System

Abstract

To provide a system.SOLUTION: A system includes: means for collecting detailed information on an object from a seller and collecting a condition of a desired object from a buyer; means for generating a prompt sentence on the basis of the collected information on the seller and the buyer; means for inputting the prompt sentence to a regenerative AI model for matching the seller and the buyer; and means for notifying the seller and the buyer of a matching result outputted by the regenerative AI model.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Because buying and selling a home requires specialized knowledge, many people find it difficult to judge whether the transaction is legitimate, and some end up falling prey to unscrupulous real estate agents. It can also be used for buying and selling vacant homes in rural areas, and is also needed as an approach to the social problem of Tokyo's overconcentration in recent years. [Means for solving the problem]

[0005] We provide a housing sales platform system in which generative AI acts as a consultant, connecting sellers and buyers through P2P, supporting transactions between sellers and buyers, and determining whether a transaction is appropriate. Furthermore, by including a means for generative AI to match buyers and sellers based on their needs, we can achieve more appropriate transactions. Furthermore, by providing a system that can also be applied to the sale and purchase of vacant homes in rural areas, we can address the social issue of overconcentration in Tokyo. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The home buying and selling platform system of the present invention uses generative AI to connect sellers and buyers via P2P. The generative AI collects information from sellers (e.g., detailed property information, desired price, etc.) and information from buyers (e.g., desired property conditions, budget, etc.), and performs optimal matching based on this information.

[0029] "Example 2"

[0030] Furthermore, this system supports transactions between sellers and buyers. Specifically, the generative AI manages the progress of the transaction and provides instructions to smoothly carry out procedures such as the submission and signing of necessary documents and settlement.

[0031] "Example 3"

[0032] The system also has the ability to determine whether a transaction is appropriate. The generative AI analyzes the property price, transaction conditions, etc., and evaluates appropriateness based on market rates, laws, etc. If it is determined to be inappropriate, it notifies both the seller and the buyer and encourages them to conduct a fair transaction.

[0033] "Example 4"

[0034] This system can also be applied to the sale and purchase of vacant houses in rural areas. For example, it can aggregate information on vacant houses in rural areas and provide it to interested buyers. It can also provide information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.), encouraging people to move to rural areas.

[0035] The processing flow of each embodiment will be described below.

[0036] "Example 1"

[0037] Step 1: The generative AI collects information from the seller (e.g., detailed property information, asking price, etc.).

[0038] Step 2: Similarly, the generative AI collects information from the buyer (e.g., desired property conditions, budget, etc.).

[0039] Step 3: The generative AI performs optimal matching based on the collected information and connects sellers and buyers via P2P.

[0040] "Example 2"

[0041] Step 1: After matching the seller and buyer, the generative AI manages the progress of the transaction.

[0042] Step 2: The generative AI provides instructions to the seller and buyer to smoothly complete procedures such as submitting necessary documents, signing, and completing payments.

[0043] "Example 3"

[0044] Step 1: The generative AI analyzes the property price, transaction terms, etc.

[0045] Step 2: The generative AI evaluates the appropriateness of the transaction based on market prices, laws and regulations, etc.

[0046] Step 3: If the transaction is deemed inappropriate, the generative AI notifies both the seller and the buyer and encourages them to make the transaction appropriate.

[0047] "Example 4"

[0048] Step 1: The generative AI aggregates information on vacant houses in local areas.

[0049] Step 2: The generative AI provides aggregated vacant house information to interested buyers.

[0050] Step 3: The generative AI will also provide information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.), encouraging people to move to rural areas.

[0051] Example 1

[0052] Next, a description will be given of Example 1 of Form 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."

[0053] Conventional housing buying and selling platforms often failed to efficiently match sellers and buyers, and the fairness and transparency of transactions were often not ensured. Furthermore, they were difficult to apply to the sale of vacant houses in rural areas. This meant that the needs of sellers and buyers were not fully met, and transactions were delayed.

[0054] 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.

[0055] In this invention, the server includes a means for a user to input information, a means for the server to collect information, a means for the server to send prompts to the generative AI model, a means for the generative AI model to perform matching, and a means for the server to notify the matching results. This makes it possible to efficiently collect information on sellers and buyers and perform optimal matching using the generative AI model. Furthermore, it is possible to provide a system that ensures the fairness and transparency of transactions and is applicable to the sale and purchase of vacant houses in rural areas.

[0056] "Generative AI" is an artificial intelligence technology that generates data based on information provided by users and matches sellers and buyers.

[0057] A "consultant" is someone whose role is to provide advice and support to help smooth transactions between sellers and buyers.

[0058] "P2P" refers to a peer-to-peer network in which sellers and buyers transact directly.

[0059] "Transaction support" means functions and processes that support transactions between buyers and sellers.

[0060] "Means for determining whether a transaction is fair" refers to the functions and processes for evaluating whether a transaction between a seller and a buyer is being conducted fairly and properly.

[0061] "User information entry means" refers to the interface or method by which sellers and buyers enter their information into the system.

[0062] "Means by which the server collects information" refers to the functions and processes by which the server collects and stores information entered by users.

[0063] "Means by which the server sends prompts to the generative AI model" refers to the functions and processes by which the server sends instructions to the generative AI model based on the information collected by the server.

[0064] "Means by which the generative AI model performs matching" refers to the functions and processes by which the generative AI model matches the conditions of the seller and buyer and performs the optimal match.

[0065] "Means for the server to notify matching results" refers to the functions and processes for informing sellers and buyers of the matching results output by the generative AI model.

[0066] "Vacant house sales in rural areas" refers to transactions involving the buying and selling of vacant houses located in rural areas.

[0067] MODE FOR CARRYING OUT THE INVENTION

[0068] This invention relates to a home buying and selling platform system that uses generative AI to connect sellers and buyers via P2P. A specific embodiment of this system will be described below.

[0069] 1. Generate the system program

[0070] The server generates the program for the home buying and selling platform system. This program has the function of connecting sellers and buyers via P2P using a generative AI model. An example of the generative AI model used is GPT-4 (registered trademark) from OpenAI (registered trademark).

[0071] 2. Explain the program's processing in natural language

[0072] The server uses a generative AI model to collect information on sellers and buyers and perform optimal matching. Specifically, it performs the following processes:

[0073] Seller information gathering:

[0074] The server collects property details (e.g., location, layout, age, asking price, etc.) from sellers. This information is entered through a web form or a mobile app.

[0075] Buyer information gathering:

[0076] The server collects the buyer's desired property conditions (e.g., desired area, floor plan, budget, etc.) This information is also entered via a web form or mobile app.

[0077] Data processing and calculations:

[0078] The server inputs the collected information about sellers and buyers into a generative AI model, which then performs optimal matching based on the seller and buyer's conditions.

[0079] Matching result notification:

[0080] The server notifies the seller and buyer of the matching results output by the generative AI model via email or in-app notifications.

[0081] 3. Add concrete examples

[0082] For example, if a seller enters "a 3LDK apartment in Shibuya Ward, Tokyo, with a desired price of 50 million yen," and a buyer enters "a 3LDK apartment in Tokyo, with a budget of 60 million yen or less," the generative AI model will make the optimal match based on these conditions.

[0083] 4. Examples of prompts

[0084] "Seller's information: 3LDK apartment in Shibuya Ward, Tokyo, asking price: 50 million yen. Buyer's information: 3LDK apartment in Tokyo, budget: 60 million yen or less. Please use this information to find the best match."

[0085] In this way, the server utilizes generative AI models to provide a system that optimally matches buyers and sellers based on their requirements. This system ensures fairness and transparency in transactions and can also be applied to the sale of vacant houses in rural areas.

[0086] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0087] Step 1: User Enters Information

[0088] Users (sellers or buyers) enter information using the home buying and selling platform's web form or mobile app. Sellers enter detailed property information (location, floor plan, age, asking price, etc.), while buyers enter the desired property conditions (desired area, floor plan, budget, etc.). The entered information is sent to the server. Specifically, the user enters information in each field and clicks the "Submit" button.

[0089] Step 2: The server collects information

[0090] The server collects the information entered by the user in real time and stores it in a database. The server checks the format of the entered information and displays an error message to the user if there are any errors. Specifically, the server receives the input data and executes an SQL query to store it in the database.

[0091] Step 3: The server sends a prompt to the generative AI model

[0092] The server generates a prompt based on the collected seller and buyer information. For example, it generates a prompt like this: "Seller information: 3LDK apartment in Shibuya Ward, Tokyo, asking price 50 million yen. Buyer information: 3LDK apartment in Tokyo, budget within 60 million yen." The server sends this prompt as an API request to the generative AI model. Specifically, the server generates the prompt and sends an HTTP POST request to the API endpoint of the generative AI model.

[0093] Step 4: Generative AI model performs matching

[0094] The generative AI model compares the seller's and buyer's conditions based on the prompt text sent from the server and performs the optimal match. The model compares the seller's property information with the buyer's desired conditions and generates the most suitable match result. Specifically, the generative AI model analyzes the prompt text and evaluates the degree of match of the conditions using an internal algorithm.

[0095] Step 5: The server notifies the match result

[0096] The server notifies the seller and buyer of the matching results received from the generative AI model. Notifications are sent via email or in-app notifications. For example, a message may be sent saying, "We have found a buyer interested in your property. Please check the details." Specifically, the server receives the matching results and sends a notification to the user via an email server or push notification service.

[0097] In this way, the server, terminals, and users work together to ensure smooth operation of the home buying and selling platform system.

[0098] (Application example 1)

[0099] Next, a description will be given of Application Example 1 of Embodiment 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."

[0100] Conventional home buying and selling platforms were not efficient in matching sellers and buyers, and had the constraint of requiring buyers to visit the property in person. Furthermore, they were difficult to apply to the sale of vacant homes in rural areas. To solve these issues, a more efficient and flexible matching system and a property viewing function in virtual space were needed.

[0101] 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.

[0102] In this invention, the server includes a means for the generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for users to view properties in a virtual space, and a means for proposing optimal properties based on the user's desired conditions. This enables efficient matching between sellers and buyers, and allows users to view properties in a virtual space without visiting the site. It can also be applied to the sale and purchase of vacant houses in rural areas.

[0103] "Generative AI" is an artificial intelligence technology that makes optimal matches based on information about sellers and buyers.

[0104] A "consultant" is an expert or system that acts as a bridge between buyers and sellers.

[0105] "P2P" stands for peer-to-peer, a networking method that allows direct communication without going through a central server.

[0106] "Transaction support means" are functions and services that facilitate transactions between sellers and buyers.

[0107] "Means for determining whether a transaction is appropriate" refers to the function of evaluating whether the transaction is legally and ethically appropriate.

[0108] "Virtual space" is a virtual three-dimensional space generated using computer technology.

[0109] "Means to tour the property" refers to a function that allows users to visually check the interior and surroundings of the property in a virtual space.

[0110] "Desired conditions" are the requirements such as the property characteristics and budget that the user desires.

[0111] "Means to suggest the most suitable property" is a function that selects and suggests the most suitable property based on the user's desired conditions.

[0112] "Vacant house sales in rural areas" refers to the sale and purchase of vacant houses located in areas outside of urban areas.

[0113] The embodiments of the present invention will be described in detail below.

[0114] System configuration

[0115] This system is configured using the following hardware and software.

[0116] Hardware: Smartphone, Head-Mounted Display (HMD)

[0117] Software: Unity (virtual space creation), TENSORFLOW (registered trademark) (generative AI model implementation), Firebase (database)

[0118] Program processing

[0119] Data collection

[0120] The server stores property information from sellers (e.g., property details, desired price) in Firebase. It also stores desired conditions from buyers (e.g., desired property conditions, budget) in Firebase.

[0121] Training generative AI models

[0122] The server uses TensorFlow to train a generative AI model that matches buyers and sellers based on their information, and then suggests the best properties based on their needs.

[0123] Building a virtual space

[0124] The server uses Unity to create a 3D model of the property, allowing users to tour the property in a virtual space, which they access using their smartphone or HMD.

[0125] Matching and Proposals

[0126] When a user inputs their desired conditions, the server uses a generative AI model to suggest the most suitable property, which the user can then view in a virtual space.

[0127] Data processing and calculation

[0128] The server processes the data entered by the user in real time and performs data calculations to suggest the most suitable properties, allowing users to find properties efficiently.

[0129] Specific examples

[0130] Users open the smartphone app and input the desired property conditions (e.g., 3LDK, budget of less than 50 million yen, within 10 minutes' walk from the station). The server then suggests the most suitable property based on these conditions, and the user can view the property in a virtual space using an HMD.

[0131] Prompt Sentence Examples

[0132] Enter the desired property conditions. For example, 3 bedrooms, 3 bedrooms, 50 million yen or less, within a 10-minute walk from the station.

[0133] In this way, this invention realizes efficient matching between sellers and buyers, allows users to view properties in a virtual space without visiting the site, and can also be applied to the sale and purchase of vacant houses in rural areas.

[0134] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0135] Step 1:

[0136] The server collects property information from sellers (e.g., property details, asking price) and stores it in Firebase. The input is property information provided by sellers, and the output is data stored in Firebase. Specifically, the server receives the information entered by the seller and stores it in a database.

[0137] Step 2:

[0138] The server collects the buyer's desired conditions (e.g., desired property conditions, budget) and stores them in Firebase. The input is the desired conditions provided by the buyer, and the output is the data stored in Firebase. Specifically, the server receives the information entered by the buyer and stores it in a database.

[0139] Step 3:

[0140] The server uses TensorFlow to train a generative AI model that performs optimal matching based on information about sellers and buyers. The input is the seller and buyer data stored in Firebase, and the output is the trained generative AI model. Specifically, the server retrieves the data and trains the AI ​​model.

[0141] Step 4:

[0142] The server uses Unity to create a 3D model of the property, allowing users to view the property in a virtual space. The input is detailed information about the property, and the output is a 3D model placed in the virtual space. Specifically, the server generates a 3D model based on the property information and places it in the virtual space.

[0143] Step 5:

[0144] The user accesses the application using a smartphone or HMD and inputs their desired conditions. The input is the desired conditions entered by the user, and the output is the data sent to the server. In concrete terms, the user operates the application and inputs their desired conditions.

[0145] Step 6:

[0146] The server uses a generative AI model to propose the most suitable property based on the desired conditions entered by the user. The input is the user's desired conditions, and the output is the proposed property information. Specifically, the server inputs the desired conditions into the AI ​​model and selects the most suitable property.

[0147] Step 7:

[0148] The user visits the proposed property in a virtual space. The input is the proposed property information, and the output is the user's experience of visiting the property in the virtual space. Specifically, the user wears an HMD and visits the property in the virtual space.

[0149] Step 8:

[0150] The server collects user feedback and stores it in Firebase. The input is the user feedback and the output is the data stored in Firebase. Specifically, the server receives the feedback from the user and stores it in the database.

[0151] Example 2

[0152] Next, a description will be given of Example 2 of Form 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."

[0153] With conventional home buying and selling platform systems, transactions between sellers and buyers often did not proceed smoothly, with problems such as time-consuming document submission, signing, and payment procedures. It was also difficult to manage the transaction progress in real time, which led to issues such as a decrease in the transparency and efficiency of transactions.

[0154] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0155] In this invention, the server includes a means for connecting sellers and buyers via P2P with a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for managing the progress of the transaction, a means for instructing the submission and signature of necessary documents, a means for instructing payment procedures, and a means for notifying the completion of the transaction. This makes it possible to manage the progress of the transaction in real time and smoothly proceed with the necessary procedures.

[0156] "Generative AI" is a system that uses artificial intelligence technology to generate data and automatically perform specific tasks.

[0157] A "consultant" is someone with specialized knowledge who provides advice and support in a particular field.

[0158] "P2P" stands for peer-to-peer, a networking method in which individual devices communicate directly with each other without going through a central server.

[0159] A "transaction" is the act of buying and selling goods or services between a seller and a buyer.

[0160] "Progress" refers to the status of each step of the transaction.

[0161] "Documents" are documents such as contracts and certificates required for transactions.

[0162] A "signature" is the act of a party putting their name on a document to show their intention.

[0163] "Settlement" is the procedure for completing payment in a transaction.

[0164] "Notification" is a means of communication to inform interested parties of specific information.

[0165] This invention is a system that supports transactions between sellers and buyers, and uses a generative AI model to manage the progress of the transaction and issue instructions to ensure the smooth submission and signing of necessary documents and payment procedures. A specific embodiment of this system is shown below.

[0166] System configuration

[0167] server:

[0168] The server manages the progress of transactions using a generative AI model (e.g., OpenAI's GPT-4). The server has the following main functions:

[0169] Manage the progress of your transactions.

[0170] Instruct them to submit and sign the necessary documents.

[0171] Instruct the payment procedure.

[0172] Notify the completion of the transaction.

[0173] Device:

[0174] The terminal is a device used by the seller and buyer to input the information required for the transaction and communicate with the server. The terminal has the following functions:

[0175] Register product information.

[0176] Submit a purchase request.

[0177] Signing the contract.

[0178] Executing payment procedures.

[0179] User:

[0180] Users are sellers and buyers who conduct transactions through the system. Users perform the following operations:

[0181] Enter product information.

[0182] Submit a purchase request.

[0183] Signing the contract.

[0184] Executing payment procedures.

[0185] Program processing

[0186] server:

[0187] The server manages the progress of transactions using generative AI models. Specifically, the server performs the following processes:

[0188] Track each step of a transaction (e.g., contract creation, signing, payment).

[0189] Identify the next steps you need to take based on your progress.

[0190] Provide instructions to buyers and sellers regarding the submission and signing of necessary documents.

[0191] Instruct the payment procedure.

[0192] Notify the completion of the transaction.

[0193] Examples:

[0194] When a seller adds an item to a listing, the server stores the information in a database.

[0195] When a buyer purchases a product, the server automatically generates a contract using a generative AI model.

[0196] The server instructs the seller and buyer to sign the contract.

[0197] Once both parties have signed, the server will instruct the buyer to complete the payment process.

[0198] Once the payment is complete, the server sends a notification of the transaction completion to the seller and buyer.

[0199] Example prompt sentence:

[0200] "A new transaction has been initiated. Please generate a contract."

[0201] "Send notices to sellers and buyers for signature."

[0202] Please instruct the buyer to complete the payment process.

[0203] In this way, the server can utilize generative AI models to manage the progress of the transaction and smoothly carry out the necessary procedures.

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

[0205] Step 1:

[0206] Registering product information

[0207] User (seller): Enter information such as product name, price, and description, and click the "Register" button.

[0208] Input: Information such as product name, price, description, etc.

[0209] Server: Receives the product information and saves it in the database. Once saved, notifies the seller that the product information has been registered.

[0210] Output: The product information is saved in the database and a notification is sent to the seller.

[0211] Step 2:

[0212] Receiving a purchase request

[0213] User (Buyer): Select the product you want to purchase and click the "Purchase" button.

[0214] Input: Purchase request (item ID, buyer information).

[0215] Server: Receives the purchase request, updates the transaction status to "Purchase request received", and notifies the buyer that "Purchase request has been received".

[0216] Output: Transaction progress is updated and notification is sent to the buyer.

[0217] Step 3:

[0218] Generate Agreement

[0219] Server: Sends a prompt to the generative AI model saying, "A new transaction has been started. Please generate a contract."

[0220] Input: Prompt text "A new deal has been started. Please generate a contract."

[0221] Generative AI model: Generates the contract and sends it back to the server.

[0222] Server: Saves the generated contract in the database and notifies the seller and buyer that the contract has been generated.

[0223] Output: The generated contract is saved in the database and notifications are sent to the seller and buyer.

[0224] Step 4:

[0225] Requesting a contract signature

[0226] Server: Sends a notification to the seller and buyer saying "The contract has been generated and please sign."

[0227] Input: Agreement signature request notification.

[0228] Users (seller and buyer): Sign the contract and click the "Done Signing" button.

[0229] Server: Receives the signed contract and saves it in the database. Once saved, notifies the seller and buyer that the signature has been completed.

[0230] Output: The signed contract is saved in the database and notifications are sent to the seller and buyer.

[0231] Step 5:

[0232] Payment procedure instructions

[0233] Server: Sends a notification to the buyer saying, "The contract has been signed. Please proceed with payment."

[0234] Input: Payment procedure instruction notice.

[0235] User (Buyer): Complete the payment procedure and click the "Payment Complete" button.

[0236] Server: Confirms that the payment has been completed, updates the transaction status to "Payment Completed", and notifies the buyer that "Payment has been completed."

[0237] Output: Transaction progress is updated and notification is sent to the buyer.

[0238] Step 6:

[0239] Notification of transaction completion

[0240] Server: Sends a notification to the seller and buyer saying "The transaction is complete. Thank you."

[0241] Input: Transaction Completion Notification.

[0242] Output: A notification of the transaction completion is sent to the seller and buyer.

[0243] (Application example 2)

[0244] Next, a description will be given of Application Example 2 of Form 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."

[0245] Conventional home buying and selling platform systems did not provide sufficient support to ensure smooth transactions between sellers and buyers, and the process of managing the transaction progress, submitting necessary documents, electronic signatures, and payment procedures was cumbersome. Furthermore, it was not possible to provide appropriate instructions at each step of the transaction, reducing transaction efficiency. This led to problems such as transaction delays and issues, which reduced user satisfaction.

[0246] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0247] In this invention, the server includes means for the generative AI to act as a consultant and connect sellers and buyers via P2P, means for supporting transactions between sellers and buyers, means for determining whether the transaction is appropriate, means for managing the progress of the transaction in real time, means for automatically generating and submitting required documents, means for supporting electronic signatures, means for automating payment procedures, means for saving and searching transaction history, and means for the generative AI to give appropriate instructions at each step of the transaction. This makes it possible to manage the progress of the transaction in real time and smoothly proceed with the submission of required documents, electronic signatures, and payment procedures.

[0248] "Generative AI" is a system that uses artificial intelligence technology to generate data and automate specific tasks.

[0249] A "consultant" is a person or system with specialized knowledge who provides advice and assistance in a particular field.

[0250] "P2P" stands for peer-to-peer, a networking method in which data is exchanged directly between individual users without going through a central server.

[0251] A "transaction" is the act of buying and selling goods or services between a seller and a buyer.

[0252] "Progress" is the status that indicates the current stage of a transaction or project.

[0253] "Real-time" refers to processing or reaction occurring immediately, without delay.

[0254] "Documents" are documents such as contracts and certificates required for transactions.

[0255] "Automatic generation" refers to the system automatically creating the necessary data and documents without human intervention.

[0256] "Submission" is the act of sending the necessary documents and data to a designated location or system.

[0257] An "electronic signature" is a digital signature that is used to verify the authenticity of a document and the signer.

[0258] A "payment procedure" is a series of operations or processes required to complete payment in a transaction.

[0259] "Automation" refers to the system automatically carrying out processing without human intervention.

[0260] "Transaction history" is a record of past transactions.

[0261] "Storage" refers to storing data or information for later use.

[0262] "Search" is the act of finding a specific item from stored data or information.

[0263] "Instruction" refers to an order to perform a specific action or operation.

[0264] As an embodiment of the present invention, we will explain a smart transaction assistant system as an example. This system uses generative AI to assist transactions between sellers and buyers and manage the progress of transactions in real time.

[0265] System Configuration

[0266] The system uses the following hardware and software:

[0267] Hardware: Smartphone

[0268] Software: AI model library, payment gateway library

[0269] Program processing

[0270] The server performs the following processing using generative AI.

[0271] 1. Initiating a transaction: The server creates a new transaction, including the transaction ID, seller, and buyer information. The generator AI notifies the start of the transaction.

[0272] 2. Document submission: The server adds the submitted document to the transaction and notifies the next step (signature).

