system

Abstract

To provide a system that can improve the efficiency of the process from property search to contract and increase user satisfaction. [Solution] A system including: a means for a user to input desired conditions for a property; a means for transmitting the input conditions to a server; a means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions; a means for the server to use a generative AI model to generate new proposals that are close to the user's conditions; a means for the server to transmit the above-mentioned property list and proposals made by the generative AI to a terminal; a means for the terminal to display these property lists to the user; a means for obtaining and displaying detailed information about a property selected by the user; a means for the server to calculate a transaction fee and present it to the user; and a means for the user to enter into a contract for a property.

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] In the traditional real estate industry, property search and contract processes were inefficient, and it took a lot of effort to find a property that met the user's desired conditions. Furthermore, there was a risk of low user satisfaction due to a lack of ways to make new suggestions that users had not considered when selecting a property. Furthermore, the calculation of fees was often complicated and lacked transparency. [Means for solving the problem]

[0005] The present invention provides a means for a user to input desired conditions and send those conditions to a server. The server has a means for searching a property database based on the sent conditions and listing properties that meet the conditions. The server also has a means for using a generative AI model to generate new proposals that are close to the user's conditions, thereby providing the user with a variety of options. The generated property list and proposals are sent to a terminal and displayed to the user. Detailed information about the property selected by the user is obtained from the server and displayed to the user. In addition, the server has a means for calculating transaction fees and presenting them to the user. This provides a system that can streamline the process from property search to contract and improve user satisfaction.

[0006] "User" refers to an end user who uses the system to search for properties and enter into contracts.

[0007] "Property" refers to all or part of the real estate that a user has searched for and wishes to enter into a contract for.

[0008] "Desired conditions" refers to requirements that a user specifies for a property, such as floor plan, location, rent, etc.

[0009] A "terminal" is a device such as a computer, smartphone, or tablet that is operated by a user and connected to a server via the Internet.

[0010] The "server" is a system with the computing resources to receive data sent from the user's device, search the database, and make suggestions using generative AI.

[0011] A "database" is an information system for storing information about properties.

[0012] A "generative AI model" is a model that uses artificial intelligence technology to generate new proposals that meet the user's desired conditions.

[0013] "Suggestion" refers to information in which the generative AI model presents other options to consider in addition to the user's desired conditions.

[0014] "Listing" refers to the server searching the database and displaying in list form properties that meet the user's desired conditions.

[0015] "Commission" refers to the amount calculated and presented to the user as a fee incurred in connection with a property transaction. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] ---

[0038] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[0039] First, the user accesses the property search screen. The desired conditions (e.g., floor plan, location, rent, etc.) entered by the user are sent to the server via the terminal. The terminal converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[0040] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[0041] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a further request is sent to the server, which retrieves the details and sends them to the terminal.

[0042] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server compiles all necessary information, generates a contract, and sends it to the user.

[0043] Specific examples

[0044] For example, let's say a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the device sends the information to the server. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to suggest properties such as "areas with extensive pet services" and "properties where rent is negotiable."

[0045] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[0046] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[0047] The present invention aims to provide a system that efficiently and flexibly supports property selection, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[0048] The processing flow will be explained below.

[0049] System processing steps

[0050] Step 1:

[0051] The user accesses the property search screen and enters the desired conditions (e.g., 3LDK, within 10 minutes' walk from the station, rent less than 100,000 yen).

[0052] Step 2:

[0053] The terminal converts the desired conditions entered by the user into an appropriate data format and generates a request to be sent to the server.

[0054] Step 3:

[0055] The server receives the request from the terminal and analyzes the contents.

[0056] Step 4:

[0057] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[0058] Step 5:

[0059] The server runs the generative AI model to create new proposals that closely match the user's desired conditions, such as properties in areas with good pet services or properties where rent is negotiable.

[0060] Step 6:

[0061] The server compiles the listed property information and suggestions made by the generating AI and sends them to the terminal.

[0062] Step 7:

[0063] The device displays property information and suggestions on a user interface, allowing the user to view the information and select properties that interest them.

[0064] Step 8:

[0065] To view detailed information about a particular property, the user selects the property and clicks the "View Details" button.

[0066] Step 9:

[0067] The terminal sends the user's selection to the server as a request.

[0068] Step 10:

[0069] The server receives the request and retrieves the details of the selected property from the database.

[0070] Step 11:

[0071] The server sends the acquired detailed information to the terminal.

[0072] Step 12:

[0073] The terminal displays the detailed information on the user interface so that the user can check it. The user checks the detailed information and clicks the "Contract" button if they wish to enter into a contract.

[0074] Step 13:

[0075] The device sends a contract request to the server.

[0076] Step 14:

[0077] The server receives the request and calculates the transaction fee based on the property price and contract details.

[0078] Step 15:

[0079] The server sends the calculation results to the terminal.

[0080] Step 16:

[0081] The terminal displays the calculated fee on the user interface for the user to review.

[0082] Step 17:

[0083] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[0084] Step 18:

[0085] The terminal sends the final request to the server.

[0086] Step 19:

[0087] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[0088] Step 20:

[0089] The server sends the generated contract to the user and asks for final confirmation.

[0090] The above are the processing steps of this system.

[0091] Example 1

[0092] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0093] Conventional real estate search systems make it difficult for users to efficiently find the property they desire. They also lack the mechanisms to provide new suggestions based on users' desired conditions or to support the smooth progress of contract procedures. As a result, users have to compare and consider many properties themselves, which takes time and effort.

[0094] 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.

[0095] In this invention, the server includes means for a user to input desired conditions for a property, means for transmitting the input conditions to the server, means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions, means for the server to generate new proposals that are close to the user's conditions using a generative AI model, means for the server to transmit the property list and proposals made by the generative AI to a terminal, means for the terminal to display these property lists to the user, means for the server to obtain and display detailed information about a property selected by the user, means for the server to calculate a transaction fee and present it to the user, and means for the user to enter into a contract for the property. This enables users to efficiently search for properties, receive new proposals for those properties, and smoothly proceed with the contract procedure.

[0096] The "means for the user to input desired conditions for a property" is a system component that provides an interface for the user to input the conditions for the property they desire.

[0097] The "means for transmitting input conditions to a server" is a system component that has the function of converting the desired conditions input by the user into an appropriate data format and transmitting the converted data to the server.

[0098] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a system component that has the function of the server analyzing the desired conditions received from the user, searching the property database based on those conditions, and listing properties that meet the conditions.

[0099] The "means for generating new proposals that are close to the user's conditions using a generative AI model" is a system component that has the function of using a generative AI model to generate new proposals based on the user's input conditions.

[0100] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a system component that has the function of sending the listed property information and suggestions made by the generating AI model to the terminal.

[0101] The "means by which the terminal displays these property listings to the user" refers to a system component that has the functionality to display the received property listings to the user.

[0102] The "means for obtaining and displaying detailed information about a property selected by the user" is a system component that has the function of obtaining detailed information about a property in which the user is interested from the server and displaying it to the user.

[0103] The "means for the server to calculate the transaction fee and present it to the user" is a system component that has the function of calculating the transaction fee required for a property contract and presenting that information to the user.

[0104] The "means for users to enter into a contract for a property" is a system component that provides an interface and functions for users to proceed with the contract procedure for a property.

[0105] A "property database" is a data storage system that stores various information about real estate properties.

[0106] A "generative AI model" is an artificial intelligence model used to generate new suggestions based on a user's desired criteria.

[0107] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[0108] First, a user accesses the URL of the real estate search system using a web browser. At this time, the user enters their desired conditions for the property (e.g., floor plan, location, rent, etc.) in an input form. The entered conditions are converted into an appropriate data format (e.g., JSON) by the terminal and sent to the server via the Internet.

[0109] The server receives the request sent from the terminal and analyzes the desired conditions. Based on this analysis, the server searches a property database (e.g., MySQL (registered trademark) or PostgreSQL) and lists properties that meet the conditions. The server then uses a generative AI model (e.g., GPT-4 (registered trademark)) to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that includes not only properties that meet the conditions, but also proposals made by the generative AI model.

[0110] Next, the server sends these property lists and the generated proposals to the terminal. The terminal receives them and displays them in a list format on the user interface. The user can check the displayed property list and click on a property that interests them to view its detailed information. In this case, the terminal sends a request for detailed information to the server, and the server retrieves the property's detailed information from the database and sends it to the terminal.

