the user's input text, voice data, and facial expressions in real time. If the user indicates interest or satisfaction, this information is saved as an analysis result and used to match deals and suggest next steps.

[0634] Input: User text input, voice data, facial expressions

[0635] Output: Sentiment analysis results, feedback

[0636] Specific operation: The server analyzes data using an emotion engine to determine the emotional state, and provides the analysis results as feedback to be reflected in transaction matching.

[0637] Step 6: Manage your transaction history

[0638] Once a transaction is completed, the server will record all transaction data and store it in a database. Users can request to view their transaction history later, which will allow them to make better decisions based on past transaction information and sentiment data.

[0639] Input: Transaction completion data

[0640] Output: A visible transaction history

[0641] Specific operation: The server receives transaction completion data and stores all information in the database. In response to a history reference request from the user, the data is retrieved and displayed.

[0642] 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.

[0643] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0644] 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.

[0645] [Second embodiment]

[0646] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0647] 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.

[0648] 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).

[0649] 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.

[0650] 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.

[0651] 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).

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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."

[0658] This invention is a system that streamlines the transmission of information and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history, thereby realizing smooth transactions.

[0659] User Registration

[0660] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[0661] Vehicle information registration

[0662] Next, we will explain the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user that the registration was successful.

[0663] Vehicle information search

[0664] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[0665] Trade Matching

[0666] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. This matching result is generated by the server and notified to the buyer and seller's devices. Both parties can then proceed to the actual transaction.

[0667] Managing transaction history

[0668] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. This allows the user to refer to past transactions and use them as reference for future transactions.

[0669] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches it and notifies both parties. In this way, User A and User B communicate with each other and the transaction is completed. All data during this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[0670] Through these procedures, the present invention realizes improved efficiency and reliability of transactions in the used car market.

[0671] The processing flow will be explained below.

[0672] User Registration

[0673] Step 1:

[0674] The user enters their name, email address, and password in the registration form and clicks the registration button.

[0675] Step 2:

[0676] The terminal transmits the input user information to the server.

[0677] Step 3:

[0678] The server receives the user information sent from the terminal.

[0679] Step 4:

[0680] The server searches its database to see if the entered email address already exists.

[0681] Step 5:

[0682] If the server finds no duplicate email addresses, it saves the new user information in the database.

[0683] Step 6:

[0684] The server generates an authentication token for the newly registered user.

[0685] Step 7:

[0686] The server returns the generated authentication token to the user's device.

[0687] Vehicle information registration

[0688] Step 1:

[0689] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[0690] Step 2:

[0691] The terminal transmits the entered vehicle information and authentication token to the server.

[0692] Step 3:

[0693] The server receives the vehicle information and the authentication token sent from the terminal.

[0694] Step 4:

[0695] The server validates the authentication token and verifies that the user is valid.

[0696] Step 5:

[0697] The server stores the vehicle information in a database.

[0698] Step 6:

[0699] The server notifies the user's terminal of successful registration.

[0700] Vehicle information search

[0701] Step 1:

[0702] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[0703] Step 2:

[0704] The terminal transmits the entered search conditions to the server.

[0705] Step 3:

[0706] The server receives the search conditions sent from the terminal.

[0707] Step 4:

[0708] The server searches the database and retrieves vehicle information that matches the criteria.

[0709] Step 5:

[0710] The server returns the search results to the user's terminal.

[0711] Trade Matching

[0712] Step 1:

[0713] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[0714] Step 2:

[0715] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[0716] Step 3:

[0717] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[0718] Step 4:

[0719] The server notifies the generated matching results to the terminals of the seller and the buyer.

[0720] Managing transaction history

[0721] Step 1:

[0722] A user issues a request to check their transaction history.

[0723] Step 2:

[0724] The terminal sends a request for transaction history to the server.

[0725] Step 3:

[0726] The server receives the request sent from the terminal.

[0727] Step 4:

[0728] The server validates the authentication token and verifies that the user is valid.

[0729] Step 5:

[0730] The server retrieves the user's transaction history from the database.

[0731] Step 6:

[0732] The server returns the acquired transaction history to the user's terminal.

[0733] Example 1

[0734] 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."

[0735] To ensure efficient and reliable transactions between sellers and buyers in the used car market, many processes are involved, including product information registration, search, matching, and transaction history management. Performing these processes manually is extremely time-consuming and prone to errors, so there is a need for a system that automates the transmission of information and optimal transaction matching in the used car market. Additionally, there are problems with duplicate registered information and delayed transaction status updates, which need to be resolved.

[0736] 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.

[0737] In this invention, the server includes means for a user to input product information, means for the server to store the received product information in a database, means for the server to check for the existence of duplicate accounts, means for the server to generate a unique identification code for each new account, means for a seller to input vehicle information and for the server to check the relevance of the data, means for the server to analyze the trade request information based on specific criteria, means for the server to perform matching using a generated AI model, means for the server to notify the user of the matching results generated by the server, and means for the server to record the transaction history and store it for future reference, thereby realizing efficient and reliable transactions in the used car market and enabling the checking of duplicate product information and real-time updates of transaction status.

[0738] "User" refers to an individual or corporation that uses the system to input product information and conduct sales.

[0739] "Product information" refers to detailed data entered by the user regarding the used car to be sold or bought.

[0740] "Server" refers to a computer system that processes, stores, and analyzes information received from users and sends necessary notifications.

[0741] "Database" means a collection of information managed by a server that stores product information, transaction history, etc.

[0742] "Identification Code" means a unique token or ID generated by the server when registering a new account.

[0743] "AI Model" means the artificial intelligence algorithm and its implementation used by the Server for transaction matching and data analysis.

[0744] "Token" refers to a unique identification code generated for authentication and security purposes.

[0745] A "seller" refers to a user who wishes to sell a used car and registers vehicle information in the system.

[0746] "Buyer" refers to a user who wishes to purchase a used car and searches for vehicle information in the system.

[0747] "Matching" refers to the process in which the server uses an AI model to analyze the seller's vehicle information and the buyer's desired conditions and propose the optimal deal.

[0748] "Transaction History" means a detailed record of completed transactions for future reference and analysis.

[0749] "Real-time updates" refers to a process in which the status of a transaction is reflected immediately and users are notified immediately.

[0750] This invention is a system for improving the efficiency and reliability of transactions in the used car market. This system allows users to input product information, and the server stores, analyzes, and matches the received information, notifies the results, and manages transaction history to ensure smooth transactions.

[0751] Configuration requirements

[0752] Hardware and Software

[0753] Server: The main computer system that processes, stores, and analyzes information.

[0754] Usage example: Server OS (Linux), Web server (Apache)

[0755] Terminal: Device operated by the user (PC, smartphone, etc.)

[0756] Example of use: Web browser (Chrome, Firefox)

[0757] Database: Where information is stored

[0758] Usage example: MySQL

[0759] AI model: Artificial intelligence model used for information analysis and matching

[0760] Usage examples: TensorFlow, Scikit-learn

[0761] Main processing flow

[0762] User Registration

[0763] overview

[0764] The user completes the registration process by entering their name, email address, and password and pressing the register button. The server receives this information and stores it in a database. It also checks for duplicate accounts and generates a unique identification code (token) for new accounts. This token is used for future user authentication.

[0765] Specific examples

[0766] The user enters the following information:

[0767] Name: Yamada Taro

[0768] Email address: taro@example.com

[0769] Password: password123

[0770] When the user presses the register button, the device sends this information to the server. The server receives the data and executes an "INSERT" query in the database to store the information. It then checks for duplicate accounts using an SQL query. A unique token is generated using a UUID library and sent back to the user.

[0771] Example prompt sentence:

[0772] What happens when a user enters their name, email address, and password and clicks the register button?

[0773] Vehicle information registration

[0774] overview

[0775] The seller enters the information of the vehicle they are selling (make, model, year, price, mileage, etc.) and presses the register button. The server receives this information, verifies the token, and saves it in the database. Once saved, the user is notified that registration was successful.

[0776] Specific examples

[0777] The seller enters the following vehicle information:

[0778] Manufacturer: Toyota

[0779] Model: Corolla

[0780] Year: 2015

[0781] Price: 1.5 million yen

[0782] Mileage: 50,000 km

[0783] When the user presses the registration button, the device sends this information and the token to the server. The server receives the data and verifies the token. It then executes an "INSERT" query in the database to save the data. After saving is complete, the server sends a notification to the user that registration is complete.

[0784] Example prompt sentence:

[0785] When a seller registers their vehicle information, how does the server process it?

[0786] Vehicle information search

[0787] overview

[0788] A buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives the request and searches the database for vehicle information that matches the conditions. The results are then sent back to the buyer's terminal.

[0789] Specific examples

[0790] Buyer enters the following search criteria:

[0791] Manufacturer: Toyota

[0792] Model: Corolla

[0793] Price: Under 2 million yen

[0794] Year: 2010 onwards

[0795] When a buyer presses the search button, the terminal sends the search criteria to the server. The server receives the search criteria and executes a "SELECT" query on the database. The results are returned to the terminal in JSON format, and the buyer can check the results on the terminal.

[0796] Example prompt sentence:

[0797] When a buyer searches for a desired vehicle, how does the system handle it?

[0798] Trade Matching

[0799] overview

[0800] The server uses AI to analyze the vehicle information registered by the seller and the buyer's desired conditions to perform optimal matching, and the generated matching results are sent to the buyer and seller's devices.

[0801] Specific examples

[0802] The server uses the AI ​​model to analyze:

[0803] Seller's vehicle information: Toyota Corolla 2015 model, 1.5 million yen, 50,000 km

[0804] Buyer's desired conditions: Toyota Corolla, under 2 million yen, 2010 or later

[0805] The AI ​​model calculates the optimal matching score, the server notifies the buyer and seller of the results, and the buyer and seller can proceed with the transaction.

[0806] Example prompt sentence:

[0807] What is the procedure for AI-based trade matching?

[0808] Managing transaction history

[0809] overview

[0810] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can send a request to check the transaction history, and the server retrieves the relevant transaction history from the database and sends it back to the terminal.

[0811] Specific examples

[0812] A transaction is completed and the server records the transaction details as follows:

[0813] Seller: User A

[0814] Buyer: User B

[0815] Vehicle traded: Toyota Corolla

[0816] Transaction amount: 1.5 million yen

[0817] Transaction Date: October 1, 2023

[0818] When a user sends a request to check their transaction history, the server retrieves the relevant transaction history from the database and returns it to the terminal.

[0819] Example prompt sentence:

[0820] How does the system work when it comes to managing transaction history?

[0821] Through these specific procedures and techniques, the present invention provides a system that improves the efficiency and reliability of transactions in the used car market.

[0822] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0823] Step 1: User Registration

[0824] 1.1 The user enters their name, email address, and password and presses the registration button.

[0825] Input: Name, Email Address, Password

[0826] Output: Sending input data

[0827] What happens: The device correctly formats the input data and sends it to the server.

[0828] 1.2 The server receives the data and checks the database for duplicate accounts.

[0829] Input: Received data (name, email address, password)

[0830] Output: Results of duplicate check

[0831] What happens: The server runs a "SELECT" query against the database to check for duplicate information.

[0832] 1.3 The server stores the new account in its database and generates a unique identification code.

[0833] Enter your new account information

[0834] Output: A unique identifier (token)

[0835] What happens: The server uses a UUID library to generate a unique token and executes an "INSERT" query against the database.

[0836] 1.4 The server generates a token and sends a notification back to the user.

[0837] Input: Token

[0838] Output: Token sent notification

[0839] Specific operation: The server sends a notification message containing the generated token to the device.

[0840] Step 2: Register your vehicle information

[0841] 2.1 The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and presses the registration button.

[0842] Input: Make, Model, Year, Price, Mileage

[0843] Output: Sending input data

[0844] What happens: The device correctly formats the input data, adds a token, and sends it to the server.

[0845] 2.2 The server checks the token in the received data.

[0846] Input: Vehicle information with token

[0847] Output: Token verification result

[0848] What happens: The server runs a "SELECT" query to check the validity of the token against the database.

[0849] 2.3 The server stores the vehicle information in a database.

[0850] Input: Vehicle information (make, model, year, price, mileage)

[0851] Output: Vehicle information saved

[0852] Specific behavior: The server executes an "INSERT" query on the database and saves the data.

[0853] 2.4 The server notifies the user of successful registration.

[0854] Input: Registration success status

[0855] Output: Registration successful notification

[0856] Specific operation: The server sends a registration completion status to the device.

[0857] Step 3: Find vehicle information

[0858] 3.1 The buyer enters the desired vehicle conditions into the terminal and presses the search button.

[0859] Input: Search criteria (make, model, price, year, etc.)

[0860] Output: Sending input data

[0861] What happens: The device correctly formats the search criteria and sends them to the server.

[0862] 3.2 The server receives the request and searches the database for vehicle information that matches the relevant criteria.

[0863] Input: Search criteria

[0864] Output: Search results

[0865] Specific operation: The server executes a "SELECT" query against the database to retrieve vehicle information that matches the search criteria.

[0866] 3.3 The server returns the search results to the device.

[0867] Input: Search results

[0868] Output: Send search results

[0869] Specific operation: The server generates search results in JSON format and sends them to the device.

[0870] 3.4 The buyer checks the vehicle list displayed as a result and presses the Show Details button.

[0871] Input: Search results

[0872] Output: Verbose

[0873] Specific behavior: The device displays the search results it receives and waits for the user's action.

[0874] Step 4: Deal Matching

[0875] 4.1 The server analyzes the seller's vehicle information and the buyer's desired conditions based on AI.

[0876] Input: Seller's vehicle information, Buyer's desired conditions

[0877] Output: Analysis results

[0878] How it works: The server analyzes this information using a generative AI model and generates a matching score.

[0879] 4.2 The server uses AI to find the best match.

[0880] Input: Parsed data

[0881] Output: Matching results

[0882] Specific behavior: The server determines the best matching pair based on the matching score.

[0883] 4.3 The server notifies the buyer and seller of the matching results.

[0884] Input: Matching results

[0885] Output: Matching notification

[0886] Specific operation: The server sends a notification message containing the matching result to the device.

[0887] 4.4 The buyer and seller will contact each other to proceed with the specific transaction.

[0888] Input: Matching results

[0889] Output: Transaction contact

[0890] Specific operation: The terminal provides the means of communication and the user proceeds with the transaction.

[0891] Step 5: Manage your transaction history

[0892] 5.1 Once the transaction is complete, the terminal notifies the server that the transaction is complete.

[0893] Input: Transaction Completion Status

[0894] Output: Notification of transaction completion

[0895] Specific operation: The terminal sends the transaction completion status to the server.

[0896] 5.2 The server records the transaction details and stores them in a database.

[0897] Enter: Transaction Details

[0898] Output: Saved results

[0899] What happens: The server executes an "INSERT" query against the database to store the transaction details.

[0900] 5.3 The user sends a request from the terminal to check past transaction history.

[0901] Input: User request

[0902] Output: Transaction history request

[0903] Specific operation: The terminal sends a request for transaction history to the server.

[0904] 5.4 The server retrieves the transaction history from the database and returns it to the terminal.

[0905] Input: User request

[0906] Output: Transaction history

[0907] Specific operation: The server executes a "SELECT" query on the database to retrieve the transaction history and send it to the terminal.

[0908] 5.5 The user checks the transaction history on the terminal.

[0909] Input: Transaction History

[0910] Output: History display

[0911] Specific operation: The terminal displays the received transaction history and the user confirms it.

[0912] (Application example 1)

[0913] 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."