[0273] 3. Add Signature: The server adds a signature to the transaction and signals the next step (settlement).

[0274] 4. Process payment: The server processes the payment through the payment gateway and completes the transaction if successful.

[0275] 5. Get transaction status: The server returns the current status of the transaction.

[0276] 6. Get transaction history: The server returns the transaction history associated with the specified user.

[0277] Specific examples

[0278] For example, when a seller submits a contract, a buyer electronically signs it, and completes payment with a credit card, the following prompt sentence is generated:

[0279] "The transaction has been initiated. Please submit the necessary documents."

[0280] "The paperwork has been submitted. Now please sign."

[0281] "Signature complete. Please proceed to payment."

[0282] "Payment completed. Transaction complete."

[0283] Data processing and calculation

[0284] The server uses an AI model library to manage the transaction progress, automatically generate and submit required documents, support electronic signatures, and automate payment procedures. Transaction history is stored in a database and can be searched as needed.

[0285] In this way, the smart trading assistant system can automate each step of the transaction and provide appropriate instructions to the user, allowing the transaction to proceed smoothly.

[0286] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0287] Step 1:

[0288] The server initiates the transaction. When the user enters the information to initiate the transaction (transaction ID, seller and buyer information), the server creates a new transaction. The generative AI generates a prompt message notifying the user of the start of the transaction and sends it to the user.

[0289] Input: Transaction ID, Seller information, Buyer information

[0290] Output: Transaction start notification prompt text

[0291] Specific operation: The server creates a new transaction record in the database and uses generative AI to generate a prompt message saying, "The transaction has been initiated. Please submit the necessary documents." and sends it to the user.

[0292] Step 2:

[0293] The server accepts document submissions. When the user submits the required documents, the server adds them to the transaction. The generative AI generates a prompt message informing the user of the next step (signature) and sends it to the user.

[0294] Input: Submitted document

[0295] Output: Signature notification prompt text

[0296] Specific operation: The server saves the submitted document in a database and associates it with the transaction record. It then uses generative AI to generate a prompt message to the user: "The document has been submitted. Please sign next."

[0297] Step 3:

[0298] The server accepts the addition of a signature. When the user digitally signs, the server adds the signature to the transaction. The generative AI generates a prompt message informing the user of the next step (payment) and sends it to the user.

[0299] Input: Electronic Signature

[0300] Output: Payment notification prompt

[0301] Specific operation: The server stores the digital signature in a database and associates it with the transaction record. It then uses generative AI to generate a prompt message to the user: "Signature complete. Please proceed to payment."

[0302] Step 4:

[0303] The server processes the payment. When the user enters payment information, the server processes the payment through the payment gateway. If the payment is successful, the transaction is completed. The generative AI generates a prompt message notifying the user that the transaction is complete and sends it to the user.

[0304] Input: Payment information

[0305] Output: Transaction completion notification prompt

[0306] Specific operation: The server sends payment information to the payment gateway and receives the payment result. If the payment is successful, it updates the transaction record status to "Completed." It uses generative AI to generate a prompt message saying "Payment completed. Transaction completed." and sends it to the user.

[0307] Step 5:

[0308] The server gets the status of the transaction. When a user wants to check the status of a transaction, the server takes the transaction ID as input and returns the current transaction status.

[0309] Input: Transaction ID

[0310] Output: Current transaction status

[0311] Specific operation: The server searches the database for the transaction record corresponding to the transaction ID and returns its status to the user.

[0312] Step 6:

[0313] The server retrieves the transaction history. When a user wants to check the transaction history, the server takes the user information as input and returns the relevant transaction history.

[0314] Input: User information

[0315] Output: Transaction history

[0316] Specific operation: The server searches the database for transaction records related to the user information and returns the history to the user.

[0317] Example 3

[0318] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0319] Conventional housing buying and selling platform systems lacked objective standards for determining the appropriateness of transactions, which increased the likelihood of improper transactions occurring between sellers and buyers. Furthermore, when it came to the sale of vacant homes in rural areas, there was insufficient information gathering and promotion of fair transactions. This made it difficult for users to make transactions with confidence, and also hindered the promotion of relocation to rural areas.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0321] In this invention, the server includes a means for collecting data such as property prices and transaction terms from a database, a means for analyzing the collected data using a generative AI model to evaluate the appropriateness of the transaction, and a means for notifying both the seller and the buyer of any inappropriate transaction. This makes it possible to objectively evaluate the appropriateness of the transaction and prevent inappropriate transactions. It also allows users to trade with peace of mind, contributing to the sale of vacant houses in rural areas and promoting relocation.

[0322] A "database" is an information accumulation system that stores data such as property prices and transaction terms, and can be searched and retrieved as needed.

[0323] A "generative AI model" is an algorithm or program that uses artificial intelligence techniques to analyze data and generate results for a specific purpose.

[0324] "Fairness of transaction" is a standard for evaluating whether the price and transaction conditions of a property are reasonable based on market rates and laws and regulations.

[0325] "Notification" is a means of communication to convey evaluation results and advice regarding the appropriateness of a transaction to sellers and buyers.

[0326] An "interface" is an operation screen or input device that allows a user to access the system, input data, and check the results.

[0327] "Guidance" refers to instructions and advice that provide users with the information and advice they need to conduct proper transactions.

[0328] "Matching" is the process of finding the best trading partner based on the needs of the seller and buyer.

[0329] "Vacant house sales in rural areas" refers to transactions involving the buying and selling of unused residential properties in rural areas.

[0330] MODE FOR CARRYING OUT THE INVENTION

[0331] This invention relates to a home buying and selling platform system, and in particular to a system that uses a generative AI model to evaluate the appropriateness of a transaction and promote appropriate transactions between sellers and buyers.

[0332] Server Roles

[0333] The server first collects data such as property prices and transaction terms from a database. Databases used include MySQL (registered trademark) and PostgreSQL. The server executes SQL queries to obtain the required data.

[0334] Next, the server analyzes the collected data using a generative AI model (e.g., OpenAI GPT-4). This analysis includes evaluating whether the property price is fair compared to the market price and whether the transaction terms violate laws and regulations. Specifically, the server inputs the following prompts into the generative AI model:

[0335] "Is the price of this property fair compared to the market price? Please also check whether it violates any laws or regulations."

[0336] Based on the analysis, the server generates a notification about the invalid transaction, which includes the reason why the transaction is invalid and advice on how to make the transaction valid. The notification is sent to both the seller and the buyer via an email server (e.g., SendGrid, Amazon SES).

[0337] Device Role

[0338] The terminal provides an interface for users to access. Users can enter property information and transaction terms through the terminal. The terminal displays forms and input fields for users to enter data.

[0339] The data entered by the user is sent to the server using an HTTP request. The terminal that receives the notification from the server displays the notification to the user and provides guidance for conducting a proper transaction. Specifically, the following guidance is displayed:

[0340] "The price of this property is higher than the market price. The appropriate price is XX yen."

[0341] User Roles

[0342] The user uses the terminal to input property information and transaction terms. Specifically, the user enters the property price, location, transaction terms, etc. into a form. After checking the entered data, the user clicks the send button to send it to the server.

[0343] The user who receives the notification from the server checks the contents of the notification and reviews the terms of the transaction. For example, the user may correct the property price to an appropriate price based on the notification and send the result back to the server.

[0344] Specific examples

[0345] For example, if a user wants to purchase a vacant house in a rural area, they input the property price and terms of the transaction into their device. The server then uses a generative AI model to analyze this data and assess suitability based on market rates and regulations. The server uses prompts like the following:

[0346] "Is the price of this property fair compared to the market price? Please also check whether it violates any laws or regulations."

[0347] If the property is priced above market value, the server will notify you and offer a fair price. The notification will look like this:

[0348] "The price of this property is higher than the market price. The appropriate price is XX yen."

[0349] In this way, users can obtain information for conducting fair transactions. This can also contribute to the sale and purchase of vacant houses in rural areas and the promotion of relocation. The flow of the identification process in the third embodiment will be described with reference to FIG. 15.

[0350] Program processing flow

[0351] Step 1: Data collection

[0352] Subject: Server

[0353] The server collects data such as property prices and transaction terms from the database by executing SQL queries to retrieve the required data.

[0354] Input: Database connection information, SQL query

[0355] Output: A dataset of property prices and transaction terms

[0356] Specific operation: The server executes an SQL query such as "SELECT FROM properties WHERE status='available'" and obtains the results as a dataset.

[0357] Step 2: Data analysis

[0358] Subject: Server

[0359] The server inputs the collected data into a generative AI model for analysis, which evaluates whether the property price is fair compared to the market price and whether the transaction terms violate laws and regulations.

[0360] Input: Data set of property prices and transaction terms, prompt text

[0361] Output: Adequacy evaluation results

[0362] Specific operation: The server inputs a prompt statement to the generated AI model: "Is the price of this property appropriate compared to the market price? Please also check whether it violates any laws and regulations." and obtains the appropriateness evaluation result.

[0363] Step 3: Generate notifications

[0364] Subject: Server

[0365] The server generates a notification based on the analysis, including the reason why the transaction is not appropriate and advice on how to make the transaction appropriate.

[0366] Input: Appropriateness assessment results

[0367] Output: Notification message

[0368] Specific operation: The server generates a notification message saying, "The price of this property is higher than the market price. The appropriate price is XX yen."

[0369] Step 4: Send notification

[0370] Subject: Server

[0371] The server generates and sends notifications to both the seller and the buyer.

[0372] Input: Notification message, seller and buyer contact information

[0373] Output: Transmission result

[0374] Specific operation: The server uses the mail server to send the notification message and record the sending result.

[0375] Step 5: Data entry

[0376] Subject: Terminal

[0377] The terminal provides an interface for the user to input property information and transaction conditions.

[0378] Input: User input data (property information, transaction conditions)

[0379] Output: Input data confirmation screen

[0380] What it does: The device displays forms and input fields, allowing the user to enter data.

[0381] Step 6: Send data

[0382] Subject: Terminal

[0383] The terminal transmits the data entered by the user to the server.

[0384] Input: User-entered data

[0385] Output: Transmission result

[0386] Specific operation: The terminal uses an HTTP request to send data to the server and displays the transmission result.

[0387] Step 7: Receive notifications

[0388] Subject: Terminal

[0389] The terminal receives the notification from the server.

[0390] Input: Notification message from the server

[0391] Output: Notification display screen

[0392] Specific behavior: The device receives emails and in-app notifications and displays them to the user.

[0393] Step 8: Provide guidance

[0394] Subject: Terminal

[0395] The terminal provides guidance to the user based on the received notification.

[0396] Input: Notification message

[0397] Output: Guidance display screen

[0398] Specific operation: The device displays the guidance, "The price of this property is higher than the market price. The appropriate price is XX yen."

[0399] Step 9: Enter property information

[0400] Subject: User

[0401] The user uses the terminal to input property information and transaction conditions.

[0402] Input: Property information, transaction terms

[0403] Output: Input data

[0404] Specific operation: The user enters the property price, location, terms of transaction, etc. into the form.

[0405] Step 10: Confirm data transmission

[0406] Subject: User

[0407] The user checks the entered data and sends it to the server.

[0408] Input: Input data

[0409] Output: Transmission result

[0410] Specific Action: The user clicks the submit button to submit the data.

[0411] Step 11: Check notifications

[0412] Subject: User

[0413] The user checks the notification from the server.

[0414] Input: Notification message

[0415] Output: Understanding the notification content

[0416] What happens: The user opens an email or in-app notification and checks the content.

[0417] Step 12: Review the terms of the transaction

[0418] Subject: User

[0419] The user reviews the terms of the transaction based on the notification.

[0420] Input: Notification message, terms and conditions

[0421] Output: Modified trading conditions

[0422] Specific operation: The user corrects the price and conditions to the appropriate one and sends it back to the server.

[0423] (Application example 3)

[0424] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0425] Conventional housing sales platform systems lacked sufficient means to determine whether a transaction between a seller and a buyer was appropriate, making it difficult to aggregate and provide information, especially for the sale of vacant homes in rural areas. Furthermore, users had limited means to check property details and obtain information about living in rural areas, making it difficult to promote relocation to rural areas.

[0426] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0427] In this invention, the server includes a means for a generative AI to act as a consultant, connecting sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether a transaction is appropriate, a means for aggregating vacant house information and providing it to users, a means for providing virtual tours, a means for providing lifestyle information, and an AI chatbot means for providing information in response to user questions. This makes it possible to smoothly sell and buy vacant houses in rural areas while ensuring the appropriateness of transactions. Furthermore, users can more specifically consider moving to rural areas through virtual tours and lifestyle information.

[0428] "Generative AI" refers to artificial intelligence that generates new information and content based on data.

[0429] A "consultant" is a professional who has specialized knowledge and provides advice and guidance in a particular field.

[0430] "P2P" stands for peer-to-peer, a networking method in which individual devices communicate directly without going through a central server.

[0431] A "transaction" is the act of exchanging goods or services between a seller and a buyer.

[0432] "Fair" means that it is justifiable based on laws and regulations and market prices.

[0433] "Vacant house information" refers to information about houses that are not currently in use.

[0434] "Aggregation" means combining multiple pieces of information into one.

[0435] "User" means a person who uses the system or service.

[0436] A "virtual tour" is a service that allows you to virtually tour a property or location using computer technology.

[0437] "Lifestyle information" refers to information necessary for daily life (e.g., transportation, medical care, education, etc.).

[0438] An "AI chatbot" is a program that uses artificial intelligence to interact with users.

[0439] A system for carrying out this invention is configured as follows: The server includes means for connecting sellers and buyers via P2P using generative AI, means for supporting transactions between sellers and buyers, means for determining whether a transaction is appropriate, means for aggregating vacant house information and providing it to users, means for providing virtual tours, means for providing lifestyle information, and AI chatbot means for providing information in response to user questions.

[0440] Program processing explanation

[0441] 1. Collection and provision of vacant house information

[0442] The server aggregates information on vacant houses in local areas by retrieving information from external databases and APIs, allowing users to easily view information on vacant houses in local areas through their smartphones or head-mounted displays (HMDs).

[0443] 2. Providing virtual tours

[0444] The server generates 3D models and 360-degree views based on the acquired vacant property information and provides users with a virtual tour, allowing them to check the property details without actually visiting the property.

[0445] 3. Transaction Appropriateness Assessment

[0446] The server uses generative AI to analyze the property price and transaction conditions, and evaluates the appropriateness of the transaction based on market prices and laws and regulations. If it is determined to be inappropriate, it notifies both the seller and the buyer and encourages them to conduct a fair transaction.

[0447] 4. Providing information on daily life

[0448] The server retrieves information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.) from external databases and APIs and provides it to users, allowing them to specifically consider moving to rural areas.

[0449] 5. AI Chatbots

[0450] The server is equipped with an AI chatbot that provides information in response to user questions. When users input their questions in natural language, the chatbot provides the appropriate information.

[0451] Hardware and software used

[0452] Hardware: Server, smartphone, head-mounted display (HMD)

[0453] Software: Generative AI models, databases, APIs, chatbot platforms

[0454] Specific examples

[0455] For example, if a user is looking for a vacant house in a rural area, they can use a smartphone app to search for property information and take a virtual tour. The app evaluates the suitability of the transaction and displays a notification if it is not suitable. It also provides information about daily life in the rural area (e.g., the nearest hospitals and schools, transportation access, etc.).

[0456] Prompt Sentence Examples

[0457] "I'm looking for a vacant house in a rural area. Please rate whether the transaction for property ID 123 is appropriate. Also, please let me know about living information in the area."

[0458] In this way, users can enter questions in natural language and the AI ​​chatbot will respond and provide information.

[0459] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0460] Step 1:

[0461] The server retrieves local vacant house information from external databases and APIs. The region is specified as input, and a list of vacant house information is obtained as output. Specifically, the server sends an API request and stores the retrieved data in an internal database.

[0462] Step 2:

[0463] The server generates 3D models and 360-degree views based on the acquired vacant property information. The input is the vacant property information, and the output is the data for the virtual tour. Specifically, the server uses 3D modeling software to create a virtual model of the property, which users can access.

[0464] Step 3:

[0465] Users can take virtual tours using a smartphone or a head-mounted display (HMD). The input is the data for the virtual tour, and the output is a visual experience for the user. Specifically, the user launches the application and checks the property details.

[0466] Step 4:

[0467] The server uses generative AI to analyze the property price and transaction terms, and evaluates the appropriateness of the transaction based on market prices and laws and regulations. The property price and transaction terms are input, and the appropriateness evaluation result is obtained as output. Specifically, the server inputs the data into the AI ​​model and calculates the evaluation result.

[0468] Step 5:

[0469] If the server determines that the transaction is invalid, it notifies both the seller and the buyer. The input is the validity evaluation result, and the output is a notification message. Specifically, the server sends a message through the notification system.

[0470] Step 6:

[0471] The server retrieves information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.) from external databases and APIs and provides it to users. The region is specified as input, and lifestyle information is obtained as output. Specifically, the server sends an API request and displays the retrieved data to the user.

[0472] Step 7:

[0473] Users check lifestyle information using smartphones or head-mounted displays (HMDs). The lifestyle information is the input, and the user's understanding is the output. Specifically, users view the information through an application.

[0474] Step 8:

[0475] The server is equipped with an AI chatbot that provides information in response to user questions. The input is the user's question, and the output is an answer. Specifically, the server uses the chatbot platform to analyze the question and generate an appropriate answer.

[0476] Step 9:

[0477] Users input questions to an AI chatbot using a smartphone or head-mounted display (HMD). The input is the user's question, and the output is the chatbot's answer. Specifically, the user inputs a question through the application and receives an answer.

[0478] 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.

[0479] "Example 1"

[0480] One embodiment of the present invention is a home buying and selling platform system in which generative AI uses an emotion engine to recognize the emotions of sellers and buyers. This emotion engine analyzes emotions from the text and voice information entered into the system by the seller and buyer. For example, if a seller enters text such as "This house is full of memories, so I want to sell it to someone who will cherish it," the emotion engine will recognize the seller's "attachment" and "expectations." "Example 2"

[0481] It also includes a means to optimize matching based on the emotions of sellers and buyers using an emotion engine. Specifically, it recognizes the seller's "feelings" and "expectations" and then searches for a buyer who meets those expectations. For example, if a buyer enters text such as "I like old houses and would like to carefully renovate them and live in them," it will match that buyer with the aforementioned seller.

[0482] "Example 3"

[0483] Furthermore, it also includes a means of using an emotion engine to manage the progress of a transaction based on the emotions of the seller and buyer. Specifically, it recognizes the emotions of the seller and buyer at each step of the transaction and manages the progress of the transaction accordingly. For example, if a buyer enters text such as "I'm worried because the contract is moving too quickly," it will recognize that emotion and take measures such as temporarily delaying the progress of the transaction.

[0484] The processing flow of each embodiment will be described below.

[0485] "Example 1"

[0486] Step 1: The seller enters their property information into the system along with their sentiment as text or voice information.

[0487] Step 2: The generative AI uses an emotion engine to analyze the seller's emotions from the input information.

[0488] Step 3: Save the analysis results in a database.

[0489] "Example 2"

[0490] Step 1: The buyer enters the property information they are looking for into the system along with their feelings as text or voice information.

[0491] Step 2: The generative AI uses an emotion engine to analyze the buyer's emotions from the input information.

[0492] Step 3: Compare the analysis results with the seller sentiment stored in the database to find matching sellers.

[0493] Step 4: Notify the seller and buyer of the matching results.

[0494] "Example 3"

[0495] Step 1: The seller and buyer initiate a transaction.

[0496] Step 2: At each step of the transaction, the seller and buyer input their emotions as text or voice information.

[0497] Step 3: The generative AI uses an emotion engine to analyze the emotions of the seller and buyer from the input information.

[0498] Step 4: Manage the progress of the transaction based on the analysis results.

[0499] Example 1

[0500] Next, a description will be given of Example 1 of Form 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."

[0501] Conventional housing sales platforms have difficulty matching buyers and sellers while taking into full consideration the needs and feelings of the buyers and sellers, resulting in problems such as poor transaction accuracy and low satisfaction. Furthermore, there have been issues with transactions not progressing due to a lack of appropriate matching, even in the case of vacant houses in rural areas.

[0502] 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.

[0503] In this invention, the server includes a means for connecting sellers and buyers via P2P using a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for collecting information on sellers and buyers, a means for analyzing the emotions of sellers and buyers using an emotion engine, a means for optimally matching sellers and buyers based on their conditions and emotions using generative AI, and a means for notifying the sellers and buyers of the matching results. This enables optimal matching that takes into account the needs and emotions of sellers and buyers, improving the appropriateness and satisfaction of transactions. It can also be applied to the sale and purchase of vacant homes in rural areas, which is expected to promote transactions.

[0504] "Generative AI" is artificial intelligence that makes optimal matches based on information about sellers and buyers.

[0505] A "consultant" is an expert who acts as a P2P link between sellers and buyers.

[0506] "Transaction aids" are methods and tools used to facilitate transactions between buyers and sellers.

[0507] "Means for determining whether a transaction is fair" refers to methods or tools for evaluating whether the content of a transaction is fair and fair.

[0508] "Information gathering means" are the methods and tools used to gather the necessary data from sellers and buyers.

[0509] An "emotion engine" is a technology that analyzes emotions from text and voice information entered by sellers and buyers.

[0510] "Matching means" are methods or tools that suggest optimal combinations based on the conditions and feelings of the seller and buyer.

[0511] "Means for notifying matching results" refers to methods or tools for informing sellers and buyers of the matching results proposed by generative AI.

[0512] "Vacant house sales in rural areas" refers to transactions involving the sale and purchase of vacant houses located in rural areas.

[0513] MODE FOR CARRYING OUT THE INVENTION

[0514] This invention relates to a home buying and selling platform system that connects sellers and buyers via P2P using generative AI and an emotion engine. A specific embodiment of this system will be described below.

[0515] System configuration

[0516] This system consists of three main elements: a server, a terminal, and a user. The server is equipped with a generative AI and an emotion engine, and is responsible for collecting, analyzing, and matching information between sellers and buyers. The terminal is a device through which sellers and buyers input information and receive matching results. The user is an individual or corporation that plays the role of a seller or buyer.

[0517] Program processing

[0518] The server first collects the information entered by the user. Sellers enter detailed property information and asking prices, while buyers enter the conditions and budget for the property they are looking for. This information is collected through a dedicated web form or mobile application.

[0519] Next, the server uses an emotion engine to analyze emotions from the text and voice information entered by the user. The emotion engine extracts emotions using natural language processing technology. For example, if a seller enters text such as, "This house is full of memories, so I want to sell it to someone who will cherish it," the emotion engine will recognize the seller's "attachment" and "expectations."

[0520] The server then uses generative AI to perform optimal matching based on the collected information and the results of sentiment analysis. The generative AI considers the conditions and emotions of the seller and buyer to propose the optimal combination of property and buyer. This proposal is then sent to the seller and buyer's devices.

[0521] Specific examples

[0522] For example, if a seller enters the following information:

[0523] Property details: 3LDK, 10-year-old building, 10-minute walk from the station

[0524] Asking price: 30 million yen

[0525] Emotional information: "This house is full of memories, so I want to sell it to someone who will cherish it."

[0526] On the other hand, suppose the buyer enters the following information:

[0527] Desired property conditions: 3LDK, within 15 minutes' walk from the station

[0528] Budget: 35 million yen

[0529] Emotional information: "I'm looking for a home where my family can live for a long time."

[0530] The server collects this information and analyzes it using an emotion engine to make the best match, taking into account the seller's "attachment" and the buyer's feelings of "looking for a home where the family can live for a long time."