[0111] If the user wishes to enter into a contract for a property, they indicate their intention by clicking the "Contract" button. The device sends this information to the server, which then calculates the fees required for the transaction and displays them on the device. If the user agrees to the fees, they click the "Confirm" button to proceed with the contract. The server then compiles all the information required for the contract, generates a formal contract, and sends it to the user. The contract is sent by email, and a link is also provided for the user to download.

[0112] Specific examples

[0113] Below is a specific example. If a user searches for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen," the user enters their desired criteria into the search screen. The device sends this information to the server, which then searches its database. It lists properties that match the criteria and uses a generative AI model to generate suggestions such as "areas with extensive pet services" and "properties where rent is negotiable."

[0114] This information is sent to the terminal and displayed on the user interface. The user can view the displayed property list, select a property that interests them, and check its detailed information. Finally, if the user wishes to enter into a contract, the server calculates the fee and presents it to the user. Once the user confirms the fee and proceeds with the contract procedure, the server generates a contract and sends it to the user.

[0115] In this way, the present invention is a system that enables users to efficiently search and select properties, receive new proposals, and smoothly proceed with contracts.

[0116] Prompt Sentence Examples

[0117] "Search for pet-friendly 2LDK apartments in Tokyo for less than 150,000 yen per month."

[0118] This system greatly improves user convenience and provides groundbreaking support for efficiently conducting real estate transactions.

[0119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0120] Step 1:

[0121] The user accesses the property search screen.

[0122] Input: A user accesses the URL of the real estate search system in a web browser.

[0123] Specific behavior: A user opens a browser, enters the system's URL, and arrives at the search screen.

[0124] Output: Property search screen will be displayed.

[0125] Step 2:

[0126] The user inputs the desired conditions.

[0127] Input: The user enters desired conditions (e.g., floor plan, location, rent, etc.) into the input form on the search screen.

[0128] Specific operation: The user enters conditions such as "2LDK," "Tokyo," "under 150,000 yen," and "pets allowed" into the input form and clicks the search button.

[0129] Output: The desired conditions are retained in the input form.

[0130] Step 3:

[0131] The terminal sends the input information to the server.

[0132] Input: The desired conditions entered by the user.

[0133] Specific operation: The device converts the input desired conditions into an appropriate data format such as JSON and sends a request to the server via the Internet.

[0134] Output: The request data sent to the server.

[0135] Step 4:

[0136] The server analyzes the conditions and searches the database.

[0137] Input: Desired conditions sent from the terminal.

[0138] What happens: The server analyzes the request and searches the property database using a SQL query, such as "SELECT FROM properties WHERE location="Tokyo" AND rent <= 150000 AND type="2LDK" AND pet_friendly=True."

[0139] Output: A list of properties that match the criteria.

[0140] Step 5:

[0141] The server generates suggestions using a generative AI model.

[0142] Input: A list of properties that match your criteria.

[0143] How it works: The server uses a generative AI model (e.g., GPT-4) to generate new proposals based on the user's desired conditions. For example, it creates proposals such as "areas with extensive pet services" or "properties where rent is negotiable."

[0144] Output: The new list of suggestions generated.

[0145] Step 6:

[0146] The server sends property information and suggestions to the device.

[0147] Input: A list of properties that fit your criteria and a list of suggestions generated by a generative AI model.

[0148] Specific operation: The server sends this information to the terminal.

[0149] Output: Property and proposal information sent to your device.

[0150] Step 7:

[0151] The terminal displays the property listing to the user.

[0152] Input: Property information and proposal information received from the server.

[0153] Specific operation: The terminal displays this information in a list format on the user interface.

[0154] Output: The property list and proposal list displayed to the user.

[0155] Step 8:

[0156] A user views property details.

[0157] Input: Property listings in which the user is interested.

[0158] Specific operation: The user clicks on a property they are interested in and views detailed information. A request for detailed information is sent from the device to the server.

[0159] Output: A request is sent to the server for more information.

[0160] Step 9:

[0161] The server retrieves the details and sends them to the device.

[0162] Input: Request for more information.

[0163] Specific operation: The server retrieves detailed information about the property from the database and sends it to the terminal.

[0164] Output: Detailed information sent to the terminal.

[0165] Step 10:

[0166] A user requests a contract and the terminal transmits the information to the server.

[0167] Input: The property the user wishes to contract for and their intentions.

[0168] Specific operation: The user clicks the "Contract" button, and the information is sent from the device to the server.

[0169] Output: The contract request information sent to the server.

[0170] Step 11:

[0171] The server calculates the fee and displays it on the terminal.

[0172] Input: Contract information and property details.

[0173] Specific operation: The server calculates the fee required for the transaction and sends that information to the terminal.

[0174] Output: Fee information displayed on the terminal.

[0175] Step 12:

[0176] The user confirms the fee and proceeds with the contract.

[0177] Input: Fee information confirmed by the user.

[0178] Specific behavior: The user agrees to the fee and clicks the "Confirm" button.

[0179] Output: Fee confirmation information is sent to the server.

[0180] Step 13:

[0181] The server generates a contract and sends it to the user.

[0182] Input: Fee verification information and all information required for the contract.

[0183] What happens: The server generates a formal contract and sends it to the user via email, along with a link for the user to download it.

[0184] Output: The contract and download link sent to the user.

[0185] (Application example 1)

[0186] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0187] Conventional real estate search systems limit the means by which users can visually check property information in detail, making it difficult to understand properties from a realistic perspective. Furthermore, the contract procedures, from property selection to contract signing, are cumbersome, and improvements are needed to improve the user experience.

[0188] 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.

[0189] In this invention, the server includes a means for displaying detailed information about a property selected in a virtual space as a 360-degree virtual tour when the user wears a head-mounted display, and a means for the user to enter into a contract for the property, which allows the user to check the property in detail from a realistic perspective and realize a smooth contract procedure.

[0190] A "user" is an entity that searches for real estate properties and carries out procedures such as contracts.

[0191] "Property" refers to real estate, including residential properties such as apartments, condominiums, and detached houses.

[0192] "Desired conditions" are specific requests such as floor plan, location, rent, etc. that a user sets when searching for a property.

[0193] A "server" is a computer system that receives requests from users, searches a property database, and provides the results.

[0194] "Terminal" means a device on which a user inputs desired search criteria and receives and displays search results from the server, and includes smartphones, tablets, computers, etc.

[0195] A "property database" refers to a database that stores information on various real estate properties.

[0196] A "generative AI model" is an artificial intelligence model that generates new proposals that are close to the user's desired conditions.

[0197] A "head-mounted display" is a device that allows users to visually experience a virtual reality space by wearing it on their head.

[0198] "Virtual space" refers to a virtual three-dimensional space constructed using a computer system.

[0199] A "360-degree virtual tour" is a video technology that provides an environment in which users can view detailed information about a property from any angle within a virtual space.

[0200] "Transaction fees" are fees incurred when entering into a property contract and are calculated based on the property price and transaction details.

[0201] "Contract" refers to the formal procedure for the property selected by the user.

[0202] The present invention is a real estate search system that allows users to check real estate properties in detail in a virtual space using a head-mounted display and proceed to a contract. The system operates through the interaction between the user, the terminal, and the server.

[0203] First, the user puts on a head-mounted display and accesses a virtual real estate store. The user then controls a virtual avatar, moves to a property search terminal, and enters their desired conditions. These desired conditions (e.g., floor plan, location, rent, etc.) are sent to a server via the terminal. The terminal then converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[0204] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[0205] The device organizes the property information and proposals received from the server and displays them on a visual interface in the virtual space. Users can review the displayed property list and select a property they are interested in, and detailed information about it is displayed as a 360-degree virtual tour. This allows users to view the property in detail as if they were in person.

[0206] When the user finally selects the property they wish to sign a contract for, the server calculates the transaction fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server collects all necessary information, generates a contract, and sends it to the user.

[0207] This processing is performed using the following hardware and software:

[0208] Hardware: Head-mounted display (HMD), high-performance personal computer (PC)

[0209] Software: Virtual reality (VR) engines (Unity, Unreal Engine), generative AI models (OpenAI® GPT-4, HuggingFace's Transformers), web application frameworks (Flask, Django), database management systems (MySQL, PostgreSQL)

[0210] For example, let's say a user is looking for a "2LDK apartment in Shibuya Ward, with a monthly fee of less than 200,000 yen, and within a 10-minute walk from the station." The user enters their desired conditions and sends them to the server. The server receives this information, searches its database, and uses a generative AI model to suggest properties in popular areas or newly built properties. This information is displayed in the virtual space, and when the user selects a property that interests them, a 360-degree virtual tour of that property begins. The user can then check the property in detail and proceed with the contract process.