[0914] In the used car trading market, achieving efficient and fast matching between sellers and buyers is a challenge. Conventional systems require complicated information input, search, and matching processes, resulting in a lack of reliability and efficiency in transactions. Furthermore, few systems allow users to check the transaction status in real time, making it difficult to keep track of the transaction progress in a timely manner.

[0915] 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.

[0916] In this invention, the server includes: a means for a user to input product information; a means for storing the received product information in a database; a means for the server to analyze transaction request information to perform matching based on specific criteria; a means for notifying the user of the matching results generated by the server; a means for the server to record transaction history and store it for future reference; a means for a user to input and confirm transaction information using a mobile device; a means for the server to analyze the information obtained from the mobile device and use a generative AI model to provide optimal matching; a means for updating the transaction status in real time based on transaction conditions and notifying the user; and a means for analyzing the requirements obtained from the user using prompt sentences and presenting optimal product information based on the analysis results, thereby enabling efficient and fast matching between sellers and buyers and improving the reliability and efficiency of transactions.

[0917] "User" refers to a general user of the system.

[0918] "Product Information" refers to detailed data relating to the products that are the subject of a transaction.

[0919] "Server" refers to the central processing unit that receives, stores, analyzes, and matches product information.

[0920] "Database" refers to a structured collection of information for storing data such as product information and transaction history.

[0921] "Matching" refers to the process of analyzing the conditions of the seller and buyer and optimally connecting the two.

[0922] "Desired transaction information" refers to the requests and conditions regarding the transaction entered by the user.

[0923] "Transaction history" refers to a detailed record of past transactions.

[0924] "Mobile terminal" refers to a portable information and communication device such as a smartphone or tablet.

[0925] A "generative AI model" refers to an artificial intelligence algorithm that generates optimal results based on large amounts of data.

[0926] A "prompt sentence" refers to an instruction sentence for accurately obtaining the user's requests or conditions.

[0927] This invention provides a system that aims to improve the efficiency and reliability of transactions in the used car market. A means is provided for users to input product information, and the server receives the information and stores it in a database. Specific embodiments of this system are described below.

[0928] First, a user accesses the system using a mobile device (e.g., smartphone, tablet). The user enters product information (manufacturer, model, year, price, mileage, etc.) and sends it to the system. This information is received by the server and stored in a database.

[0929] The server analyzes the information provided by each user and checks for duplicate product information, preventing the same product from being registered multiple times. The server also searches for information in its database based on the entered conditions and finds the best match based on the specified criteria.

[0930] In the matching process, the server uses a generative AI model that analyzes the user's desired transaction information to generate the optimal match. For example, if a user desires a "2015 Toyota Corolla," the server searches and analyzes the corresponding vehicle information to find the best match.

[0931] The generated matching results are notified to the user's mobile device. The user can then receive the notification and proceed with the transaction. Once the transaction is completed, the server records the transaction history in a database and saves it for future reference. Furthermore, the server updates the transaction status in real time based on the transaction conditions and notifies the user.

[0932] As a concrete example, suppose a user uses the system to search for "Toyota Corolla 2015 model." In this case, the server uses the generative AI model to analyze the user's prompt, "Toyota Corolla 2015 model," and searches for related information in the database. If a suitable vehicle is found, the server notifies the user of the matching results and allows the user to proceed with the specific transaction.

[0933] In this process, the server uses a back-end system based on Python, and the database is PostgreSQL or MongoDB. The front-end is built using HTML, CSS, and JavaScript. This system configuration improves the efficiency and reliability of used car transactions.

[0934] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0935] Step 1:

[0936] The user enters product information.

[0937] Input: Vehicle information such as make, model, year, price, mileage, etc.

[0938] Specific operation: The user enters product information into the input form on the mobile device and presses the "Submit" button.

[0939] Output: The entered vehicle information is sent to the server.

[0940] Step 2:

[0941] The server stores the received product information in a database.

[0942] Input: Vehicle information sent by the user

[0943] What happens: The server receives the input information and saves it to the database. The Python code saves it to the database.

[0944] Output: Vehicle information stored in the database

[0945] Step 3:

[0946] The server checks for duplicate product information.

[0947] Input: Vehicle information stored in the database

[0948] What happens: The server compares the new data with existing data in the database to see if there are any duplicates.

[0949] Output: Whether there are any duplicates. If there are any duplicates, an error message is displayed to the user.

[0950] Step 4:

[0951] The user inputs desired transaction information.

[0952] Input: Desired vehicle conditions (make, model, year, price range, etc.)

[0953] Specific operation: The user inputs the desired vehicle conditions on the mobile terminal and presses the "Search" button.

[0954] Output: The entered transaction request information is sent to the server.

[0955] Step 5:

[0956] The server analyzes the desired transaction information and searches the database for matching vehicle information.

[0957] Input: Transaction request information sent by the user, vehicle information in the database

[0958] Specific operation: The server uses the generative AI model to analyze the input information and search the database for matching vehicle information. Data analysis is performed using the generative AI model.

[0959] Output: List of matching vehicle information

[0960] Step 6:

[0961] The server generates the matching results and notifies the user.

[0962] Input: List of matching vehicle information

[0963] Specific operation: The server compiles matching vehicle information as a matching result and notifies the user's mobile device.

[0964] Output: Matching results displayed on the user's mobile device

[0965] Step 7:

[0966] The user proceeds with the transaction and enters and confirms the required information.

[0967] Input: Vehicle information and additional information included in the matching results

[0968] Specific operations: A user uses a mobile device to enter and confirm transaction information.

[0969] Output: The progress of the transaction is sent to the server.

[0970] Step 8:

[0971] The server records the transaction history and stores it for future reference.

[0972] Input: Detailed information after transaction completion

[0973] What happens: The server receives the final transaction information and saves it to the database. This is done using Python code.

[0974] Output: Transaction history stored in a database

[0975] Step 9:

[0976] The server updates the transaction status in real time based on the transaction conditions and notifies the user.

[0977] Input: In-progress transaction status information

[0978] Specific operation: The server monitors the transaction status in real time and notifies the user according to changes in conditions and progress.

[0979] Output: Real-time transaction status displayed on the user's mobile device

[0980] Step 10:

[0981] The system analyzes the required specifications obtained from the user using prompt statements and presents optimal product information based on the analysis results.

[0982] Input: Prompt from the user

[0983] Specific operation: The server inputs the prompt sentence into the generative AI model, obtains the analysis results, and presents the most suitable product information to the user based on the analysis results.

[0984] Output: The best product information presented to the user

[0985] 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.

[0986] This invention improves the trading experience in the used car market by combining an emotion engine with a system that streamlines the transmission of information and transaction matching between sellers and buyers. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. It also includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[0987] User Registration

[0988] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[0989] Vehicle information registration

[0990] This section explains the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user's device that the registration was successful.

[0991] Vehicle information search

[0992] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[0993] Trade Matching

[0994] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. The matching results are generated by the server and notified to the buyer and seller's devices. Furthermore, an emotion engine analyzes the user's reactions and provides feedback based on emotional data, improving the quality of the transaction.

[0995] Emotion Engine Operation

[0996] The emotion engine analyzes the user's facial expressions, tone of voice, and text message content during input and operation to detect emotions in real time. For example, when a user is browsing vehicle information, the emotion engine detects interest and satisfaction from the user's facial expressions. This information is sent to the server and reflected in the matching results.

[0997] Managing transaction history

[0998] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. The emotion data obtained by the emotion engine is also stored as history and can be used as a reference for future transactions. This allows users to refer to past transactions and make better decisions for future transactions.

[0999] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches them and notifies both parties. At this time, the emotion engine analyzes User B's reaction and confirms that the match is satisfactory. In this way, User A and User B communicate and the transaction is completed. All data from this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[1000] Through these procedures, the present invention realizes efficient transactions, improved reliability, and an improved trading experience in the used car market.

[1001] The processing flow will be explained below.

[1002] User Registration

[1003] Step 1:

[1004] The user enters their name, email address, and password in the registration form and clicks the registration button.

[1005] Step 2:

[1006] The terminal transmits the input user information to the server.

[1007] Step 3:

[1008] The server receives the user information sent from the terminal.

[1009] Step 4:

[1010] The server searches its database to see if the entered email address already exists.

[1011] Step 5:

[1012] If the server finds no duplicate email addresses, it saves the new user information in the database.

[1013] Step 6:

[1014] The server generates an authentication token for the newly registered user.

[1015] Step 7:

[1016] The server returns the generated authentication token to the user's device.

[1017] Vehicle information registration

[1018] Step 1:

[1019] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[1020] Step 2:

[1021] The terminal transmits the entered vehicle information and authentication token to the server.

[1022] Step 3:

[1023] The server receives the vehicle information and the authentication token sent from the terminal.

[1024] Step 4:

[1025] The server validates the authentication token and verifies that the user is valid.

[1026] Step 5:

[1027] The server stores the vehicle information in a database.

[1028] Step 6:

[1029] The server notifies the user's terminal of successful registration.

[1030] Vehicle information search

[1031] Step 1:

[1032] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[1033] Step 2:

[1034] The terminal transmits the entered search conditions to the server.

[1035] Step 3:

[1036] The server receives the search conditions sent from the terminal.

[1037] Step 4:

[1038] The server searches the database and retrieves vehicle information that matches the criteria.

[1039] Step 5:

[1040] The server returns the search results to the user's terminal.

[1041] Trade Matching

[1042] Step 1:

[1043] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[1044] Step 2:

[1045] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[1046] Step 3:

[1047] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[1048] Step 4:

[1049] The server notifies the generated matching results to the terminals of the seller and the buyer.

[1050] Step 5:

[1051] The emotion engine analyzes the user's facial expressions, tone of voice, and text messages when performing operations or inputting text to detect the user's emotions.

[1052] Step 6:

[1053] The server receives the emotion data from the emotion engine and reflects it in the matching results.

[1054] Step 7:

[1055] The server notifies the seller and buyer terminals of the feedback based on the emotion.

[1056] Managing transaction history

[1057] Step 1:

[1058] A user issues a request to check their transaction history.

[1059] Step 2:

[1060] The terminal sends a request for transaction history to the server.

[1061] Step 3:

[1062] The server receives the request sent from the terminal.

[1063] Step 4:

[1064] The server validates the authentication token and verifies that the user is valid.

[1065] Step 5:

[1066] The server retrieves the user's transaction history from the database.

[1067] Step 6:

[1068] The server returns the acquired transaction history to the user's terminal.

[1069] Step 7:

[1070] Emotion data obtained by the emotion engine is also saved as history and used as a reference for future transactions.

[1071] As a result, the present invention improves the efficiency and reliability of transactions in the used car market, and improves the trading experience.

[1072] Example 2

[1073] 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."

[1074] In traditional used car markets, information matching between sellers and buyers is often inefficient, resulting in problems such as insufficient improvement of transaction reliability and user experience. Furthermore, the quality of transactions can decline because users' feelings are not taken into consideration during transactions. Furthermore, transaction history management is inadequate, limiting its use as reference information for future transactions.

[1075] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input product information, a means for the server to store the received product information in a database, a means for the server to analyze transaction request information to perform matching based on specific criteria, a means for the server to notify the user of the matching results generated by the server, a means for the server to detect the user's emotions and provide feedback to improve the quality of the transaction based on the detected emotions, and a means for the server to record the transaction history and store it for future reference. This enables more efficient transactions, improved reliability, and an improved trading experience.

[1076] "Product information" refers to specific information about the product being traded (e.g., vehicle manufacturer, model, year, price, mileage, etc.).

[1077] "Server" refers to a computer system that manages and processes data over a network and responds to user requests.

[1078] A "database" refers to an information system that enables efficient storage, retrieval, and updating of large amounts of data.

[1079] "Deal Desired Information" refers to the transaction conditions desired by the user (e.g., price range, product characteristics, etc.).

[1080] "Matching" refers to the process of analyzing information on sellers and buyers to find the optimal combination.

[1081] An "emotion engine" refers to a system that detects emotions by analyzing a user's facial expressions, voice, and text messages.

[1082] "Feedback" refers to information provided for improvement or adjustment based on a user's behavior and feelings.

[1083] "Transaction history" refers to detailed information about past transactions (e.g., transaction date and time, price, participant information, etc.).

[1084] "Token" refers to a unique identifier used for user authentication and data protection.

[1085] "Duplicate checking" refers to the process of checking whether newly entered information already exists by comparing it with existing data.

[1086] This invention improves the trading experience by combining an emotion engine with a system that streamlines information transmission and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. Furthermore, it includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[1087] Hardware and software used

[1088] The system is implemented using the following hardware and software:

[1089] Server: A high-performance server machine for processing and managing data.

[1090] Database: Use a relational database system such as MySQL or PostgreSQL.

[1091] Emotion Engine: An emotion analysis system using OpenCV and TensorFlow.

[1092] User Interface: Web application using HTML, CSS, and JavaScript.

[1093] Specific operation of the system

[1094] The system operates as follows:

[1095] 1. User Registration:

[1096] A user enters their name, email address, and password into a web form and clicks the Register button. The server receives this information and stores it in a MySQL database using an INSERT statement. The server checks for duplicate accounts and generates a unique token that is emailed back to the user.

[1097] 2. Product information registration:

[1098] The seller enters information such as the make, model, year, price, and mileage, and clicks the register button. The server receives this information, verifies the seller's token, and saves it in the MySQL database using an INSERT statement. Once saved, the server sends a registration success message to the user's device via an AJAX request.

[1099] 3. Product Information Search:

[1100] The buyer enters the desired vehicle conditions (e.g. price range, model year, mileage) and clicks the search button. The server receives the request and performs a SELECT statement from the MySQL database based on the conditions. The results are compiled in JSON format and displayed in the buyer's browser via an AJAX request.

[1101] 4. Trade Matching:

[1102] The server receives the seller's vehicle information and the buyer's conditions and analyzes them using a Python AI library (e.g., scikit-learn). It performs the best match and generates the results in JSON format. The server notifies the user of the results using AJAX. The emotion engine captures and analyzes the user's facial expressions and voice using the webcam and microphone, and the server receives the emotion data and provides feedback.

[1103] 5. Emotion Engine in Action:

[1104] When a user browses vehicle information, their facial expressions and voice are captured in real time via a webcam and microphone. The emotion engine analyzes the data using OpenCV and TensorFlow to detect their interests and satisfaction. The emotion data is sent to the server and reflected in the matching results.

[1105] 6. Transaction History Management:

[1106] When a transaction is completed, the server records the details of the transaction (e.g., seller / buyer information, transaction date and time, transaction price). The recorded information is saved in a MySQL database using an INSERT statement. When a user sends a request to check the history, the server retrieves the transaction history from the database using a SELECT statement and returns it to the user in JSON format. Emotion data generated by the emotion engine is also saved as history and used as reference information for the next transaction.

[1107] Specific examples

[1108] For example, consider the case where User A registers vehicle information in the system and User B performs a search based on that information. The vehicle information entered by User A is saved on the server, and User B enters search criteria and presses the search button. The server searches for vehicle information that matches the criteria, compiles the results, and displays them on the buyer's browser. The AI ​​generates the optimal matching results, and the emotion engine analyzes User B's reaction to determine his or her satisfaction level. Ultimately, User A and User B complete a transaction.

[1109] Prompt Sentence Examples

[1110] The following can be used as an example of an input prompt for a generative AI model:

[1111] "We are considering a system that efficiently matches information between sellers and buyers in the used car market. In particular, the system will have the function of optimally combining the seller's vehicle information with the buyer's desired conditions and providing feedback based on the user's emotional data. Please provide a detailed explanation in natural language of the specific hardware and software, processing details, and operation of the emotion engine."