[0531] Example prompts to input to the generative AI model:

[0532] Seller Information:

[0533] Property details: 3LDK, 10-year-old building, 10-minute walk from the station

[0534] Asking price: 30 million yen

[0535] Emotional information: "This house is full of memories, so I want to sell it to someone who will cherish it."

[0536] Buyer Information:

[0537] Desired property conditions: 3LDK, within 15 minutes' walk from the station

[0538] Budget: 35 million yen

[0539] Emotional information: "I'm looking for a home where my family can live for a long time."

[0540] Based on this information, we will propose the best match for you.

[0541] In this way, optimal matching that takes into account the needs and feelings of the seller and buyer becomes possible, improving the fairness and satisfaction of the transaction. It can also be applied to the sale of vacant houses in rural areas, and is expected to promote transactions.

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

[0543] Step 1:

[0544] The user enters information

[0545] Users (sellers and buyers) enter the necessary information using a dedicated web form or mobile application. Sellers enter detailed property information and desired price, while buyers enter the desired property conditions and budget. Users also enter emotional information.

[0546] Input: Seller's property information, asking price, sentiment information, buyer's desired conditions, budget, sentiment information

[0547] Output: The entered information is sent to the server

[0548] Specific behavior:

[0549] The seller enters the following information into a web form: "3LDK, 10-year-old building, 10-minute walk from the station, asking price 30 million yen."

[0550] A buyer enters the following into the mobile app: "3LDK, within 15 minutes' walk from the station, budget 35 million yen."

[0551] Step 2:

[0552] The server collects information

[0553] The server collects the information entered by the user and stores it in a database.

[0554] Input: Information entered by the user

[0555] Output: Information stored in the database

[0556] Specific behavior:

[0557] The server stores the seller's input information in a database.

[0558] The server stores the buyer's input information in a database.

[0559] Step 3:

[0560] The server analyzes emotions using an emotion engine

[0561] The server uses an emotion engine to analyze emotions from text and voice information entered by the user. The emotion engine extracts emotions using natural language processing technology.

[0562] Input: User text and voice information stored in a database

[0563] Output: Parsed emotion information

[0564] Specific behavior:

[0565] The server analyzes the seller's text, such as "This house is full of memories, so I would like to sell it to someone who will cherish it," and extracts the seller's "attachment" and "expectations."

[0566] The server analyzes the buyer's text, "I'm looking for a home where my family can live for a long time," and extracts "security" and "expectations."

[0567] Step 4:

[0568] The server performs matching using generative AI

[0569] The server uses generative AI to perform optimal matching based on the collected information and the results of sentiment analysis. The generative AI considers the conditions and emotions of both the seller and buyer to propose the best combination of property and buyer.

[0570] Input: Information stored in the database, analyzed emotional information

[0571] Output: Best matching result

[0572] Specific behavior:

[0573] The server inputs the seller's property information and emotional information into the generative AI.

[0574] The server inputs the buyer's desired conditions and emotional information into the generative AI.

[0575] The generative AI calculates the optimal match and returns the results to the server.

[0576] Step 5:

[0577] The server notifies the match result

[0578] The server notifies the seller and buyer of the matching results obtained from the generative AI via email or in-app notifications.

[0579] Input: Best match result

[0580] Output: Matching results notified to sellers and buyers

[0581] Specific behavior:

[0582] The server notifies the seller that "we have found a buyer interested in your property."

[0583] The server notifies the buyer that "We have found a property that meets your requirements."

[0584] Step 6:

[0585] The user checks the matching results

[0586] Users receive notifications from the server and check the matching results. Sellers and buyers can then communicate within the system to negotiate in detail.

[0587] Input: Notification from the server

[0588] Output: Confirmed match results, contact information

[0589] Specific behavior:

[0590] The seller opens the in-app notification to check the match results.

[0591] The buyer opens the email and checks the matching results.

[0592] (Application example 1)

[0593] Next, a description will be given of Application Example 1 of Embodiment 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."

[0594] Conventional home buying and selling platform systems do not take into account the emotions of buyers and sellers when matching, which can result in low transaction satisfaction. Furthermore, real-time notification of matching results and improvements to matching accuracy based on feedback are not sufficiently implemented, resulting in issues with transaction efficiency and accuracy.

[0595] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for connecting sellers and buyers via P2P using a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a sentiment analysis means for analyzing the sentiments of the seller and buyer, a means for optimal matching based on information about the seller and buyer, a means for notifying the matching results in real time, and a means for collecting feedback from the seller and buyer and improving matching accuracy. This enables optimal matching that takes into account the sentiments of the seller and buyer, thereby improving transaction satisfaction and efficiency.

[0596] "Generative AI" is artificial intelligence that makes optimal matches based on information about sellers and buyers.

[0597] A "consultant" is an expert who acts as a P2P link between sellers and buyers.

[0598] "P2P" refers to a peer-to-peer network structure in which sellers and buyers transact directly.

[0599] "Transaction support means" are support functions that facilitate transactions between sellers and buyers.

[0600] "Means for determining whether a transaction is appropriate" refers to a function that evaluates whether the transaction content is fair and appropriate.

[0601] "Sentiment analysis means" is a technology for analyzing the emotions of sellers and buyers.

[0602] "Matching means" is a function that finds the most suitable trading partner based on information about the seller and buyer.

[0603] "Real-time notification means" is a function that instantly notifies sellers and buyers of matching results.

[0604] "Feedback collection means" is a function that collects opinions and ratings from sellers and buyers.

[0605] "Means for improving matching accuracy" refers to a function that improves matching accuracy based on collected feedback.

[0606] As an embodiment of this invention, we provide a system in which an emotion-aware real estate matching application is installed on a smartphone or smart glasses. This system uses generative AI and an emotion analysis engine to analyze the emotions of sellers and buyers and perform optimal matching.

[0607] System configuration

[0608] 1. Hardware:

[0609] Smartphone or smart glasses

[0610] server

[0611] 2. Software:

[0612] Generative AI models (e.g., OpenAI API)

[0613] Sentiment analysis engines (e.g., TextBlob library)

[0614] Matching Algorithm

[0615] Real-time notification system

[0616] Processing flow

[0617] Emotion analysis

[0618] Users enter text or voice information into the system as sellers or buyers. The server uses a sentiment analysis engine to analyze emotions from this information. For example, if a seller enters, "This house is full of memories, so I want to sell it to someone who will cherish it," the sentiment analysis engine will recognize emotions such as "attachment" and "expectations."

[0619] matching

[0620] The server uses a generative AI model to find the best match based on the seller and buyer information. The generative AI model matches based on prompts like the following:

[0621] Seller information: This house is full of memories and I would like to sell it to someone who will cherish it.

[0622] Buyer Information: I am looking for a quiet home where I can spend time with my family.

[0623] Make the best match.

[0624] Real-time notifications

[0625] Matching results are notified to users in real time, allowing them to instantly check the progress of their transactions.

[0626] Gathering feedback and improving accuracy

[0627] After a transaction is completed, the server collects feedback from the seller and buyer, which is used to improve the accuracy of the matching algorithm.

[0628] Specific examples

[0629] For example, if a seller enters, "This house is full of memories, so I want to sell it to someone who will cherish it," and a buyer enters, "I'm looking for a house in a quiet environment where I can spend time with my family," the generative AI model will use this information to find the optimal match. The sentiment analysis engine will analyze the seller's emotions, such as "attachment" and "expectations," and provide matching results that take these into consideration.

[0630] In this way, optimal matching that takes into account the emotions of sellers and buyers becomes possible, improving transaction satisfaction and efficiency.

[0631] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0632] Step 1:

[0633] Users input text or voice information into the system as sellers or buyers. For sellers, the input information is detailed property information and desired price, and for buyers, the desired property conditions and budget. This information is sent from the terminal to the server.

[0634] Step 2:

[0635] The server uses a sentiment analysis engine (e.g., TextBlob library) to analyze emotions from input text and voice information. For example, if a seller inputs, "This house is full of memories, so I want to sell it to someone who will cherish it," the sentiment analysis engine will recognize emotions such as "attachment" and "expectations." The input is text information, and the output is the result of the sentiment analysis.

[0636] Step 3:

[0637] The server generates a prompt based on the seller and buyer information. The generated prompt is passed to the generative AI model. For example, the following prompt is generated:

[0638] Seller information: This house is full of memories and I would like to sell it to someone who will cherish it.

[0639] Buyer Information: I am looking for a quiet home where I can spend time with my family.

[0640] Make the best match.

[0641] The input is the seller and buyer information, and the output is a prompt statement.

[0642] Step 4:

[0643] The server uses a generative AI model (e.g., OpenAI API) to find the best match based on the prompt. The generative AI model analyzes the seller and buyer information to find the best trading partner. The input is the prompt, and the output is the matching result.

[0644] Step 5:

[0645] The server notifies the user of the matching results in real time. The notification is sent to the terminal, allowing the user to immediately check the progress of the transaction. The input is the matching result, and the output is the real-time notification.

[0646] Step 6:

[0647] After the transaction is completed, the server collects feedback from the seller and the buyer. The feedback is information such as the satisfaction level of the transaction and areas for improvement. The input is the feedback from the user, and the output is the collected feedback data.

[0648] Step 7:

[0649] The server improves the accuracy of the matching algorithm based on the collected feedback. By analyzing the feedback data and incorporating it into the next match, more accurate matching becomes possible. The input is the feedback data, and the output is an improved matching algorithm.

[0650] Example 2

[0651] Next, a description will be given of Example 2 of Form 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."

[0652] Conventional home buying and selling platform systems often failed to match buyers and sellers with due consideration for their feelings and needs, resulting in transactions not progressing smoothly. Furthermore, the procedures for submitting necessary documents, signing, and making payments were cumbersome, placing a heavy burden on users. Furthermore, there was a lack of systems that could be applied to the sale of vacant homes in rural areas.

[0653] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0654] In this invention, the server includes a means for the generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for optimizing matching based on the emotions of the seller and buyer using an emotion engine, and a means for the generative AI to manage the progress of the transaction and issue instructions to smoothly proceed with procedures such as the submission and signing of necessary documents and payment. This enables optimal matching that takes into account the emotions and needs of the seller and buyer, and ensures smooth progress of the transaction. It also simplifies the necessary procedures and reduces the burden on users. Furthermore, a system that can be applied to the sale and purchase of vacant houses in rural areas is provided.

[0655] "Generative AI" is an artificial intelligence that acts as a consultant between sellers and buyers and manages the progress of transactions.

[0656] "P2P" is a peer-to-peer communication method in which sellers and buyers transact directly.

[0657] "Transaction support tools" are functions and processes that facilitate transactions between buyers and sellers.

[0658] "Means for determining whether a transaction is appropriate" refers to the function of evaluating whether the transaction is legally and ethically appropriate.

[0659] The "emotion engine" is a technology that analyzes the emotions of sellers and buyers and makes optimal matches based on that.

[0660] "Means for optimizing matching" is a function that takes into account the emotions and needs of sellers and buyers to find the best trading partner.

[0661] "Means for managing the progress of a transaction" refers to a function that monitors each step of a transaction and instructs the necessary procedures.

[0662] "Means for issuing instructions to smoothly proceed with procedures such as document submission, signatures, and payment" refers to a function that instructs the user to submit documents required for the transaction, obtain signatures, and complete payment procedures.

[0663] "Vacant house sales in rural areas" refers to transactions involving the sale and purchase of vacant houses located in rural areas.

[0664] MODE FOR CARRYING OUT THE INVENTION

[0665] This invention is a system that supports transactions between sellers and buyers, and uses generative AI and an emotion engine to manage the progress of transactions and optimize matching based on emotions. Specific embodiments of this system are described below.

[0666] System configuration

[0667] This system consists of three main components: a server, a terminal, and a user. The server is equipped with a generative AI and an emotion engine, and manages the progress of transactions and performs matching based on emotions. The terminal is a device that allows users to access the system and input the necessary information. Users act as sellers and buyers and conduct transactions.

[0668] Hardware and software used

[0669] Server: A server with a high-performance processor and large memory capacity is required. Specifically, a server with an Intel Xeon processor or AMD EPYC processor is suitable.

[0670] Generative AI: Built using deep learning frameworks such as TensorFlow and PyTorch.

[0671] Emotion engine: An emotion analysis engine that uses natural language processing (NLP) technology, specifically models such as BERT and GPT-3 (registered trademark).

[0672] Terminal: The device through which the user accesses the service, including PCs, smartphones, tablets, etc.

[0673] System Operation

[0674] The server manages the progress of the transaction using generative AI. Specifically, it performs the following steps:

[0675] Submitting required documents

[0676] Get signatures

[0677] Payment procedure

[0678] To ensure that these procedures go smoothly, the server issues instructions to users (sellers and buyers). For example, when a deadline for submitting documents approaches, the server sends reminders to users.

[0679] The server also uses an emotion engine to match buyers and sellers based on their emotions. Specifically, it recognizes the seller's "feelings" and "expectations" and searches for buyers who match those. For example, if a buyer enters text such as "I like old houses and would like to carefully renovate them and live in them," the server will match that buyer with the aforementioned seller.

[0680] Specific examples

[0681] As a concrete example, consider the following scenario:

[0682] Seller A thinks, "This house is full of family memories, so I want to sell it to someone who will cherish it."

[0683] Buyer B thinks, "I like old houses and would like to carefully renovate them and live in them."

[0684] In this case, the server uses an emotion engine to match seller A with buyer B.

[0685] Prompt Sentence Examples

[0686] Example prompts to input to the generative AI model:

[0687] Seller's feelings: This house is filled with family memories, so I want to sell it to someone who will cherish it.

[0688] Buyer's feelings: They love old houses and want to carefully renovate them and live in them.

[0689] Based on this prompt, the server matches seller A with buyer B.

[0690] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0691] Step 1:

[0692] User Registration and Login

[0693] Input: A user accesses the system using a terminal and enters their name, email address, and password.

[0694] Data processing: The server stores the entered information in a database.

[0695] Output: A registration completion email is sent to the user.

[0696] Specific operation: The user opens a browser on their device, accesses the system's website, enters the required information in the registration form, and clicks the Register button. The server saves the entered information in the database and sends an email confirming registration. The user logs in using the registered information.

[0697] Step 2:

[0698] Entering seller and buyer information

[0699] Input: Sellers enter text about the property details and their feelings, and buyers enter text about the conditions and feelings about the property they are looking for.

[0700] Data processing: The server stores this information in a database.

[0701] Output: The seller and buyer information is saved in the database.

[0702] Specific operation: Sellers upload property photos and descriptions and enter emotional text. Buyers enter the desired property conditions (e.g., price range, location, layout) and enter emotional text. The server stores this information in a database.

[0703] Step 3:

[0704] Emotion analysis using an emotion engine

[0705] Input: Seller and buyer input information

[0706] Data processing: The server uses an emotion engine to analyze the information entered by the seller and buyer and extracts emotion keywords.

[0707] Output: Sentiment analysis results are obtained.

[0708] Specific operation: The server starts the emotion engine and analyzes the input information of the seller and buyer. The emotion engine performs text analysis and extracts emotion keywords.

[0709] Step 4:

[0710] Transaction progress management using generative AI

[0711] Input: Seller and buyer information and sentiment analysis results

[0712] Data processing: The server uses generative AI to manage the progress of the transaction and calculates the deadlines for submitting required documents and the timing for obtaining signatures.

[0713] Output: A reminder is sent to the user.

[0714] How it works: The server manages the progress of the transaction using generative AI, which sends reminders to the user, such as "The deadline for document submission is approaching."

[0715] Step 5:

[0716] Matching and Notifications

[0717] Input: Sentiment analysis results and seller and buyer information

[0718] Data processing: The server matches sellers and buyers based on the analysis results of the emotion engine.

[0719] Output: If a match is found, notifications are sent to the seller and buyer.

[0720] Specific operation: The server matches sellers and buyers based on the analysis results of the emotion engine. If a match is made, the server sends a notification to the seller and buyer saying "Matching has been made."

[0721] Step 6:

[0722] Submitting documents and obtaining signatures

[0723] Input: Required documents and signature information

[0724] Data processing: The server checks the submitted document and asks the user to sign if a signature is required.

[0725] Output: The submitted documents and signatures are saved on the server.

[0726] Specific operation: The user uploads the required documents using the device. The server checks the submitted documents and notifies the user that a signature is required if one is required. The user signs the documents using the device and sends them to the server.

[0727] Step 7:

[0728] Completing the payment process

[0729] Input: Payment information

[0730] Data processing: The server initiates the payment process and provides the necessary information to the user.

[0731] Output: The payment is confirmed to be successful and the transaction is confirmed.

[0732] Specific operation: The server starts the payment process and notifies the user, "Please complete the payment process." The user completes the payment using the terminal. The server confirms that the payment has been completed and notifies the user that the transaction is complete.

[0733] (Application example 2)

[0734] Next, a description will be given of Application Example 2 of Form 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."

[0735] Conventional home buying and selling platform systems lacked sufficient support to facilitate smooth transactions between sellers and buyers, particularly because they did not match buyers based on their emotions, resulting in low transaction satisfaction. Furthermore, there was a lack of means to manage the progress of transactions in real time and smoothly carry out procedures such as the submission and signing of necessary documents and payments. Furthermore, there was also the issue of a lack of systems applicable to the sale of vacant homes in rural areas.

[0736] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0737] In this invention, the server includes a means for connecting sellers and buyers via P2P using a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for optimizing matching based on the emotions of the seller and buyer using an emotion engine, and a means for managing the progress of the transaction via an application installed on a smartphone and smoothly proceeding with procedures such as the submission and signing of necessary documents and payment. This enables optimal matching based on the emotions of the seller and buyer, manages the progress of the transaction in real time, and smoothly proceeds with the necessary procedures. It also provides a system that can be applied to the sale and purchase of vacant houses in rural areas.

[0738] "Generative AI" is a system that uses artificial intelligence technology to assist transactions between buyers and sellers and manage the progress of transactions.

[0739] A "consultant" is someone who connects sellers and buyers via P2P and provides advice and support to ensure smooth transactions.

[0740] "P2P" stands for peer-to-peer and refers to a method of direct transactions between sellers and buyers.

[0741] "Means to support transactions" refers to functions that support various procedures to smoothly advance transactions between sellers and buyers.

[0742] "Means for determining whether a transaction is appropriate" refers to the function of evaluating whether the transaction is legally and ethically appropriate.

[0743] The "emotion engine" is a technology that analyzes the emotions of sellers and buyers and makes optimal matches based on those emotions.

[0744] "Means for optimizing matching" refers to a function that finds the best trading partner based on the emotions and needs of sellers and buyers.

[0745] An "application installed on a smartphone" is software that runs on a smartphone, manages the progress of transactions, and assists with procedures such as the submission and signing of necessary documents and payment.

[0746] "Means for managing transaction progress" refers to the ability to track each stage of a transaction in real time and prompt necessary actions.

[0747] "Means for smoothly carrying out procedures such as the submission, signing, and payment of necessary documents" refers to functions that enable efficient procedures such as the submission, signing, and payment of documents required for a transaction.

[0748] "A system that can also be applied to the sale and purchase of vacant houses in rural areas" refers to a system that can handle the sale and purchase of vacant houses not only in urban areas but also in rural areas.

[0749] A system for implementing this invention is configured using a generative AI, an emotion engine, and a smartphone application. A specific embodiment of the system will be described below.

[0750] System Configuration

[0751] 1. Hardware:

[0752] Server: A high-performance server for running generative AI models and emotion engines.

[0753] Smartphone: A device through which users conduct transactions.

[0754] 2. Software:

[0755] Generative AI model: An AI model built using TensorFlow and Keras.

[0756] Emotion engine: Uses emotion analysis APIs such as IBM Watson (registered trademark).

[0757] Smartphone application: Developed using Python, JavaScript (registered trademark), React Native, etc.

[0758] Data processing and calculation

[0759] 1. Data Collection:

[0760] The server collects input data (text, images, etc.) from sellers and buyers.

[0761] For example, a seller might enter, "This house is filled with many memories. I would like to sell it to someone who will cherish it."

[0762] 2. Data Preprocessing:

[0763] The server preprocesses the text data using an NLP library (e.g., spaCy), specifically tokenizing it and removing stop words.

[0764] 3. Emotion analysis:

[0765] The server uses a sentiment analysis API to analyze the sentiment of sellers and buyers.

[0766] For example, if a buyer enters, "I like old houses and would like to carefully renovate them and live in them," that sentiment is analyzed.

[0767] 4. Generative AI Models:

[0768] The server runs a generative AI model built using TensorFlow and Keras and manages the progress of transactions.

[0769] For example, it tracks each stage of a transaction in real time and prompts you to take any necessary action.

[0770] 5. Matching Algorithm:

[0771] The server implements an algorithm that performs optimal matching based on emotional data of sellers and buyers.

[0772] For example, it matches the seller's feeling of "strong attachment" with the buyer's feeling of "wanting to carefully renovate an old house."

[0773] Examples and prompts

[0774] Specific examples

[0775] 1. Seller Input:

[0776] "This house is filled with so many memories. I would like to sell it to someone who will cherish it."

[0777] 2. Buyer Input:

[0778] "I like old houses and would like to carefully renovate them and live in them."

[0779] Prompt Sentence Examples

[0780] Seller sentiment analysis prompt:

[0781] Seller's text: "This house is filled with memories. I would like to sell it to someone who will cherish it."

[0782] Analyze the seller's sentiment.

[0783] Buyer sentiment analysis prompt:

[0784] Buyer's text: "I love old houses and would like to carefully renovate them and live in them."

[0785] Analyze buyer sentiment.

[0786] Matching prompt:

[0787] Seller's sentiment: "I have a strong emotional attachment to this product"

[0788] Buyer's sentiment: "I want to carefully renovate an old house."

[0789] Match these two together.

[0790] In this way, a system is built that achieves optimal matching based on the emotions of sellers and buyers.

[0791] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0792] Step 1:

[0793] A user launches a smartphone application and logs in as a seller or buyer.

[0794] Input: User login information (user ID, password)

[0795] Output: User authentication result (success / failure)

[0796] Specific operation: The smartphone application sends the user's login information to the server, which then refers to the database for authentication. If authentication is successful, the user can proceed to the next step.

[0797] Step 2:

[0798] The user enters information as a seller or buyer.

[0799] Input: Seller's property information and sentiment text, Buyer's desired conditions and sentiment text

[0800] Output: Verification result of the entered information (success / failure)

[0801] Specific operation: The smartphone application sends the information entered by the user to the server, which stores the information in a database. If the input is correct, the process proceeds to the next step.

[0802] Step 3:

[0803] The server pre-processes the input data of the seller and the buyer.

[0804] Input: Seller and buyer input data (text)

[0805] Output: Preprocessed text data

[0806] Specific operation: The server uses an NLP library (e.g., spaCy) to tokenize the text data and remove stop words. The preprocessed data is used in the next step.

[0807] Step 4:

[0808] The server performs sentiment analysis.

[0809] Input: Preprocessed text data

[0810] Output: Sentiment analysis results (sentiment scores and emotion tags)

[0811] Specific operation: The server uses an emotion analysis API (e.g., IBM Watson) to analyze the emotions of the seller and buyer. The analysis results are stored in a database.

[0812] Step 5:

[0813] The server manages the progress of the transaction using a generative AI model.

[0814] Input: Sentiment analysis results of sellers and buyers, transaction progress data

[0815] Output: Instructions and notifications about the progress of the transaction

[0816] How it works: The server runs a generative AI model built with TensorFlow and Keras to track each stage of the transaction in real time, notifying the user of any required actions (document submission, signature, payment, etc.).

[0817] Step 6:

[0818] The server matches buyers and sellers.