[0211] Example prompts to input to the generative AI model:

[0212] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[0213] The present invention allows the user to check the property in detail from a realistic perspective and smoothly proceed with the contract procedure.

[0214] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0215] Step 1:

[0216] The user wears a head-mounted display and accesses a virtual real estate store. The user operates a virtual avatar, moves to a property search terminal, and enters desired conditions. Specifically, information such as floor plan, location, and rent is entered into a dedicated input form, and the terminal receives this as data. This data is then sent to the server.

[0217] Step 2:

[0218] The terminal converts the desired condition data entered by the user into an appropriate data format and sends a request to the server via the Internet. Here, the input data is the desired conditions, and the output is the request data converted into the appropriate data format. Data serialization technology is used for the conversion.

[0219] Step 3:

[0220] The server receives the request data sent from the terminal and analyzes the desired conditions. Based on the analysis results, the server searches the property database. The input data are the desired conditions, and the output data is a list of properties that meet the conditions. The database search is performed using an SQL query.

[0221] Step 4:

[0222] The server uses a generative AI model to generate new proposals that are close to the user's desired conditions. The input data is the desired conditions and a property list, and a prompt for the generative AI model is also generated. Specifically, the following prompt is used:

[0223] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[0224] The output data is a list of proposed properties generated by the generative AI. The generative AI model is run using OpenAI GPT-4 and HuggingFace's Transformers.

[0225] Step 5:

[0226] The server compiles search results from the property database and proposed properties based on the generative AI model, and sends them to the terminal. The input data is the property list and proposed properties, and the output data is a list of real estate information that integrates these. This data is sent in JSON format.

[0227] Step 6:

[0228] The terminal organizes the real estate information received from the server and displays it on a visual interface in the virtual space. The input data is a consolidated real estate information list, and the output is the visual information displayed on the user interface. This is done using a VR engine (Unity, Unreal Engine).

[0229] Step 7:

[0230] The user selects a property that interests them from the displayed property list and checks its detailed information as a 360-degree virtual tour. At this time, the ID of the selected property is used as input data, and a request is sent to the server. The output data is the video data of the 360-degree virtual tour.

[0231] Step 8:

[0232] The server acquires detailed information about the selected property and sends it to the terminal as video data for a 360-degree virtual tour. The input data is the property ID, and the output data is the 360-degree video data. High-resolution video files are used to acquire the data.

[0233] Step 9:

[0234] When a user checks the 360-degree virtual tour and selects a property they wish to purchase, the server calculates the transaction fee and presents it to the user via their terminal. The input data are property information and user information, and the output data is the transaction fee. Basic arithmetic operations are used for this calculation.

[0235] Step 10:

[0236] When the user confirms the fees and presses the "Contract" button, the server officially starts the contract procedure, gathers all the necessary information, generates a contract, and sends it to the user. The input data is a set of contract information, and the output data is the generated contract. Document generation software is used for this process.

[0237] 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.

[0238] ---

[0239] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[0240] First, the user accesses the property search screen and enters their desired conditions (e.g., floor plan, location, rent, etc.). Based on the user's input and operations, the emotion engine analyzes the user's emotions. The device converts the desired conditions entered by the user and the results of the emotion analysis into an appropriate data format and generates a request to send to the server.

[0241] The server receives requests from the device and analyzes their contents. Based on the analysis, the server searches its property database and lists properties that meet the user's requirements. The server then uses a generative AI model to generate new proposals that are close to the user's desired conditions. These proposals may include, for example, properties in areas with extensive pet services or properties where rent is negotiable.

[0242] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby transmitting the optimal property listing based on the user's emotional data to the terminal.

[0243] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the details and sends them to the terminal.

[0244] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[0245] Specific examples

[0246] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[0247] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[0248] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[0249] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[0250] The present invention aims to provide a system that recognizes a user's emotions and supports the selection of the most suitable property based on those emotions, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[0251] The processing flow will be explained below.

[0252] System processing steps

[0253] Step 1:

[0254] The user accesses the property search screen and enters the desired conditions (e.g., floor plan, location, rent, etc.).

[0255] Step 2:

[0256] The emotion engine analyzes the user's input and operation methods (e.g., keyboard typing speed, mouse movements, etc.) and generates the user's emotion data.

[0257] Step 3:

[0258] The terminal transmits a request to the server, which includes the desired conditions input by the user and the emotion data analyzed by the emotion engine.

[0259] Step 4:

[0260] The server receives the request from the terminal and analyzes its contents (desired conditions and emotional data).

[0261] Step 5:

[0262] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[0263] Step 6:

[0264] The server runs the generative AI model and generates new proposals that are close to the user's desired conditions (e.g., properties with good surrounding environments, properties with extensive pet services, etc.).

[0265] Step 7:

[0266] The server adjusts the display order of property listings and proposals based on the user's emotional data analyzed by the emotion engine.

[0267] Step 8:

[0268] The server compiles the listed property information and suggestions from the emotion engine and sends them to the terminal.

[0269] Step 9:

[0270] The terminal organizes the property information and proposals received from the server and displays them on the user interface.

[0271] Step 10:

[0272] The user reviews the displayed property list and clicks to view details of the property that interests them.

[0273] Step 11:

[0274] The terminal sends the user's selection to the server as a request.

[0275] Step 12:

[0276] The server receives the request and retrieves the details of the selected property from the database.

[0277] Step 13:

[0278] The server sends the acquired detailed information to the terminal.

[0279] Step 14:

[0280] The terminal displays the detailed information on the user interface so that the user can check it.

[0281] Step 15:

[0282] The user checks the detailed information and, if he wishes to enter into a contract, clicks the "Contract" button.

[0283] Step 16:

[0284] The device sends a contract request to the server.

[0285] Step 17:

[0286] The server receives the request and calculates the transaction fee based on the property price and contract details.

[0287] Step 18:

[0288] The server sends the calculation results to the terminal.

[0289] Step 19:

[0290] The terminal displays the calculated fee on the user interface for the user to review.

[0291] Step 20:

[0292] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[0293] Step 21:

[0294] The terminal sends the final request to the server.

[0295] Step 22:

[0296] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[0297] Step 23:

[0298] The server sends the generated contract to the user and asks for final confirmation.

[0299] The above are the processing steps of this system.

[0300] Example 2

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

[0302] Conventional real estate search systems simply listed properties based on the user's input criteria without considering the user's feelings, making it difficult to fully meet the user's needs. Furthermore, the inability to make suggestions based on the user's feelings narrowed the range of choices, making it difficult to find the perfect property. Furthermore, the process of entering into a property contract was complicated, creating the problem of stress for users.

[0303] 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.

[0304] In this invention, the server includes a means for transmitting input conditions and emotion data to the server, a means for searching a property database based on the transmitted conditions and emotion data to list properties that meet the conditions, and a means for optimizing the property list and generated proposals using an emotion engine. This enables optimal property proposals based on the user's emotions, thereby increasing user satisfaction. Furthermore, by taking emotion data into consideration, properties that interest the user can be efficiently proposed, and contract procedures can proceed smoothly.

[0305] "Input conditions" refers to the desired conditions (e.g., location, layout, rent, etc.) specified by the user when searching for a property.

[0306] "Emotion data" refers to data that represents the user's emotional state, and refers to information acquired based on facial expression recognition, operation speed, and the like.

[0307] "Server" refers to a computer system that receives conditions and emotional data entered by users, searches a property database, and generates and optimizes optimal proposals using a generative AI model.

[0308] A "property database" is a database that stores information about properties, and refers to an information source that can be searched based on the user's desired conditions.

[0309] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates new proposals based on a user's desired conditions.

[0310] An "emotion engine" refers to a technology that analyzes users' emotional data and optimizes property listings and proposals based on the results.

[0311] "Terminal" refers to the device (e.g., PC, smartphone, tablet) used by a user to search for properties and view detailed information.

[0312] "Transaction fee" refers to the fee incurred when a user proceeds with a property contract, and is calculated based on the property price and transaction details.

[0313] "Detailed information" refers to additional information about the property (e.g., specific facilities, surrounding environment, contract terms, etc.).

[0314] "Means of entering into a contract" refers to a series of processes and procedures for the user to proceed with the contract procedure for the property they desire.

[0315] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[0316] System configuration

[0317] This system is configured using the following main hardware and software:

[0318] 1. Device: The device on which a user searches for properties and views detailed information. Examples include computers, smartphones, and tablets.