[1112] This allows you to understand the specific operation of the entire system and the technical details associated with it.

[1113] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1114] Step 1:

[1115] A user fills in a web form with their name, email address, and password and clicks the Register button.

[1116] Input: The user enters their name, email address, and password.

[1117] Specific operation: The terminal sends input data to the server.

[1118] Output: The server receives the input data.

[1119] Step 2:

[1120] The server processes the received registration information and stores it in a database.

[1121] Input: The server receives the user's name, email address, and password.

[1122] Specific operation: The server saves this data in the MySQL database using an INSERT statement.

[1123] Output: User information is saved to a database and checked for duplicate accounts.

[1124] Step 3:

[1125] The server checks for unique email addresses and generates a token for new registrations.

[1126] Input: The server retrieves a list of registered email addresses.

[1127] What happens: The server runs a SELECT statement to check for duplicate email addresses. If there are no duplicates, it uses the UUID library to generate a new token.

[1128] Output: A unique token is generated and sent back to the user.

[1129] Step 4:

[1130] The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and clicks the registration button.

[1131] Input: The seller enters vehicle information (make, model, year, price, mileage).

[1132] Specific operation: The terminal sends input data to the server.

[1133] Output: The server receives the input data.

[1134] Step 5:

[1135] The server processes the received vehicle information and stores it in a database.

[1136] Input: The server receives the seller's vehicle information.

[1137] Specific operation: The server verifies the user token and then saves the vehicle information to the MySQL database using an INSERT statement.

[1138] Output: Vehicle information is saved in the database.

[1139] Step 6:

[1140] The server notifies the user's terminal of successful registration.

[1141] Input: The server determines that the vehicle information has been saved.

[1142] Specific operation: The server uses JavaScript to display a registration success message in the user's browser via an AJAX request.

[1143] Output: A notification of successful registration is displayed on the user's device.

[1144] Step 7:

[1145] The buyer enters the vehicle conditions they desire and clicks the search button.

[1146] Input: The buyer enters their desired conditions (price range, model year, mileage, etc.).

[1147] Specific operation: The terminal sends search criteria to the server.

[1148] Output: The server receives the search criteria.

[1149] Step 8:

[1150] The server searches the database for vehicle information based on the received search criteria.

[1151] Input: The server receives the purchase request terms.

[1152] Specific operation: The server executes the SELECT statement and retrieves vehicle information that matches the conditions from the database.

[1153] Output: A list of vehicles that match the criteria is generated.

[1154] Step 9:

[1155] The server returns the search results to the buyer's terminal for display.

[1156] Input: The server has a list of vehicles that match the criteria.

[1157] Specific operation: The server sends the search results in JSON format to the buyer's browser via an AJAX request.

[1158] Output: The vehicle list is displayed on the buyer's terminal.

[1159] Step 10:

[1160] The server analyzes the information of the seller and buyer and makes the best match.

[1161] Input: The server receives the seller's vehicle information and the buyer's desired conditions.

[1162] Specific operation: The server analyzes the information using a Python AI library (e.g., scikit-learn).

[1163] Output: The best matching result is generated.

[1164] Step 11:

[1165] The server notifies the seller and buyer of the matching results.

[1166] Input: The server has the generated matching results.

[1167] Specific operation: The server uses AJAX to send the matching results in JSON format to the user.

[1168] Output: The matching results are displayed on the user's device.

[1169] Step 12:

[1170] The emotion engine analyzes emotions from user input and operations and sends the data to the server.

[1171] Input: Capture real-time facial expressions and voice while the user is viewing vehicle information.

[1172] Specific operation: The emotion engine analyzes facial expression and voice data using OpenCV and TensorFlow.

[1173] Output: The analyzed emotion data is sent to the server.

[1174] Step 13:

[1175] The server analyzes the received emotion data and provides feedback.

[1176] Input: The server receives the user's emotion data.

[1177] Specific operation: The server analyzes the emotional data and reflects it in the matching results or provides it to the user as feedback.

[1178] Output: Feedback is displayed on the user's terminal, improving the quality of the transaction.

[1179] Step 14:

[1180] If the transaction is completed, the server records the transaction details and stores them in a database.

[1181] Input: The server receives the transaction completion information.

[1182] Specific operation: The server saves the transaction details (e.g., seller / buyer information, transaction date and time, transaction price) into the MySQL database using an INSERT statement.

[1183] Output: Transaction details stored in database.

[1184] Step 15:

[1185] The user sends a request to the server to check the transaction history.

[1186] Input: A user submits a request for transaction history.

[1187] Specific operation: The terminal sends a transaction history request to the server.

[1188] Output: The server receives the request.

[1189] Step 16:

[1190] The server retrieves the relevant transaction history from the database and returns it to the user's terminal.

[1191] Input: The server receives a transaction history request.

[1192] Specific operation: The server executes the SELECT statement and retrieves the relevant transaction history.

[1193] Output: The transaction history is sent to the user's device in JSON format.

[1194] Step 17:

[1195] Emotional data generated by the emotion engine is also stored in the transaction history and used as a reference for future transactions.

[1196] Input: The server has emotion data at the time of the transaction.

[1197] Specific operation: The emotion engine saves the emotion data collected during the transaction into the database using an INSERT statement.

[1198] Output: The sentiment data is included in the trading history and used as reference for the next trade.

[1199] (Application example 2)

[1200] 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."

[1201] The main functions of conventional trading systems in the used car market were matching sellers and buyers and managing transaction information, but there was no mechanism to improve the quality of transactions by taking user emotions and satisfaction into consideration.In addition, there was a lack of a way to improve the user experience through real-time emotional feedback during transactions, making improving user satisfaction a challenge.

[1202] The specification process by the specification 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 a means for a user to input product information, a means for the server to store the received product information in a database, a means for the server to analyze transaction request information to perform matching based on specific criteria, a means for the server to notify the user of the matching results generated by the server, a means for the server to record transaction history and store it for future reference, and a means for analyzing user emotions in real time and providing feedback to improve the quality of transactions. This enables more efficient transactions, improved user satisfaction, and an improved quality of the trading experience.

[1203] "Means for users to input product information" refers to an interface that allows users to input information about the products to be traded in text or other formats.

[1204] The term "means for storing the product information received by the server in a database" refers to a process and mechanism for the server to store the product-related data received from the user in a database.

[1205] "Means for the server to analyze transaction request information in order to perform matching based on specific criteria" refers to a mechanism in which the server analyzes the desired information of sellers and buyers based on pre-set criteria and matches the optimal transaction.

[1206] "Means for notifying the user of the matching results generated by the server" refers to a communication mechanism by which the server generates the matching results and notifies the user of them in real time or at an appropriate timing.

[1207] "Means by which the server records transaction history and stores it for future reference" refers to a mechanism by which the server records the content and results of transactions in a database and stores them for future reference and analysis.

[1208] "Means for analyzing user emotions in real time and providing feedback to improve the quality of trading" refers to a mechanism for analyzing emotions from users' facial expressions, voice, text messages, etc., and providing feedback in real time to improve the user's trading experience based on the results.

[1209] The present invention is a system for streamlining transactions and improving user experience in the used car market. The system allows users to input product information, receives it from a server, stores it in a database, analyzes the desired trade information based on specific criteria, notifies users of matching results, and records and saves transaction history for future reference. The system also includes a function for analyzing users' sentiment in real time and providing feedback to improve the quality of transactions.

[1210] User Registration

[1211] A user registers with the system by entering their name, email address, and password. The server receives this information, stores it in a database, and checks for duplicate accounts. Upon registration, a unique token is generated and returned to the user, which is used for future user authentication.

[1212] Registering product information

[1213] The user enters information about the used car they want to sell, such as the manufacturer, model, year, price, and mileage, and then presses the register button. The server receives this, verifies the user's token, and saves it in the database. Once the save is complete, the server notifies the user that the registration was successful.

[1214] Search for product information

[1215] The user enters the desired vehicle conditions and presses the search button. The server then receives the request and searches the database for vehicles that match the conditions. The results are compiled and notified to the user. The user can then check the details from the displayed list of vehicles and select the vehicle they wish to trade.

[1216] Trade Matching

[1217] The server analyzes product information and transaction request information to find the best match between the two. This analysis is performed using a machine learning algorithm. Matching results are generated and notified to the user. At the same time, an emotion engine analyzes the user's reactions in real time and provides feedback to the user.

[1218] Emotion Engine Operation

[1219] The emotion engine analyzes users' input text, voice data, facial expressions, etc. to detect emotions in real time. For example, when a user is browsing a specific vehicle, the engine analyzes their facial expressions and tone of voice to determine their level of satisfaction and interest. This information is sent to the server and reflected in matching results and transaction history.

[1220] Managing transaction history

[1221] Once a transaction is completed, the server records the transaction details and stores them in a database. Users can then send a request to check their transaction history. At this time, emotional data is also stored as a history and used as a reference for future transactions. This allows users to refer to past transactions and make better decisions.

[1222] Hardware and software used

[1223] Hardware: User's smartphone (iOS or Android)

[1224] Software: Python, sentiment analysis API (e.g., Emotion Detection API)

[1225] Specific examples of processing steps

[1226] If a user inputs information about the "2018 Toyota Corolla" and expresses an interest in the vehicle, the emotion engine analyzes that interest and sends it to the server. Based on this information, the server can make suggestions that will provide a high level of satisfaction.

[1227] Example prompt sentence:

[1228] "When searching for a vehicle on a used car website and selecting the car you want to buy, analyze the user's sentiment towards the description text that appears and suggest the next step action. The user entered the following information: 'Toyota Corolla 2018 model. Price: 1.5 million yen.' Also, the user's sentiment text is 'I really like this car!'"

[1229] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1230] Step 1: User Registration

[1231] The user enters their name, email address, and password. The server receives this information and checks whether there are any duplicate accounts. After checking, the server generates a unique token and stores the information in a database. After the user authentication information is saved, the server returns a success notification to the user.

[1232] Input: Name, Email Address, Password

[1233] Output: Token, save successful message

[1234] Specific operation: The server receives the input data, checks it against existing data in the database to confirm it is a duplicate, then registers the user as a new user in the database, generates an authentication token, and returns it.

[1235] Step 2: Register your product information

[1236] The user enters information about the vehicle they are selling (make, model, year, price, mileage, etc.) into the system. The server receives this information, verifies the user token, and saves it in the database. Once saved, the server sends a notification of successful registration to the user's device.

[1237] Input: Vehicle information such as make, model, year, price, mileage, etc.

[1238] Output: Registration successful message

[1239] Specific operation: The server receives the product information and token, verifies the token, saves the information to the database, and notifies the user after the save is successful.

[1240] Step 3: Search for product information

[1241] The user enters search criteria for the desired vehicle (e.g., manufacturer, model, year, price range, etc.) and presses the search button. The server receives the search criteria and searches the database for vehicle information that matches the criteria. The search results are returned to the user's terminal.

[1242] Input: Search criteria (make, model, year, price range, etc.)

[1243] Output: Search result vehicle list

[1244] Specific operation: The server receives the search criteria, queries the database to extract matching vehicle information, and returns the results to the user device.

[1245] Step 4: Deal Matching

[1246] The server analyzes registered product information and user transaction preferences to find the best match. It uses machine learning algorithms to compare the seller and buyer's desired conditions and find the best combination. The matching results are then notified to the user.

[1247] Input: Product information, transaction request information

[1248] Output: Matching results

[1249] What it does: The server uses machine learning algorithms to analyze the information, calculate the best matches, and notify the user of the generated matches.

[1250] Step 5: Sentiment Analysis and Feedback

[1251] The server uses an emotion engine to analyze the user's input text, voice data, and facial expressions in real time. If the user indicates interest or satisfaction, this information is saved as an analysis result and used to match deals and suggest next steps.

[1252] Input: User text input, voice data, facial expressions

[1253] Output: Sentiment analysis results, feedback

[1254] Specific operation: The server analyzes data using an emotion engine to determine the emotional state, and provides the analysis results as feedback to be reflected in transaction matching.

[1255] Step 6: Manage your transaction history

[1256] Once a transaction is completed, the server will record all transaction data and store it in a database. Users can request to view their transaction history later, which will allow them to make better decisions based on past transaction information and sentiment data.

[1257] Input: Transaction completion data

[1258] Output: A visible transaction history

[1259] Specific operation: The server receives transaction completion data and stores all information in the database. In response to a history reference request from the user, the data is retrieved and displayed.

[1260] 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.

[1261] 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.

[1262] 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.

[1263] [Third embodiment]

[1264] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1265] 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.

[1266] 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).

[1267] 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.

[1268] 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.

[1269] 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).

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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.

[1274] 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.

[1275] 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."

[1276] This invention is a system that streamlines the transmission of information and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history, thereby realizing smooth transactions.

[1277] User Registration

[1278] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[1279] Vehicle information registration

[1280] Next, we will explain the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user that the registration was successful.

[1281] Vehicle information search

[1282] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[1283] Trade Matching

[1284] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. This matching result is generated by the server and notified to the buyer and seller's devices. Both parties can then proceed to the actual transaction.

[1285] Managing transaction history

[1286] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. This allows the user to refer to past transactions and use them as reference for future transactions.

[1287] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches it and notifies both parties. In this way, User A and User B communicate with each other and the transaction is completed. All data during this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[1288] Through these procedures, the present invention realizes improved efficiency and reliability of transactions in the used car market.

[1289] The processing flow will be explained below.

[1290] User Registration

[1291] Step 1:

[1292] The user enters their name, email address, and password in the registration form and clicks the registration button.

[1293] Step 2:

[1294] The terminal transmits the input user information to the server.

[1295] Step 3:

[1296] The server receives the user information sent from the terminal.

[1297] Step 4:

[1298] The server searches its database to see if the entered email address already exists.

[1299] Step 5:

[1300] If the server finds no duplicate email addresses, it saves the new user information in the database.

[1301] Step 6:

[1302] The server generates an authentication token for the newly registered user.

[1303] Step 7:

[1304] The server returns the generated authentication token to the user's device.

[1305] Vehicle information registration

[1306] Step 1:

[1307] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[1308] Step 2:

[1309] The terminal transmits the entered vehicle information and authentication token to the server.

[1310] Step 3:

[1311] The server receives the vehicle information and the authentication token sent from the terminal.

[1312] Step 4:

[1313] The server validates the authentication token and verifies that the user is valid.

[1314] Step 5:

[1315] The server stores the vehicle information in a database.

[1316] Step 6:

[1317] The server notifies the user's terminal of successful registration.

[1318] Vehicle information search

[1319] Step 1:

[1320] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[1321] Step 2:

[1322] The terminal transmits the entered search conditions to the server.

[1323] Step 3:

[1324] The server receives the search conditions sent from the terminal.

[1325] Step 4:

[1326] The server searches the database and retrieves vehicle information that matches the criteria.

[1327] Step 5:

[1328] The server returns the search results to the user's terminal.

[1329] Trade Matching

[1330] Step 1:

[1331] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[1332] Step 2:

[1333] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[1334] Step 3:

[1335] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[1336] Step 4:

[1337] The server notifies the generated matching results to the terminals of the seller and the buyer.

[1338] Managing transaction history

[1339] Step 1:

[1340] A user issues a request to check their transaction history.

[1341] Step 2:

[1342] The terminal sends a request for transaction history to the server.

[1343] Step 3:

[1344] The server receives the request sent from the terminal.

[1345] Step 4:

[1346] The server validates the authentication token and verifies that the user is valid.

[1347] Step 5:

[1348] The server retrieves the user's transaction history from the database.

[1349] Step 6:

[1350] The server returns the acquired transaction history to the user's terminal.