[0819] Input: Seller and buyer sentiment analysis results, needs data

[0820] Output: Matching results (information on the best trading partner)

[0821] Specific operation: The server runs an algorithm to find the best match based on the emotional and needs data of the seller and buyer. The matching results are notified to the user.

[0822] Step 7:

[0823] The user completes the transaction.

[0824] Input: Transaction documents, signatures, and payment information

[0825] Output: Transaction completion confirmation result (success / failure)

[0826] Specific operation: The user submits the necessary documents, signs, and completes the payment via the smartphone application. The server verifies this information and notifies the user that the transaction is complete.

[0827] Example 3

[0828] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0829] Conventional housing trading platform systems do not adequately assess the appropriateness of transactions or manage the emotions of sellers and buyers, resulting in a lack of transparency and reliability in transactions. Furthermore, there is a lack of information on vacant houses in rural areas and matching based on the needs of sellers and buyers, making it difficult to promote the sale of vacant houses in rural areas.

[0830] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0831] In this invention, the server includes a means for a generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for collecting data such as the property price, transaction conditions, market rates, and laws and regulations, a means for recognizing the emotions of sellers and buyers using an emotion engine and managing the progress of the transaction, and a means for aggregating information on vacant houses in rural areas and providing it to interested buyers. This improves the transparency and reliability of transactions and makes it possible to promote the buying and selling of vacant houses in rural areas.

[0832] "Generative AI" is an artificial intelligence technology that generates new information and models based on data.

[0833] A "consultant" is a person who has specialized knowledge and is tasked with providing advice and assistance in a particular field.

[0834] "P2P" is an abbreviation for Peer-to-Peer, a network type in which individual devices communicate directly without going through a central server.

[0835] "Fairness of transactions" refers to whether transactions are fair and reasonable based on market prices and laws and regulations.

[0836] An "emotion engine" is a technology that analyzes and recognizes human emotions from data such as text and voice.

[0837] "Vacant house information" refers to information about houses that are not currently in use and are available for sale or rent.

[0838] "Market going rates" refers to the general price range for a product in a particular market.

[0839] "Laws and regulations" refers to laws and regulations enacted by the national or local government.

[0840] "Data collection" is the process of gathering the necessary information from various sources.

[0841] The "transaction status" indicates the stage at which the transaction is in progress.

[0842] "Matching" is the process of matching the needs of sellers and buyers to find the optimal combination.

[0843] MODE FOR CARRYING OUT THE INVENTION

[0844] The present invention relates to a home buying and selling platform system using generative AI. This system includes a server, a terminal, and a user, and is implemented as follows.

[0845] 1. Generating the system program

[0846] The server generates the system's program using a generative AI model. This generative AI model is input with data such as property price, transaction conditions, market price, and laws and regulations. Specifically, it retrieves property information from a database and collects market price data and legal data via API.

[0847] 2. Explanation of program processing

[0848] The server executes the generated program and performs the following processes.

[0849] Transaction fairness assessment

[0850] The server analyzes the property price and transaction conditions, and evaluates the appropriateness of the transaction based on market rates and laws and regulations. This evaluation uses market and legal data stored in the database. For example, if the property price is more than 20% higher than the market rate, the server will determine that the transaction is "inappropriate."

[0851] Notification of suitability assessment results

[0852] The server notifies the seller and buyer of the results of the transaction suitability assessment. The results are sent to the seller and buyer via email or in-app notification. For example, a message may be sent saying, "This transaction is deemed unsuitable because it is priced higher than the market rate."

[0853] Aggregating and providing information on vacant houses in rural areas

[0854] The server aggregates information on vacant houses in local areas and provides it to interested buyers. It collects information on vacant houses from local governments and real estate agents and stores it in a database. When a buyer enters their desired conditions, the server lists properties that match the conditions and provides them to the buyer. For example, if a buyer enters conditions such as "3LDK, within a 10-minute walk from the station, budget of 20 million yen or less," the server will list properties that match the conditions.

[0855] Emotional engine trading management

[0856] The server uses an emotion engine to recognize the emotions of the seller and buyer and manages the progress of the transaction accordingly. The text entered by the seller and buyer is analyzed and the emotion engine recognizes emotions. For example, if a buyer enters "I'm worried because the contract is progressing too quickly," the server will recognize that emotion and temporarily delay the progress of the transaction.

[0857] 3. Examples and prompts

[0858] As a concrete example, the following scenario can be considered.

[0859] Examples of transaction fairness assessment

[0860] If the property price is higher than the market price, the server will determine that the transaction is not appropriate and notify the seller and buyer.

[0861] Example prompt: "If the property is priced above market value, please evaluate the transaction and let me know if it is not."

[0862] Specific examples of vacant house sales in rural areas

[0863] We collect information on vacant houses in local areas and provide properties that meet the buyer's desired conditions.

[0864] Example prompt: "Collect information on vacant houses in the local area and create a list of properties that meet the buyer's desired criteria."

[0865] A concrete example of transaction management using an emotion engine

[0866] If a buyer types, "I'm worried that the deal is moving too quickly," the server will recognize that sentiment and temporarily slow down the transaction.

[0867] Example prompt: "If the buyer feels anxious, acknowledge their feelings and temporarily delay the transaction."

[0868] The above is an embodiment of the present invention. This system improves the transparency and reliability of transactions, and makes it possible to promote the buying and selling of vacant houses in rural areas. The flow of the identification process in the third embodiment will be explained using FIG. 21.

[0869] Step 1:

[0870] Transaction data collection

[0871] The server collects data such as property prices, transaction conditions, market rates, laws and regulations, etc.

[0872] Input: Property information from the database, market price data and legal data via API

[0873] Data processing: Consolidating collected data and converting it into an analyzable format

[0874] Output: A consolidated transaction dataset

[0875] Specific operation: The server retrieves property information from the database, collects market price data and legal data through APIs, and consolidates this data into an analyzable format.

[0876] Step 2:

[0877] Transaction fairness assessment

[0878] The server evaluates the appropriateness of the transaction based on the collected data.

[0879] Input: Consolidated transaction dataset

[0880] Data calculations: Using generative AI models to compare property prices with market rates and check transaction conditions in accordance with laws and regulations

[0881] Output: Transaction fairness assessment results

[0882] Specific operation: The server uses the generative AI model to compare the property price with the market price and check the transaction conditions based on laws and regulations. For example, if the property price is more than 20% higher than the market price, it will determine that the transaction is "inappropriate."

[0883] Step 3:

[0884] Notification of suitability assessment results

[0885] The server notifies the seller and buyer of the results of the transaction suitability assessment.

[0886] Input: Transaction fairness assessment result

[0887] Data processing: Converting evaluation results into notification messages

[0888] Output: Notification messages to seller and buyer

[0889] What it does: The server sends the evaluation results to the seller and buyer via email or in-app notification, for example, a message saying, "This transaction is deemed unsuitable because it is priced higher than the market rate."

[0890] Step 4:

[0891] Aggregating and providing information on vacant houses in rural areas

[0892] The server aggregates information on vacant houses in the local area and provides it to interested buyers.

[0893] Input: Vacant house information from local governments and real estate agents

[0894] Data processing: Store vacant house information in a database and search based on buyers' desired conditions

[0895] Output: A list of properties that match the criteria

[0896] Specific operation: The server collects information on vacant houses from local governments and real estate agents and stores it in a database. When a buyer enters their desired conditions, the server lists properties that match the conditions and provides them to the buyer. For example, if the buyer enters the conditions "3LDK, within a 10-minute walk from the station, budget within 20 million yen," the server will list properties that match the conditions.

[0897] Step 5:

[0898] Emotional engine trading management

[0899] The server uses an emotion engine to recognize the emotions of the seller and the buyer and manages the progress of the transaction accordingly.

[0900] Input: Text entered by the seller and buyer

[0901] Data Computing: Sentiment engine analyzes text and recognizes emotions

[0902] Output: Adjusting trading progress based on sentiment

[0903] How it works: The server analyzes the text entered by the seller and buyer and recognizes emotions using an emotion engine. For example, if a buyer enters, "I'm worried because the contract is moving too quickly," the server will recognize that emotion and temporarily delay the transaction.

[0904] (Application example 3)

[0905] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0906] Conventional housing sales platform systems lack sufficient means for determining the appropriateness of a transaction, and do not manage the progress of the transaction while taking into account the feelings of the seller and buyer. Furthermore, when it comes to the sale of vacant houses in rural areas, the collection and provision of property information is not done efficiently, and there is insufficient effort to promote relocation to rural areas. This reduces the transparency and reliability of transactions, posing a challenge in preventing the effective use of vacant houses in rural areas.

[0907] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0908] In this invention, the server includes a means for generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for aggregating and providing property information, and a means for recognizing the emotions of sellers and buyers and managing the progress of the transaction. This will improve the transparency and reliability of transactions, as well as enable efficient buying and selling of vacant houses in rural areas and promote migration to rural areas.

[0909] "Generative AI" is an artificial intelligence technology that generates new information and content based on data.

[0910] A "consultant" is a professional with specialized knowledge who provides advice and assistance in a particular field.

[0911] "P2P" is an abbreviation for Peer-to-Peer, a networking method in which individual devices communicate directly without going through a central server.

[0912] A "transaction" is the act of buying and selling goods or services between a seller and a buyer.

[0913] "Fairness" is a standard for evaluating whether a transaction is fair based on laws and regulations and market prices.

[0914] "Property Information" means information containing detailed data and characteristics about real estate.

[0915] "Aggregation" is the act of bringing together dispersed information.

[0916] "Providing" is the act of handing over necessary information or services to another person.

[0917] "Emotions" refer to a person's psychological state or feelings.

[0918] "Recognition" is the act of understanding and grasping specific information or a situation.

[0919] "Progress" is the state that indicates the stage at which a particular process or task is.

[0920] "Management" is the act of planning, organizing, directing and controlling to achieve specific objectives.

[0921] A system for implementing this invention includes means for connecting sellers and buyers via P2P using generative AI, means for supporting transactions, means for determining the appropriateness of transactions, means for aggregating and providing property information, and means for recognizing the emotions of sellers and buyers and managing the progress of transactions.

[0922] System Program

[0923] This system is realized using the following hardware and software.

[0924] Hardware: Servers, smartphones, smart glasses

[0925] Software: Generative AI models (e.g., OpenAI's GPT-3), emotion recognition engines, database management systems, API communication libraries (e.g., requests)

[0926] Processing Description

[0927] Aggregation and provision of property information

[0928] The server retrieves property information for the specified area from the API and aggregates it in a database. When a user requests property information, the server extracts the relevant information from the database and provides it to the user's device.

[0929] Transaction fairness assessment

[0930] The server inputs the property price, market price, and legal requirements as prompts into the generative AI model to evaluate the suitability of the transaction. The evaluation results are notified to both the seller and the buyer.

[0931] Transaction progress management using emotion engine

[0932] The server passes the text entered by the user to an emotion recognition engine to recognize the emotion. Based on the results, the server adjusts the progress of the transaction. For example, if the user enters "I'm worried because the contract is progressing too quickly," the server will temporarily delay the progress of the transaction.

[0933] Specific examples

[0934] Providing property information

[0935] When a user requests, "Please tell me information about vacant houses in a specific local area," the server retrieves the relevant property information from the database and provides it to the user's terminal.

[0936] Transaction Due Diligence Prompt

[0937] Property price: 2.5 million yen, Market price: 3 million yen, Legal conditions: Compliant with laws and regulations. Is this transaction fair?

[0938] Transaction progress management prompts using emotion engine

[0939] User sentiment: I'm worried that the deal is moving too quickly. How do I manage the progress of the deal?

[0940] This will improve the transparency and reliability of transactions, as well as enable efficient buying and selling of vacant homes in rural areas and promote migration to rural areas.

[0941] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0942] Step 1:

[0943] The user requests property information using the terminal.

[0944] Input: A user requests, "Please tell me about vacant houses in a specific rural area."

[0945] Output: The request is sent to the server.

[0946] Specific operation: A user uses a smartphone or smart glasses to operate an application to request property information.

[0947] Step 2:

[0948] The server retrieves property information from the API and aggregates it in a database.

[0949] Input: The server receives the user's request.

[0950] Output: The property information is saved in the database.

[0951] Specific operation: The server uses the API communication library (e.g., requests) to obtain property information for the specified area and save it in the database management system.

[0952] Step 3:

[0953] The server extracts the relevant property information from the database and provides it to the user's terminal.

[0954] Input: The server searches the database for property information.

[0955] Output: The property information is sent to the user's device.

[0956] Specific operation: The server uses a database management system to search for the relevant property information and transmits it to the user's terminal.

[0957] Step 4:

[0958] The server inputs the property price, market price, and legal conditions as prompts into the generative AI model to evaluate the suitability of the transaction.

[0959] Input: Property price, market price, legal conditions

[0960] Output: Transaction appropriateness evaluation results

[0961] Specific operation: The server inputs a prompt sentence into a generative AI model (e.g., OpenAI's GPT-3) and obtains the evaluation result.

[0962] Example prompt sentence:

[0963] Property price: 2.5 million yen, Market price: 3 million yen, Legal conditions: Compliant with laws and regulations. Is this transaction fair?

[0964] Step 5:

[0965] The server notifies both the seller and the buyer of the evaluation results.

[0966] Input: Transaction appropriateness evaluation results

[0967] Output: Notification message

[0968] Specific operation: The server generates a notification message based on the evaluation result and sends it to the seller and buyer terminals.

[0969] Step 6:

[0970] Users input their emotions during the transaction.

[0971] Input: Text input about the user's emotions

[0972] Output: Input data to the emotion recognition engine

[0973] Specific operation: A user inputs text about emotions using a smartphone or smart glasses.

[0974] Step 7:

[0975] The server passes the user's input to an emotion recognition engine to recognize the emotion.

[0976] Input: Text input about the user's emotions

[0977] Output: Emotion recognition result

[0978] Specific operation: The server passes the text to the emotion recognition engine and obtains the emotion recognition results.

[0979] Step 8:

[0980] The server adjusts the progress of the transaction based on the emotion recognition results.

[0981] Input: Emotion recognition results

[0982] Output: Transaction progress adjustment instructions

[0983] Specific operation: The server adjusts the progress of the transaction based on the emotion recognition results, temporarily delaying the progress of the transaction if necessary.

[0984] Example prompt sentence:

[0985] User sentiment: I'm worried that the deal is moving too quickly. How do I manage the progress of the deal?

[0986] 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.

[0987] 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> ) 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.

[0988] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[0989] 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.

[0990] [Second embodiment]

[0991] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0992] 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.

[0993] 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).

[0994] 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.

[0995] 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.

[0996] 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).

[0997] 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.

[0998] 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.

[0999] 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.

[1000] 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.

[1001] 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.

[1002] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1003] "Example 1"

[1004] The home buying and selling platform system of the present invention uses generative AI to connect sellers and buyers via P2P. The generative AI collects information from sellers (e.g., detailed property information, desired price, etc.) and information from buyers (e.g., desired property conditions, budget, etc.), and performs optimal matching based on this information.

[1005] "Example 2"

[1006] Furthermore, this system supports transactions between sellers and buyers. Specifically, the generative AI manages the progress of the transaction and provides instructions to smoothly carry out procedures such as the submission and signing of necessary documents and settlement.

[1007] "Example 3"

[1008] The system also has the ability to determine whether a transaction is appropriate. The generative AI analyzes the property price, transaction conditions, etc., and evaluates appropriateness based on market rates, laws, etc. If it is determined to be inappropriate, it notifies both the seller and the buyer and encourages them to conduct a fair transaction.

[1009] "Example 4"

[1010] This system can also be applied to the sale and purchase of vacant houses in rural areas. For example, it can aggregate information on vacant houses in rural areas and provide it to interested buyers. It can also provide information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.), encouraging people to move to rural areas.

[1011] The processing flow of each embodiment will be described below.

[1012] "Example 1"

[1013] Step 1: The generative AI collects information from the seller (e.g., detailed property information, asking price, etc.).

[1014] Step 2: Similarly, the generative AI collects information from the buyer (e.g., desired property conditions, budget, etc.).

[1015] Step 3: The generative AI performs optimal matching based on the collected information and connects sellers and buyers via P2P.

[1016] "Example 2"

[1017] Step 1: After matching the seller and buyer, the generative AI manages the progress of the transaction.

[1018] Step 2: The generative AI provides instructions to the seller and buyer to smoothly complete procedures such as submitting necessary documents, signing, and completing payments.

[1019] "Example 3"

[1020] Step 1: The generative AI analyzes the property price, transaction terms, etc.

[1021] Step 2: The generative AI evaluates the appropriateness of the transaction based on market prices, laws and regulations, etc.

[1022] Step 3: If the transaction is deemed inappropriate, the generative AI notifies both the seller and the buyer and encourages them to make the transaction appropriate.

[1023] "Example 4"

[1024] Step 1: The generative AI aggregates information on vacant houses in local areas.

[1025] Step 2: The generative AI provides aggregated vacant house information to interested buyers.

[1026] Step 3: The generative AI will also provide information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.), encouraging people to move to rural areas.

[1027] Example 1

[1028] Next, a description will be given of Example 1 of Form 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."

[1029] Conventional housing buying and selling platforms often failed to efficiently match sellers and buyers, and the fairness and transparency of transactions were often not ensured. Furthermore, they were difficult to apply to the sale of vacant houses in rural areas. This meant that the needs of sellers and buyers were not fully met, and transactions were delayed.

[1030] 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.

[1031] In this invention, the server includes a means for a user to input information, a means for the server to collect information, a means for the server to send prompts to the generative AI model, a means for the generative AI model to perform matching, and a means for the server to notify the matching results. This makes it possible to efficiently collect information on sellers and buyers and perform optimal matching using the generative AI model. Furthermore, it is possible to provide a system that ensures the fairness and transparency of transactions and is applicable to the sale and purchase of vacant houses in rural areas.

[1032] "Generative AI" is an artificial intelligence technology that generates data based on information provided by users and matches sellers and buyers.

[1033] A "consultant" is someone whose role is to provide advice and support to help smooth transactions between sellers and buyers.

[1034] "P2P" refers to a peer-to-peer network in which sellers and buyers transact directly.

[1035] "Transaction support" means functions and processes that support transactions between buyers and sellers.

[1036] "Means for determining whether a transaction is fair" refers to the functions and processes for evaluating whether a transaction between a seller and a buyer is being conducted fairly and properly.

[1037] "User information entry means" refers to the interface or method by which sellers and buyers enter their information into the system.

[1038] "Means by which the server collects information" refers to the functions and processes by which the server collects and stores information entered by users.

[1039] "Means by which the server sends prompts to the generative AI model" refers to the functions and processes by which the server sends instructions to the generative AI model based on the information collected by the server.

[1040] "Means by which the generative AI model performs matching" refers to the functions and processes by which the generative AI model matches the conditions of the seller and buyer and performs the optimal match.

[1041] "Means for the server to notify matching results" refers to the functions and processes for informing sellers and buyers of the matching results output by the generative AI model.

[1042] "Vacant house sales in rural areas" refers to transactions involving the buying and selling of vacant houses located in rural areas.

[1043] MODE FOR CARRYING OUT THE INVENTION

[1044] This invention relates to a home buying and selling platform system that uses generative AI to connect sellers and buyers via P2P. A specific embodiment of this system will be described below.

[1045] 1. Generate the system program

[1046] The server generates the program for the home buying and selling platform system. This program has the function of connecting sellers and buyers via P2P using a generative AI model. One example of the generative AI model used is OpenAI's GPT-4.

[1047] 2. Explain the program's processing in natural language

[1048] The server uses a generative AI model to collect information on sellers and buyers and perform optimal matching. Specifically, it performs the following processes:

[1049] Seller information gathering:

[1050] The server collects property details (e.g., location, layout, age, asking price, etc.) from sellers. This information is entered through a web form or a mobile app.

[1051] Buyer information gathering:

[1052] The server collects the buyer's desired property conditions (e.g., desired area, floor plan, budget, etc.) This information is also entered via a web form or mobile app.

[1053] Data processing and calculations:

[1054] The server inputs the collected information about sellers and buyers into a generative AI model, which then performs optimal matching based on the seller and buyer's conditions.

[1055] Matching result notification:

[1056] The server notifies the seller and buyer of the matching results output by the generative AI model via email or in-app notifications.

[1057] 3. Add concrete examples

[1058] For example, if a seller enters "a 3LDK apartment in Shibuya Ward, Tokyo, with a desired price of 50 million yen," and a buyer enters "a 3LDK apartment in Tokyo, with a budget of 60 million yen or less," the generative AI model will make the optimal match based on these conditions.

[1059] 4. Examples of prompts

[1060] "Seller's information: 3LDK apartment in Shibuya Ward, Tokyo, asking price: 50 million yen. Buyer's information: 3LDK apartment in Tokyo, budget: 60 million yen or less. Please use this information to find the best match."

[1061] In this way, the server utilizes generative AI models to provide a system that optimally matches buyers and sellers based on their requirements. This system ensures fairness and transparency in transactions and can also be applied to the sale of vacant houses in rural areas.

[1062] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1063] Step 1: User Enters Information

[1064] Users (sellers or buyers) enter information using the home buying and selling platform's web form or mobile app. Sellers enter detailed property information (location, floor plan, age, asking price, etc.), while buyers enter the desired property conditions (desired area, floor plan, budget, etc.). The entered information is sent to the server. Specifically, the user enters information in each field and clicks the "Submit" button.

[1065] Step 2: The server collects information

[1066] The server collects the information entered by the user in real time and stores it in a database. The server checks the format of the entered information and displays an error message to the user if there are any errors. Specifically, the server receives the input data and executes an SQL query to store it in the database.

[1067] Step 3: The server sends a prompt to the generative AI model

[1068] The server generates a prompt based on the collected seller and buyer information. For example, it generates a prompt like this: "Seller information: 3LDK apartment in Shibuya Ward, Tokyo, asking price 50 million yen. Buyer information: 3LDK apartment in Tokyo, budget within 60 million yen." The server sends this prompt as an API request to the generative AI model. Specifically, the server generates the prompt and sends an HTTP POST request to the API endpoint of the generative AI model.

[1069] Step 4: Generative AI model performs matching

[1070] The generative AI model compares the seller's and buyer's conditions based on the prompt text sent from the server and performs the optimal match. The model compares the seller's property information with the buyer's desired conditions and generates the most suitable match result. Specifically, the generative AI model analyzes the prompt text and evaluates the degree of match of the conditions using an internal algorithm.

[1071] Step 5: The server notifies the match result

[1072] The server notifies the seller and buyer of the matching results received from the generative AI model. Notifications are sent via email or in-app notifications. For example, a message may be sent saying, "We have found a buyer interested in your property. Please check the details." Specifically, the server receives the matching results and sends a notification to the user via an email server or push notification service.

[1073] In this way, the server, terminals, and users work together to ensure smooth operation of the home buying and selling platform system.

[1074] (Application example 1)

[1075] Next, a description will be given of Application Example 1 of Form 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."

[1076] Conventional home buying and selling platforms were not efficient in matching sellers and buyers, and had the constraint of requiring buyers to visit the property in person. Furthermore, they were difficult to apply to the sale of vacant homes in rural areas. To solve these issues, a more efficient and flexible matching system and a property viewing function in virtual space were needed.

[1077] 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.

[1078] In this invention, the server includes a means for the generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for users to view properties in a virtual space, and a means for proposing optimal properties based on the user's desired conditions. This enables efficient matching between sellers and buyers, and allows users to view properties in a virtual space without visiting the site. It can also be applied to the sale and purchase of vacant houses in rural areas.

[1079] "Generative AI" is an artificial intelligence technology that makes optimal matches based on information about sellers and buyers.