[0319] 2. Server: A remote computer system that processes user requests, searches a property database, and utilizes an emotion engine. The server manages a database such as MySQL and uses a generative AI model (e.g., OpenAI GPT-4) and an emotion engine (e.g., IBM Watson® Tone Analyzer).

[0320] 3. Property database: A database that stores information about properties. It provides the necessary property information based on search criteria.

[0321] 4. Emotion Engine: Software that analyzes user emotional data and optimizes property listings and offers based on the results.

[0322] System Operation

[0323] The user accesses the real estate search screen and enters their desired conditions (for example, floor plan, location, rent, etc.). Specifically, they enter "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[0324] The terminal converts the desired conditions and emotion data entered by the user into an appropriate data format and generates a request to send to the server. The emotion data includes the user's facial expression, operation speed, etc., and the resulting emotion analysis data.

[0325] The server receives requests from the device and analyzes the content. The analyzed information includes, for example, desired conditions and emotional data. The server searches the property database and lists properties that match the conditions. The server then uses a generative AI model to generate new proposals that are closer to the user's desired conditions. These proposals include, for example, "areas with extensive pet services" and "properties where rent is negotiable."

[0326] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby generating an optimal property listing based on the user's emotional data and sending it to the terminal.

[0327] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the detailed information and sends it to the terminal.

[0328] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[0329] Specific examples

[0330] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[0331] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[0332] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[0333] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[0334] Prompt Sentence Examples

[0335] "A user is looking for a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month. The user enters search criteria, and emotional data is also collected. The server should generate a list of properties that match the criteria, suggesting areas with good pet services and properties where the rent is negotiable. Generate an optimal list of properties based on the user's emotional data, and send that list to the device."

[0336] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0337] Step 1:

[0338] The user accesses the property search screen and enters the desired conditions.

[0339] Specific operation: The user opens a real estate search screen via a web browser or app and enters specific criteria, such as "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[0340] Input: Desired conditions

[0341] Output: Data format of the desired conditions entered

[0342] Step 2:

[0343] The terminal converts the user's desired conditions and emotional data into an appropriate data format.

[0344] Specific operation: The device collects the desired conditions entered by the user and emotional data from sensors such as the camera and microphone, analyzes them, and converts them into an appropriate data format such as JSON.

[0345] Input: Desired conditions, emotional data

[0346] Output: Converted desired conditions and emotion data

[0347] Step 3:

[0348] The device sends a request to the server.

[0349] Specific operation: The device sends the converted desired conditions and emotion data to the server as an HTTP request.

[0350] Input: Converted desired condition data and emotion data

[0351] Output: Request sent to the server

[0352] Step 4:

[0353] The server receives the request and parses it.

[0354] Specific operation: The server receives an HTTP request, analyzes it, and obtains the desired conditions and emotion data. It then separates the desired conditions for database search and the emotion data for emotion analysis.

[0355] Input: The request sent to the server

[0356] Output: Analyzed desired conditions and emotion data

[0357] Step 5:

[0358] The server searches the property database and lists properties that match the criteria.

[0359] Specific operation: The server searches a property database (e.g., MySQL) based on the analyzed desired conditions, and filters and lists properties that match the conditions.

[0360] Input: Parsed desired conditions

[0361] Output: Listed property data

[0362] Step 6:

[0363] The server generates new proposals using a generative AI model.

[0364] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) to add suggestions to the listed property data, such as "areas with extensive pet services" and "properties where rent is negotiable."

[0365] Input: Listed property data

[0366] Output: The newly generated proposal

[0367] Step 7:

[0368] The server uses an emotion engine to optimize property listings and offers.

[0369] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotion data. Based on the results, it prioritizes the listed properties and generated suggestions to create an optimized listing.

[0370] Input: emotion data, newly generated suggestions

[0371] Output: Optimized property listings and recommendations

[0372] Step 8:

[0373] The server sends the optimized property listings and suggestions to the device.

[0374] Specific operation: The server converts the optimized property listings and proposals into an appropriate data format, such as JSON, and sends it to the terminal as an HTTP response.

[0375] Input: Optimized property listings and proposals

[0376] Output: Property list and proposals sent to the device

[0377] Step 9:

[0378] The device displays the property information and allows the user to view the details.

[0379] Specific operation: The terminal displays the property information and suggestions received from the server on the user interface. The user can check the displayed property list and click to view detailed information on the property that interests them.

[0380] Input: Property listings and offers sent to your device

[0381] Output: Property list and details displayed in a user interface

[0382] Step 10:

[0383] The user selects the property they wish to contract for and confirms the transaction fee.

[0384] Specific operation: When a user presses the "Contract" button for a specific property, the terminal sends a request to the server again. The server calculates the transaction fee for this property and returns it to the terminal.

[0385] Input: User selection information

[0386] Output: Calculated transaction fee

[0387] Step 11:

[0388] The server initiates the contract procedure and sends the necessary information to the user.

[0389] Specific operation: When the user checks the fees and property details and presses the "Contract" button, the server responds to this action and starts the contract procedure, collating the necessary information and sending it to the user.

[0390] Input: User's contract intention confirmation information

[0391] Output: Information required for contract procedures and contract

[0392] (Application example 2)

[0393] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0394] Conventional real estate search systems simply list properties based on the user's desired conditions, but are unable to make recommendations that are optimized for the user's emotions and circumstances. This leaves them lacking in ingenuity to improve user satisfaction. There is also room for improvement in proposing payment methods that take the user's emotions into account, and in calculating transaction fees. Furthermore, there is a need for a system that can facilitate a series of real estate transactions in a smoother and more personalized manner.

[0395] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input desired property conditions; means for transmitting the input conditions to the server; means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions; means for the server to generate new proposals that are close to the user's conditions using a generative AI model; means for the server to transmit the property list and the generative AI proposals to a terminal; means for the terminal to display these property lists to the user; means for recognizing the user's emotions and proposing a payment method based on the emotions; means for acquiring and displaying detailed information about the property selected by the user; means for the server to calculate a transaction fee and present it to the user; and means for the user to enter into a contract for the property. This enables optimal property proposals and payment methods to be proposed while taking the user's emotions into consideration. Furthermore, smooth transaction progress and improved user satisfaction are achieved.

[0396] "Means for inputting desired conditions for a property" refers to an interface that allows a user to specify the characteristics and requirements of a property they desire.

[0397] The "means for transmitting the input conditions to the server" refers to a communication means for transmitting the information input by the user to a remote server.

[0398] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a method in which the server finds properties from the database that meet the conditions received and presents them to the user.

[0399] "Means for the server to use a generative AI model to generate new proposals that are close to the user's conditions" refers to a system that utilizes artificial intelligence technology to automatically generate new proposals based on the user's conditions.

[0400] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a method for transferring the generated property list and suggestions to the user's device.

[0401] "Means by which the terminal displays these property listings to the user" refers to an interface for visually displaying the property listings on the user's device.

[0402] "Means for recognizing a user's emotions and suggesting payment methods based on those emotions" refers to a method for analyzing a user's emotional state and presenting appropriate payment options.

[0403] "Means for obtaining and displaying detailed information about a property selected by a user" refers to a method for obtaining specific information about a property selected by a user and displaying it.

[0404] "Means for the server to calculate transaction fees and present them to the user" refers to a method for automatically calculating fees related to real estate transactions and notifying the user of the results.

[0405] "Means by which a user enters into a contract for a property" refers to the method by which a user completes the contract procedures for the property selected by the user.

[0406] The present invention is a real estate search system that recognizes a user's emotions and suggests optimal properties and payment methods. This system is composed of multiple components, such as a server, a user terminal, an emotion recognition engine, and a generative AI model. Specific embodiments for implementing the present invention are described below.

[0407] 1. System Configuration

[0408] 1.1 User terminal

[0409] The user terminal uses a device such as a smartphone, smart glasses, or head-mounted display, and provides an interface for the user to input desired conditions for a property. Once the user enters the desired conditions, they are sent to the server.

[0410] 1.2 Server

[0411] The server searches a property database based on the received desired conditions and lists properties that match the conditions. The server also uses a generative AI model to generate new proposals that are close to the user's conditions. These proposals can include information about the property's surrounding environment and services.

[0412] 1.3 Emotion Recognition Engine

[0413] The emotion recognition engine has the ability to analyze the user's emotional state. For example, it analyzes the user's facial image and recognizes whether the user is feeling happiness, stress, surprise, etc. This emotional information is sent to the server and used to optimize property listings and payment methods.

[0414] 2. Data processing and calculation

[0415] 2.1 Data Acquisition

[0416] The user enters the desired property conditions and the terminal sends the data to the server, which analyzes the received data and searches the property database to find properties that meet the conditions.