[1351] Example 1

[1352] 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."

[1353] To ensure efficient and reliable transactions between sellers and buyers in the used car market, many processes are involved, including product information registration, search, matching, and transaction history management. Performing these processes manually is extremely time-consuming and prone to errors, so there is a need for a system that automates the transmission of information and optimal transaction matching in the used car market. Additionally, there are problems with duplicate registered information and delayed transaction status updates, which need to be resolved.

[1354] 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.

[1355] In this invention, the server includes means for a user to input product information, means for the server to store the received product information in a database, means for the server to check for the existence of duplicate accounts, means for the server to generate a unique identification code for each new account, means for a seller to input vehicle information and for the server to check the relevance of the data, means for the server to analyze the trade request information based on specific criteria, means for the server to perform matching using a generated AI model, means for the server to notify the user of the matching results generated by the server, and means for the server to record the transaction history and store it for future reference, thereby realizing efficient and reliable transactions in the used car market and enabling the checking of duplicate product information and real-time updates of transaction status.

[1356] "User" refers to an individual or corporation that uses the system to input product information and conduct sales.

[1357] "Product information" refers to detailed data entered by the user regarding the used car to be sold or bought.

[1358] "Server" refers to a computer system that processes, stores, and analyzes information received from users and sends necessary notifications.

[1359] "Database" means a collection of information managed by a server that stores product information, transaction history, etc.

[1360] "Identification Code" means a unique token or ID generated by the server when registering a new account.

[1361] "AI Model" means the artificial intelligence algorithm and its implementation used by the Server for transaction matching and data analysis.

[1362] "Token" refers to a unique identification code generated for authentication and security purposes.

[1363] A "seller" refers to a user who wishes to sell a used car and registers vehicle information in the system.

[1364] "Buyer" refers to a user who wishes to purchase a used car and searches for vehicle information in the system.

[1365] "Matching" refers to the process in which the server uses an AI model to analyze the seller's vehicle information and the buyer's desired conditions and propose the optimal deal.

[1366] "Transaction History" means a detailed record of completed transactions for future reference and analysis.

[1367] "Real-time updates" refers to a process in which the status of a transaction is reflected immediately and users are notified immediately.

[1368] This invention is a system for improving the efficiency and reliability of transactions in the used car market. This system allows users to input product information, and the server stores, analyzes, and matches the received information, notifies the results, and manages transaction history to ensure smooth transactions.

[1369] Configuration requirements

[1370] Hardware and Software

[1371] Server: The main computer system that processes, stores, and analyzes information.

[1372] Usage example: Server OS (Linux), Web server (Apache)

[1373] Terminal: Device operated by the user (PC, smartphone, etc.)

[1374] Example of use: Web browser (Chrome, Firefox)

[1375] Database: Where information is stored

[1376] Usage example: MySQL

[1377] AI model: Artificial intelligence model used for information analysis and matching

[1378] Usage examples: TensorFlow, Scikit-learn

[1379] Main processing flow

[1380] User Registration

[1381] overview

[1382] The user completes the registration process by entering their name, email address, and password and pressing the register button. The server receives this information and stores it in a database. It also checks for duplicate accounts and generates a unique identification code (token) for new accounts. This token is used for future user authentication.

[1383] Specific examples

[1384] The user enters the following information:

[1385] Name: Yamada Taro

[1386] Email address: taro@example.com

[1387] Password: password123

[1388] When the user presses the register button, the device sends this information to the server. The server receives the data and executes an "INSERT" query in the database to store the information. It then checks for duplicate accounts using an SQL query. A unique token is generated using a UUID library and sent back to the user.

[1389] Example prompt sentence:

[1390] What happens when a user enters their name, email address, and password and clicks the register button?

[1391] Vehicle information registration

[1392] overview

[1393] The seller enters the information of the vehicle they are selling (make, model, year, price, mileage, etc.) and presses the register button. The server receives this information, verifies the token, and saves it in the database. Once saved, the user is notified that registration was successful.

[1394] Specific examples

[1395] The seller enters the following vehicle information:

[1396] Manufacturer: Toyota

[1397] Model: Corolla

[1398] Year: 2015

[1399] Price: 1.5 million yen

[1400] Mileage: 50,000 km

[1401] When the user presses the registration button, the device sends this information and the token to the server. The server receives the data and verifies the token. It then executes an "INSERT" query in the database to save the data. After saving is complete, the server sends a notification to the user that registration is complete.

[1402] Example prompt sentence:

[1403] When a seller registers their vehicle information, how does the server process it?

[1404] Vehicle information search

[1405] overview

[1406] A buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives the request and searches the database for vehicle information that matches the conditions. The results are then sent back to the buyer's terminal.

[1407] Specific examples

[1408] Buyer enters the following search criteria:

[1409] Manufacturer: Toyota

[1410] Model: Corolla

[1411] Price: Under 2 million yen

[1412] Year: 2010 onwards

[1413] When a buyer presses the search button, the terminal sends the search criteria to the server. The server receives the search criteria and executes a "SELECT" query on the database. The results are returned to the terminal in JSON format, and the buyer can check the results on the terminal.

[1414] Example prompt sentence:

[1415] When a buyer searches for a desired vehicle, how does the system handle it?

[1416] Trade Matching

[1417] overview

[1418] The server uses AI to analyze the vehicle information registered by the seller and the buyer's desired conditions to perform optimal matching, and the generated matching results are sent to the buyer and seller's devices.

[1419] Specific examples

[1420] The server uses the AI ​​model to analyze:

[1421] Seller's vehicle information: Toyota Corolla 2015 model, 1.5 million yen, 50,000 km

[1422] Buyer's desired conditions: Toyota Corolla, under 2 million yen, 2010 or later

[1423] The AI ​​model calculates the optimal matching score, the server notifies the buyer and seller of the results, and the buyer and seller can proceed with the transaction.

[1424] Example prompt sentence:

[1425] What is the procedure for AI-based trade matching?

[1426] Managing transaction history

[1427] overview

[1428] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can send a request to check the transaction history, and the server retrieves the relevant transaction history from the database and sends it back to the terminal.

[1429] Specific examples

[1430] A transaction is completed and the server records the transaction details as follows:

[1431] Seller: User A

[1432] Buyer: User B

[1433] Vehicle traded: Toyota Corolla

[1434] Transaction amount: 1.5 million yen

[1435] Transaction Date: October 1, 2023

[1436] When a user sends a request to check their transaction history, the server retrieves the relevant transaction history from the database and returns it to the terminal.

[1437] Example prompt sentence:

[1438] How does the system work when it comes to managing transaction history?

[1439] Through these specific procedures and techniques, the present invention provides a system that improves the efficiency and reliability of transactions in the used car market.

[1440] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1441] Step 1: User Registration

[1442] 1.1 The user enters their name, email address, and password and presses the registration button.

[1443] Input: Name, Email Address, Password

[1444] Output: Sending input data

[1445] What happens: The device correctly formats the input data and sends it to the server.

[1446] 1.2 The server receives the data and checks the database for duplicate accounts.

[1447] Input: Received data (name, email address, password)

[1448] Output: Results of duplicate check

[1449] What happens: The server runs a "SELECT" query against the database to check for duplicate information.

[1450] 1.3 The server stores the new account in its database and generates a unique identification code.

[1451] Enter your new account information

[1452] Output: A unique identifier (token)

[1453] What happens: The server uses a UUID library to generate a unique token and executes an "INSERT" query against the database.

[1454] 1.4 The server generates a token and sends a notification back to the user.

[1455] Input: Token

[1456] Output: Token sent notification

[1457] Specific operation: The server sends a notification message containing the generated token to the device.

[1458] Step 2: Register your vehicle information

[1459] 2.1 The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and presses the registration button.

[1460] Input: Make, Model, Year, Price, Mileage

[1461] Output: Sending input data

[1462] What happens: The device correctly formats the input data, adds a token, and sends it to the server.

[1463] 2.2 The server checks the token in the received data.

[1464] Input: Vehicle information with token

[1465] Output: Token verification result

[1466] What happens: The server runs a "SELECT" query to check the validity of the token against the database.

[1467] 2.3 The server stores the vehicle information in a database.

[1468] Input: Vehicle information (make, model, year, price, mileage)

[1469] Output: Vehicle information saved

[1470] Specific behavior: The server executes an "INSERT" query on the database and saves the data.

[1471] 2.4 The server notifies the user of successful registration.

[1472] Input: Registration success status

[1473] Output: Registration successful notification

[1474] Specific operation: The server sends a registration completion status to the device.

[1475] Step 3: Find vehicle information

[1476] 3.1 The buyer enters the desired vehicle conditions into the terminal and presses the search button.

[1477] Input: Search criteria (make, model, price, year, etc.)

[1478] Output: Sending input data

[1479] What happens: The device correctly formats the search criteria and sends them to the server.

[1480] 3.2 The server receives the request and searches the database for vehicle information that matches the relevant criteria.

[1481] Input: Search criteria

[1482] Output: Search results

[1483] Specific operation: The server executes a "SELECT" query against the database to retrieve vehicle information that matches the search criteria.

[1484] 3.3 The server returns the search results to the device.

[1485] Input: Search results

[1486] Output: Send search results

[1487] Specific operation: The server generates search results in JSON format and sends them to the device.

[1488] 3.4 The buyer checks the vehicle list displayed as a result and presses the Show Details button.

[1489] Input: Search results

[1490] Output: Verbose

[1491] Specific behavior: The device displays the search results it receives and waits for the user's action.

[1492] Step 4: Deal Matching

[1493] 4.1 The server analyzes the seller's vehicle information and the buyer's desired conditions based on AI.

[1494] Input: Seller's vehicle information, Buyer's desired conditions

[1495] Output: Analysis results

[1496] How it works: The server analyzes this information using a generative AI model and generates a matching score.

[1497] 4.2 The server uses AI to find the best match.

[1498] Input: Parsed data

[1499] Output: Matching results

[1500] Specific behavior: The server determines the best matching pair based on the matching score.

[1501] 4.3 The server notifies the buyer and seller of the matching results.

[1502] Input: Matching results

[1503] Output: Matching notification

[1504] Specific operation: The server sends a notification message containing the matching result to the device.

[1505] 4.4 The buyer and seller will contact each other to proceed with the specific transaction.

[1506] Input: Matching results

[1507] Output: Transaction contact

[1508] Specific operation: The terminal provides the means of communication and the user proceeds with the transaction.

[1509] Step 5: Manage your transaction history

[1510] 5.1 Once the transaction is complete, the terminal notifies the server that the transaction is complete.

[1511] Input: Transaction Completion Status

[1512] Output: Notification of transaction completion

[1513] Specific operation: The terminal sends the transaction completion status to the server.

[1514] 5.2 The server records the transaction details and stores them in a database.

[1515] Enter: Transaction Details

[1516] Output: Saved results

[1517] What happens: The server executes an "INSERT" query against the database to store the transaction details.

[1518] 5.3 The user sends a request from the terminal to check past transaction history.

[1519] Input: User request

[1520] Output: Transaction history request

[1521] Specific operation: The terminal sends a request for transaction history to the server.

[1522] 5.4 The server retrieves the transaction history from the database and returns it to the terminal.

[1523] Input: User request

[1524] Output: Transaction history

[1525] Specific operation: The server executes a "SELECT" query on the database to retrieve the transaction history and send it to the terminal.

[1526] 5.5 The user checks the transaction history on the terminal.

[1527] Input: Transaction History

[1528] Output: History display

[1529] Specific operation: The terminal displays the received transaction history and the user confirms it.

[1530] (Application example 1)

[1531] 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."

[1532] In the used car trading market, achieving efficient and fast matching between sellers and buyers is a challenge. Conventional systems require complicated information input, search, and matching processes, resulting in a lack of reliability and efficiency in transactions. Furthermore, few systems allow users to check the transaction status in real time, making it difficult to keep track of the transaction progress in a timely manner.

[1533] 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.

[1534] In this invention, the server includes: a means for a user to input product information; a means for storing the received product information in a database; a means for the server to analyze transaction request information to perform matching based on specific criteria; a means for notifying the user of the matching results generated by the server; a means for the server to record transaction history and store it for future reference; a means for a user to input and confirm transaction information using a mobile device; a means for the server to analyze the information obtained from the mobile device and use a generative AI model to provide optimal matching; a means for updating the transaction status in real time based on transaction conditions and notifying the user; and a means for analyzing the requirements obtained from the user using prompt sentences and presenting optimal product information based on the analysis results, thereby enabling efficient and fast matching between sellers and buyers and improving the reliability and efficiency of transactions.

[1535] "User" refers to a general user of the system.

[1536] "Product Information" refers to detailed data relating to the products that are the subject of a transaction.

[1537] "Server" refers to the central processing unit that receives, stores, analyzes, and matches product information.

[1538] "Database" refers to a structured collection of information for storing data such as product information and transaction history.

[1539] "Matching" refers to the process of analyzing the conditions of the seller and buyer and optimally connecting the two.

[1540] "Desired transaction information" refers to the requests and conditions regarding the transaction entered by the user.

[1541] "Transaction history" refers to a detailed record of past transactions.

[1542] "Mobile terminal" refers to a portable information and communication device such as a smartphone or tablet.

[1543] A "generative AI model" refers to an artificial intelligence algorithm that generates optimal results based on large amounts of data.

[1544] A "prompt sentence" refers to an instruction sentence for accurately obtaining the user's requests or conditions.

[1545] This invention provides a system that aims to improve the efficiency and reliability of transactions in the used car market. A means is provided for users to input product information, and the server receives the information and stores it in a database. Specific embodiments of this system are described below.

[1546] First, a user accesses the system using a mobile device (e.g., smartphone, tablet). The user enters product information (manufacturer, model, year, price, mileage, etc.) and sends it to the system. This information is received by the server and stored in a database.

[1547] The server analyzes the information provided by each user and checks for duplicate product information, preventing the same product from being registered multiple times. The server also searches for information in its database based on the entered conditions and finds the best match based on the specified criteria.

[1548] In the matching process, the server uses a generative AI model that analyzes the user's desired transaction information to generate the optimal match. For example, if a user desires a "2015 Toyota Corolla," the server searches and analyzes the corresponding vehicle information to find the best match.

[1549] The generated matching results are notified to the user's mobile device. The user can then receive the notification and proceed with the transaction. Once the transaction is completed, the server records the transaction history in a database and saves it for future reference. Furthermore, the server updates the transaction status in real time based on the transaction conditions and notifies the user.

[1550] As a concrete example, suppose a user uses the system to search for "Toyota Corolla 2015 model." In this case, the server uses the generative AI model to analyze the user's prompt, "Toyota Corolla 2015 model," and searches for related information in the database. If a suitable vehicle is found, the server notifies the user of the matching results and allows the user to proceed with the specific transaction.

[1551] In this process, the server uses a back-end system based on Python, and the database is PostgreSQL or MongoDB. The front-end is built using HTML, CSS, and JavaScript. This system configuration improves the efficiency and reliability of used car transactions.

[1552] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1553] Step 1:

[1554] The user enters product information.

[1555] Input: Vehicle information such as make, model, year, price, mileage, etc.

[1556] Specific operation: The user enters product information into the input form on the mobile device and presses the "Submit" button.

[1557] Output: The entered vehicle information is sent to the server.

[1558] Step 2:

[1559] The server stores the received product information in a database.

[1560] Input: Vehicle information sent by the user

[1561] What happens: The server receives the input information and saves it to the database. The Python code saves it to the database.

[1562] Output: Vehicle information stored in the database

[1563] Step 3:

[1564] The server checks for duplicate product information.