[1080] A "consultant" is an expert or system that acts as a bridge between buyers and sellers.

[1081] "P2P" stands for peer-to-peer, a networking method that allows direct communication without going through a central server.

[1082] "Transaction support means" are functions and services that facilitate transactions between sellers and buyers.

[1083] "Means for determining whether a transaction is appropriate" refers to the function of evaluating whether the transaction is legally and ethically appropriate.

[1084] "Virtual space" is a virtual three-dimensional space generated using computer technology.

[1085] "Means to tour the property" refers to a function that allows users to visually check the interior and surroundings of the property in a virtual space.

[1086] "Desired conditions" are the requirements such as the property characteristics and budget that the user desires.

[1087] "Means to suggest the most suitable property" is a function that selects and suggests the most suitable property based on the user's desired conditions.

[1088] "Vacant house sales in rural areas" refers to the sale and purchase of vacant houses located in areas outside of urban areas.

[1089] The embodiments of the present invention will be described in detail below.

[1090] System configuration

[1091] This system is configured using the following hardware and software.

[1092] Hardware: Smartphone, Head-Mounted Display (HMD)

[1093] Software: Unity (virtual space creation), TensorFlow (generative AI model implementation), Firebase (database)

[1094] Program processing

[1095] Data collection

[1096] The server stores property information from sellers (e.g., property details, desired price) in Firebase. It also stores desired conditions from buyers (e.g., desired property conditions, budget) in Firebase.

[1097] Training generative AI models

[1098] The server uses TensorFlow to train a generative AI model that matches buyers and sellers based on their information, and then suggests the best properties based on their needs.

[1099] Building a virtual space

[1100] The server uses Unity to create a 3D model of the property, allowing users to tour the property in a virtual space, which they access using their smartphone or HMD.

[1101] Matching and Proposals

[1102] When a user inputs their desired conditions, the server uses a generative AI model to suggest the most suitable property, which the user can then view in a virtual space.

[1103] Data processing and calculation

[1104] The server processes the data entered by the user in real time and performs data calculations to suggest the most suitable properties, allowing users to find properties efficiently.

[1105] Specific examples

[1106] Users open the smartphone app and input the desired property conditions (e.g., 3LDK, budget of less than 50 million yen, within 10 minutes' walk from the station). The server then suggests the most suitable property based on these conditions, and the user can view the property in a virtual space using an HMD.

[1107] Prompt Sentence Examples

[1108] Enter the desired property conditions. For example, 3 bedrooms, 3 bedrooms, 50 million yen or less, within a 10-minute walk from the station.

[1109] In this way, this invention realizes efficient matching between sellers and buyers, allows users to view properties in a virtual space without visiting the site, and can also be applied to the sale and purchase of vacant houses in rural areas.

[1110] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1111] Step 1:

[1112] The server collects property information from sellers (e.g., property details, asking price) and stores it in Firebase. The input is property information provided by sellers, and the output is data stored in Firebase. Specifically, the server receives the information entered by the seller and stores it in a database.

[1113] Step 2:

[1114] The server collects the buyer's desired conditions (e.g., desired property conditions, budget) and stores them in Firebase. The input is the desired conditions provided by the buyer, and the output is the data stored in Firebase. Specifically, the server receives the information entered by the buyer and stores it in a database.

[1115] Step 3:

[1116] The server uses TensorFlow to train a generative AI model that performs optimal matching based on information about sellers and buyers. The input is the seller and buyer data stored in Firebase, and the output is the trained generative AI model. Specifically, the server retrieves the data and trains the AI ​​model.

[1117] Step 4:

[1118] The server uses Unity to create a 3D model of the property, allowing users to view the property in a virtual space. The input is detailed information about the property, and the output is a 3D model placed in the virtual space. Specifically, the server generates a 3D model based on the property information and places it in the virtual space.

[1119] Step 5:

[1120] The user accesses the application using a smartphone or HMD and inputs their desired conditions. The input is the desired conditions entered by the user, and the output is the data sent to the server. In concrete terms, the user operates the application and inputs their desired conditions.

[1121] Step 6:

[1122] The server uses a generative AI model to propose the most suitable property based on the desired conditions entered by the user. The input is the user's desired conditions, and the output is the proposed property information. Specifically, the server inputs the desired conditions into the AI ​​model and selects the most suitable property.

[1123] Step 7:

[1124] The user visits the proposed property in a virtual space. The input is the proposed property information, and the output is the user's experience of visiting the property in the virtual space. Specifically, the user wears an HMD and visits the property in the virtual space.

[1125] Step 8:

[1126] The server collects user feedback and stores it in Firebase. The input is the user feedback and the output is the data stored in Firebase. Specifically, the server receives the feedback from the user and stores it in the database.

[1127] Example 2

[1128] Next, a description will be given of Example 2 of Form 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."

[1129] With conventional home buying and selling platform systems, transactions between sellers and buyers often did not proceed smoothly, with problems such as time-consuming document submission, signing, and payment procedures. It was also difficult to manage the transaction progress in real time, which led to issues such as a decrease in the transparency and efficiency of transactions.

[1130] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1131] In this invention, the server includes a means for connecting sellers and buyers via P2P with a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for managing the progress of the transaction, a means for instructing the submission and signature of necessary documents, a means for instructing payment procedures, and a means for notifying the completion of the transaction. This makes it possible to manage the progress of the transaction in real time and smoothly proceed with the necessary procedures.

[1132] "Generative AI" is a system that uses artificial intelligence technology to generate data and automatically perform specific tasks.

[1133] A "consultant" is someone with specialized knowledge who provides advice and support in a particular field.

[1134] "P2P" stands for peer-to-peer, a networking method in which individual devices communicate directly with each other without going through a central server.

[1135] A "transaction" is the act of buying and selling goods or services between a seller and a buyer.

[1136] "Progress" refers to the status of each step of the transaction.

[1137] "Documents" are documents such as contracts and certificates required for transactions.

[1138] A "signature" is the act of a party putting their name on a document to show their intention.

[1139] "Settlement" is the procedure for completing payment in a transaction.

[1140] "Notification" is a means of communication to inform interested parties of specific information.

[1141] This invention is a system that supports transactions between sellers and buyers, and uses a generative AI model to manage the progress of the transaction and issue instructions to ensure the smooth submission and signing of necessary documents and payment procedures. A specific embodiment of this system is shown below.

[1142] System configuration

[1143] server:

[1144] The server manages the progress of transactions using a generative AI model (e.g., OpenAI's GPT-4). The server has the following main functions:

[1145] Manage the progress of your transactions.

[1146] Instruct them to submit and sign the necessary documents.

[1147] Instruct the payment procedure.

[1148] Notify the completion of the transaction.

[1149] Device:

[1150] The terminal is a device used by the seller and buyer to input the information required for the transaction and communicate with the server. The terminal has the following functions:

[1151] Register product information.

[1152] Submit a purchase request.

[1153] Signing the contract.

[1154] Executing payment procedures.

[1155] User:

[1156] Users are sellers and buyers who conduct transactions through the system. Users perform the following operations:

[1157] Enter product information.

[1158] Submit a purchase request.

[1159] Signing the contract.

[1160] Executing payment procedures.

[1161] Program processing

[1162] server:

[1163] The server manages the progress of transactions using generative AI models. Specifically, the server performs the following processes:

[1164] Track each step of a transaction (e.g., contract creation, signing, payment).

[1165] Identify the next steps you need to take based on your progress.

[1166] Provide instructions to buyers and sellers regarding the submission and signing of necessary documents.

[1167] Instruct the payment procedure.

[1168] Notify the completion of the transaction.

[1169] Examples:

[1170] When a seller adds an item to a listing, the server stores the information in a database.

[1171] When a buyer purchases a product, the server automatically generates a contract using a generative AI model.

[1172] The server instructs the seller and buyer to sign the contract.

[1173] Once both parties have signed, the server will instruct the buyer to complete the payment process.

[1174] Once the payment is complete, the server sends a notification of the transaction completion to the seller and buyer.

[1175] Example prompt sentence:

[1176] "A new transaction has been initiated. Please generate a contract."

[1177] "Send notices to sellers and buyers for signature."

[1178] Please instruct the buyer to complete the payment process.

[1179] In this way, the server can utilize generative AI models to manage the progress of the transaction and smoothly carry out the necessary procedures.

[1180] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1181] Step 1:

[1182] Registering product information

[1183] User (seller): Enter information such as product name, price, and description, and click the "Register" button.

[1184] Input: Information such as product name, price, description, etc.

[1185] Server: Receives the product information and saves it in the database. Once saved, notifies the seller that the product information has been registered.

[1186] Output: The product information is saved in the database and a notification is sent to the seller.

[1187] Step 2:

[1188] Receiving a purchase request

[1189] User (Buyer): Select the product you want to purchase and click the "Purchase" button.

[1190] Input: Purchase request (item ID, buyer information).

[1191] Server: Receives the purchase request, updates the transaction status to "Purchase request received", and notifies the buyer that "Purchase request has been received".

[1192] Output: Transaction progress is updated and notification is sent to the buyer.

[1193] Step 3:

[1194] Generate Agreement

[1195] Server: Sends a prompt to the generative AI model saying, "A new transaction has been started. Please generate a contract."

[1196] Input: Prompt text "A new deal has been started. Please generate a contract."

[1197] Generative AI model: Generates the contract and sends it back to the server.

[1198] Server: Saves the generated contract in the database and notifies the seller and buyer that the contract has been generated.

[1199] Output: The generated contract is saved in the database and notifications are sent to the seller and buyer.

[1200] Step 4:

[1201] Requesting a contract signature

[1202] Server: Sends a notification to the seller and buyer saying "The contract has been generated and please sign."

[1203] Input: Agreement signature request notification.

[1204] Users (seller and buyer): Sign the contract and click the "Done Signing" button.

[1205] Server: Receives the signed contract and saves it in the database. Once saved, notifies the seller and buyer that the signature has been completed.

[1206] Output: The signed contract is saved in the database and notifications are sent to the seller and buyer.

[1207] Step 5:

[1208] Payment procedure instructions

[1209] Server: Sends a notification to the buyer saying, "The contract has been signed. Please proceed with payment."

[1210] Input: Payment procedure instruction notice.

[1211] User (Buyer): Complete the payment procedure and click the "Payment Complete" button.

[1212] Server: Confirms that the payment has been completed, updates the transaction status to "Payment Completed", and notifies the buyer that "Payment has been completed."

[1213] Output: Transaction progress is updated and notification is sent to the buyer.

[1214] Step 6:

[1215] Notification of transaction completion

[1216] Server: Sends a notification to the seller and buyer saying "The transaction is complete. Thank you."

[1217] Input: Transaction Completion Notification.

[1218] Output: A notification of the transaction completion is sent to the seller and buyer.

[1219] (Application example 2)

[1220] Next, a description will be given of Application Example 2 of Form 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."

[1221] Conventional home buying and selling platform systems did not provide sufficient support to ensure smooth transactions between sellers and buyers, and the process of managing the transaction progress, submitting necessary documents, electronic signatures, and payment procedures was cumbersome. Furthermore, it was not possible to provide appropriate instructions at each step of the transaction, reducing transaction efficiency. This led to problems such as transaction delays and issues, which reduced user satisfaction.

[1222] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1223] In this invention, the server includes means for the generative AI to act as a consultant and connect sellers and buyers via P2P, means for supporting transactions between sellers and buyers, means for determining whether the transaction is appropriate, means for managing the progress of the transaction in real time, means for automatically generating and submitting required documents, means for supporting electronic signatures, means for automating payment procedures, means for saving and searching transaction history, and means for the generative AI to give appropriate instructions at each step of the transaction. This makes it possible to manage the progress of the transaction in real time and smoothly proceed with the submission of required documents, electronic signatures, and payment procedures.

[1224] "Generative AI" is a system that uses artificial intelligence technology to generate data and automate specific tasks.

[1225] A "consultant" is a person or system with specialized knowledge who provides advice and assistance in a particular field.

[1226] "P2P" stands for peer-to-peer, a networking method in which data is exchanged directly between individual users without going through a central server.

[1227] A "transaction" is the act of buying and selling goods or services between a seller and a buyer.

[1228] "Progress" is the status that indicates the current stage of a transaction or project.

[1229] "Real-time" refers to processing or reaction occurring immediately, without delay.

[1230] "Documents" are documents such as contracts and certificates required for transactions.

[1231] "Automatic generation" refers to the system automatically creating the necessary data and documents without human intervention.

[1232] "Submission" is the act of sending the necessary documents and data to a designated location or system.

[1233] An "electronic signature" is a digital signature that is used to verify the authenticity of a document and the signer.

[1234] A "payment procedure" is a series of operations or processes required to complete payment in a transaction.

[1235] "Automation" refers to the system automatically carrying out processing without human intervention.

[1236] "Transaction history" is a record of past transactions.

[1237] "Storage" refers to storing data or information for later use.

[1238] "Search" is the act of finding a specific item from stored data or information.

[1239] "Instruction" refers to an order to perform a specific action or operation.

[1240] As an embodiment of the present invention, we will explain a smart transaction assistant system as an example. This system uses generative AI to assist transactions between sellers and buyers and manage the progress of transactions in real time.

[1241] System Configuration

[1242] The system uses the following hardware and software:

[1243] Hardware: Smartphone

[1244] Software: AI model library, payment gateway library

[1245] Program processing

[1246] The server performs the following processing using generative AI.

[1247] 1. Initiating a transaction: The server creates a new transaction, including the transaction ID, seller, and buyer information. The generator AI notifies the start of the transaction.

[1248] 2. Document submission: The server adds the submitted document to the transaction and notifies the next step (signature).

[1249] 3. Add Signature: The server adds a signature to the transaction and signals the next step (settlement).

[1250] 4. Process payment: The server processes the payment through the payment gateway and completes the transaction if successful.

[1251] 5. Get transaction status: The server returns the current status of the transaction.

[1252] 6. Get transaction history: The server returns the transaction history associated with the specified user.

[1253] Specific examples

[1254] For example, when a seller submits a contract, a buyer electronically signs it, and completes payment with a credit card, the following prompt sentence is generated:

[1255] "The transaction has been initiated. Please submit the necessary documents."

[1256] "The paperwork has been submitted. Now please sign."

[1257] "Signature complete. Please proceed to payment."

[1258] "Payment completed. Transaction complete."

[1259] Data processing and calculation

[1260] The server uses an AI model library to manage the transaction progress, automatically generate and submit required documents, support electronic signatures, and automate payment procedures. Transaction history is stored in a database and can be searched as needed.

[1261] In this way, the smart trading assistant system can automate each step of the transaction and provide appropriate instructions to the user, allowing the transaction to proceed smoothly.

[1262] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1263] Step 1:

[1264] The server initiates the transaction. When the user enters the information to initiate the transaction (transaction ID, seller and buyer information), the server creates a new transaction. The generative AI generates a prompt message notifying the user of the start of the transaction and sends it to the user.

[1265] Input: Transaction ID, Seller information, Buyer information

[1266] Output: Transaction start notification prompt text

[1267] Specific operation: The server creates a new transaction record in the database and uses generative AI to generate a prompt message saying, "The transaction has been initiated. Please submit the necessary documents." and sends it to the user.

[1268] Step 2:

[1269] The server accepts document submissions. When the user submits the required documents, the server adds them to the transaction. The generative AI generates a prompt message informing the user of the next step (signature) and sends it to the user.

[1270] Input: Submitted document

[1271] Output: Signature notification prompt text

[1272] Specific operation: The server saves the submitted document in a database and associates it with the transaction record. It then uses generative AI to generate a prompt message to the user: "The document has been submitted. Please sign next."

[1273] Step 3:

[1274] The server accepts the addition of a signature. When the user digitally signs, the server adds the signature to the transaction. The generative AI generates a prompt message informing the user of the next step (payment) and sends it to the user.

[1275] Input: Electronic Signature

[1276] Output: Payment notification prompt

[1277] Specific operation: The server stores the digital signature in a database and associates it with the transaction record. It then uses generative AI to generate a prompt message to the user: "Signature complete. Please proceed to payment."

[1278] Step 4:

[1279] The server processes the payment. When the user enters payment information, the server processes the payment through the payment gateway. If the payment is successful, the transaction is completed. The generative AI generates a prompt message notifying the user that the transaction is complete and sends it to the user.

[1280] Input: Payment information

[1281] Output: Transaction completion notification prompt

[1282] Specific operation: The server sends payment information to the payment gateway and receives the payment result. If the payment is successful, it updates the transaction record status to "Completed." It uses generative AI to generate a prompt message saying "Payment completed. Transaction completed." and sends it to the user.

[1283] Step 5:

[1284] The server gets the status of the transaction. When a user wants to check the status of a transaction, the server takes the transaction ID as input and returns the current transaction status.

[1285] Input: Transaction ID

[1286] Output: Current transaction status

[1287] Specific operation: The server searches the database for the transaction record corresponding to the transaction ID and returns its status to the user.

[1288] Step 6:

[1289] The server retrieves the transaction history. When a user wants to check the transaction history, the server takes the user information as input and returns the relevant transaction history.

[1290] Input: User information

[1291] Output: Transaction history

[1292] Specific operation: The server searches the database for transaction records related to the user information and returns the history to the user.

[1293] Example 3

[1294] Next, a description will be given of Example 3 of Form Example 3. 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."

[1295] Conventional housing buying and selling platform systems lacked objective standards for determining the appropriateness of transactions, which increased the likelihood of improper transactions occurring between sellers and buyers. Furthermore, when it came to the sale of vacant homes in rural areas, there was insufficient information gathering and promotion of fair transactions. This made it difficult for users to make transactions with confidence, and also hindered the promotion of relocation to rural areas.

[1296] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1297] In this invention, the server includes a means for collecting data such as property prices and transaction terms from a database, a means for analyzing the collected data using a generative AI model to evaluate the appropriateness of the transaction, and a means for notifying both the seller and the buyer of any inappropriate transaction. This makes it possible to objectively evaluate the appropriateness of the transaction and prevent inappropriate transactions. It also allows users to trade with peace of mind, contributing to the sale of vacant houses in rural areas and promoting relocation.

[1298] A "database" is an information accumulation system that stores data such as property prices and transaction terms, and can be searched and retrieved as needed.

[1299] A "generative AI model" is an algorithm or program that uses artificial intelligence techniques to analyze data and generate results for a specific purpose.

[1300] "Fairness of transaction" is a standard for evaluating whether the price and transaction conditions of a property are reasonable based on market rates and laws and regulations.

[1301] "Notification" is a means of communication to convey evaluation results and advice regarding the appropriateness of a transaction to sellers and buyers.

[1302] An "interface" is an operation screen or input device that allows a user to access the system, input data, and check the results.

[1303] "Guidance" refers to instructions and advice that provide users with the information and advice they need to conduct proper transactions.

[1304] "Matching" is the process of finding the best trading partner based on the needs of the seller and buyer.

[1305] "Vacant house sales in rural areas" refers to transactions involving the buying and selling of unused residential properties in rural areas.

[1306] MODE FOR CARRYING OUT THE INVENTION

[1307] This invention relates to a home buying and selling platform system, and in particular to a system that uses a generative AI model to evaluate the appropriateness of a transaction and promote appropriate transactions between sellers and buyers.

[1308] Server Roles

[1309] The server first collects data such as property prices and transaction terms from a database, such as MySQL or PostgreSQL, and then executes an SQL query to retrieve the required data.

[1310] Next, the server analyzes the collected data using a generative AI model (e.g., OpenAI GPT-4). This analysis includes evaluating whether the property price is fair compared to the market price and whether the transaction terms violate laws and regulations. Specifically, the server inputs the following prompts into the generative AI model:

[1311] "Is the price of this property fair compared to the market price? Please also check whether it violates any laws or regulations."

[1312] Based on the analysis, the server generates a notification about the invalid transaction, which includes the reason why the transaction is invalid and advice on how to make the transaction valid. The notification is sent to both the seller and the buyer via an email server (e.g., SendGrid, Amazon SES).

[1313] Device Role

[1314] The terminal provides an interface for users to access. Users can enter property information and transaction terms through the terminal. The terminal displays forms and input fields for users to enter data.

[1315] The data entered by the user is sent to the server using an HTTP request. The terminal that receives the notification from the server displays the notification to the user and provides guidance for conducting a proper transaction. Specifically, the following guidance is displayed:

[1316] "The price of this property is higher than the market price. The appropriate price is XX yen."

[1317] User Roles

[1318] The user uses the terminal to input property information and transaction terms. Specifically, the user enters the property price, location, transaction terms, etc. into a form. After checking the entered data, the user clicks the send button to send it to the server.

[1319] The user who receives the notification from the server checks the contents of the notification and reviews the terms of the transaction. For example, the user may correct the property price to an appropriate price based on the notification and send the result back to the server.

[1320] Specific examples

[1321] For example, if a user wants to purchase a vacant house in a rural area, they input the property price and terms of the transaction into their device. The server then uses a generative AI model to analyze this data and assess suitability based on market rates and regulations. The server uses prompts like the following:

[1322] "Is the price of this property fair compared to the market price? Please also check whether it violates any laws or regulations."

[1323] If the property is priced above market value, the server will notify you and offer a fair price. The notification will look like this:

[1324] "The price of this property is higher than the market price. The appropriate price is XX yen."

[1325] In this way, users can obtain information for conducting fair transactions. This can also contribute to the sale and purchase of vacant houses in rural areas and the promotion of relocation. The flow of the identification process in the third embodiment will be described with reference to FIG. 15.

[1326] Program processing flow

[1327] Step 1: Data collection

[1328] Subject: Server

[1329] The server collects data such as property prices and transaction terms from the database by executing SQL queries to retrieve the required data.

[1330] Input: Database connection information, SQL query

[1331] Output: A dataset of property prices and transaction terms

[1332] Specific operation: The server executes an SQL query such as "SELECT FROM properties WHERE status='available'" and obtains the results as a dataset.

[1333] Step 2: Data analysis

[1334] Subject: Server

[1335] The server inputs the collected data into a generative AI model for analysis, which evaluates whether the property price is fair compared to the market price and whether the transaction terms violate laws and regulations.

[1336] Input: Data set of property prices and transaction terms, prompt text

[1337] Output: Adequacy evaluation results

[1338] Specific operation: The server inputs a prompt statement to the generated AI model: "Is the price of this property appropriate compared to the market price? Please also check whether it violates any laws and regulations." and obtains the appropriateness evaluation result.

[1339] Step 3: Generate notifications

[1340] Subject: Server

[1341] The server generates a notification based on the analysis, including the reason why the transaction is not appropriate and advice on how to make the transaction appropriate.

[1342] Input: Appropriateness assessment results

[1343] Output: Notification message

[1344] Specific operation: The server generates a notification message saying, "The price of this property is higher than the market price. The appropriate price is XX yen."

[1345] Step 4: Send notification

[1346] Subject: Server

[1347] The server generates and sends notifications to both the seller and the buyer.

[1348] Input: Notification message, seller and buyer contact information

[1349] Output: Transmission result

[1350] Specific operation: The server uses the mail server to send the notification message and record the sending result.

[1351] Step 5: Data entry

[1352] Subject: Terminal

[1353] The terminal provides an interface for the user to input property information and transaction conditions.

[1354] Input: User input data (property information, transaction conditions)

[1355] Output: Input data confirmation screen

[1356] What it does: The device displays forms and input fields, allowing the user to enter data.

[1357] Step 6: Send data

[1358] Subject: Terminal

[1359] The terminal transmits the data entered by the user to the server.

[1360] Input: User-entered data

[1361] Output: Transmission result

[1362] Specific operation: The terminal uses an HTTP request to send data to the server and displays the transmission result.

[1363] Step 7: Receive notifications

[1364] Subject: Terminal

[1365] The terminal receives the notification from the server.