[0417] 2.2 Emotion recognition

[0418] It uses cameras and sensors to recognize emotions from images of the user's face. The emotion recognition engine uses libraries such as OpenCV and dlib to analyze the user's facial expressions and behavior.

[0419] 2.3 Proposal Generation by AI

[0420] The server uses a generative AI model (e.g., GPT-3®) to generate new property suggestions, which are optimized based on the user's desired conditions and emotional information.

[0421] 3. Specific Examples

[0422] Let's say a user is looking for a "2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month." The user enters their desired conditions, and the emotion recognition engine analyzes the user's input, facial expressions, and operation speed. As a result, the request sent to the server includes the desired conditions as well as the user's emotional data. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to make suggestions such as "areas with extensive pet services" and "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions, and then sends them.

[0423] Prompt Sentence Examples

[0424] Recognize emotions from a user's facial image and suggest payment options that optimize the user experience. For example, if a user is feeling stressed, offer a relaxation coupon and recommend credit card payment.

[0425] In this way, the present invention is a system that can provide optimal property proposals and payment methods while taking into consideration the user's feelings, making it possible to proceed with real estate transactions in a smoother and more personalized manner.

[0426] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0427] Step 1:

[0428] The user operates the terminal and inputs the desired conditions for the property. The input conditions are detailed information such as "a 2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." Once this input is complete, the desired condition data is sent to the server. The input here is the user's desired requirements and the associated fields, and the output is the transmission of that data.

[0429] Specific behavior:

[0430] The user opens the property search app and enters each item (location, rent, floor plan, etc.) along the interface. They then press the "Search" button, which sends the data to the server.

[0431] Step 2:

[0432] The server analyzes the desired conditions received and searches the property database based on them. It then lists properties that match the conditions from the property information in the database. In this process, a search query is generated based on the desired conditions entered, and data that matches the conditions is extracted based on that query. The output is a list of properties that match the conditions.

[0433] Specific behavior:

[0434] The server analyzes the received data, generates SQL queries, etc., and executes searches against the database. The resulting property list is then temporarily saved.

[0435] Step 3:

[0436] The server uses an emotion recognition engine to analyze the data to recognize the user's emotions. The emotion recognition engine takes the user's facial image data acquired from the camera as input and outputs the user's emotional state. This output is one of several emotional states, such as "happiness" or "stress."

[0437] Specific behavior:

[0438] The user takes a facial image using the device camera or streams video in real time, and the emotion recognition engine processes the video. The result is sent to the server as the user's current emotional state.

[0439] Step 4:

[0440] The server uses a generative AI model to generate new property proposals based on the desired conditions and the user's emotional information. The generative AI model, for example, uses GPT-3, receives the desired conditions and emotional information as input, and outputs proposals for optimal properties and services. This output is a new proposal list.

[0441] Specific behavior:

[0442] The server sends a request to the generative AI model using a "prompt sentence," receives the generated suggestions, and stores them (e.g., "Please suggest properties in Tokyo with good pet services for users who are feeling stressed").

[0443] Step 5:

[0444] The server sends the property list and the proposals made by the AI ​​to the terminal. The input is the property list and the new proposal list, and the output is sending these lists to the user terminal.

[0445] Specific behavior:

[0446] The server combines the property list with the AI-generated proposal list, generates a data packet to send to the user's device, and transmits it. The user's device receives this data.

[0447] Step 6:

[0448] The terminal displays these property lists to the user using a user interface that presents the information in a format that is easily understandable to the user. The input is the property list and the proposal list, and the output is the display on the user interface.

[0449] Specific behavior:

[0450] The device analyzes the data it receives and displays it in an easy-to-understand format. For example, it could display properties in a list format with a button for more detailed information.

[0451] Step 7:

[0452] The detailed information of the property selected by the user is retrieved and displayed. When the user selects a property of interest, the terminal again sends a request to the server to retrieve the detailed information. The input is the user's selection, and the output is the detailed information of that property.

[0453] Specific behavior:

[0454] When a user clicks on a property they are interested in, the device requests detailed information about that property from the server, which then receives and displays the detailed data.

[0455] Step 8:

[0456] The server calculates the transaction fee and presents it to the user. The transaction fee is calculated based on the property price and transaction details. The input is the property price and transaction terms, and the output is the calculated fee.

[0457] Specific behavior:

[0458] The server collects data related to the transaction, automatically calculates fees, and generates and transmits data to be presented to the user.

[0459] Step 9:

[0460] The user goes through the process of signing a contract for a property. When the user finally selects the property they wish to sign a contract for, the terminal assists them in proceeding with the contract procedure. The input is the user's final selection, and the output is the official completion of the contract procedure.

[0461] Specific behavior:

[0462] When the user presses the "Contract" button, the device provides an interface for entering the necessary contract information and sends a formal contract procedure request to the server. The server then generates a contract and sends it to both parties.

[0463] 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.

[0464] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0465] 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.

[0466] [Second embodiment]

[0467] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0468] 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.

[0469] 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).

[0470] 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.

[0471] 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.

[0472] 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).

[0473] 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.

[0474] 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.

[0475] 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.

[0476] 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.

[0477] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0478] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0479] ---

[0480] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[0481] First, the user accesses the property search screen. The desired conditions (e.g., floor plan, location, rent, etc.) entered by the user are sent to the server via the terminal. The terminal converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[0482] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[0483] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a further request is sent to the server, which retrieves the details and sends them to the terminal.

[0484] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server compiles all necessary information, generates a contract, and sends it to the user.

[0485] Specific examples

[0486] For example, let's say a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the device sends the information to the server. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to suggest properties such as "areas with extensive pet services" and "properties where rent is negotiable."

[0487] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[0488] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[0489] The present invention aims to provide a system that efficiently and flexibly supports property selection, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[0490] The processing flow will be explained below.

[0491] System processing steps

[0492] Step 1:

[0493] The user accesses the property search screen and enters the desired conditions (e.g., 3LDK, within 10 minutes' walk from the station, rent less than 100,000 yen).

[0494] Step 2:

[0495] The terminal converts the desired conditions entered by the user into an appropriate data format and generates a request to be sent to the server.

[0496] Step 3:

[0497] The server receives the request from the terminal and analyzes the contents.

[0498] Step 4:

[0499] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[0500] Step 5:

[0501] The server runs the generative AI model to create new proposals that closely match the user's desired conditions, such as properties in areas with good pet services or properties where rent is negotiable.

[0502] Step 6:

[0503] The server compiles the listed property information and suggestions made by the generating AI and sends them to the terminal.

[0504] Step 7:

[0505] The device displays property information and suggestions on a user interface, allowing the user to view the information and select properties that interest them.

[0506] Step 8:

[0507] To view detailed information about a particular property, the user selects the property and clicks the "View Details" button.

[0508] Step 9:

[0509] The terminal sends the user's selection to the server as a request.

[0510] Step 10:

[0511] The server receives the request and retrieves the details of the selected property from the database.

[0512] Step 11:

[0513] The server sends the acquired detailed information to the terminal.

[0514] Step 12:

[0515] The terminal displays the detailed information on the user interface so that the user can check it. The user checks the detailed information and clicks the "Contract" button if they wish to enter into a contract.

[0516] Step 13:

[0517] The device sends a contract request to the server.

[0518] Step 14:

[0519] The server receives the request and calculates the transaction fee based on the property price and contract details.

[0520] Step 15:

[0521] The server sends the calculation results to the terminal.

[0522] Step 16:

[0523] The terminal displays the calculated fee on the user interface for the user to review.

[0524] Step 17:

[0525] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[0526] Step 18:

[0527] The terminal sends the final request to the server.

[0528] Step 19:

[0529] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[0530] Step 20:

[0531] The server sends the generated contract to the user and asks for final confirmation.

[0532] The above are the processing steps of this system.

[0533] Example 1

[0534] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0535] Conventional real estate search systems make it difficult for users to efficiently find the property they desire. They also lack the mechanisms to provide new suggestions based on users' desired conditions or to support the smooth progress of contract procedures. As a result, users have to compare and consider many properties themselves, which takes time and effort.

[0536] 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.

[0537] In this invention, the server includes means for a user to input desired conditions for a property, means for transmitting the input conditions to the server, means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions, means for the server to generate new proposals that are close to the user's conditions using a generative AI model, means for the server to transmit the property list and proposals made by the generative AI to a terminal, means for the terminal to display these property lists to the user, means for the server to obtain and display detailed information about a property selected by the user, means for the server to calculate a transaction fee and present it to the user, and means for the user to enter into a contract for the property. This enables users to efficiently search for properties, receive new proposals for those properties, and smoothly proceed with the contract procedure.