[1565] Input: Vehicle information stored in the database

[1566] What happens: The server compares the new data with existing data in the database to see if there are any duplicates.

[1567] Output: Whether there are any duplicates. If there are any duplicates, an error message is displayed to the user.

[1568] Step 4:

[1569] The user inputs desired transaction information.

[1570] Input: Desired vehicle conditions (make, model, year, price range, etc.)

[1571] Specific operation: The user inputs the desired vehicle conditions on the mobile terminal and presses the "Search" button.

[1572] Output: The entered transaction request information is sent to the server.

[1573] Step 5:

[1574] The server analyzes the desired transaction information and searches the database for matching vehicle information.

[1575] Input: Transaction request information sent by the user, vehicle information in the database

[1576] Specific operation: The server uses the generative AI model to analyze the input information and search the database for matching vehicle information. Data analysis is performed using the generative AI model.

[1577] Output: List of matching vehicle information

[1578] Step 6:

[1579] The server generates the matching results and notifies the user.

[1580] Input: List of matching vehicle information

[1581] Specific operation: The server compiles matching vehicle information as a matching result and notifies the user's mobile device.

[1582] Output: Matching results displayed on the user's mobile device

[1583] Step 7:

[1584] The user proceeds with the transaction and enters and confirms the required information.

[1585] Input: Vehicle information and additional information included in the matching results

[1586] Specific operations: A user uses a mobile device to enter and confirm transaction information.

[1587] Output: The progress of the transaction is sent to the server.

[1588] Step 8:

[1589] The server records the transaction history and stores it for future reference.

[1590] Input: Detailed information after transaction completion

[1591] What happens: The server receives the final transaction information and saves it to the database. This is done using Python code.

[1592] Output: Transaction history stored in a database

[1593] Step 9:

[1594] The server updates the transaction status in real time based on the transaction conditions and notifies the user.

[1595] Input: In-progress transaction status information

[1596] Specific operation: The server monitors the transaction status in real time and notifies the user according to changes in conditions and progress.

[1597] Output: Real-time transaction status displayed on the user's mobile device

[1598] Step 10:

[1599] The system analyzes the required specifications obtained from the user using prompt statements and presents optimal product information based on the analysis results.

[1600] Input: Prompt from the user

[1601] Specific operation: The server inputs the prompt sentence into the generative AI model, obtains the analysis results, and presents the most suitable product information to the user based on the analysis results.

[1602] Output: The best product information presented to the user

[1603] 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.

[1604] This invention improves the trading experience in the used car market by combining an emotion engine with a system that streamlines the transmission of information and transaction matching between sellers and buyers. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. It also includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[1605] User Registration

[1606] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[1607] Vehicle information registration

[1608] This section explains the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user's device that the registration was successful.

[1609] Vehicle information search

[1610] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[1611] Trade Matching

[1612] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. The matching results are generated by the server and notified to the buyer and seller's devices. Furthermore, an emotion engine analyzes the user's reactions and provides feedback based on emotional data, improving the quality of the transaction.

[1613] Emotion Engine Operation

[1614] The emotion engine analyzes the user's facial expressions, tone of voice, and text message content during input and operation to detect emotions in real time. For example, when a user is browsing vehicle information, the emotion engine detects interest and satisfaction from the user's facial expressions. This information is sent to the server and reflected in the matching results.

[1615] Managing transaction history

[1616] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. The emotion data obtained by the emotion engine is also stored as history and can be used as a reference for future transactions. This allows users to refer to past transactions and make better decisions for future transactions.

[1617] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches them and notifies both parties. At this time, the emotion engine analyzes User B's reaction and confirms that the match is satisfactory. In this way, User A and User B communicate and the transaction is completed. All data from this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[1618] Through these procedures, the present invention realizes efficient transactions, improved reliability, and an improved trading experience in the used car market.

[1619] The processing flow will be explained below.

[1620] User Registration

[1621] Step 1:

[1622] The user enters their name, email address, and password in the registration form and clicks the registration button.

[1623] Step 2:

[1624] The terminal transmits the input user information to the server.

[1625] Step 3:

[1626] The server receives the user information sent from the terminal.

[1627] Step 4:

[1628] The server searches its database to see if the entered email address already exists.

[1629] Step 5:

[1630] If the server finds no duplicate email addresses, it saves the new user information in the database.

[1631] Step 6:

[1632] The server generates an authentication token for the newly registered user.

[1633] Step 7:

[1634] The server returns the generated authentication token to the user's device.

[1635] Vehicle information registration

[1636] Step 1:

[1637] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[1638] Step 2:

[1639] The terminal transmits the entered vehicle information and authentication token to the server.

[1640] Step 3:

[1641] The server receives the vehicle information and the authentication token sent from the terminal.

[1642] Step 4:

[1643] The server validates the authentication token and verifies that the user is valid.

[1644] Step 5:

[1645] The server stores the vehicle information in a database.

[1646] Step 6:

[1647] The server notifies the user's terminal of successful registration.

[1648] Vehicle information search

[1649] Step 1:

[1650] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[1651] Step 2:

[1652] The terminal transmits the entered search conditions to the server.

[1653] Step 3:

[1654] The server receives the search conditions sent from the terminal.

[1655] Step 4:

[1656] The server searches the database and retrieves vehicle information that matches the criteria.

[1657] Step 5:

[1658] The server returns the search results to the user's terminal.

[1659] Trade Matching

[1660] Step 1:

[1661] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[1662] Step 2:

[1663] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[1664] Step 3:

[1665] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[1666] Step 4:

[1667] The server notifies the generated matching results to the terminals of the seller and the buyer.

[1668] Step 5:

[1669] The emotion engine analyzes the user's facial expressions, tone of voice, and text messages when performing operations or inputting text to detect the user's emotions.

[1670] Step 6:

[1671] The server receives the emotion data from the emotion engine and reflects it in the matching results.

[1672] Step 7:

[1673] The server notifies the seller and buyer terminals of the feedback based on the emotion.

[1674] Managing transaction history

[1675] Step 1:

[1676] A user issues a request to check their transaction history.

[1677] Step 2:

[1678] The terminal sends a request for transaction history to the server.

[1679] Step 3:

[1680] The server receives the request sent from the terminal.

[1681] Step 4:

[1682] The server validates the authentication token and verifies that the user is valid.

[1683] Step 5:

[1684] The server retrieves the user's transaction history from the database.

[1685] Step 6:

[1686] The server returns the acquired transaction history to the user's terminal.

[1687] Step 7:

[1688] Emotion data obtained by the emotion engine is also saved as history and used as a reference for future transactions.

[1689] As a result, the present invention improves the efficiency and reliability of transactions in the used car market, and improves the trading experience.

[1690] Example 2

[1691] 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."

[1692] In traditional used car markets, information matching between sellers and buyers is often inefficient, resulting in problems such as insufficient improvement of transaction reliability and user experience. Furthermore, the quality of transactions can decline because users' feelings are not taken into consideration during transactions. Furthermore, transaction history management is inadequate, limiting its use as reference information for future transactions.

[1693] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input product information, a means for the server to store the received product information in a database, a means for the server to analyze transaction request information to perform matching based on specific criteria, a means for the server to notify the user of the matching results generated by the server, a means for the server to detect the user's emotions and provide feedback to improve the quality of the transaction based on the detected emotions, and a means for the server to record the transaction history and store it for future reference. This enables more efficient transactions, improved reliability, and an improved trading experience.

[1694] "Product information" refers to specific information about the product being traded (e.g., vehicle manufacturer, model, year, price, mileage, etc.).

[1695] "Server" refers to a computer system that manages and processes data over a network and responds to user requests.

[1696] A "database" refers to an information system that enables efficient storage, retrieval, and updating of large amounts of data.

[1697] "Deal Desired Information" refers to the transaction conditions desired by the user (e.g., price range, product characteristics, etc.).

[1698] "Matching" refers to the process of analyzing information on sellers and buyers to find the optimal combination.

[1699] An "emotion engine" refers to a system that detects emotions by analyzing a user's facial expressions, voice, and text messages.

[1700] "Feedback" refers to information provided for improvement or adjustment based on a user's behavior and feelings.

[1701] "Transaction history" refers to detailed information about past transactions (e.g., transaction date and time, price, participant information, etc.).

[1702] "Token" refers to a unique identifier used for user authentication and data protection.

[1703] "Duplicate checking" refers to the process of checking whether newly entered information already exists by comparing it with existing data.

[1704] This invention improves the trading experience by combining an emotion engine with a system that streamlines information transmission and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. Furthermore, it includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[1705] Hardware and software used

[1706] The system is implemented using the following hardware and software:

[1707] Server: A high-performance server machine for processing and managing data.

[1708] Database: Use a relational database system such as MySQL or PostgreSQL.

[1709] Emotion Engine: An emotion analysis system using OpenCV and TensorFlow.

[1710] User Interface: Web application using HTML, CSS, and JavaScript.

[1711] Specific operation of the system

[1712] The system operates as follows:

[1713] 1. User Registration:

[1714] A user enters their name, email address, and password into a web form and clicks the Register button. The server receives this information and stores it in a MySQL database using an INSERT statement. The server checks for duplicate accounts and generates a unique token that is emailed back to the user.

[1715] 2. Product information registration:

[1716] The seller enters information such as the make, model, year, price, and mileage, and clicks the register button. The server receives this information, verifies the seller's token, and saves it in the MySQL database using an INSERT statement. Once saved, the server sends a registration success message to the user's device via an AJAX request.

[1717] 3. Product Information Search:

[1718] The buyer enters the desired vehicle conditions (e.g. price range, model year, mileage) and clicks the search button. The server receives the request and performs a SELECT statement from the MySQL database based on the conditions. The results are compiled in JSON format and displayed in the buyer's browser via an AJAX request.

[1719] 4. Trade Matching:

[1720] The server receives the seller's vehicle information and the buyer's conditions and analyzes them using a Python AI library (e.g., scikit-learn). It performs the best match and generates the results in JSON format. The server notifies the user of the results using AJAX. The emotion engine captures and analyzes the user's facial expressions and voice using the webcam and microphone, and the server receives the emotion data and provides feedback.

[1721] 5. Emotion Engine in Action:

[1722] When a user browses vehicle information, their facial expressions and voice are captured in real time via a webcam and microphone. The emotion engine analyzes the data using OpenCV and TensorFlow to detect their interests and satisfaction. The emotion data is sent to the server and reflected in the matching results.

[1723] 6. Transaction History Management:

[1724] When a transaction is completed, the server records the details of the transaction (e.g., seller / buyer information, transaction date and time, transaction price). The recorded information is saved in a MySQL database using an INSERT statement. When a user sends a request to check the history, the server retrieves the transaction history from the database using a SELECT statement and returns it to the user in JSON format. Emotion data generated by the emotion engine is also saved as history and used as reference information for the next transaction.

[1725] Specific examples

[1726] For example, consider the case where User A registers vehicle information in the system and User B performs a search based on that information. The vehicle information entered by User A is saved on the server, and User B enters search criteria and presses the search button. The server searches for vehicle information that matches the criteria, compiles the results, and displays them on the buyer's browser. The AI ​​generates the optimal matching results, and the emotion engine analyzes User B's reaction to determine his or her satisfaction level. Ultimately, User A and User B complete a transaction.

[1727] Prompt Sentence Examples

[1728] The following can be used as an example of an input prompt for a generative AI model:

[1729] "We are considering a system that efficiently matches information between sellers and buyers in the used car market. In particular, the system will have the function of optimally combining the seller's vehicle information with the buyer's desired conditions and providing feedback based on the user's emotional data. Please provide a detailed explanation in natural language of the specific hardware and software, processing details, and operation of the emotion engine."

[1730] This allows you to understand the specific operation of the entire system and the technical details associated with it.

[1731] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1732] Step 1:

[1733] A user fills in a web form with their name, email address, and password and clicks the Register button.

[1734] Input: The user enters their name, email address, and password.

[1735] Specific operation: The terminal sends input data to the server.

[1736] Output: The server receives the input data.

[1737] Step 2:

[1738] The server processes the received registration information and stores it in a database.

[1739] Input: The server receives the user's name, email address, and password.

[1740] Specific operation: The server saves this data in the MySQL database using an INSERT statement.

[1741] Output: User information is saved to a database and checked for duplicate accounts.

[1742] Step 3:

[1743] The server checks for unique email addresses and generates a token for new registrations.

[1744] Input: The server retrieves a list of registered email addresses.

[1745] What happens: The server runs a SELECT statement to check for duplicate email addresses. If there are no duplicates, it uses the UUID library to generate a new token.

[1746] Output: A unique token is generated and sent back to the user.

[1747] Step 4:

[1748] The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and clicks the registration button.

[1749] Input: The seller enters vehicle information (make, model, year, price, mileage).

[1750] Specific operation: The terminal sends input data to the server.

[1751] Output: The server receives the input data.

[1752] Step 5:

[1753] The server processes the received vehicle information and stores it in a database.

[1754] Input: The server receives the seller's vehicle information.

[1755] Specific operation: The server verifies the user token and then saves the vehicle information to the MySQL database using an INSERT statement.

[1756] Output: Vehicle information is saved in the database.

[1757] Step 6:

[1758] The server notifies the user's terminal of successful registration.

[1759] Input: The server determines that the vehicle information has been saved.

[1760] Specific operation: The server uses JavaScript to display a registration success message in the user's browser via an AJAX request.

[1761] Output: A notification of successful registration is displayed on the user's device.

[1762] Step 7:

[1763] The buyer enters the vehicle conditions they desire and clicks the search button.

[1764] Input: The buyer enters their desired conditions (price range, model year, mileage, etc.).

[1765] Specific operation: The terminal sends search criteria to the server.

[1766] Output: The server receives the search criteria.

[1767] Step 8:

[1768] The server searches the database for vehicle information based on the received search criteria.

[1769] Input: The server receives the purchase request terms.

[1770] Specific operation: The server executes the SELECT statement and retrieves vehicle information that matches the conditions from the database.

[1771] Output: A list of vehicles that match the criteria is generated.

[1772] Step 9:

[1773] The server returns the search results to the buyer's terminal for display.

[1774] Input: The server has a list of vehicles that match the criteria.

[1775] Specific operation: The server sends the search results in JSON format to the buyer's browser via an AJAX request.

[1776] Output: The vehicle list is displayed on the buyer's terminal.

[1777] Step 10:

[1778] The server analyzes the information of the seller and buyer and makes the best match.

[1779] Input: The server receives the seller's vehicle information and the buyer's desired conditions.

[1780] Specific operation: The server analyzes the information using a Python AI library (e.g., scikit-learn).

[1781] Output: The best matching result is generated.

[1782] Step 11:

[1783] The server notifies the seller and buyer of the matching results.

[1784] Input: The server has the generated matching results.

[1785] Specific operation: The server uses AJAX to send the matching results in JSON format to the user.

[1786] Output: The matching results are displayed on the user's device.

[1787] Step 12:

[1788] The emotion engine analyzes emotions from user input and operations and sends the data to the server.

[1789] Input: Capture real-time facial expressions and voice while the user is viewing vehicle information.

[1790] Specific operation: The emotion engine analyzes facial expression and voice data using OpenCV and TensorFlow.

[1791] Output: The analyzed emotion data is sent to the server.

[1792] Step 13:

[1793] The server analyzes the received emotion data and provides feedback.

[1794] Input: The server receives the user's emotion data.

[1795] Specific operation: The server analyzes the emotional data and reflects it in the matching results or provides it to the user as feedback.

[1796] Output: Feedback is displayed on the user's terminal, improving the quality of the transaction.

[1797] Step 14:

[1798] If the transaction is completed, the server records the transaction details and stores them in a database.