[1366] Input: Notification message from the server

[1367] Output: Notification display screen

[1368] Specific behavior: The device receives emails and in-app notifications and displays them to the user.

[1369] Step 8: Provide guidance

[1370] Subject: Terminal

[1371] The terminal provides guidance to the user based on the received notification.

[1372] Input: Notification message

[1373] Output: Guidance display screen

[1374] Specific operation: The device displays the guidance, "The price of this property is higher than the market price. The appropriate price is XX yen."

[1375] Step 9: Enter property information

[1376] Subject: User

[1377] The user uses the terminal to input property information and transaction conditions.

[1378] Input: Property information, transaction terms

[1379] Output: Input data

[1380] Specific operation: The user enters the property price, location, terms of transaction, etc. into the form.

[1381] Step 10: Confirm data transmission

[1382] Subject: User

[1383] The user checks the entered data and sends it to the server.

[1384] Input: Input data

[1385] Output: Transmission result

[1386] Specific Action: The user clicks the submit button to submit the data.

[1387] Step 11: Check notifications

[1388] Subject: User

[1389] The user checks the notification from the server.

[1390] Input: Notification message

[1391] Output: Understanding the notification content

[1392] What happens: The user opens an email or in-app notification and checks the content.

[1393] Step 12: Review the terms of the transaction

[1394] Subject: User

[1395] The user reviews the terms of the transaction based on the notification.

[1396] Input: Notification message, terms and conditions

[1397] Output: Modified trading conditions

[1398] Specific operation: The user corrects the price and conditions to the appropriate one and sends it back to the server.

[1399] (Application example 3)

[1400] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1401] Conventional housing sales platform systems lacked sufficient means to determine whether a transaction between a seller and a buyer was appropriate, making it difficult to aggregate and provide information, especially for the sale of vacant homes in rural areas. Furthermore, users had limited means to check property details and obtain information about living in rural areas, making it difficult to promote relocation to rural areas.

[1402] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1403] In this invention, the server includes a means for a generative AI to act as a consultant, connecting sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether a transaction is appropriate, a means for aggregating vacant house information and providing it to users, a means for providing virtual tours, a means for providing lifestyle information, and an AI chatbot means for providing information in response to user questions. This makes it possible to smoothly sell and buy vacant houses in rural areas while ensuring the appropriateness of transactions. Furthermore, users can more specifically consider moving to rural areas through virtual tours and lifestyle information.

[1404] "Generative AI" refers to artificial intelligence that generates new information and content based on data.

[1405] A "consultant" is a professional who has specialized knowledge and provides advice and guidance in a particular field.

[1406] "P2P" stands for peer-to-peer, a networking method in which individual devices communicate directly without going through a central server.

[1407] A "transaction" is the act of exchanging goods or services between a seller and a buyer.

[1408] "Fair" means that it is justifiable based on laws and regulations and market prices.

[1409] "Vacant house information" refers to information about houses that are not currently in use.

[1410] "Aggregation" means combining multiple pieces of information into one.

[1411] "User" means a person who uses the system or service.

[1412] A "virtual tour" is a service that allows you to virtually tour a property or location using computer technology.

[1413] "Lifestyle information" refers to information necessary for daily life (e.g., transportation, medical care, education, etc.).

[1414] An "AI chatbot" is a program that uses artificial intelligence to interact with users.

[1415] A system for carrying out this invention is configured as follows: The server includes means for connecting sellers and buyers via P2P using generative AI, means for supporting transactions between sellers and buyers, means for determining whether a transaction is appropriate, means for aggregating vacant house information and providing it to users, means for providing virtual tours, means for providing lifestyle information, and AI chatbot means for providing information in response to user questions.

[1416] Program processing explanation

[1417] 1. Collection and provision of vacant house information

[1418] The server aggregates information on vacant houses in local areas by retrieving information from external databases and APIs, allowing users to easily view information on vacant houses in local areas through their smartphones or head-mounted displays (HMDs).

[1419] 2. Providing virtual tours

[1420] The server generates 3D models and 360-degree views based on the acquired vacant property information and provides users with a virtual tour, allowing them to check the property details without actually visiting the property.

[1421] 3. Transaction Appropriateness Assessment

[1422] The server uses generative AI to analyze the property price and transaction conditions, and evaluates the appropriateness of the transaction based on market prices and laws and regulations. If it is determined to be inappropriate, it notifies both the seller and the buyer and encourages them to conduct a fair transaction.

[1423] 4. Providing information on daily life

[1424] The server retrieves information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.) from external databases and APIs and provides it to users, allowing them to specifically consider moving to rural areas.

[1425] 5. AI Chatbots

[1426] The server is equipped with an AI chatbot that provides information in response to user questions. When users input their questions in natural language, the chatbot provides the appropriate information.

[1427] Hardware and software used

[1428] Hardware: Server, smartphone, head-mounted display (HMD)

[1429] Software: Generative AI models, databases, APIs, chatbot platforms

[1430] Specific examples

[1431] For example, if a user is looking for a vacant house in a rural area, they can use a smartphone app to search for property information and take a virtual tour. The app evaluates the suitability of the transaction and displays a notification if it is not suitable. It also provides information about daily life in the rural area (e.g., the nearest hospitals and schools, transportation access, etc.).

[1432] Prompt Sentence Examples

[1433] "I'm looking for a vacant house in a rural area. Please rate whether the transaction for property ID 123 is appropriate. Also, please let me know about living information in the area."

[1434] In this way, users can enter questions in natural language and the AI ​​chatbot will respond and provide information.

[1435] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1436] Step 1:

[1437] The server retrieves local vacant house information from external databases and APIs. The region is specified as input, and a list of vacant house information is obtained as output. Specifically, the server sends an API request and stores the retrieved data in an internal database.

[1438] Step 2:

[1439] The server generates 3D models and 360-degree views based on the acquired vacant property information. The input is the vacant property information, and the output is the data for the virtual tour. Specifically, the server uses 3D modeling software to create a virtual model of the property, which users can access.

[1440] Step 3:

[1441] Users can take virtual tours using a smartphone or a head-mounted display (HMD). The input is the data for the virtual tour, and the output is a visual experience for the user. Specifically, the user launches the application and checks the property details.

[1442] Step 4:

[1443] The server uses generative AI to analyze the property price and transaction terms, and evaluates the appropriateness of the transaction based on market prices and laws and regulations. The property price and transaction terms are input, and the appropriateness evaluation result is obtained as output. Specifically, the server inputs the data into the AI ​​model and calculates the evaluation result.

[1444] Step 5:

[1445] If the server determines that the transaction is invalid, it notifies both the seller and the buyer. The input is the validity evaluation result, and the output is a notification message. Specifically, the server sends a message through the notification system.

[1446] Step 6:

[1447] The server retrieves information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.) from external databases and APIs and provides it to users. The region is specified as input, and lifestyle information is obtained as output. Specifically, the server sends an API request and displays the retrieved data to the user.

[1448] Step 7:

[1449] Users check lifestyle information using smartphones or head-mounted displays (HMDs). The lifestyle information is the input, and the user's understanding is the output. Specifically, users view the information through an application.

[1450] Step 8:

[1451] The server is equipped with an AI chatbot that provides information in response to user questions. The input is the user's question, and the output is an answer. Specifically, the server uses the chatbot platform to analyze the question and generate an appropriate answer.

[1452] Step 9:

[1453] Users input questions to an AI chatbot using a smartphone or head-mounted display (HMD). The input is the user's question, and the output is the chatbot's answer. Specifically, the user inputs a question through the application and receives an answer.

[1454] 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.

[1455] "Example 1"

[1456] One embodiment of the present invention is a home buying and selling platform system in which generative AI uses an emotion engine to recognize the emotions of sellers and buyers. This emotion engine analyzes emotions from the text and voice information entered into the system by the seller and buyer. For example, if a seller enters text such as "This house is full of memories, so I want to sell it to someone who will cherish it," the emotion engine will recognize the seller's "attachment" and "expectations." "Example 2"

[1457] It also includes a means to optimize matching based on the emotions of sellers and buyers using an emotion engine. Specifically, it recognizes the seller's "feelings" and "expectations" and then searches for a buyer who meets those expectations. For example, if a buyer enters text such as "I like old houses and would like to carefully renovate them and live in them," it will match that buyer with the aforementioned seller.

[1458] "Example 3"

[1459] Furthermore, it also includes a means of using an emotion engine to manage the progress of a transaction based on the emotions of the seller and buyer. Specifically, it recognizes the emotions of the seller and buyer at each step of the transaction and manages the progress of the transaction accordingly. For example, if a buyer enters text such as "I'm worried because the contract is moving too quickly," it will recognize that emotion and take measures such as temporarily delaying the progress of the transaction.

[1460] The processing flow of each embodiment will be described below.

[1461] "Example 1"

[1462] Step 1: The seller enters their property information into the system along with their sentiment as text or voice information.

[1463] Step 2: The generative AI uses an emotion engine to analyze the seller's emotions from the input information.

[1464] Step 3: Save the analysis results in a database.

[1465] "Example 2"

[1466] Step 1: The buyer enters the property information they are looking for into the system along with their feelings as text or voice information.

[1467] Step 2: The generative AI uses an emotion engine to analyze the buyer's emotions from the input information.

[1468] Step 3: Compare the analysis results with the seller sentiment stored in the database to find matching sellers.

[1469] Step 4: Notify the seller and buyer of the matching results.

[1470] "Example 3"

[1471] Step 1: The seller and buyer initiate a transaction.

[1472] Step 2: At each step of the transaction, the seller and buyer input their emotions as text or voice information.

[1473] Step 3: The generative AI uses an emotion engine to analyze the emotions of the seller and buyer from the input information.

[1474] Step 4: Manage the progress of the transaction based on the analysis results.

[1475] Example 1

[1476] Next, a description will be given of Example 1 of Form 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."

[1477] Conventional housing sales platforms have difficulty matching buyers and sellers while taking into full consideration the needs and feelings of the buyers and sellers, resulting in problems such as poor transaction accuracy and low satisfaction. Furthermore, there have been issues with transactions not progressing due to a lack of appropriate matching, even in the case of vacant houses in rural areas.

[1478] 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.

[1479] In this invention, the server includes a means for connecting sellers and buyers via P2P using a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for collecting information on sellers and buyers, a means for analyzing the emotions of sellers and buyers using an emotion engine, a means for optimally matching sellers and buyers based on their conditions and emotions using generative AI, and a means for notifying the sellers and buyers of the matching results. This enables optimal matching that takes into account the needs and emotions of sellers and buyers, improving the appropriateness and satisfaction of transactions. It can also be applied to the sale and purchase of vacant homes in rural areas, which is expected to promote transactions.

[1480] "Generative AI" is artificial intelligence that makes optimal matches based on information about sellers and buyers.

[1481] A "consultant" is an expert who acts as a P2P link between sellers and buyers.

[1482] "Transaction aids" are methods and tools used to facilitate transactions between buyers and sellers.

[1483] "Means for determining whether a transaction is fair" refers to methods or tools for evaluating whether the content of a transaction is fair and fair.

[1484] "Information gathering means" are the methods and tools used to gather the necessary data from sellers and buyers.

[1485] An "emotion engine" is a technology that analyzes emotions from text and voice information entered by sellers and buyers.

[1486] "Matching means" are methods or tools that suggest optimal combinations based on the conditions and feelings of the seller and buyer.

[1487] "Means for notifying matching results" refers to methods or tools for informing sellers and buyers of the matching results proposed by generative AI.

[1488] "Vacant house sales in rural areas" refers to transactions involving the sale and purchase of vacant houses located in rural areas.

[1489] MODE FOR CARRYING OUT THE INVENTION

[1490] This invention relates to a home buying and selling platform system that connects sellers and buyers via P2P using generative AI and an emotion engine. A specific embodiment of this system will be described below.

[1491] System configuration

[1492] This system consists of three main elements: a server, a terminal, and a user. The server is equipped with a generative AI and an emotion engine, and is responsible for collecting, analyzing, and matching information between sellers and buyers. The terminal is a device through which sellers and buyers input information and receive matching results. The user is an individual or corporation that plays the role of a seller or buyer.

[1493] Program processing

[1494] The server first collects the information entered by the user. Sellers enter detailed property information and asking prices, while buyers enter the conditions and budget for the property they are looking for. This information is collected through a dedicated web form or mobile application.

[1495] Next, the server uses an emotion engine to analyze emotions from the text and voice information entered by the user. The emotion engine extracts emotions using natural language processing technology. For example, if a seller enters text such as, "This house is full of memories, so I want to sell it to someone who will cherish it," the emotion engine will recognize the seller's "attachment" and "expectations."

[1496] The server then uses generative AI to perform optimal matching based on the collected information and the results of sentiment analysis. The generative AI considers the conditions and emotions of the seller and buyer to propose the optimal combination of property and buyer. This proposal is then sent to the seller and buyer's devices.

[1497] Specific examples

[1498] For example, if a seller enters the following information:

[1499] Property details: 3LDK, 10-year-old building, 10-minute walk from the station

[1500] Asking price: 30 million yen

[1501] Emotional information: "This house is full of memories, so I want to sell it to someone who will cherish it."

[1502] On the other hand, suppose the buyer enters the following information:

[1503] Desired property conditions: 3LDK, within 15 minutes' walk from the station

[1504] Budget: 35 million yen

[1505] Emotional information: "I'm looking for a home where my family can live for a long time."

[1506] The server collects this information and analyzes it using an emotion engine to make the best match, taking into account the seller's "attachment" and the buyer's feelings of "looking for a home where the family can live for a long time."

[1507] Example prompts to input to the generative AI model:

[1508] Seller Information:

[1509] Property details: 3LDK, 10-year-old building, 10-minute walk from the station

[1510] Asking price: 30 million yen

[1511] Emotional information: "This house is full of memories, so I want to sell it to someone who will cherish it."

[1512] Buyer Information:

[1513] Desired property conditions: 3LDK, within 15 minutes' walk from the station

[1514] Budget: 35 million yen

[1515] Emotional information: "I'm looking for a home where my family can live for a long time."

[1516] Based on this information, we will propose the best match for you.

[1517] In this way, optimal matching that takes into account the needs and feelings of the seller and buyer becomes possible, improving the fairness and satisfaction of the transaction. It can also be applied to the sale of vacant houses in rural areas, and is expected to promote transactions.

[1518] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1519] Step 1:

[1520] The user enters information

[1521] Users (sellers and buyers) enter the necessary information using a dedicated web form or mobile application. Sellers enter detailed property information and desired price, while buyers enter the desired property conditions and budget. Users also enter emotional information.

[1522] Input: Seller's property information, asking price, sentiment information, buyer's desired conditions, budget, sentiment information

[1523] Output: The entered information is sent to the server

[1524] Specific behavior:

[1525] The seller enters the following information into a web form: "3LDK, 10-year-old building, 10-minute walk from the station, asking price 30 million yen."

[1526] A buyer enters the following into the mobile app: "3LDK, within 15 minutes' walk from the station, budget 35 million yen."

[1527] Step 2:

[1528] The server collects information

[1529] The server collects the information entered by the user and stores it in a database.

[1530] Input: Information entered by the user

[1531] Output: Information stored in the database

[1532] Specific behavior:

[1533] The server stores the seller's input information in a database.

[1534] The server stores the buyer's input information in a database.

[1535] Step 3:

[1536] The server analyzes emotions using an emotion engine

[1537] The server uses an emotion engine to analyze emotions from text and voice information entered by the user. The emotion engine extracts emotions using natural language processing technology.

[1538] Input: User text and voice information stored in a database

[1539] Output: Parsed emotion information

[1540] Specific behavior:

[1541] The server analyzes the seller's text, such as "This house is full of memories, so I would like to sell it to someone who will cherish it," and extracts the seller's "attachment" and "expectations."

[1542] The server analyzes the buyer's text, "I'm looking for a home where my family can live for a long time," and extracts "security" and "expectations."

[1543] Step 4:

[1544] The server performs matching using generative AI

[1545] The server uses generative AI to perform optimal matching based on the collected information and the results of sentiment analysis. The generative AI considers the conditions and emotions of both the seller and buyer to propose the best combination of property and buyer.

[1546] Input: Information stored in the database, analyzed emotional information

[1547] Output: Best matching result

[1548] Specific behavior:

[1549] The server inputs the seller's property information and emotional information into the generative AI.

[1550] The server inputs the buyer's desired conditions and emotional information into the generative AI.

[1551] The generative AI calculates the optimal match and returns the results to the server.

[1552] Step 5:

[1553] The server notifies the match result

[1554] The server notifies the seller and buyer of the matching results obtained from the generative AI via email or in-app notifications.

[1555] Input: Best match result

[1556] Output: Matching results notified to sellers and buyers

[1557] Specific behavior:

[1558] The server notifies the seller that "we have found a buyer interested in your property."

[1559] The server notifies the buyer that "We have found a property that meets your requirements."

[1560] Step 6:

[1561] The user checks the matching results

[1562] Users receive notifications from the server and check the matching results. Sellers and buyers can then communicate within the system to negotiate in detail.

[1563] Input: Notification from the server

[1564] Output: Confirmed match results, contact information

[1565] Specific behavior:

[1566] The seller opens the in-app notification to check the match results.

[1567] The buyer opens the email and checks the matching results.

[1568] (Application example 1)

[1569] Next, a description will be given of Application Example 1 of Form 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."

[1570] Conventional home buying and selling platform systems do not take into account the emotions of buyers and sellers when matching, which can result in low transaction satisfaction. Furthermore, real-time notification of matching results and improvements to matching accuracy based on feedback are not sufficiently implemented, resulting in issues with transaction efficiency and accuracy.

[1571] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for connecting sellers and buyers via P2P using a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a sentiment analysis means for analyzing the sentiments of the seller and buyer, a means for optimal matching based on information about the seller and buyer, a means for notifying the matching results in real time, and a means for collecting feedback from the seller and buyer and improving matching accuracy. This enables optimal matching that takes into account the sentiments of the seller and buyer, thereby improving transaction satisfaction and efficiency.

[1572] "Generative AI" is artificial intelligence that makes optimal matches based on information about sellers and buyers.

[1573] A "consultant" is an expert who acts as a P2P link between sellers and buyers.

[1574] "P2P" refers to a peer-to-peer network structure in which sellers and buyers transact directly.

[1575] "Transaction support means" are support functions that facilitate transactions between sellers and buyers.

[1576] "Means for determining whether a transaction is appropriate" refers to a function that evaluates whether the transaction content is fair and appropriate.

[1577] "Sentiment analysis means" is a technology for analyzing the emotions of sellers and buyers.

[1578] "Matching means" is a function that finds the most suitable trading partner based on information about the seller and buyer.

[1579] "Real-time notification means" is a function that instantly notifies sellers and buyers of matching results.

[1580] "Feedback collection means" is a function that collects opinions and ratings from sellers and buyers.

[1581] "Means for improving matching accuracy" refers to a function that improves matching accuracy based on collected feedback.

[1582] As an embodiment of this invention, we provide a system in which an emotion-aware real estate matching application is installed on a smartphone or smart glasses. This system uses generative AI and an emotion analysis engine to analyze the emotions of sellers and buyers and perform optimal matching.

[1583] System configuration

[1584] 1. Hardware:

[1585] Smartphone or smart glasses

[1586] server

[1587] 2. Software:

[1588] Generative AI models (e.g., OpenAI API)

[1589] Sentiment analysis engines (e.g., TextBlob library)

[1590] Matching Algorithm

[1591] Real-time notification system

[1592] Processing flow

[1593] Emotion analysis

[1594] Users enter text or voice information into the system as sellers or buyers. The server uses a sentiment analysis engine to analyze emotions from this information. For example, if a seller enters, "This house is full of memories, so I want to sell it to someone who will cherish it," the sentiment analysis engine will recognize emotions such as "attachment" and "expectations."

[1595] matching

[1596] The server uses a generative AI model to find the best match based on the seller and buyer information. The generative AI model matches based on prompts like the following:

[1597] Seller information: This house is full of memories and I would like to sell it to someone who will cherish it.

[1598] Buyer Information: I am looking for a quiet home where I can spend time with my family.

[1599] Make the best match.

[1600] Real-time notifications

[1601] Matching results are notified to users in real time, allowing them to instantly check the progress of their transactions.

[1602] Gathering feedback and improving accuracy

[1603] After a transaction is completed, the server collects feedback from the seller and buyer, which is used to improve the accuracy of the matching algorithm.

[1604] Specific examples

[1605] For example, if a seller enters, "This house is full of memories, so I want to sell it to someone who will cherish it," and a buyer enters, "I'm looking for a house in a quiet environment where I can spend time with my family," the generative AI model will use this information to find the optimal match. The sentiment analysis engine will analyze the seller's emotions, such as "attachment" and "expectations," and provide matching results that take these into consideration.

[1606] In this way, optimal matching that takes into account the emotions of sellers and buyers becomes possible, improving transaction satisfaction and efficiency.

[1607] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1608] Step 1:

[1609] Users input text or voice information into the system as sellers or buyers. For sellers, the input information is detailed property information and desired price, and for buyers, the desired property conditions and budget. This information is sent from the terminal to the server.

[1610] Step 2:

[1611] The server uses a sentiment analysis engine (e.g., TextBlob library) to analyze emotions from input text and voice information. For example, if a seller inputs, "This house is full of memories, so I want to sell it to someone who will cherish it," the sentiment analysis engine will recognize emotions such as "attachment" and "expectations." The input is text information, and the output is the result of the sentiment analysis.

[1612] Step 3:

[1613] The server generates a prompt based on the seller and buyer information. The generated prompt is passed to the generative AI model. For example, the following prompt is generated:

[1614] Seller information: This house is full of memories and I would like to sell it to someone who will cherish it.

[1615] Buyer Information: I am looking for a quiet home where I can spend time with my family.

[1616] Make the best match.

[1617] The input is the seller and buyer information, and the output is a prompt statement.

[1618] Step 4:

[1619] The server uses a generative AI model (e.g., OpenAI API) to find the best match based on the prompt. The generative AI model analyzes the seller and buyer information to find the best trading partner. The input is the prompt, and the output is the matching result.

[1620] Step 5:

[1621] The server notifies the user of the matching results in real time. The notification is sent to the terminal, allowing the user to immediately check the progress of the transaction. The input is the matching result, and the output is the real-time notification.

[1622] Step 6:

[1623] After the transaction is completed, the server collects feedback from the seller and the buyer. The feedback is information such as the satisfaction level of the transaction and areas for improvement. The input is the feedback from the user, and the output is the collected feedback data.

[1624] Step 7:

[1625] The server improves the accuracy of the matching algorithm based on the collected feedback. By analyzing the feedback data and incorporating it into the next match, more accurate matching becomes possible. The input is the feedback data, and the output is an improved matching algorithm.

[1626] Example 2

[1627] Next, a description will be given of Example 2 of Form 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."

[1628] Conventional home buying and selling platform systems often failed to match buyers and sellers with due consideration for their feelings and needs, resulting in transactions not progressing smoothly. Furthermore, the procedures for submitting necessary documents, signing, and making payments were cumbersome, placing a heavy burden on users. Furthermore, there was a lack of systems that could be applied to the sale of vacant homes in rural areas.

[1629] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1630] In this invention, the server includes a means for the generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for optimizing matching based on the emotions of the seller and buyer using an emotion engine, and a means for the generative AI to manage the progress of the transaction and issue instructions to smoothly proceed with procedures such as the submission and signing of necessary documents and payment. This enables optimal matching that takes into account the emotions and needs of the seller and buyer, and ensures smooth progress of the transaction. It also simplifies the necessary procedures and reduces the burden on users. Furthermore, a system that can be applied to the sale and purchase of vacant houses in rural areas is provided.