[0538] The "means for the user to input desired conditions for a property" is a system component that provides an interface for the user to input the conditions for the property they desire.

[0539] The "means for transmitting input conditions to a server" is a system component that has the function of converting the desired conditions input by the user into an appropriate data format and transmitting the converted data to the server.

[0540] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a system component that has the function of the server analyzing the desired conditions received from the user, searching the property database based on those conditions, and listing properties that meet the conditions.

[0541] The "means for generating new proposals that are close to the user's conditions using a generative AI model" is a system component that has the function of using a generative AI model to generate new proposals based on the user's input conditions.

[0542] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a system component that has the function of sending the listed property information and suggestions made by the generating AI model to the terminal.

[0543] The "means by which the terminal displays these property listings to the user" refers to a system component that has the functionality to display the received property listings to the user.

[0544] The "means for obtaining and displaying detailed information about a property selected by the user" is a system component that has the function of obtaining detailed information about a property in which the user is interested from the server and displaying it to the user.

[0545] The "means for the server to calculate the transaction fee and present it to the user" is a system component that has the function of calculating the transaction fee required for a property contract and presenting that information to the user.

[0546] The "means for users to enter into a contract for a property" is a system component that provides an interface and functions for users to proceed with the contract procedure for a property.

[0547] A "property database" is a data storage system that stores various information about real estate properties.

[0548] A "generative AI model" is an artificial intelligence model used to generate new suggestions based on a user's desired criteria.

[0549] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[0550] First, a user accesses the URL of the real estate search system using a web browser. At this time, the user enters their desired conditions for the property (e.g., floor plan, location, rent, etc.) in an input form. The entered conditions are converted into an appropriate data format (e.g., JSON) by the terminal and sent to the server via the Internet.

[0551] The server receives the request sent from the device and analyzes the desired conditions. Based on this analysis, the server searches a property database (e.g., MySQL or PostgreSQL) and lists properties that match the conditions. The server then uses a generative AI model (e.g., GPT-4) to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that includes not only properties that match the conditions, but also proposals made by the generative AI model.

[0552] Next, the server sends these property lists and the generated proposals to the terminal. The terminal receives them and displays them in a list format on the user interface. The user can check the displayed property list and click on a property that interests them to view its detailed information. In this case, the terminal sends a request for detailed information to the server, and the server retrieves the property's detailed information from the database and sends it to the terminal.

[0553] If the user wishes to enter into a contract for a property, they indicate their intention by clicking the "Contract" button. The device sends this information to the server, which then calculates the fees required for the transaction and displays them on the device. If the user agrees to the fees, they click the "Confirm" button to proceed with the contract. The server then compiles all the information required for the contract, generates a formal contract, and sends it to the user. The contract is sent by email, and a link is also provided for the user to download.

[0554] Specific examples

[0555] Below is a specific example. If a user searches for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen," the user enters their desired criteria into the search screen. The device sends this information to the server, which then searches its database. It lists properties that match the criteria and uses a generative AI model to generate suggestions such as "areas with extensive pet services" and "properties where rent is negotiable."

[0556] This information is sent to the terminal and displayed on the user interface. The user can view the displayed property list, select a property that interests them, and check its detailed information. Finally, if the user wishes to enter into a contract, the server calculates the fee and presents it to the user. Once the user confirms the fee and proceeds with the contract procedure, the server generates a contract and sends it to the user.

[0557] In this way, the present invention is a system that enables users to efficiently search and select properties, receive new proposals, and smoothly proceed with contracts.

[0558] Prompt Sentence Examples

[0559] "Search for pet-friendly 2LDK apartments in Tokyo for less than 150,000 yen per month."

[0560] This system greatly improves user convenience and provides groundbreaking support for efficiently conducting real estate transactions.

[0561] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0562] Step 1:

[0563] The user accesses the property search screen.

[0564] Input: A user accesses the URL of the real estate search system in a web browser.

[0565] Specific behavior: A user opens a browser, enters the system's URL, and arrives at the search screen.

[0566] Output: Property search screen will be displayed.

[0567] Step 2:

[0568] The user inputs the desired conditions.

[0569] Input: The user enters desired conditions (e.g., floor plan, location, rent, etc.) into the input form on the search screen.

[0570] Specific operation: The user enters conditions such as "2LDK," "Tokyo," "under 150,000 yen," and "pets allowed" into the input form and clicks the search button.

[0571] Output: The desired conditions are retained in the input form.

[0572] Step 3:

[0573] The terminal sends the input information to the server.

[0574] Input: The desired conditions entered by the user.

[0575] Specific operation: The device converts the input desired conditions into an appropriate data format such as JSON and sends a request to the server via the Internet.

[0576] Output: The request data sent to the server.

[0577] Step 4:

[0578] The server analyzes the conditions and searches the database.

[0579] Input: Desired conditions sent from the terminal.

[0580] What happens: The server analyzes the request and searches the property database using a SQL query, such as "SELECT FROM properties WHERE location="Tokyo" AND rent <= 150000 AND type="2LDK" AND pet_friendly=True."

[0581] Output: A list of properties that match the criteria.

[0582] Step 5:

[0583] The server generates suggestions using a generative AI model.

[0584] Input: A list of properties that match your criteria.

[0585] How it works: The server uses a generative AI model (e.g., GPT-4) to generate new proposals based on the user's desired conditions. For example, it creates proposals such as "areas with extensive pet services" or "properties where rent is negotiable."

[0586] Output: The new list of suggestions generated.

[0587] Step 6:

[0588] The server sends property information and suggestions to the device.

[0589] Input: A list of properties that fit your criteria and a list of suggestions generated by a generative AI model.

[0590] Specific operation: The server sends this information to the terminal.

[0591] Output: Property and proposal information sent to your device.

[0592] Step 7:

[0593] The terminal displays the property listing to the user.

[0594] Input: Property information and proposal information received from the server.

[0595] Specific operation: The terminal displays this information in a list format on the user interface.

[0596] Output: The property list and proposal list displayed to the user.

[0597] Step 8:

[0598] A user views property details.

[0599] Input: Property listings in which the user is interested.

[0600] Specific operation: The user clicks on a property they are interested in and views detailed information. A request for detailed information is sent from the device to the server.

[0601] Output: A request is sent to the server for more information.

[0602] Step 9:

[0603] The server retrieves the details and sends them to the device.

[0604] Input: Request for more information.

[0605] Specific operation: The server retrieves detailed information about the property from the database and sends it to the terminal.

[0606] Output: Detailed information sent to the terminal.

[0607] Step 10:

[0608] A user requests a contract and the terminal transmits the information to the server.

[0609] Input: The property the user wishes to contract for and their intentions.

[0610] Specific operation: The user clicks the "Contract" button, and the information is sent from the device to the server.

[0611] Output: The contract request information sent to the server.

[0612] Step 11:

[0613] The server calculates the fee and displays it on the terminal.

[0614] Input: Contract information and property details.

[0615] Specific operation: The server calculates the fee required for the transaction and sends that information to the terminal.

[0616] Output: Fee information displayed on the terminal.

[0617] Step 12:

[0618] The user confirms the fee and proceeds with the contract.

[0619] Input: Fee information confirmed by the user.

[0620] Specific behavior: The user agrees to the fee and clicks the "Confirm" button.

[0621] Output: Fee confirmation information is sent to the server.

[0622] Step 13:

[0623] The server generates a contract and sends it to the user.

[0624] Input: Fee verification information and all information required for the contract.

[0625] What happens: The server generates a formal contract and sends it to the user via email, along with a link for the user to download it.

[0626] Output: The contract and download link sent to the user.

[0627] (Application example 1)

[0628] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0629] Conventional real estate search systems limit the means by which users can visually check property information in detail, making it difficult to understand properties from a realistic perspective. Furthermore, the contract procedures, from property selection to contract signing, are cumbersome, and improvements are needed to improve the user experience.

[0630] 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.

[0631] In this invention, the server includes a means for displaying detailed information about a property selected in a virtual space as a 360-degree virtual tour when the user wears a head-mounted display, and a means for the user to enter into a contract for the property, which allows the user to check the property in detail from a realistic perspective and realize a smooth contract procedure.

[0632] A "user" is an entity that searches for real estate properties and carries out procedures such as contracts.

[0633] "Property" refers to real estate, including residential properties such as apartments, condominiums, and detached houses.