[1799] Input: The server receives the transaction completion information.

[1800] Specific operation: The server saves the transaction details (e.g., seller / buyer information, transaction date and time, transaction price) into the MySQL database using an INSERT statement.

[1801] Output: Transaction details stored in database.

[1802] Step 15:

[1803] The user sends a request to the server to check the transaction history.

[1804] Input: A user submits a request for transaction history.

[1805] Specific operation: The terminal sends a transaction history request to the server.

[1806] Output: The server receives the request.

[1807] Step 16:

[1808] The server retrieves the relevant transaction history from the database and returns it to the user's terminal.

[1809] Input: The server receives a transaction history request.

[1810] Specific operation: The server executes the SELECT statement and retrieves the relevant transaction history.

[1811] Output: The transaction history is sent to the user's device in JSON format.

[1812] Step 17:

[1813] Emotional data generated by the emotion engine is also stored in the transaction history and used as a reference for future transactions.

[1814] Input: The server has emotion data at the time of the transaction.

[1815] Specific operation: The emotion engine saves the emotion data collected during the transaction into the database using an INSERT statement.

[1816] Output: The sentiment data is included in the trading history and used as reference for the next trade.

[1817] (Application example 2)

[1818] 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."

[1819] The main functions of conventional trading systems in the used car market were matching sellers and buyers and managing transaction information, but there was no mechanism to improve the quality of transactions by taking user emotions and satisfaction into consideration.In addition, there was a lack of a way to improve the user experience through real-time emotional feedback during transactions, making improving user satisfaction a challenge.

[1820] The specification process by the specification 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 a means for a user to input product information, a means for the server to store the received product information in a database, a means for the server to analyze transaction request information to perform matching based on specific criteria, a means for the server to notify the user of the matching results generated by the server, a means for the server to record transaction history and store it for future reference, and a means for analyzing user emotions in real time and providing feedback to improve the quality of transactions. This enables more efficient transactions, improved user satisfaction, and an improved quality of the trading experience.

[1821] "Means for users to input product information" refers to an interface that allows users to input information about the products to be traded in text or other formats.

[1822] The term "means for storing the product information received by the server in a database" refers to a process and mechanism for the server to store the product-related data received from the user in a database.

[1823] "Means for the server to analyze transaction request information in order to perform matching based on specific criteria" refers to a mechanism in which the server analyzes the desired information of sellers and buyers based on pre-set criteria and matches the optimal transaction.

[1824] "Means for notifying the user of the matching results generated by the server" refers to a communication mechanism by which the server generates the matching results and notifies the user of them in real time or at an appropriate timing.

[1825] "Means by which the server records transaction history and stores it for future reference" refers to a mechanism by which the server records the content and results of transactions in a database and stores them for future reference and analysis.

[1826] "Means for analyzing user emotions in real time and providing feedback to improve the quality of trading" refers to a mechanism for analyzing emotions from users' facial expressions, voice, text messages, etc., and providing feedback in real time to improve the user's trading experience based on the results.

[1827] The present invention is a system for streamlining transactions and improving user experience in the used car market. The system allows users to input product information, receives it from a server, stores it in a database, analyzes the desired trade information based on specific criteria, notifies users of matching results, and records and saves transaction history for future reference. The system also includes a function for analyzing users' sentiment in real time and providing feedback to improve the quality of transactions.

[1828] User Registration

[1829] A user registers with the system by entering their name, email address, and password. The server receives this information, stores it in a database, and checks for duplicate accounts. Upon registration, a unique token is generated and returned to the user, which is used for future user authentication.

[1830] Registering product information

[1831] The user enters information about the used car they want to sell, such as the manufacturer, model, year, price, and mileage, and then presses the register button. The server receives this, verifies the user's token, and saves it in the database. Once the save is complete, the server notifies the user that the registration was successful.

[1832] Search for product information

[1833] The user enters the desired vehicle conditions and presses the search button. The server then receives the request and searches the database for vehicles that match the conditions. The results are compiled and notified to the user. The user can then check the details from the displayed list of vehicles and select the vehicle they wish to trade.

[1834] Trade Matching

[1835] The server analyzes product information and transaction request information to find the best match between the two. This analysis is performed using a machine learning algorithm. Matching results are generated and notified to the user. At the same time, an emotion engine analyzes the user's reactions in real time and provides feedback to the user.

[1836] Emotion Engine Operation

[1837] The emotion engine analyzes users' input text, voice data, facial expressions, etc. to detect emotions in real time. For example, when a user is browsing a specific vehicle, the engine analyzes their facial expressions and tone of voice to determine their level of satisfaction and interest. This information is sent to the server and reflected in matching results and transaction history.

[1838] Managing transaction history

[1839] Once a transaction is completed, the server records the transaction details and stores them in a database. Users can then send a request to check their transaction history. At this time, emotional data is also stored as a history and used as a reference for future transactions. This allows users to refer to past transactions and make better decisions.

[1840] Hardware and software used

[1841] Hardware: User's smartphone (iOS or Android)

[1842] Software: Python, sentiment analysis API (e.g., Emotion Detection API)

[1843] Specific examples of processing steps

[1844] If a user inputs information about the "2018 Toyota Corolla" and expresses an interest in the vehicle, the emotion engine analyzes that interest and sends it to the server. Based on this information, the server can make suggestions that will provide a high level of satisfaction.

[1845] Example prompt sentence:

[1846] "When searching for a vehicle on a used car website and selecting the car you want to buy, analyze the user's sentiment towards the description text that appears and suggest the next step action. The user entered the following information: 'Toyota Corolla 2018 model. Price: 1.5 million yen.' Also, the user's sentiment text is 'I really like this car!'"

[1847] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1848] Step 1: User Registration

[1849] The user enters their name, email address, and password. The server receives this information and checks whether there are any duplicate accounts. After checking, the server generates a unique token and stores the information in a database. After the user authentication information is saved, the server returns a success notification to the user.

[1850] Input: Name, Email Address, Password

[1851] Output: Token, save successful message

[1852] Specific operation: The server receives the input data, checks it against existing data in the database to confirm it is a duplicate, then registers the user as a new user in the database, generates an authentication token, and returns it.

[1853] Step 2: Register your product information

[1854] The user enters information about the vehicle they are selling (make, model, year, price, mileage, etc.) into the system. The server receives this information, verifies the user token, and saves it in the database. Once saved, the server sends a notification of successful registration to the user's device.

[1855] Input: Vehicle information such as make, model, year, price, mileage, etc.

[1856] Output: Registration successful message

[1857] Specific operation: The server receives the product information and token, verifies the token, saves the information to the database, and notifies the user after the save is successful.

[1858] Step 3: Search for product information

[1859] The user enters search criteria for the desired vehicle (e.g., manufacturer, model, year, price range, etc.) and presses the search button. The server receives the search criteria and searches the database for vehicle information that matches the criteria. The search results are returned to the user's terminal.

[1860] Input: Search criteria (make, model, year, price range, etc.)

[1861] Output: Search result vehicle list

[1862] Specific operation: The server receives the search criteria, queries the database to extract matching vehicle information, and returns the results to the user device.

[1863] Step 4: Deal Matching

[1864] The server analyzes registered product information and user transaction preferences to find the best match. It uses machine learning algorithms to compare the seller and buyer's desired conditions and find the best combination. The matching results are then notified to the user.

[1865] Input: Product information, transaction request information

[1866] Output: Matching results

[1867] What it does: The server uses machine learning algorithms to analyze the information, calculate the best matches, and notify the user of the generated matches.

[1868] Step 5: Sentiment Analysis and Feedback

[1869] The server uses an emotion engine to analyze the user's input text, voice data, and facial expressions in real time. If the user indicates interest or satisfaction, this information is saved as an analysis result and used to match deals and suggest next steps.

[1870] Input: User text input, voice data, facial expressions

[1871] Output: Sentiment analysis results, feedback

[1872] Specific operation: The server analyzes data using an emotion engine to determine the emotional state, and provides the analysis results as feedback to be reflected in transaction matching.

[1873] Step 6: Manage your transaction history

[1874] Once a transaction is completed, the server will record all transaction data and store it in a database. Users can request to view their transaction history later, which will allow them to make better decisions based on past transaction information and sentiment data.

[1875] Input: Transaction completion data

[1876] Output: A visible transaction history

[1877] Specific operation: The server receives transaction completion data and stores all information in the database. In response to a history reference request from the user, the data is retrieved and displayed.

[1878] 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.

[1879] 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.

[1880] 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.

[1881] [Fourth embodiment]

[1882] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1883] 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.

[1884] 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).

[1885] 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.

[1886] 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.

[1887] 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).

[1888] 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.

[1889] 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.

[1890] 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.

[1891] 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.

[1892] 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.

[1893] 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.

[1894] 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."

[1895] This invention is a system that streamlines the transmission of information and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history, thereby realizing smooth transactions.

[1896] User Registration

[1897] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[1898] Vehicle information registration

[1899] Next, we will explain the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user that the registration was successful.

[1900] Vehicle information search

[1901] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[1902] Trade Matching

[1903] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. This matching result is generated by the server and notified to the buyer and seller's devices. Both parties can then proceed to the actual transaction.

[1904] Managing transaction history

[1905] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. This allows the user to refer to past transactions and use them as reference for future transactions.

[1906] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches it and notifies both parties. In this way, User A and User B communicate with each other and the transaction is completed. All data during this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[1907] Through these procedures, the present invention realizes improved efficiency and reliability of transactions in the used car market.

[1908] The processing flow will be explained below.

[1909] User Registration

[1910] Step 1:

[1911] The user enters their name, email address, and password in the registration form and clicks the registration button.

[1912] Step 2:

[1913] The terminal transmits the input user information to the server.

[1914] Step 3:

[1915] The server receives the user information sent from the terminal.

[1916] Step 4:

[1917] The server searches its database to see if the entered email address already exists.

[1918] Step 5:

[1919] If the server finds no duplicate email addresses, it saves the new user information in the database.

[1920] Step 6:

[1921] The server generates an authentication token for the newly registered user.

[1922] Step 7:

[1923] The server returns the generated authentication token to the user's device.

[1924] Vehicle information registration

[1925] Step 1:

[1926] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[1927] Step 2:

[1928] The terminal transmits the entered vehicle information and authentication token to the server.

[1929] Step 3:

[1930] The server receives the vehicle information and the authentication token sent from the terminal.

[1931] Step 4:

[1932] The server validates the authentication token and verifies that the user is valid.

[1933] Step 5:

[1934] The server stores the vehicle information in a database.

[1935] Step 6:

[1936] The server notifies the user's terminal of successful registration.

[1937] Vehicle information search

[1938] Step 1:

[1939] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[1940] Step 2:

[1941] The terminal transmits the entered search conditions to the server.

[1942] Step 3:

[1943] The server receives the search conditions sent from the terminal.

[1944] Step 4:

[1945] The server searches the database and retrieves vehicle information that matches the criteria.

[1946] Step 5:

[1947] The server returns the search results to the user's terminal.

[1948] Trade Matching

[1949] Step 1:

[1950] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[1951] Step 2:

[1952] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[1953] Step 3:

[1954] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[1955] Step 4:

[1956] The server notifies the generated matching results to the terminals of the seller and the buyer.

[1957] Managing transaction history

[1958] Step 1:

[1959] A user issues a request to check their transaction history.

[1960] Step 2:

[1961] The terminal sends a request for transaction history to the server.

[1962] Step 3:

[1963] The server receives the request sent from the terminal.

[1964] Step 4:

[1965] The server validates the authentication token and verifies that the user is valid.

[1966] Step 5:

[1967] The server retrieves the user's transaction history from the database.

[1968] Step 6:

[1969] The server returns the acquired transaction history to the user's terminal.

[1970] Example 1

[1971] 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."

[1972] To ensure efficient and reliable transactions between sellers and buyers in the used car market, many processes are involved, including product information registration, search, matching, and transaction history management. Performing these processes manually is extremely time-consuming and prone to errors, so there is a need for a system that automates the transmission of information and optimal transaction matching in the used car market. Additionally, there are problems with duplicate registered information and delayed transaction status updates, which need to be resolved.

[1973] 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.

[1974] In this invention, the server includes means for a user to input product information, means for the server to store the received product information in a database, means for the server to check for the existence of duplicate accounts, means for the server to generate a unique identification code for each new account, means for a seller to input vehicle information and for the server to check the relevance of the data, means for the server to analyze the trade request information based on specific criteria, means for the server to perform matching using a generated AI model, means for the server to notify the user of the matching results generated by the server, and means for the server to record the transaction history and store it for future reference, thereby realizing efficient and reliable transactions in the used car market and enabling the checking of duplicate product information and real-time updates of transaction status.

[1975] "User" refers to an individual or corporation that uses the system to input product information and conduct sales.

[1976] "Product information" refers to detailed data entered by the user regarding the used car to be sold or bought.

[1977] "Server" refers to a computer system that processes, stores, and analyzes information received from users and sends necessary notifications.

[1978] "Database" means a collection of information managed by a server that stores product information, transaction history, etc.

[1979] "Identification Code" means a unique token or ID generated by the server when registering a new account.

[1980] "AI Model" means the artificial intelligence algorithm and its implementation used by the Server for transaction matching and data analysis.

[1981] "Token" refers to a unique identification code generated for authentication and security purposes.

[1982] A "seller" refers to a user who wishes to sell a used car and registers vehicle information in the system.

[1983] "Buyer" refers to a user who wishes to purchase a used car and searches for vehicle information in the system.

[1984] "Matching" refers to the process in which the server uses an AI model to analyze the seller's vehicle information and the buyer's desired conditions and propose the optimal deal.

[1985] "Transaction History" means a detailed record of completed transactions for future reference and analysis.

[1986] "Real-time updates" refers to a process in which the status of a transaction is reflected immediately and users are notified immediately.

[1987] This invention is a system for improving the efficiency and reliability of transactions in the used car market. This system allows users to input product information, and the server stores, analyzes, and matches the received information, notifies the results, and manages transaction history to ensure smooth transactions.

[1988] Configuration requirements

[1989] Hardware and Software

[1990] Server: The main computer system that processes, stores, and analyzes information.

[1991] Usage example: Server OS (Linux), Web server (Apache)

[1992] Terminal: Device operated by the user (PC, smartphone, etc.)

[1993] Example of use: Web browser (Chrome, Firefox)

[1994] Database: Where information is stored

[1995] Usage example: MySQL

[1996] AI model: Artificial intelligence model used for information analysis and matching

[1997] Usage examples: TensorFlow, Scikit-learn

[1998] Main processing flow

[1999] User Registration

[2000] overview

[2001] The user completes the registration process by entering their name, email address, and password and pressing the register button. The server receives this information and stores it in a database. It also checks for duplicate accounts and generates a unique identification code (token) for new accounts. This token is used for future user authentication.

[2002] Specific examples

[2003] The user enters the following information:

[2004] Name: Yamada Taro

[2005] Email address: taro@example.com

[2006] Password: password123

[2007] When the user presses the register button, the device sends this information to the server. The server receives the data and executes an "INSERT" query in the database to store the information. It then checks for duplicate accounts using an SQL query. A unique token is generated using a UUID library and sent back to the user.

[2008] Example prompt sentence:

[2009] What happens when a user enters their name, email address, and password and clicks the register button?

[2010] Vehicle information registration

[2011] overview

[2012] The seller enters the information of the vehicle they are selling (make, model, year, price, mileage, etc.) and presses the register button. The server receives this information, verifies the token, and saves it in the database. Once saved, the user is notified that registration was successful.