[1631] "Generative AI" is an artificial intelligence that acts as a consultant between sellers and buyers and manages the progress of transactions.

[1632] "P2P" is a peer-to-peer communication method in which sellers and buyers transact directly.

[1633] "Transaction support tools" are functions and processes that facilitate transactions between buyers and sellers.

[1634] "Means for determining whether a transaction is appropriate" refers to the function of evaluating whether the transaction is legally and ethically appropriate.

[1635] The "emotion engine" is a technology that analyzes the emotions of sellers and buyers and makes optimal matches based on that.

[1636] "Means for optimizing matching" is a function that takes into account the emotions and needs of sellers and buyers to find the best trading partner.

[1637] "Means for managing the progress of a transaction" refers to a function that monitors each step of a transaction and instructs the necessary procedures.

[1638] "Means for issuing instructions to smoothly proceed with procedures such as document submission, signatures, and payment" refers to a function that instructs the user to submit documents required for the transaction, obtain signatures, and complete payment procedures.

[1639] "Vacant house sales in rural areas" refers to transactions involving the sale and purchase of vacant houses located in rural areas.

[1640] MODE FOR CARRYING OUT THE INVENTION

[1641] This invention is a system that supports transactions between sellers and buyers, and uses generative AI and an emotion engine to manage the progress of transactions and optimize matching based on emotions. Specific embodiments of this system are described below.

[1642] System configuration

[1643] This system consists of three main components: a server, a terminal, and a user. The server is equipped with a generative AI and an emotion engine, and manages the progress of transactions and performs matching based on emotions. The terminal is a device that allows users to access the system and input the necessary information. Users act as sellers and buyers and conduct transactions.

[1644] Hardware and software used

[1645] Server: A server with a high-performance processor and large memory capacity is required. Specifically, a server with an Intel Xeon processor or AMD EPYC processor is suitable.

[1646] Generative AI: Built using deep learning frameworks such as TensorFlow and PyTorch.

[1647] Emotion engine: An emotion analysis engine that uses natural language processing (NLP) technology, specifically models such as BERT and GPT-3.

[1648] Terminal: The device through which the user accesses the service, including PCs, smartphones, tablets, etc.

[1649] System Operation

[1650] The server manages the progress of the transaction using generative AI. Specifically, it performs the following steps:

[1651] Submitting required documents

[1652] Get signatures

[1653] Payment procedure

[1654] To ensure that these procedures go smoothly, the server issues instructions to users (sellers and buyers). For example, when a deadline for submitting documents approaches, the server sends reminders to users.

[1655] The server also uses an emotion engine to match buyers and sellers based on their emotions. Specifically, it recognizes the seller's "feelings" and "expectations" and searches for buyers who match those. For example, if a buyer enters text such as "I like old houses and would like to carefully renovate them and live in them," the server will match that buyer with the aforementioned seller.

[1656] Specific examples

[1657] As a concrete example, consider the following scenario:

[1658] Seller A thinks, "This house is full of family memories, so I want to sell it to someone who will cherish it."

[1659] Buyer B thinks, "I like old houses and would like to carefully renovate them and live in them."

[1660] In this case, the server uses an emotion engine to match seller A with buyer B.

[1661] Prompt Sentence Examples

[1662] Example prompts to input to the generative AI model:

[1663] Seller's feelings: This house is filled with family memories, so I want to sell it to someone who will cherish it.

[1664] Buyer's feelings: They love old houses and want to carefully renovate them and live in them.

[1665] Based on this prompt, the server matches seller A with buyer B.

[1666] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1667] Step 1:

[1668] User Registration and Login

[1669] Input: A user accesses the system using a terminal and enters their name, email address, and password.

[1670] Data processing: The server stores the entered information in a database.

[1671] Output: A registration completion email is sent to the user.

[1672] Specific operation: The user opens a browser on their device, accesses the system's website, enters the required information in the registration form, and clicks the Register button. The server saves the entered information in the database and sends an email confirming registration. The user logs in using the registered information.

[1673] Step 2:

[1674] Entering seller and buyer information

[1675] Input: Sellers enter text about the property details and their feelings, and buyers enter text about the conditions and feelings about the property they are looking for.

[1676] Data processing: The server stores this information in a database.

[1677] Output: The seller and buyer information is saved in the database.

[1678] Specific operation: Sellers upload property photos and descriptions and enter emotional text. Buyers enter the desired property conditions (e.g., price range, location, layout) and enter emotional text. The server stores this information in a database.

[1679] Step 3:

[1680] Emotion analysis using an emotion engine

[1681] Input: Seller and buyer input information

[1682] Data processing: The server uses an emotion engine to analyze the information entered by the seller and buyer and extracts emotion keywords.

[1683] Output: Sentiment analysis results are obtained.

[1684] Specific operation: The server starts the emotion engine and analyzes the input information of the seller and buyer. The emotion engine performs text analysis and extracts emotion keywords.

[1685] Step 4:

[1686] Transaction progress management using generative AI

[1687] Input: Seller and buyer information and sentiment analysis results

[1688] Data processing: The server uses generative AI to manage the progress of the transaction and calculates the deadlines for submitting required documents and the timing for obtaining signatures.

[1689] Output: A reminder is sent to the user.

[1690] How it works: The server manages the progress of the transaction using generative AI, which sends reminders to the user, such as "The deadline for document submission is approaching."

[1691] Step 5:

[1692] Matching and Notifications

[1693] Input: Sentiment analysis results and seller and buyer information

[1694] Data processing: The server matches sellers and buyers based on the analysis results of the emotion engine.

[1695] Output: If a match is found, notifications are sent to the seller and buyer.

[1696] Specific operation: The server matches sellers and buyers based on the analysis results of the emotion engine. If a match is made, the server sends a notification to the seller and buyer saying "Matching has been made."

[1697] Step 6:

[1698] Submitting documents and obtaining signatures

[1699] Input: Required documents and signature information

[1700] Data processing: The server checks the submitted document and asks the user to sign if a signature is required.

[1701] Output: The submitted documents and signatures are saved on the server.

[1702] Specific operation: The user uploads the required documents using the device. The server checks the submitted documents and notifies the user that a signature is required if one is required. The user signs the documents using the device and sends them to the server.

[1703] Step 7:

[1704] Completing the payment process

[1705] Input: Payment information

[1706] Data processing: The server initiates the payment process and provides the necessary information to the user.

[1707] Output: The payment is confirmed to be successful and the transaction is confirmed.

[1708] Specific operation: The server starts the payment process and notifies the user, "Please complete the payment process." The user completes the payment using the terminal. The server confirms that the payment has been completed and notifies the user that the transaction is complete.

[1709] (Application example 2)

[1710] Next, a description will be given of Application Example 2 of Form 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."

[1711] Conventional home buying and selling platform systems lacked sufficient support to facilitate smooth transactions between sellers and buyers, particularly because they did not match buyers based on their emotions, resulting in low transaction satisfaction. Furthermore, there was a lack of means to manage the progress of transactions in real time and smoothly carry out procedures such as the submission and signing of necessary documents and payments. Furthermore, there was also the issue of a lack of systems applicable to the sale of vacant homes in rural areas.

[1712] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1713] In this invention, the server includes a means for connecting sellers and buyers via P2P using a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for optimizing matching based on the emotions of the seller and buyer using an emotion engine, and a means for managing the progress of the transaction via an application installed on a smartphone and smoothly proceeding with procedures such as the submission and signing of necessary documents and payment. This enables optimal matching based on the emotions of the seller and buyer, manages the progress of the transaction in real time, and smoothly proceeds with the necessary procedures. It also provides a system that can be applied to the sale and purchase of vacant houses in rural areas.

[1714] "Generative AI" is a system that uses artificial intelligence technology to assist transactions between buyers and sellers and manage the progress of transactions.

[1715] A "consultant" is someone who connects sellers and buyers via P2P and provides advice and support to ensure smooth transactions.

[1716] "P2P" stands for peer-to-peer and refers to a method of direct transactions between sellers and buyers.

[1717] "Means to support transactions" refers to functions that support various procedures to smoothly advance transactions between sellers and buyers.

[1718] "Means for determining whether a transaction is appropriate" refers to the function of evaluating whether the transaction is legally and ethically appropriate.

[1719] The "emotion engine" is a technology that analyzes the emotions of sellers and buyers and makes optimal matches based on those emotions.

[1720] "Means for optimizing matching" refers to a function that finds the best trading partner based on the emotions and needs of sellers and buyers.

[1721] An "application installed on a smartphone" is software that runs on a smartphone, manages the progress of transactions, and assists with procedures such as the submission and signing of necessary documents and payment.

[1722] "Means for managing transaction progress" refers to the ability to track each stage of a transaction in real time and prompt necessary actions.

[1723] "Means for smoothly carrying out procedures such as the submission, signing, and payment of necessary documents" refers to functions that enable efficient procedures such as the submission, signing, and payment of documents required for a transaction.

[1724] "A system that can also be applied to the sale and purchase of vacant houses in rural areas" refers to a system that can handle the sale and purchase of vacant houses not only in urban areas but also in rural areas.

[1725] A system for implementing this invention is configured using a generative AI, an emotion engine, and a smartphone application. A specific embodiment of the system will be described below.

[1726] System Configuration

[1727] 1. Hardware:

[1728] Server: A high-performance server for running generative AI models and emotion engines.

[1729] Smartphone: A device through which users conduct transactions.

[1730] 2. Software:

[1731] Generative AI model: An AI model built using TensorFlow and Keras.

[1732] Sentiment engine: Uses sentiment analysis APIs such as IBM Watson.

[1733] Smartphone application: Developed using Python, JavaScript, React Native, etc.

[1734] Data processing and calculation

[1735] 1. Data Collection:

[1736] The server collects input data (text, images, etc.) from sellers and buyers.

[1737] For example, a seller might enter, "This house is filled with many memories. I would like to sell it to someone who will cherish it."

[1738] 2. Data Preprocessing:

[1739] The server preprocesses the text data using an NLP library (e.g., spaCy), specifically tokenizing it and removing stop words.

[1740] 3. Emotion analysis:

[1741] The server uses a sentiment analysis API to analyze the sentiment of sellers and buyers.

[1742] For example, if a buyer enters, "I like old houses and would like to carefully renovate them and live in them," that sentiment is analyzed.

[1743] 4. Generative AI Models:

[1744] The server runs a generative AI model built using TensorFlow and Keras and manages the progress of transactions.

[1745] For example, it tracks each stage of a transaction in real time and prompts you to take any necessary action.

[1746] 5. Matching Algorithm:

[1747] The server implements an algorithm that performs optimal matching based on emotional data of sellers and buyers.

[1748] For example, it matches the seller's feeling of "strong attachment" with the buyer's feeling of "wanting to carefully renovate an old house."

[1749] Examples and prompts

[1750] Specific examples

[1751] 1. Seller Input:

[1752] "This house is filled with so many memories. I would like to sell it to someone who will cherish it."

[1753] 2. Buyer Input:

[1754] "I like old houses and would like to carefully renovate them and live in them."

[1755] Prompt Sentence Examples

[1756] Seller sentiment analysis prompt:

[1757] Seller's text: "This house is filled with memories. I would like to sell it to someone who will cherish it."

[1758] Analyze the seller's sentiment.

[1759] Buyer sentiment analysis prompt:

[1760] Buyer's text: "I love old houses and would like to carefully renovate them and live in them."

[1761] Analyze buyer sentiment.

[1762] Matching prompt:

[1763] Seller's sentiment: "I have a strong emotional attachment to this product"

[1764] Buyer's sentiment: "I want to carefully renovate an old house."

[1765] Match these two together.

[1766] In this way, a system is built that achieves optimal matching based on the emotions of sellers and buyers.

[1767] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1768] Step 1:

[1769] A user launches a smartphone application and logs in as a seller or buyer.

[1770] Input: User login information (user ID, password)

[1771] Output: User authentication result (success / failure)

[1772] Specific operation: The smartphone application sends the user's login information to the server, which then refers to the database for authentication. If authentication is successful, the user can proceed to the next step.

[1773] Step 2:

[1774] The user enters information as a seller or buyer.

[1775] Input: Seller's property information and sentiment text, Buyer's desired conditions and sentiment text

[1776] Output: Verification result of the entered information (success / failure)

[1777] Specific operation: The smartphone application sends the information entered by the user to the server, which stores the information in a database. If the input is correct, the process proceeds to the next step.

[1778] Step 3:

[1779] The server pre-processes the input data of the seller and the buyer.

[1780] Input: Seller and buyer input data (text)

[1781] Output: Preprocessed text data

[1782] Specific operation: The server uses an NLP library (e.g., spaCy) to tokenize the text data and remove stop words. The preprocessed data is used in the next step.

[1783] Step 4:

[1784] The server performs sentiment analysis.

[1785] Input: Preprocessed text data

[1786] Output: Sentiment analysis results (sentiment scores and emotion tags)

[1787] Specific operation: The server uses an emotion analysis API (e.g., IBM Watson) to analyze the emotions of the seller and buyer. The analysis results are stored in a database.

[1788] Step 5:

[1789] The server manages the progress of the transaction using a generative AI model.

[1790] Input: Sentiment analysis results of sellers and buyers, transaction progress data

[1791] Output: Instructions and notifications about the progress of the transaction

[1792] How it works: The server runs a generative AI model built with TensorFlow and Keras to track each stage of the transaction in real time, notifying the user of any required actions (document submission, signature, payment, etc.).

[1793] Step 6:

[1794] The server matches buyers and sellers.

[1795] Input: Seller and buyer sentiment analysis results, needs data

[1796] Output: Matching results (information on the best trading partner)

[1797] Specific operation: The server runs an algorithm to find the best match based on the emotional and needs data of the seller and buyer. The matching results are notified to the user.

[1798] Step 7:

[1799] The user completes the transaction.

[1800] Input: Transaction documents, signatures, and payment information

[1801] Output: Transaction completion confirmation result (success / failure)

[1802] Specific operation: The user submits the necessary documents, signs, and completes the payment via the smartphone application. The server verifies this information and notifies the user that the transaction is complete.

[1803] Example 3

[1804] Next, a description will be given of Example 3 of Form Example 3. 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."

[1805] Conventional housing trading platform systems do not adequately assess the appropriateness of transactions or manage the emotions of sellers and buyers, resulting in a lack of transparency and reliability in transactions. Furthermore, there is a lack of information on vacant houses in rural areas and matching based on the needs of sellers and buyers, making it difficult to promote the sale of vacant houses in rural areas.

[1806] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1807] In this invention, the server includes a means for a generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for collecting data such as the property price, transaction conditions, market rates, and laws and regulations, a means for recognizing the emotions of sellers and buyers using an emotion engine and managing the progress of the transaction, and a means for aggregating information on vacant houses in rural areas and providing it to interested buyers. This improves the transparency and reliability of transactions and makes it possible to promote the buying and selling of vacant houses in rural areas.

[1808] "Generative AI" is an artificial intelligence technology that generates new information and models based on data.

[1809] A "consultant" is a person who has specialized knowledge and is tasked with providing advice and assistance in a particular field.

[1810] "P2P" is an abbreviation for Peer-to-Peer, a network type in which individual devices communicate directly without going through a central server.

[1811] "Fairness of transactions" refers to whether transactions are fair and reasonable based on market prices and laws and regulations.

[1812] An "emotion engine" is a technology that analyzes and recognizes human emotions from data such as text and voice.

[1813] "Vacant house information" refers to information about houses that are not currently in use and are available for sale or rent.

[1814] "Market going rates" refers to the general price range for a product in a particular market.

[1815] "Laws and regulations" refers to laws and regulations enacted by the national or local government.

[1816] "Data collection" is the process of gathering the necessary information from various sources.

[1817] The "transaction status" indicates the stage at which the transaction is in progress.

[1818] "Matching" is the process of matching the needs of sellers and buyers to find the optimal combination.

[1819] MODE FOR CARRYING OUT THE INVENTION

[1820] The present invention relates to a home buying and selling platform system using generative AI. This system includes a server, a terminal, and a user, and is implemented as follows.

[1821] 1. Generating the system program

[1822] The server generates the system's program using a generative AI model. This generative AI model is input with data such as property price, transaction conditions, market price, and laws and regulations. Specifically, it retrieves property information from a database and collects market price data and legal data via API.

[1823] 2. Explanation of program processing

[1824] The server executes the generated program and performs the following processes.

[1825] Transaction fairness assessment

[1826] The server analyzes the property price and transaction conditions, and evaluates the appropriateness of the transaction based on market rates and laws and regulations. This evaluation uses market and legal data stored in the database. For example, if the property price is more than 20% higher than the market rate, the server will determine that the transaction is "inappropriate."

[1827] Notification of suitability assessment results

[1828] The server notifies the seller and buyer of the results of the transaction suitability assessment. The results are sent to the seller and buyer via email or in-app notification. For example, a message may be sent saying, "This transaction is deemed unsuitable because it is priced higher than the market rate."

[1829] Aggregating and providing information on vacant houses in rural areas

[1830] The server aggregates information on vacant houses in local areas and provides it to interested buyers. It collects information on vacant houses from local governments and real estate agents and stores it in a database. When a buyer enters their desired conditions, the server lists properties that match the conditions and provides them to the buyer. For example, if a buyer enters conditions such as "3LDK, within a 10-minute walk from the station, budget of 20 million yen or less," the server will list properties that match the conditions.

[1831] Emotional engine trading management

[1832] The server uses an emotion engine to recognize the emotions of the seller and buyer and manages the progress of the transaction accordingly. The text entered by the seller and buyer is analyzed and the emotion engine recognizes emotions. For example, if a buyer enters "I'm worried because the contract is progressing too quickly," the server will recognize that emotion and temporarily delay the progress of the transaction.

[1833] 3. Examples and prompts

[1834] As a concrete example, the following scenario can be considered.

[1835] Examples of transaction fairness assessment

[1836] If the property price is higher than the market price, the server will determine that the transaction is not appropriate and notify the seller and buyer.

[1837] Example prompt: "If the property is priced above market value, please evaluate the transaction and let me know if it is not."

[1838] Specific examples of vacant house sales in rural areas

[1839] We collect information on vacant houses in local areas and provide properties that meet the buyer's desired conditions.

[1840] Example prompt: "Collect information on vacant houses in the local area and create a list of properties that meet the buyer's desired criteria."

[1841] A concrete example of transaction management using an emotion engine

[1842] If a buyer types, "I'm worried that the deal is moving too quickly," the server will recognize that sentiment and temporarily slow down the transaction.

[1843] Example prompt: "If the buyer feels anxious, acknowledge their feelings and temporarily delay the transaction."

[1844] The above is an embodiment of the present invention. This system improves the transparency and reliability of transactions, and makes it possible to promote the buying and selling of vacant houses in rural areas. The flow of the identification process in the third embodiment will be explained using FIG. 21.

[1845] Step 1:

[1846] Transaction data collection

[1847] The server collects data such as property prices, transaction conditions, market rates, laws and regulations, etc.

[1848] Input: Property information from the database, market price data and legal data via API

[1849] Data processing: Consolidating collected data and converting it into an analyzable format

[1850] Output: A consolidated transaction dataset

[1851] Specific operation: The server retrieves property information from the database, collects market price data and legal data through APIs, and consolidates this data into an analyzable format.

[1852] Step 2:

[1853] Transaction fairness assessment

[1854] The server evaluates the appropriateness of the transaction based on the collected data.

[1855] Input: Consolidated transaction dataset

[1856] Data calculations: Using generative AI models to compare property prices with market rates and check transaction conditions in accordance with laws and regulations

[1857] Output: Transaction fairness assessment results

[1858] Specific operation: The server uses the generative AI model to compare the property price with the market price and check the transaction conditions based on laws and regulations. For example, if the property price is more than 20% higher than the market price, it will determine that the transaction is "inappropriate."

[1859] Step 3:

[1860] Notification of suitability assessment results

[1861] The server notifies the seller and buyer of the results of the transaction suitability assessment.

[1862] Input: Transaction fairness assessment result

[1863] Data processing: Converting evaluation results into notification messages

[1864] Output: Notification messages to seller and buyer

[1865] What it does: The server sends the evaluation results to the seller and buyer via email or in-app notification, for example, a message saying, "This transaction is deemed unsuitable because it is priced higher than the market rate."

[1866] Step 4:

[1867] Aggregating and providing information on vacant houses in rural areas

[1868] The server aggregates information on vacant houses in the local area and provides it to interested buyers.

[1869] Input: Vacant house information from local governments and real estate agents

[1870] Data processing: Store vacant house information in a database and search based on buyers' desired conditions

[1871] Output: A list of properties that match the criteria

[1872] Specific operation: The server collects information on vacant houses from local governments and real estate agents and stores it in a database. When a buyer enters their desired conditions, the server lists properties that match the conditions and provides them to the buyer. For example, if the buyer enters the conditions "3LDK, within a 10-minute walk from the station, budget within 20 million yen," the server will list properties that match the conditions.

[1873] Step 5:

[1874] Emotional engine trading management

[1875] The server uses an emotion engine to recognize the emotions of the seller and the buyer and manages the progress of the transaction accordingly.

[1876] Input: Text entered by the seller and buyer

[1877] Data Computing: Sentiment engine analyzes text and recognizes emotions

[1878] Output: Adjusting trading progress based on sentiment

[1879] How it works: The server analyzes the text entered by the seller and buyer and recognizes emotions using an emotion engine. For example, if a buyer enters, "I'm worried because the contract is moving too quickly," the server will recognize that emotion and temporarily delay the transaction.

[1880] (Application example 3)

[1881] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1882] Conventional housing sales platform systems lack sufficient means for determining the appropriateness of a transaction, and do not manage the progress of the transaction while taking into account the feelings of the seller and buyer. Furthermore, when it comes to the sale of vacant houses in rural areas, the collection and provision of property information is not done efficiently, and there is insufficient effort to promote relocation to rural areas. This reduces the transparency and reliability of transactions, posing a challenge in preventing the effective use of vacant houses in rural areas.

[1883] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1884] In this invention, the server includes a means for generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for aggregating and providing property information, and a means for recognizing the emotions of sellers and buyers and managing the progress of the transaction. This will improve the transparency and reliability of transactions, as well as enable efficient buying and selling of vacant houses in rural areas and promote migration to rural areas.

[1885] "Generative AI" is an artificial intelligence technology that generates new information and content based on data.

[1886] A "consultant" is a professional with specialized knowledge who provides advice and assistance in a particular field.

[1887] "P2P" is an abbreviation for Peer-to-Peer, a networking method in which individual devices communicate directly without going through a central server.

[1888] A "transaction" is the act of buying and selling goods or services between a seller and a buyer.

[1889] "Fairness" is a standard for evaluating whether a transaction is fair based on laws and regulations and market prices.

[1890] "Property Information" means information containing detailed data and characteristics about real estate.

[1891] "Aggregation" is the act of bringing together dispersed information.

[1892] "Providing" is the act of handing over necessary information or services to another person.

[1893] "Emotions" refer to a person's psychological state or feelings.

[1894] "Recognition" is the act of understanding and grasping specific information or a situation.

[1895] "Progress" is the state that indicates the stage at which a particular process or task is.

[1896] "Management" is the act of planning, organizing, directing and controlling to achieve specific objectives.

[1897] A system for implementing this invention includes means for connecting sellers and buyers via P2P using generative AI, means for supporting transactions, means for determining the appropriateness of transactions, means for aggregating and providing property information, and means for recognizing the emotions of sellers and buyers and managing the progress of transactions.

[1898] System Program

[1899] This system is realized using the following hardware and software.