[0634] "Desired conditions" are specific requests such as floor plan, location, rent, etc. that a user sets when searching for a property.

[0635] A "server" is a computer system that receives requests from users, searches a property database, and provides the results.

[0636] "Terminal" means a device on which a user inputs desired search criteria and receives and displays search results from the server, and includes smartphones, tablets, computers, etc.

[0637] A "property database" refers to a database that stores information on various real estate properties.

[0638] A "generative AI model" is an artificial intelligence model that generates new proposals that are close to the user's desired conditions.

[0639] A "head-mounted display" is a device that allows users to visually experience a virtual reality space by wearing it on their head.

[0640] "Virtual space" refers to a virtual three-dimensional space constructed using a computer system.

[0641] A "360-degree virtual tour" is a video technology that provides an environment in which users can view detailed information about a property from any angle within a virtual space.

[0642] "Transaction fees" are fees incurred when entering into a property contract and are calculated based on the property price and transaction details.

[0643] "Contract" refers to the formal procedure for the property selected by the user.

[0644] The present invention is a real estate search system that allows users to check real estate properties in detail in a virtual space using a head-mounted display and proceed to a contract. The system operates through the interaction between the user, the terminal, and the server.

[0645] First, the user puts on a head-mounted display and accesses a virtual real estate store. The user then controls a virtual avatar, moves to a property search terminal, and enters their desired conditions. These desired conditions (e.g., floor plan, location, rent, etc.) are sent to a server via the terminal. The terminal then converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[0646] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[0647] The device organizes the property information and proposals received from the server and displays them on a visual interface in the virtual space. Users can review the displayed property list and select a property they are interested in, and detailed information about it is displayed as a 360-degree virtual tour. This allows users to view the property in detail as if they were in person.

[0648] When the user finally selects the property they wish to sign a contract for, the server calculates the transaction fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server collects all necessary information, generates a contract, and sends it to the user.

[0649] This processing is performed using the following hardware and software:

[0650] Hardware: Head-mounted display (HMD), high-performance personal computer (PC)

[0651] Software: Virtual reality (VR) engines (Unity, Unreal Engine), generative AI models (OpenAI GPT-4, HuggingFace's Transformers), web application frameworks (Flask, Django), database management systems (MySQL, PostgreSQL)

[0652] For example, let's say a user is looking for a "2LDK apartment in Shibuya Ward, with a monthly fee of less than 200,000 yen, and within a 10-minute walk from the station." The user enters their desired conditions and sends them to the server. The server receives this information, searches its database, and uses a generative AI model to suggest properties in popular areas or newly built properties. This information is displayed in the virtual space, and when the user selects a property that interests them, a 360-degree virtual tour of that property begins. The user can then check the property in detail and proceed with the contract process.

[0653] Example prompts to input to the generative AI model:

[0654] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[0655] The present invention allows the user to check the property in detail from a realistic perspective and smoothly proceed with the contract procedure.

[0656] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0657] Step 1:

[0658] The user wears a head-mounted display and accesses a virtual real estate store. The user operates a virtual avatar, moves to a property search terminal, and enters desired conditions. Specifically, information such as floor plan, location, and rent is entered into a dedicated input form, and the terminal receives this as data. This data is then sent to the server.

[0659] Step 2:

[0660] The terminal converts the desired condition data entered by the user into an appropriate data format and sends a request to the server via the Internet. Here, the input data is the desired conditions, and the output is the request data converted into the appropriate data format. Data serialization technology is used for the conversion.

[0661] Step 3:

[0662] The server receives the request data sent from the terminal and analyzes the desired conditions. Based on the analysis results, the server searches the property database. The input data are the desired conditions, and the output data is a list of properties that meet the conditions. The database search is performed using an SQL query.

[0663] Step 4:

[0664] The server uses a generative AI model to generate new proposals that are close to the user's desired conditions. The input data is the desired conditions and a property list, and a prompt for the generative AI model is also generated. Specifically, the following prompt is used:

[0665] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[0666] The output data is a list of proposed properties generated by the generative AI. The generative AI model is run using OpenAI GPT-4 and HuggingFace's Transformers.

[0667] Step 5:

[0668] The server compiles search results from the property database and proposed properties based on the generative AI model, and sends them to the terminal. The input data is the property list and proposed properties, and the output data is a list of real estate information that integrates these. This data is sent in JSON format.

[0669] Step 6:

[0670] The terminal organizes the real estate information received from the server and displays it on a visual interface in the virtual space. The input data is a consolidated real estate information list, and the output is the visual information displayed on the user interface. This is done using a VR engine (Unity, Unreal Engine).

[0671] Step 7:

[0672] The user selects a property that interests them from the displayed property list and checks its detailed information as a 360-degree virtual tour. At this time, the ID of the selected property is used as input data, and a request is sent to the server. The output data is the video data of the 360-degree virtual tour.

[0673] Step 8:

[0674] The server acquires detailed information about the selected property and sends it to the terminal as video data for a 360-degree virtual tour. The input data is the property ID, and the output data is the 360-degree video data. High-resolution video files are used to acquire the data.

[0675] Step 9:

[0676] When a user checks the 360-degree virtual tour and selects a property they wish to purchase, the server calculates the transaction fee and presents it to the user via their terminal. The input data are property information and user information, and the output data is the transaction fee. Basic arithmetic operations are used for this calculation.

[0677] Step 10:

[0678] When the user confirms the fees and presses the "Contract" button, the server officially starts the contract procedure, gathers all the necessary information, generates a contract, and sends it to the user. The input data is a set of contract information, and the output data is the generated contract. Document generation software is used for this process.

[0679] 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.

[0680] ---

[0681] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[0682] First, the user accesses the property search screen and enters their desired conditions (e.g., floor plan, location, rent, etc.). Based on the user's input and operations, the emotion engine analyzes the user's emotions. The device converts the desired conditions entered by the user and the results of the emotion analysis into an appropriate data format and generates a request to send to the server.

[0683] The server receives requests from the device and analyzes their contents. Based on the analysis, the server searches its property database and lists properties that meet the user's requirements. The server then uses a generative AI model to generate new proposals that are close to the user's desired conditions. These proposals may include, for example, properties in areas with extensive pet services or properties where rent is negotiable.

[0684] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby transmitting the optimal property listing based on the user's emotional data to the terminal.

[0685] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the details and sends them to the terminal.

[0686] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[0687] Specific examples

[0688] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[0689] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[0690] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[0691] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[0692] The present invention aims to provide a system that recognizes a user's emotions and supports the selection of the most suitable property based on those emotions, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[0693] The processing flow will be explained below.

[0694] System processing steps

[0695] Step 1:

[0696] The user accesses the property search screen and enters the desired conditions (e.g., floor plan, location, rent, etc.).

[0697] Step 2:

[0698] The emotion engine analyzes the user's input and operation methods (e.g., keyboard typing speed, mouse movements, etc.) and generates the user's emotion data.

[0699] Step 3:

[0700] The terminal transmits a request to the server, which includes the desired conditions input by the user and the emotion data analyzed by the emotion engine.

[0701] Step 4:

[0702] The server receives the request from the terminal and analyzes its contents (desired conditions and emotional data).

[0703] Step 5:

[0704] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[0705] Step 6:

[0706] The server runs the generative AI model and generates new proposals that are close to the user's desired conditions (e.g., properties with good surrounding environments, properties with extensive pet services, etc.).

[0707] Step 7:

[0708] The server adjusts the display order of property listings and proposals based on the user's emotional data analyzed by the emotion engine.

[0709] Step 8:

[0710] The server compiles the listed property information and suggestions from the emotion engine and sends them to the terminal.

[0711] Step 9:

[0712] The terminal organizes the property information and proposals received from the server and displays them on the user interface.

[0713] Step 10:

[0714] The user reviews the displayed property list and clicks to view details of the property that interests them.

[0715] Step 11:

[0716] The terminal sends the user's selection to the server as a request.

[0717] Step 12:

[0718] The server receives the request and retrieves the details of the selected property from the database.

[0719] Step 13:

[0720] The server sends the acquired detailed information to the terminal.

[0721] Step 14:

[0722] The terminal displays the detailed information on the user interface so that the user can check it.

[0723] Step 15:

[0724] The user checks the detailed information and, if he wishes to enter into a contract, clicks the "Contract" button.

[0725] Step 16:

[0726] The device sends a contract request to the server.

[0727] Step 17:

[0728] The server receives the request and calculates the transaction fee based on the property price and contract details.

[0729] Step 18:

[0730] The server sends the calculation results to the terminal.