[2013] Specific examples

[2014] The seller enters the following vehicle information:

[2015] Manufacturer: Toyota

[2016] Model: Corolla

[2017] Year: 2015

[2018] Price: 1.5 million yen

[2019] Mileage: 50,000 km

[2020] When the user presses the registration button, the device sends this information and the token to the server. The server receives the data and verifies the token. It then executes an "INSERT" query in the database to save the data. After saving is complete, the server sends a notification to the user that registration is complete.

[2021] Example prompt sentence:

[2022] When a seller registers their vehicle information, how does the server process it?

[2023] Vehicle information search

[2024] overview

[2025] A buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives the request and searches the database for vehicle information that matches the conditions. The results are then sent back to the buyer's terminal.

[2026] Specific examples

[2027] Buyer enters the following search criteria:

[2028] Manufacturer: Toyota

[2029] Model: Corolla

[2030] Price: Under 2 million yen

[2031] Year: 2010 onwards

[2032] When a buyer presses the search button, the terminal sends the search criteria to the server. The server receives the search criteria and executes a "SELECT" query on the database. The results are returned to the terminal in JSON format, and the buyer can check the results on the terminal.

[2033] Example prompt sentence:

[2034] When a buyer searches for a desired vehicle, how does the system handle it?

[2035] Trade Matching

[2036] overview

[2037] The server uses AI to analyze the vehicle information registered by the seller and the buyer's desired conditions to perform optimal matching, and the generated matching results are sent to the buyer and seller's devices.

[2038] Specific examples

[2039] The server uses the AI ​​model to analyze:

[2040] Seller's vehicle information: Toyota Corolla 2015 model, 1.5 million yen, 50,000 km

[2041] Buyer's desired conditions: Toyota Corolla, under 2 million yen, 2010 or later

[2042] The AI ​​model calculates the optimal matching score, the server notifies the buyer and seller of the results, and the buyer and seller can proceed with the transaction.

[2043] Example prompt sentence:

[2044] What is the procedure for AI-based trade matching?

[2045] Managing transaction history

[2046] overview

[2047] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can send a request to check the transaction history, and the server retrieves the relevant transaction history from the database and sends it back to the terminal.

[2048] Specific examples

[2049] A transaction is completed and the server records the transaction details as follows:

[2050] Seller: User A

[2051] Buyer: User B

[2052] Vehicle traded: Toyota Corolla

[2053] Transaction amount: 1.5 million yen

[2054] Transaction Date: October 1, 2023

[2055] When a user sends a request to check their transaction history, the server retrieves the relevant transaction history from the database and returns it to the terminal.

[2056] Example prompt sentence:

[2057] How does the system work when it comes to managing transaction history?

[2058] Through these specific procedures and techniques, the present invention provides a system that improves the efficiency and reliability of transactions in the used car market.

[2059] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2060] Step 1: User Registration

[2061] 1.1 The user enters their name, email address, and password and presses the registration button.

[2062] Input: Name, Email Address, Password

[2063] Output: Sending input data

[2064] What happens: The device correctly formats the input data and sends it to the server.

[2065] 1.2 The server receives the data and checks the database for duplicate accounts.

[2066] Input: Received data (name, email address, password)

[2067] Output: Results of duplicate check

[2068] What happens: The server runs a "SELECT" query against the database to check for duplicate information.

[2069] 1.3 The server stores the new account in its database and generates a unique identification code.

[2070] Enter your new account information

[2071] Output: A unique identifier (token)

[2072] What happens: The server uses a UUID library to generate a unique token and executes an "INSERT" query against the database.

[2073] 1.4 The server generates a token and sends a notification back to the user.

[2074] Input: Token

[2075] Output: Token sent notification

[2076] Specific operation: The server sends a notification message containing the generated token to the device.

[2077] Step 2: Register your vehicle information

[2078] 2.1 The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and presses the registration button.

[2079] Input: Make, Model, Year, Price, Mileage

[2080] Output: Sending input data

[2081] What happens: The device correctly formats the input data, adds a token, and sends it to the server.

[2082] 2.2 The server checks the token in the received data.

[2083] Input: Vehicle information with token

[2084] Output: Token verification result

[2085] What happens: The server runs a "SELECT" query to check the validity of the token against the database.

[2086] 2.3 The server stores the vehicle information in a database.

[2087] Input: Vehicle information (make, model, year, price, mileage)

[2088] Output: Vehicle information saved

[2089] Specific behavior: The server executes an "INSERT" query on the database and saves the data.

[2090] 2.4 The server notifies the user of successful registration.

[2091] Input: Registration success status

[2092] Output: Registration successful notification

[2093] Specific operation: The server sends a registration completion status to the device.

[2094] Step 3: Find vehicle information

[2095] 3.1 The buyer enters the desired vehicle conditions into the terminal and presses the search button.

[2096] Input: Search criteria (make, model, price, year, etc.)

[2097] Output: Sending input data

[2098] What happens: The device correctly formats the search criteria and sends them to the server.

[2099] 3.2 The server receives the request and searches the database for vehicle information that matches the relevant criteria.

[2100] Input: Search criteria

[2101] Output: Search results

[2102] Specific operation: The server executes a "SELECT" query against the database to retrieve vehicle information that matches the search criteria.

[2103] 3.3 The server returns the search results to the device.

[2104] Input: Search results

[2105] Output: Send search results

[2106] Specific operation: The server generates search results in JSON format and sends them to the device.

[2107] 3.4 The buyer checks the vehicle list displayed as a result and presses the Show Details button.

[2108] Input: Search results

[2109] Output: Verbose

[2110] Specific behavior: The device displays the search results it receives and waits for the user's action.

[2111] Step 4: Deal Matching

[2112] 4.1 The server analyzes the seller's vehicle information and the buyer's desired conditions based on AI.

[2113] Input: Seller's vehicle information, Buyer's desired conditions

[2114] Output: Analysis results

[2115] How it works: The server analyzes this information using a generative AI model and generates a matching score.

[2116] 4.2 The server uses AI to find the best match.

[2117] Input: Parsed data

[2118] Output: Matching results

[2119] Specific behavior: The server determines the best matching pair based on the matching score.

[2120] 4.3 The server notifies the buyer and seller of the matching results.

[2121] Input: Matching results

[2122] Output: Matching notification

[2123] Specific operation: The server sends a notification message containing the matching result to the device.

[2124] 4.4 The buyer and seller will contact each other to proceed with the specific transaction.

[2125] Input: Matching results

[2126] Output: Transaction contact

[2127] Specific operation: The terminal provides the means of communication and the user proceeds with the transaction.

[2128] Step 5: Manage your transaction history

[2129] 5.1 Once the transaction is complete, the terminal notifies the server that the transaction is complete.

[2130] Input: Transaction Completion Status

[2131] Output: Notification of transaction completion

[2132] Specific operation: The terminal sends the transaction completion status to the server.

[2133] 5.2 The server records the transaction details and stores them in a database.

[2134] Enter: Transaction Details

[2135] Output: Saved results

[2136] What happens: The server executes an "INSERT" query against the database to store the transaction details.

[2137] 5.3 The user sends a request from the terminal to check past transaction history.

[2138] Input: User request

[2139] Output: Transaction history request

[2140] Specific operation: The terminal sends a request for transaction history to the server.

[2141] 5.4 The server retrieves the transaction history from the database and returns it to the terminal.

[2142] Input: User request

[2143] Output: Transaction history

[2144] Specific operation: The server executes a "SELECT" query on the database to retrieve the transaction history and send it to the terminal.

[2145] 5.5 The user checks the transaction history on the terminal.

[2146] Input: Transaction History

[2147] Output: History display

[2148] Specific operation: The terminal displays the received transaction history and the user confirms it.

[2149] (Application example 1)

[2150] 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."

[2151] In the used car trading market, achieving efficient and fast matching between sellers and buyers is a challenge. Conventional systems require complicated information input, search, and matching processes, resulting in a lack of reliability and efficiency in transactions. Furthermore, few systems allow users to check the transaction status in real time, making it difficult to keep track of the transaction progress in a timely manner.

[2152] 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.

[2153] In this invention, the server includes: a means for a user to input product information; a means for storing the received product information in a database; a means for the server to analyze transaction request information to perform matching based on specific criteria; a means for notifying the user of the matching results generated by the server; a means for the server to record transaction history and store it for future reference; a means for a user to input and confirm transaction information using a mobile device; a means for the server to analyze the information obtained from the mobile device and use a generative AI model to provide optimal matching; a means for updating the transaction status in real time based on transaction conditions and notifying the user; and a means for analyzing the requirements obtained from the user using prompt sentences and presenting optimal product information based on the analysis results, thereby enabling efficient and fast matching between sellers and buyers and improving the reliability and efficiency of transactions.

[2154] "User" refers to a general user of the system.

[2155] "Product Information" refers to detailed data relating to the products that are the subject of a transaction.

[2156] "Server" refers to the central processing unit that receives, stores, analyzes, and matches product information.

[2157] "Database" refers to a structured collection of information for storing data such as product information and transaction history.

[2158] "Matching" refers to the process of analyzing the conditions of the seller and buyer and optimally connecting the two.

[2159] "Desired transaction information" refers to the requests and conditions regarding the transaction entered by the user.

[2160] "Transaction history" refers to a detailed record of past transactions.

[2161] "Mobile terminal" refers to a portable information and communication device such as a smartphone or tablet.

[2162] A "generative AI model" refers to an artificial intelligence algorithm that generates optimal results based on large amounts of data.

[2163] A "prompt sentence" refers to an instruction sentence for accurately obtaining the user's requests or conditions.

[2164] This invention provides a system that aims to improve the efficiency and reliability of transactions in the used car market. A means is provided for users to input product information, and the server receives the information and stores it in a database. Specific embodiments of this system are described below.

[2165] First, a user accesses the system using a mobile device (e.g., smartphone, tablet). The user enters product information (manufacturer, model, year, price, mileage, etc.) and sends it to the system. This information is received by the server and stored in a database.

[2166] The server analyzes the information provided by each user and checks for duplicate product information, preventing the same product from being registered multiple times. The server also searches for information in its database based on the entered conditions and finds the best match based on the specified criteria.

[2167] In the matching process, the server uses a generative AI model that analyzes the user's desired transaction information to generate the optimal match. For example, if a user desires a "2015 Toyota Corolla," the server searches and analyzes the corresponding vehicle information to find the best match.

[2168] The generated matching results are notified to the user's mobile device. The user can then receive the notification and proceed with the transaction. Once the transaction is completed, the server records the transaction history in a database and saves it for future reference. Furthermore, the server updates the transaction status in real time based on the transaction conditions and notifies the user.

[2169] As a concrete example, suppose a user uses the system to search for "Toyota Corolla 2015 model." In this case, the server uses the generative AI model to analyze the user's prompt, "Toyota Corolla 2015 model," and searches for related information in the database. If a suitable vehicle is found, the server notifies the user of the matching results and allows the user to proceed with the specific transaction.

[2170] In this process, the server uses a back-end system based on Python, and the database is PostgreSQL or MongoDB. The front-end is built using HTML, CSS, and JavaScript. This system configuration improves the efficiency and reliability of used car transactions.

[2171] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2172] Step 1:

[2173] The user enters product information.

[2174] Input: Vehicle information such as make, model, year, price, mileage, etc.

[2175] Specific operation: The user enters product information into the input form on the mobile device and presses the "Submit" button.

[2176] Output: The entered vehicle information is sent to the server.

[2177] Step 2:

[2178] The server stores the received product information in a database.

[2179] Input: Vehicle information sent by the user

[2180] What happens: The server receives the input information and saves it to the database. The Python code saves it to the database.

[2181] Output: Vehicle information stored in the database

[2182] Step 3:

[2183] The server checks for duplicate product information.

[2184] Input: Vehicle information stored in the database

[2185] What happens: The server compares the new data with existing data in the database to see if there are any duplicates.

[2186] Output: Whether there are any duplicates. If there are any duplicates, an error message is displayed to the user.

[2187] Step 4:

[2188] The user inputs desired transaction information.

[2189] Input: Desired vehicle conditions (make, model, year, price range, etc.)

[2190] Specific operation: The user inputs the desired vehicle conditions on the mobile terminal and presses the "Search" button.

[2191] Output: The entered transaction request information is sent to the server.

[2192] Step 5:

[2193] The server analyzes the desired transaction information and searches the database for matching vehicle information.

[2194] Input: Transaction request information sent by the user, vehicle information in the database

[2195] Specific operation: The server uses the generative AI model to analyze the input information and search the database for matching vehicle information. Data analysis is performed using the generative AI model.

[2196] Output: List of matching vehicle information

[2197] Step 6:

[2198] The server generates the matching results and notifies the user.

[2199] Input: List of matching vehicle information

[2200] Specific operation: The server compiles matching vehicle information as a matching result and notifies the user's mobile device.

[2201] Output: Matching results displayed on the user's mobile device

[2202] Step 7:

[2203] The user proceeds with the transaction and enters and confirms the required information.

[2204] Input: Vehicle information and additional information included in the matching results

[2205] Specific operations: A user uses a mobile device to enter and confirm transaction information.

[2206] Output: The progress of the transaction is sent to the server.

[2207] Step 8:

[2208] The server records the transaction history and stores it for future reference.

[2209] Input: Detailed information after transaction completion

[2210] What happens: The server receives the final transaction information and saves it to the database. This is done using Python code.

[2211] Output: Transaction history stored in a database

[2212] Step 9:

[2213] The server updates the transaction status in real time based on the transaction conditions and notifies the user.

[2214] Input: In-progress transaction status information

[2215] Specific operation: The server monitors the transaction status in real time and notifies the user according to changes in conditions and progress.

[2216] Output: Real-time transaction status displayed on the user's mobile device

[2217] Step 10:

[2218] The system analyzes the required specifications obtained from the user using prompt statements and presents optimal product information based on the analysis results.

[2219] Input: Prompt from the user

[2220] Specific operation: The server inputs the prompt sentence into the generative AI model, obtains the analysis results, and presents the most suitable product information to the user based on the analysis results.

[2221] Output: The best product information presented to the user

[2222] 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.

[2223] This invention improves the trading experience in the used car market by combining an emotion engine with a system that streamlines the transmission of information and transaction matching between sellers and buyers. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. It also includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[2224] User Registration

[2225] In order for a user to use the system, they must first register. The user enters their name, email address, and password, and then clicks the register button to submit their information. The server receives this information and stores it in a database. At the same time, the server checks whether there are any duplicate accounts, and generates a unique token when a new account is registered and returns it to the user. This token is used for future user authentication.

[2226] Vehicle information registration

[2227] This section explains the procedure for a seller to register information about a vehicle they are selling in the system. The seller enters information such as the manufacturer, model, year, price, and mileage, and presses the register button. The server receives this information, verifies the user's token, and then saves the vehicle information in the database. Once the save is complete, the server notifies the user's device that the registration was successful.

[2228] Vehicle information search

[2229] The buyer enters the desired vehicle conditions and presses the search button to send a search request to the system. The server receives this request and searches the database for vehicle information that matches the entered conditions. The server compiles the results and returns them to the terminal. The buyer then checks the details from the displayed list of vehicles and selects the vehicle they wish to trade for.

[2230] Trade Matching

[2231] The server uses AI to perform optimal matching based on the vehicle information registered by the seller and the buyer's desired conditions. Specifically, the AI ​​analyzes the seller's vehicle information and the buyer's desired conditions to find the optimal combination of the two. The matching results are generated by the server and notified to the buyer and seller's devices. Furthermore, an emotion engine analyzes the user's reactions and provides feedback based on emotional data, improving the quality of the transaction.