[1900] Hardware: Servers, smartphones, smart glasses

[1901] Software: Generative AI models (e.g., OpenAI's GPT-3), emotion recognition engines, database management systems, API communication libraries (e.g., requests)

[1902] Processing Description

[1903] Aggregation and provision of property information

[1904] The server retrieves property information for the specified area from the API and aggregates it in a database. When a user requests property information, the server extracts the relevant information from the database and provides it to the user's device.

[1905] Transaction fairness assessment

[1906] The server inputs the property price, market price, and legal requirements as prompts into the generative AI model to evaluate the suitability of the transaction. The evaluation results are notified to both the seller and the buyer.

[1907] Transaction progress management using emotion engine

[1908] The server passes the text entered by the user to an emotion recognition engine to recognize the emotion. Based on the results, the server adjusts the progress of the transaction. For example, if the user enters "I'm worried because the contract is progressing too quickly," the server will temporarily delay the progress of the transaction.

[1909] Specific examples

[1910] Providing property information

[1911] When a user requests, "Please tell me information about vacant houses in a specific local area," the server retrieves the relevant property information from the database and provides it to the user's terminal.

[1912] Transaction Due Diligence Prompt

[1913] Property price: 2.5 million yen, Market price: 3 million yen, Legal conditions: Compliant with laws and regulations. Is this transaction fair?

[1914] Transaction progress management prompts using emotion engine

[1915] User sentiment: I'm worried that the deal is moving too quickly. How do I manage the progress of the deal?

[1916] This will improve the transparency and reliability of transactions, as well as enable efficient buying and selling of vacant homes in rural areas and promote migration to rural areas.

[1917] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1918] Step 1:

[1919] The user requests property information using the terminal.

[1920] Input: A user requests, "Please tell me about vacant houses in a specific rural area."

[1921] Output: The request is sent to the server.

[1922] Specific operation: A user uses a smartphone or smart glasses to operate an application to request property information.

[1923] Step 2:

[1924] The server retrieves property information from the API and aggregates it in a database.

[1925] Input: The server receives the user's request.

[1926] Output: The property information is saved in the database.

[1927] Specific operation: The server uses the API communication library (e.g., requests) to obtain property information for the specified area and save it in the database management system.

[1928] Step 3:

[1929] The server extracts the relevant property information from the database and provides it to the user's terminal.

[1930] Input: The server searches the database for property information.

[1931] Output: The property information is sent to the user's device.

[1932] Specific operation: The server uses a database management system to search for the relevant property information and transmits it to the user's terminal.

[1933] Step 4:

[1934] The server inputs the property price, market price, and legal conditions as prompts into the generative AI model to evaluate the suitability of the transaction.

[1935] Input: Property price, market price, legal conditions

[1936] Output: Transaction appropriateness evaluation results

[1937] Specific operation: The server inputs a prompt sentence into a generative AI model (e.g., OpenAI's GPT-3) and obtains the evaluation result.

[1938] Example prompt sentence:

[1939] Property price: 2.5 million yen, Market price: 3 million yen, Legal conditions: Compliant with laws and regulations. Is this transaction fair?

[1940] Step 5:

[1941] The server notifies both the seller and the buyer of the evaluation results.

[1942] Input: Transaction appropriateness evaluation results

[1943] Output: Notification message

[1944] Specific operation: The server generates a notification message based on the evaluation result and sends it to the seller and buyer terminals.

[1945] Step 6:

[1946] Users input their emotions during the transaction.

[1947] Input: Text input about the user's emotions

[1948] Output: Input data to the emotion recognition engine

[1949] Specific operation: A user inputs text about emotions using a smartphone or smart glasses.

[1950] Step 7:

[1951] The server passes the user's input to an emotion recognition engine to recognize the emotion.

[1952] Input: Text input about the user's emotions

[1953] Output: Emotion recognition result

[1954] Specific operation: The server passes the text to the emotion recognition engine and obtains the emotion recognition results.

[1955] Step 8:

[1956] The server adjusts the progress of the transaction based on the emotion recognition results.

[1957] Input: Emotion recognition results

[1958] Output: Transaction progress adjustment instructions

[1959] Specific operation: The server adjusts the progress of the transaction based on the emotion recognition results, temporarily delaying the progress of the transaction if necessary.

[1960] Example prompt sentence:

[1961] User sentiment: I'm worried that the deal is moving too quickly. How do I manage the progress of the deal?

[1962] 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.

[1963] 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> ) 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.

[1964] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1965] 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.

[1966] [Third embodiment]

[1967] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1968] 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.

[1969] 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).

[1970] 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.

[1971] 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.

[1972] 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).

[1973] 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.

[1974] 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.

[1975] 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.

[1976] 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.

[1977] 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.

[1978] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1979] "Example 1"

[1980] The home buying and selling platform system of the present invention uses generative AI to connect sellers and buyers via P2P. The generative AI collects information from sellers (e.g., detailed property information, desired price, etc.) and information from buyers (e.g., desired property conditions, budget, etc.), and performs optimal matching based on this information.

[1981] "Example 2"

[1982] Furthermore, this system supports transactions between sellers and buyers. Specifically, the generative AI manages the progress of the transaction and provides instructions to smoothly carry out procedures such as the submission and signing of necessary documents and settlement.

[1983] "Example 3"

[1984] The system also has the ability to determine whether a transaction is appropriate. The generative AI analyzes the property price, transaction conditions, etc., and evaluates appropriateness based on market rates, laws, etc. If it is determined to be inappropriate, it notifies both the seller and the buyer and encourages them to conduct a fair transaction.

[1985] "Example 4"

[1986] This system can also be applied to the sale and purchase of vacant houses in rural areas. For example, it can aggregate information on vacant houses in rural areas and provide it to interested buyers. It can also provide information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.), encouraging people to move to rural areas.

[1987] The processing flow of each embodiment will be described below.

[1988] "Example 1"

[1989] Step 1: The generative AI collects information from the seller (e.g., detailed property information, asking price, etc.).

[1990] Step 2: Similarly, the generative AI collects information from the buyer (e.g., desired property conditions, budget, etc.).

[1991] Step 3: The generative AI performs optimal matching based on the collected information and connects sellers and buyers via P2P.

[1992] "Example 2"

[1993] Step 1: After matching the seller and buyer, the generative AI manages the progress of the transaction.

[1994] Step 2: The generative AI provides instructions to the seller and buyer to smoothly complete procedures such as submitting necessary documents, signing, and completing payments.

[1995] "Example 3"

[1996] Step 1: The generative AI analyzes the property price, transaction terms, etc.

[1997] Step 2: The generative AI evaluates the appropriateness of the transaction based on market prices, laws and regulations, etc.

[1998] Step 3: If the transaction is deemed inappropriate, the generative AI notifies both the seller and the buyer and encourages them to make the transaction appropriate.

[1999] "Example 4"

[2000] Step 1: The generative AI aggregates information on vacant houses in local areas.

[2001] Step 2: The generative AI provides aggregated vacant house information to interested buyers.

[2002] Step 3: The generative AI will also provide information necessary for living in rural areas (e.g., living environment, transportation access, local attractions, etc.), encouraging people to move to rural areas.

[2003] Example 1

[2004] Next, a description will be given of Example 1 of Form 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."

[2005] Conventional housing buying and selling platforms often failed to efficiently match sellers and buyers, and the fairness and transparency of transactions were often not ensured. Furthermore, they were difficult to apply to the sale of vacant houses in rural areas. This meant that the needs of sellers and buyers were not fully met, and transactions were delayed.

[2006] 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.

[2007] In this invention, the server includes a means for a user to input information, a means for the server to collect information, a means for the server to send prompts to the generative AI model, a means for the generative AI model to perform matching, and a means for the server to notify the matching results. This makes it possible to efficiently collect information on sellers and buyers and perform optimal matching using the generative AI model. Furthermore, it is possible to provide a system that ensures the fairness and transparency of transactions and is applicable to the sale and purchase of vacant houses in rural areas.

[2008] "Generative AI" is an artificial intelligence technology that generates data based on information provided by users and matches sellers and buyers.

[2009] A "consultant" is someone whose role is to provide advice and support to help smooth transactions between sellers and buyers.

[2010] "P2P" refers to a peer-to-peer network in which sellers and buyers transact directly.

[2011] "Transaction support" means functions and processes that support transactions between buyers and sellers.

[2012] "Means for determining whether a transaction is fair" refers to the functions and processes for evaluating whether a transaction between a seller and a buyer is being conducted fairly and properly.

[2013] "User information entry means" refers to the interface or method by which sellers and buyers enter their information into the system.

[2014] "Means by which the server collects information" refers to the functions and processes by which the server collects and stores information entered by users.

[2015] "Means by which the server sends prompts to the generative AI model" refers to the functions and processes by which the server sends instructions to the generative AI model based on the information collected by the server.

[2016] "Means by which the generative AI model performs matching" refers to the functions and processes by which the generative AI model matches the conditions of the seller and buyer and performs the optimal match.

[2017] "Means for the server to notify matching results" refers to the functions and processes for informing sellers and buyers of the matching results output by the generative AI model.

[2018] "Vacant house sales in rural areas" refers to transactions involving the buying and selling of vacant houses located in rural areas.

[2019] MODE FOR CARRYING OUT THE INVENTION

[2020] This invention relates to a home buying and selling platform system that uses generative AI to connect sellers and buyers via P2P. A specific embodiment of this system will be described below.

[2021] 1. Generate the system program

[2022] The server generates the program for the home buying and selling platform system. This program has the function of connecting sellers and buyers via P2P using a generative AI model. One example of the generative AI model used is OpenAI's GPT-4.

[2023] 2. Explain the program's processing in natural language

[2024] The server uses a generative AI model to collect information on sellers and buyers and perform optimal matching. Specifically, it performs the following processes:

[2025] Seller information gathering:

[2026] The server collects property details (e.g., location, layout, age, asking price, etc.) from sellers. This information is entered through a web form or a mobile app.

[2027] Buyer information gathering:

[2028] The server collects the buyer's desired property conditions (e.g., desired area, floor plan, budget, etc.) This information is also entered via a web form or mobile app.

[2029] Data processing and calculations:

[2030] The server inputs the collected information about sellers and buyers into a generative AI model, which then performs optimal matching based on the seller and buyer's conditions.

[2031] Matching result notification:

[2032] The server notifies the seller and buyer of the matching results output by the generative AI model via email or in-app notifications.

[2033] 3. Add concrete examples

[2034] For example, if a seller enters "a 3LDK apartment in Shibuya Ward, Tokyo, with a desired price of 50 million yen," and a buyer enters "a 3LDK apartment in Tokyo, with a budget of 60 million yen or less," the generative AI model will make the optimal match based on these conditions.

[2035] 4. Examples of prompts

[2036] "Seller's information: 3LDK apartment in Shibuya Ward, Tokyo, asking price: 50 million yen. Buyer's information: 3LDK apartment in Tokyo, budget: 60 million yen or less. Please use this information to find the best match."

[2037] In this way, the server utilizes generative AI models to provide a system that optimally matches buyers and sellers based on their requirements. This system ensures fairness and transparency in transactions and can also be applied to the sale of vacant houses in rural areas.

[2038] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2039] Step 1: User Enters Information

[2040] Users (sellers or buyers) enter information using the home buying and selling platform's web form or mobile app. Sellers enter detailed property information (location, floor plan, age, asking price, etc.), while buyers enter the desired property conditions (desired area, floor plan, budget, etc.). The entered information is sent to the server. Specifically, the user enters information in each field and clicks the "Submit" button.

[2041] Step 2: The server collects information

[2042] The server collects the information entered by the user in real time and stores it in a database. The server checks the format of the entered information and displays an error message to the user if there are any errors. Specifically, the server receives the input data and executes an SQL query to store it in the database.

[2043] Step 3: The server sends a prompt to the generative AI model

[2044] The server generates a prompt based on the collected seller and buyer information. For example, it generates a prompt like this: "Seller information: 3LDK apartment in Shibuya Ward, Tokyo, asking price 50 million yen. Buyer information: 3LDK apartment in Tokyo, budget within 60 million yen." The server sends this prompt as an API request to the generative AI model. Specifically, the server generates the prompt and sends an HTTP POST request to the API endpoint of the generative AI model.

[2045] Step 4: Generative AI model performs matching

[2046] The generative AI model compares the seller's and buyer's conditions based on the prompt text sent from the server and performs the optimal match. The model compares the seller's property information with the buyer's desired conditions and generates the most suitable match result. Specifically, the generative AI model analyzes the prompt text and evaluates the degree of match of the conditions using an internal algorithm.

[2047] Step 5: The server notifies the match result

[2048] The server notifies the seller and buyer of the matching results received from the generative AI model. Notifications are sent via email or in-app notifications. For example, a message may be sent saying, "We have found a buyer interested in your property. Please check the details." Specifically, the server receives the matching results and sends a notification to the user via an email server or push notification service.

[2049] In this way, the server, terminals, and users work together to ensure smooth operation of the home buying and selling platform system.

[2050] (Application example 1)

[2051] Next, a description will be given of Application Example 1 of Form 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."

[2052] Conventional home buying and selling platforms were not efficient in matching sellers and buyers, and had the constraint of requiring buyers to visit the property in person. Furthermore, they were difficult to apply to the sale of vacant homes in rural areas. To solve these issues, a more efficient and flexible matching system and a property viewing function in virtual space were needed.

[2053] 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.

[2054] In this invention, the server includes a means for the generative AI to act as a consultant and connect sellers and buyers via P2P, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for users to view properties in a virtual space, and a means for proposing optimal properties based on the user's desired conditions. This enables efficient matching between sellers and buyers, and allows users to view properties in a virtual space without visiting the site. It can also be applied to the sale and purchase of vacant houses in rural areas.

[2055] "Generative AI" is an artificial intelligence technology that makes optimal matches based on information about sellers and buyers.

[2056] A "consultant" is an expert or system that acts as a bridge between buyers and sellers.

[2057] "P2P" stands for peer-to-peer, a networking method that allows direct communication without going through a central server.

[2058] "Transaction support means" are functions and services that facilitate transactions between sellers and buyers.

[2059] "Means for determining whether a transaction is appropriate" refers to the function of evaluating whether the transaction is legally and ethically appropriate.

[2060] "Virtual space" is a virtual three-dimensional space generated using computer technology.

[2061] "Means to tour the property" refers to a function that allows users to visually check the interior and surroundings of the property in a virtual space.

[2062] "Desired conditions" are the requirements such as the property characteristics and budget that the user desires.

[2063] "Means to suggest the most suitable property" is a function that selects and suggests the most suitable property based on the user's desired conditions.

[2064] "Vacant house sales in rural areas" refers to the sale and purchase of vacant houses located in areas outside of urban areas.

[2065] The embodiments of the present invention will be described in detail below.

[2066] System configuration

[2067] This system is configured using the following hardware and software.

[2068] Hardware: Smartphone, Head-Mounted Display (HMD)

[2069] Software: Unity (virtual space creation), TensorFlow (generative AI model implementation), Firebase (database)

[2070] Program processing

[2071] Data collection

[2072] The server stores property information from sellers (e.g., property details, desired price) in Firebase. It also stores desired conditions from buyers (e.g., desired property conditions, budget) in Firebase.

[2073] Training generative AI models

[2074] The server uses TensorFlow to train a generative AI model that matches buyers and sellers based on their information, and then suggests the best properties based on their needs.

[2075] Building a virtual space

[2076] The server uses Unity to create a 3D model of the property, allowing users to tour the property in a virtual space, which they access using their smartphone or HMD.

[2077] Matching and Proposals

[2078] When a user inputs their desired conditions, the server uses a generative AI model to suggest the most suitable property, which the user can then view in a virtual space.

[2079] Data processing and calculation

[2080] The server processes the data entered by the user in real time and performs data calculations to suggest the most suitable properties, allowing users to find properties efficiently.

[2081] Specific examples

[2082] Users open the smartphone app and input the desired property conditions (e.g., 3LDK, budget of less than 50 million yen, within 10 minutes' walk from the station). The server then suggests the most suitable property based on these conditions, and the user can view the property in a virtual space using an HMD.

[2083] Prompt Sentence Examples

[2084] Enter the desired property conditions. For example, 3 bedrooms, 3 bedrooms, 50 million yen or less, within a 10-minute walk from the station.

[2085] In this way, this invention realizes efficient matching between sellers and buyers, allows users to view properties in a virtual space without visiting the site, and can also be applied to the sale and purchase of vacant houses in rural areas.

[2086] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2087] Step 1:

[2088] The server collects property information from sellers (e.g., property details, asking price) and stores it in Firebase. The input is property information provided by sellers, and the output is data stored in Firebase. Specifically, the server receives the information entered by the seller and stores it in a database.

[2089] Step 2:

[2090] The server collects the buyer's desired conditions (e.g., desired property conditions, budget) and stores them in Firebase. The input is the desired conditions provided by the buyer, and the output is the data stored in Firebase. Specifically, the server receives the information entered by the buyer and stores it in a database.

[2091] Step 3:

[2092] The server uses TensorFlow to train a generative AI model that performs optimal matching based on information about sellers and buyers. The input is the seller and buyer data stored in Firebase, and the output is the trained generative AI model. Specifically, the server retrieves the data and trains the AI ​​model.

[2093] Step 4:

[2094] The server uses Unity to create a 3D model of the property, allowing users to view the property in a virtual space. The input is detailed information about the property, and the output is a 3D model placed in the virtual space. Specifically, the server generates a 3D model based on the property information and places it in the virtual space.

[2095] Step 5:

[2096] The user accesses the application using a smartphone or HMD and inputs their desired conditions. The input is the desired conditions entered by the user, and the output is the data sent to the server. In concrete terms, the user operates the application and inputs their desired conditions.

[2097] Step 6:

[2098] The server uses a generative AI model to propose the most suitable property based on the desired conditions entered by the user. The input is the user's desired conditions, and the output is the proposed property information. Specifically, the server inputs the desired conditions into the AI ​​model and selects the most suitable property.

[2099] Step 7:

[2100] The user visits the proposed property in a virtual space. The input is the proposed property information, and the output is the user's experience of visiting the property in the virtual space. Specifically, the user wears an HMD and visits the property in the virtual space.

[2101] Step 8:

[2102] The server collects user feedback and stores it in Firebase. The input is the user feedback and the output is the data stored in Firebase. Specifically, the server receives the feedback from the user and stores it in the database.

[2103] Example 2

[2104] Next, a description will be given of Example 2 of Form 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."

[2105] With conventional home buying and selling platform systems, transactions between sellers and buyers often did not proceed smoothly, with problems such as time-consuming document submission, signing, and payment procedures. It was also difficult to manage the transaction progress in real time, which led to issues such as a decrease in the transparency and efficiency of transactions.

[2106] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2107] In this invention, the server includes a means for connecting sellers and buyers via P2P with a generative AI as a consultant, a means for supporting transactions between sellers and buyers, a means for determining whether the transaction is appropriate, a means for managing the progress of the transaction, a means for instructing the submission and signature of necessary documents, a means for instructing payment procedures, and a means for notifying the completion of the transaction. This makes it possible to manage the progress of the transaction in real time and smoothly proceed with the necessary procedures.

[2108] "Generative AI" is a system that uses artificial intelligence technology to generate data and automatically perform specific tasks.

[2109] A "consultant" is someone with specialized knowledge who provides advice and support in a particular field.

[2110] "P2P" stands for peer-to-peer, a networking method in which individual devices communicate directly with each other without going through a central server.

[2111] A "transaction" is the act of buying and selling goods or services between a seller and a buyer.

[2112] "Progress" refers to the status of each step of the transaction.

[2113] "Documents" are documents such as contracts and certificates required for transactions.

[2114] A "signature" is the act of a party putting their name on a document to show their intention.

[2115] "Settlement" is the procedure for completing payment in a transaction.

[2116] "Notification" is a means of communication to inform interested parties of specific information.

[2117] This invention is a system that supports transactions between sellers and buyers, and uses a generative AI model to manage the progress of the transaction and issue instructions to ensure the smooth submission and signing of necessary documents and payment procedures. A specific embodiment of this system is shown below.

[2118] System configuration

[2119] server:

[2120] The server manages the progress of transactions using a generative AI model (e.g., OpenAI's GPT-4). The server has the following main functions:

[2121] Manage the progress of your transactions.

[2122] Instruct them to submit and sign the necessary documents.

[2123] Instruct the payment procedure.

[2124] Notify the completion of the transaction.

[2125] Device:

[2126] The terminal is a device used by the seller and buyer to input the information required for the transaction and communicate with the server. The terminal has the following functions:

[2127] Register product information.

[2128] Submit a purchase request.

[2129] Signing the contract.

[2130] Executing payment procedures.

[2131] User:

[2132] Users are sellers and buyers who conduct transactions through the system. Users perform the following operations:

[2133] Enter product information.

[2134] Submit a purchase request.

[2135] Signing the contract.

[2136] Executing payment procedures.

[2137] Program processing

[2138] server:

[2139] The server manages the progress of transactions using generative AI models. Specifically, the server performs the following processes:

[2140] Track each step of a transaction (e.g., contract creation, signing, payment).

[2141] Identify the next steps you need to take based on your progress.

[2142] Provide instructions to buyers and sellers regarding the submission and signing of necessary documents.

[2143] Instruct the payment procedure.

[2144] Notify the completion of the transaction.

[2145] Examples:

[2146] When a seller adds an item to a listing, the server stores the information in a database.

[2147] When a buyer purchases a product, the server automatically generates a contract using a generative AI model.

[2148] The server instructs the seller and buyer to sign the contract.

[2149] Once both parties have signed, the server will instruct the buyer to complete the payment process.

[2150] Once the payment is complete, the server sends a notification of the transaction completion to the seller and buyer.

[2151] Example prompt sentence:

[2152] "A new transaction has been initiated. Please generate a contract."

[2153] "Send notices to sellers and buyers for signature."

[2154] Please instruct the buyer to complete the payment process.

[2155] In this way, the server can utilize generative AI models to manage the progress of the transaction and smoothly carry out the necessary procedures.

[2156] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2157] Step 1:

[2158] Registering product information

[2159] User (seller): Enter information such as product name, price, and description, and click the "Register" button.

[2160] Input: Information such as product name, price, description, etc.

[2161] Server: Receives the product information and saves it in the database. Once saved, notifies the seller that the product information has been registered.

[2162] Output: The product information is saved in the database and a notification is sent to the seller.

[2163] Step 2:

[2164] Receiving a purchase request

[2165] User (Buyer): Select the product you want to purchase and click the "Purchase" button.

[2166] Input: Purchase request (item ID, buyer information).

[2167] Server: Receives the purchase request, updates the transaction status to "Purchase request received", and notifies the buyer that "Purchase request has been received".

[2168] Output: Transaction progress is updated and notification is sent to the buyer.

[2169] Step 3:

[2170] Generate Agreement

[2171] Server: Sends a prompt to the generative AI model saying, "A new transaction has been started. Please generate a contract."

[2172] Input: Prompt text "A new deal has been started. Please generate a contract."

[2173] Generative AI model: Generates the contract and sends it back to the server.

[2174] Server: Saves the generated contract in the database and notifies the seller and buyer that the contract has been generated.

[2175] Output: The generated contract is saved in the database and notifications are sent to the seller a...

Claims

1. A means of collecting detailed property information from sellers and conditions for desired properties from buyers; means for generating a prompt sentence based on the collected seller and buyer information; A means for inputting the prompt sentence into a generative AI model that matches the seller and the buyer; A means for notifying the seller and the buyer of the matching result output by the generative AI model; A system including:

2. The system of claim 1 , wherein the generative AI model further comprises means for determining whether a transaction between the seller and the buyer is appropriate.

3. The system of claim 1 , wherein the generative AI model further includes a function for aggregating local vacant house information.

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