[2232] Emotion Engine Operation

[2233] The emotion engine analyzes the user's facial expressions, tone of voice, and text message content during input and operation to detect emotions in real time. For example, when a user is browsing vehicle information, the emotion engine detects interest and satisfaction from the user's facial expressions. This information is sent to the server and reflected in the matching results.

[2234] Managing transaction history

[2235] Once a transaction is completed, the server records the transaction details and stores them in a database. The user can then send a request to check their transaction history. The server receives this request, retrieves the relevant transaction history from the database, and sends it back to the terminal. The emotion data obtained by the emotion engine is also stored as history and can be used as a reference for future transactions. This allows users to refer to past transactions and make better decisions for future transactions.

[2236] As a concrete example, consider the case where User A registers vehicle information in the system to sell a used car, and User B searches for that vehicle as a potential purchase. The information entered by User A is saved in the system, and if it matches the search criteria of User B, the server matches them and notifies both parties. At this time, the emotion engine analyzes User B's reaction and confirms that the match is satisfactory. In this way, User A and User B communicate and the transaction is completed. All data from this process is recorded and stored for future reference, improving the reliability and efficiency of the transaction.

[2237] Through these procedures, the present invention realizes efficient transactions, improved reliability, and an improved trading experience in the used car market.

[2238] The processing flow will be explained below.

[2239] User Registration

[2240] Step 1:

[2241] The user enters their name, email address, and password in the registration form and clicks the registration button.

[2242] Step 2:

[2243] The terminal transmits the input user information to the server.

[2244] Step 3:

[2245] The server receives the user information sent from the terminal.

[2246] Step 4:

[2247] The server searches its database to see if the entered email address already exists.

[2248] Step 5:

[2249] If the server finds no duplicate email addresses, it saves the new user information in the database.

[2250] Step 6:

[2251] The server generates an authentication token for the newly registered user.

[2252] Step 7:

[2253] The server returns the generated authentication token to the user's device.

[2254] Vehicle information registration

[2255] Step 1:

[2256] The seller enters vehicle information (manufacturer, model, year, price, mileage, etc.) into the registration form and presses the registration button.

[2257] Step 2:

[2258] The terminal transmits the entered vehicle information and authentication token to the server.

[2259] Step 3:

[2260] The server receives the vehicle information and the authentication token sent from the terminal.

[2261] Step 4:

[2262] The server validates the authentication token and verifies that the user is valid.

[2263] Step 5:

[2264] The server stores the vehicle information in a database.

[2265] Step 6:

[2266] The server notifies the user's terminal of successful registration.

[2267] Vehicle information search

[2268] Step 1:

[2269] The buyer enters the desired vehicle criteria (manufacturer, model, price range, etc.) into the search form and presses the search button.

[2270] Step 2:

[2271] The terminal transmits the entered search conditions to the server.

[2272] Step 3:

[2273] The server receives the search conditions sent from the terminal.

[2274] Step 4:

[2275] The server searches the database and retrieves vehicle information that matches the criteria.

[2276] Step 5:

[2277] The server returns the search results to the user's terminal.

[2278] Trade Matching

[2279] Step 1:

[2280] The server acquires the seller's registered vehicle information and the buyer's desired conditions from the database.

[2281] Step 2:

[2282] The server inputs the seller's information and the buyer's desired conditions into the AI ​​model.

[2283] Step 3:

[2284] The AI ​​model analyzes the conditions of the seller and buyer and generates the optimal matching results.

[2285] Step 4:

[2286] The server notifies the generated matching results to the terminals of the seller and the buyer.

[2287] Step 5:

[2288] The emotion engine analyzes the user's facial expressions, tone of voice, and text messages when performing operations or inputting text to detect the user's emotions.

[2289] Step 6:

[2290] The server receives the emotion data from the emotion engine and reflects it in the matching results.

[2291] Step 7:

[2292] The server notifies the seller and buyer terminals of the feedback based on the emotion.

[2293] Managing transaction history

[2294] Step 1:

[2295] A user issues a request to check their transaction history.

[2296] Step 2:

[2297] The terminal sends a request for transaction history to the server.

[2298] Step 3:

[2299] The server receives the request sent from the terminal.

[2300] Step 4:

[2301] The server validates the authentication token and verifies that the user is valid.

[2302] Step 5:

[2303] The server retrieves the user's transaction history from the database.

[2304] Step 6:

[2305] The server returns the acquired transaction history to the user's terminal.

[2306] Step 7:

[2307] Emotion data obtained by the emotion engine is also saved as history and used as a reference for future transactions.

[2308] As a result, the present invention improves the efficiency and reliability of transactions in the used car market, and improves the trading experience.

[2309] Example 2

[2310] 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."

[2311] In traditional used car markets, information matching between sellers and buyers is often inefficient, resulting in problems such as insufficient improvement of transaction reliability and user experience. Furthermore, the quality of transactions can decline because users' feelings are not taken into consideration during transactions. Furthermore, transaction history management is inadequate, limiting its use as reference information for future transactions.

[2312] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for a user to input product information, a means for the server to store the received product information in a database, a means for the server to analyze transaction request information to perform matching based on specific criteria, a means for the server to notify the user of the matching results generated by the server, a means for the server to detect the user's emotions and provide feedback to improve the quality of the transaction based on the detected emotions, and a means for the server to record the transaction history and store it for future reference. This enables more efficient transactions, improved reliability, and an improved trading experience.

[2313] "Product information" refers to specific information about the product being traded (e.g., vehicle manufacturer, model, year, price, mileage, etc.).

[2314] "Server" refers to a computer system that manages and processes data over a network and responds to user requests.

[2315] A "database" refers to an information system that enables efficient storage, retrieval, and updating of large amounts of data.

[2316] "Deal Desired Information" refers to the transaction conditions desired by the user (e.g., price range, product characteristics, etc.).

[2317] "Matching" refers to the process of analyzing information on sellers and buyers to find the optimal combination.

[2318] An "emotion engine" refers to a system that detects emotions by analyzing a user's facial expressions, voice, and text messages.

[2319] "Feedback" refers to information provided for improvement or adjustment based on a user's behavior and feelings.

[2320] "Transaction history" refers to detailed information about past transactions (e.g., transaction date and time, price, participant information, etc.).

[2321] "Token" refers to a unique identifier used for user authentication and data protection.

[2322] "Duplicate checking" refers to the process of checking whether newly entered information already exists by comparing it with existing data.

[2323] This invention improves the trading experience by combining an emotion engine with a system that streamlines information transmission and transaction matching between sellers and buyers in the used car market. This system allows users to input product information, stores the received information on a server, analyzes and matches the information, notifies the results, and manages transaction history. Furthermore, it includes a function to detect user emotions and provide feedback to improve the quality of transactions.

[2324] Hardware and software used

[2325] The system is implemented using the following hardware and software:

[2326] Server: A high-performance server machine for processing and managing data.

[2327] Database: Use a relational database system such as MySQL or PostgreSQL.

[2328] Emotion Engine: An emotion analysis system using OpenCV and TensorFlow.

[2329] User Interface: Web application using HTML, CSS, and JavaScript.

[2330] Specific operation of the system

[2331] The system operates as follows:

[2332] 1. User Registration:

[2333] A user enters their name, email address, and password into a web form and clicks the Register button. The server receives this information and stores it in a MySQL database using an INSERT statement. The server checks for duplicate accounts and generates a unique token that is emailed back to the user.

[2334] 2. Product information registration:

[2335] The seller enters information such as the make, model, year, price, and mileage, and clicks the register button. The server receives this information, verifies the seller's token, and saves it in the MySQL database using an INSERT statement. Once saved, the server sends a registration success message to the user's device via an AJAX request.

[2336] 3. Product Information Search:

[2337] The buyer enters the desired vehicle conditions (e.g. price range, model year, mileage) and clicks the search button. The server receives the request and performs a SELECT statement from the MySQL database based on the conditions. The results are compiled in JSON format and displayed in the buyer's browser via an AJAX request.

[2338] 4. Trade Matching:

[2339] The server receives the seller's vehicle information and the buyer's conditions and analyzes them using a Python AI library (e.g., scikit-learn). It performs the best match and generates the results in JSON format. The server notifies the user of the results using AJAX. The emotion engine captures and analyzes the user's facial expressions and voice using the webcam and microphone, and the server receives the emotion data and provides feedback.

[2340] 5. Emotion Engine in Action:

[2341] When a user browses vehicle information, their facial expressions and voice are captured in real time via a webcam and microphone. The emotion engine analyzes the data using OpenCV and TensorFlow to detect their interests and satisfaction. The emotion data is sent to the server and reflected in the matching results.

[2342] 6. Transaction History Management:

[2343] When a transaction is completed, the server records the details of the transaction (e.g., seller / buyer information, transaction date and time, transaction price). The recorded information is saved in a MySQL database using an INSERT statement. When a user sends a request to check the history, the server retrieves the transaction history from the database using a SELECT statement and returns it to the user in JSON format. Emotion data generated by the emotion engine is also saved as history and used as reference information for the next transaction.

[2344] Specific examples

[2345] For example, consider the case where User A registers vehicle information in the system and User B performs a search based on that information. The vehicle information entered by User A is saved on the server, and User B enters search criteria and presses the search button. The server searches for vehicle information that matches the criteria, compiles the results, and displays them on the buyer's browser. The AI ​​generates the optimal matching results, and the emotion engine analyzes User B's reaction to determine his or her satisfaction level. Ultimately, User A and User B complete a transaction.

[2346] Prompt Sentence Examples

[2347] The following can be used as an example of an input prompt for a generative AI model:

[2348] "We are considering a system that efficiently matches information between sellers and buyers in the used car market. In particular, the system will have the function of optimally combining the seller's vehicle information with the buyer's desired conditions and providing feedback based on the user's emotional data. Please provide a detailed explanation in natural language of the specific hardware and software, processing details, and operation of the emotion engine."

[2349] This allows you to understand the specific operation of the entire system and the technical details associated with it.

[2350] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2351] Step 1:

[2352] A user fills in a web form with their name, email address, and password and clicks the Register button.

[2353] Input: The user enters their name, email address, and password.

[2354] Specific operation: The terminal sends input data to the server.

[2355] Output: The server receives the input data.

[2356] Step 2:

[2357] The server processes the received registration information and stores it in a database.

[2358] Input: The server receives the user's name, email address, and password.

[2359] Specific operation: The server saves this data in the MySQL database using an INSERT statement.

[2360] Output: User information is saved to a database and checked for duplicate accounts.

[2361] Step 3:

[2362] The server checks for unique email addresses and generates a token for new registrations.

[2363] Input: The server retrieves a list of registered email addresses.

[2364] What happens: The server runs a SELECT statement to check for duplicate email addresses. If there are no duplicates, it uses the UUID library to generate a new token.

[2365] Output: A unique token is generated and sent back to the user.

[2366] Step 4:

[2367] The seller enters vehicle information such as the manufacturer, model, year, price, and mileage, and clicks the registration button.

[2368] Input: The seller enters vehicle information (make, model, year, price, mileage).

[2369] Specific operation: The terminal sends input data to the server.

[2370] Output: The server receives the input data.

[2371] Step 5:

[2372] The server processes the received vehicle information and stores it in a database.

[2373] Input: The server receives the seller's vehicle information.

[2374] Specific operation: The server verifies the user token and then saves the vehicle information to the MySQL database using an INSERT statement.

[2375] Output: Vehicle information is saved in the database.

[2376] Step 6:

[2377] The server notifies the user's terminal of successful registration.

[2378] Input: The server determines that the vehicle information has been saved.

[2379] Specific operation: The server uses JavaScript to display a registration success message in the user's browser via an AJAX request.

[2380] Output: A notification of successful registration is displayed on the user's device.

[2381] Step 7:

[2382] The buyer enters the vehicle conditions they desire and clicks the search button.

[2383] Input: The buyer enters their desired conditions (price range, model year, mileage, etc.).

[2384] Specific operation: The terminal sends search criteria to the server.

[2385] Output: The server receives the search criteria.

[2386] Step 8:

[2387] The server searches the database for vehicle information based on the received search criteria.

[2388] Input: The server receives the purchase request terms.

[2389] Specific operation: The server executes the SELECT statement and retrieves vehicle information that matches the conditions from the database.

[2390] Output: A list of vehicles that match the criteria is generated.

[2391] Step 9:

[2392] The server returns the search results to the buyer's terminal for display.

[2393] Input: The server has a list of vehicles that match the criteria.

[2394] Specific operation: The server sends the search results in JSON format to the buyer's browser via an AJAX request.

[2395] Output: The vehicle list is displayed on the buyer's terminal.

[2396] Step 10:

[2397] The server analyzes the information of the seller and buyer and makes the best match.

[2398] Input: The server receives the seller's vehicle information and the buyer's desired conditions.

[2399] Specific operation: The server analyzes the information using a Python AI library (e.g., scikit-learn).

[2400] Output: The best matching result is generated.

[2401] Step 11:

[2402] The server notifies the seller and buyer of the matching results.

[2403] Input: The server has the generated matching results.

[2404] Specific operation: The server uses AJAX to send the matching results in JSON format to the user.

[2405] Output: The matching results are displayed on the user's device.

[2406] Step 12:

[2407] The emotion engine analyzes emotions from user input and operations and sends the data to the server.

[2408] Input: Capture real-time facial expressions and voice while the user is viewing vehicle information.

[2409] Specific operation: The emotion engine analyzes facial expression and voice data using OpenCV and TensorFlow.

[2410] Output: The analyzed emotion data is sent to the server.

[2411] Step 13:

[2412] The server analyzes the received emotion data and provides feedback.

[2413] Input: The server receives the user's emotion data.

[2414] Specific operation: The server analyzes the emotional data and reflects it in the matching results or provides it to the user as feedback.

[2415] Output: Feedback is displayed on the user's terminal, improving the quality of the transaction.

[2416] Step 14:

[2417] If the transaction is completed, the server records the transaction details and stores them in a database.

[2418] Input: The server receives the transaction completion information.

[2419] Specific operation: The server saves the transaction details (e.g., seller / buyer information, transaction date and time, transaction price) into the MySQL database using an INSERT statement.

[2420] Output: Transaction details stored in database.

[2421] Step 15:

[2422] The user sends a request to the server to check the transaction history.

[2423] Input: A user submits a request for transaction history.

[2424] Specific operation: The terminal sends a transaction history request to the server.

[2425] Output: The server receives the request.

[2426] Step 16:

[2427] The server retrieves the relevant transaction history from the database and returns it to the user's terminal.

[2428] Input: The server receives a transaction history request.

[2429] Specific operation: The server executes the SELECT statement and retrieves the relevant transaction history.

[2430] Output: The transaction history is sent to the user's device in JSON format.

[2431] Step 17:

[2432] Emotional data generated by the emotion engine is also stored in the transaction history and used as a reference for future transactions.

[2433] Input: The server has emotion data at the time of the transaction.

[2434] Specific operation: The emotion engine saves the emotion data collected during the transaction into the database using an INSERT statement.

[2435] Output: The sentiment data is included in the trading history and used as reference for the next trade.

[2436] (Application example 2)

[2437] 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."

[2438] The main functions of conventional trading systems in the used car market were matching selle...

Claims

1. A means for a user to input product information; A means for storing the product information received by the server in a database; means for analyzing the transaction information so that the server can match the transaction information based on specific criteria; means for notifying the user of the matching results generated by the server; a means by which the server records the history of transactions and stores them for future reference; A system including:

2. The system of claim 1 , further comprising means for checking for duplication of product information entered by a user.

3. 10. The system of claim 1, further comprising means for the server to provide real-time transaction status updates to the user.

Images