[0731] Step 19:

[0732] The terminal displays the calculated fee on the user interface for the user to review.

[0733] Step 20:

[0734] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[0735] Step 21:

[0736] The terminal sends the final request to the server.

[0737] Step 22:

[0738] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[0739] Step 23:

[0740] The server sends the generated contract to the user and asks for final confirmation.

[0741] The above are the processing steps of this system.

[0742] Example 2

[0743] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0744] Conventional real estate search systems simply listed properties based on the user's input criteria without considering the user's feelings, making it difficult to fully meet the user's needs. Furthermore, the inability to make suggestions based on the user's feelings narrowed the range of choices, making it difficult to find the perfect property. Furthermore, the process of entering into a property contract was complicated, creating the problem of stress for users.

[0745] 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.

[0746] In this invention, the server includes a means for transmitting input conditions and emotion data to the server, a means for searching a property database based on the transmitted conditions and emotion data to list properties that meet the conditions, and a means for optimizing the property list and generated proposals using an emotion engine. This enables optimal property proposals based on the user's emotions, thereby increasing user satisfaction. Furthermore, by taking emotion data into consideration, properties that interest the user can be efficiently proposed, and contract procedures can proceed smoothly.

[0747] "Input conditions" refers to the desired conditions (e.g., location, layout, rent, etc.) specified by the user when searching for a property.

[0748] "Emotion data" refers to data that represents the user's emotional state, and refers to information acquired based on facial expression recognition, operation speed, and the like.

[0749] "Server" refers to a computer system that receives conditions and emotional data entered by users, searches a property database, and generates and optimizes optimal proposals using a generative AI model.

[0750] A "property database" is a database that stores information about properties, and refers to an information source that can be searched based on the user's desired conditions.

[0751] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates new proposals based on a user's desired conditions.

[0752] An "emotion engine" refers to a technology that analyzes users' emotional data and optimizes property listings and proposals based on the results.

[0753] "Terminal" refers to the device (e.g., PC, smartphone, tablet) used by a user to search for properties and view detailed information.

[0754] "Transaction fee" refers to the fee incurred when a user proceeds with a property contract, and is calculated based on the property price and transaction details.

[0755] "Detailed information" refers to additional information about the property (e.g., specific facilities, surrounding environment, contract terms, etc.).

[0756] "Means of entering into a contract" refers to a series of processes and procedures for the user to proceed with the contract procedure for the property they desire.

[0757] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[0758] System configuration

[0759] This system is configured using the following main hardware and software:

[0760] 1. Device: The device on which a user searches for properties and views detailed information. Examples include computers, smartphones, and tablets.

[0761] 2. Server: A remote computer system that processes user requests, searches a property database, and uses an emotion engine. The server manages a database such as MySQL and uses a generative AI model (e.g., OpenAI GPT-4) and an emotion engine (e.g., IBM Watson Tone Analyzer).

[0762] 3. Property database: A database that stores information about properties. It provides the necessary property information based on search criteria.

[0763] 4. Emotion Engine: Software that analyzes user emotional data and optimizes property listings and offers based on the results.

[0764] System Operation

[0765] The user accesses the real estate search screen and enters their desired conditions (for example, floor plan, location, rent, etc.). Specifically, they enter "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[0766] The terminal converts the desired conditions and emotion data entered by the user into an appropriate data format and generates a request to send to the server. The emotion data includes the user's facial expression, operation speed, etc., and the resulting emotion analysis data.

[0767] The server receives requests from the device and analyzes the content. The analyzed information includes, for example, desired conditions and emotional data. The server searches the property database and lists properties that match the conditions. The server then uses a generative AI model to generate new proposals that are closer to the user's desired conditions. These proposals include, for example, "areas with extensive pet services" and "properties where rent is negotiable."

[0768] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby generating an optimal property listing based on the user's emotional data and sending it to the terminal.

[0769] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the detailed information and sends it to the terminal.

[0770] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[0771] Specific examples

[0772] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[0773] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[0774] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[0775] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[0776] Prompt Sentence Examples

[0777] "A user is looking for a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month. The user enters search criteria, and emotional data is also collected. The server should generate a list of properties that match the criteria, suggesting areas with good pet services and properties where the rent is negotiable. Generate an optimal list of properties based on the user's emotional data, and send that list to the device."

[0778] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0779] Step 1:

[0780] The user accesses the property search screen and enters the desired conditions.

[0781] Specific operation: The user opens a real estate search screen via a web browser or app and enters specific criteria, such as "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[0782] Input: Desired conditions

[0783] Output: Data format of the desired conditions entered

[0784] Step 2:

[0785] The terminal converts the user's desired conditions and emotional data into an appropriate data format.

[0786] Specific operation: The device collects the desired conditions entered by the user and emotional data from sensors such as the camera and microphone, analyzes them, and converts them into an appropriate data format such as JSON.

[0787] Input: Desired conditions, emotional data

[0788] Output: Converted desired conditions and emotion data

[0789] Step 3:

[0790] The device sends a request to the server.

[0791] Specific operation: The device sends the converted desired conditions and emotion data to the server as an HTTP request.

[0792] Input: Converted desired condition data and emotion data

[0793] Output: Request sent to the server

[0794] Step 4:

[0795] The server receives the request and parses it.

[0796] Specific operation: The server receives an HTTP request, analyzes it, and obtains the desired conditions and emotion data. It then separates the desired conditions for database search and the emotion data for emotion analysis.

[0797] Input: The request sent to the server

[0798] Output: Analyzed desired conditions and emotion data

[0799] Step 5:

[0800] The server searches the property database and lists properties that match the criteria.

[0801] Specific operation: The server searches a property database (e.g., MySQL) based on the analyzed desired conditions, and filters and lists properties that match the conditions.

[0802] Input: Parsed desired conditions

[0803] Output: Listed property data

[0804] Step 6:

[0805] The server generates new proposals using a generative AI model.

[0806] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) to add suggestions to the listed property data, such as "areas with extensive pet services" and "properties where rent is negotiable."

[0807] Input: Listed property data

[0808] Output: The newly generated proposal

[0809] Step 7:

[0810] The server uses an emotion engine to optimize property listings and offers.

[0811] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotion data. Based on the results, it prioritizes the listed properties and generated suggestions to create an optimized listing.

[0812] Input: emotion data, newly generated suggestions

[0813] Output: Optimized property listings and recommendations

[0814] Step 8:

[0815] The server sends the optimized property listings and suggestions to the device.

[0816] Specific operation: The server converts the optimized property listings and proposals into an appropriate data format, such as JSON, and sends it to the terminal as an HTTP response.

[0817] Input: Optimized property listings and proposals

[0818] Output: Property list and proposals sent to the device

[0819] Step 9:

[0820] The device displays the property information and allows the user to view the details.

[0821] Specific operation: The terminal displays the property information and suggestions received from the server on the user interface. The user can check the displayed property list and click to view detailed information on the property that interests them.

[0822] Input: Property listings and offers sent to your device

[0823] Output: Property list and details displayed in a user interface

[0824] Step 10:

[0825] The user selects the property they wish to contract for and confirms the transaction fee.

[0826] Specific operation: When a user presses the "Contract" button for a specific property, the terminal sends a request to the server again. The server calculates the transaction fee for this property and returns it to the terminal.

[0827] Input: User selection information

[0828] Output: Calculated transaction fee

[0829] Step 11:

[0830] The server initiates the contract procedure and sends the necessary information to the user.

[0831] Specific operation: When the user checks the fees and property details and presses the "Contract" button, the server responds to this action and starts the contract procedure, collating the necessary information and sending it to the user.

[0832] Input: User's contract intention confirmation information

[0833] Output: Information required for contract procedures and contract

[0834] (Application example 2)

[0835] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0836] Conventional real estate search systems simply list properties based on the user's desired conditions, but are unable to make recommendations that are optimized for the user's emotions and circumstances. This leaves them lacking in ingenuity to improve user satisfaction. There is also room for improvement in proposing payment methods that take the user's emotions into account, and in calculating transaction fees. Furthermore, there is a need for a system that can facilitate a series of real estate transactions in a smoother and more personalized manner.

[0837] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input desired property conditions; means for transmitting the input conditions to the server; means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions; means for the server to generate new proposals that are close to the user's conditions using a generative AI model; means for the server to transmit the property list and the generative AI proposals to a terminal; means for the terminal to display these property lists to the user; means for recognizing the user's emotions and proposing a payment method based on the emotions; means for acquiring and displaying detailed information about the property selected by the user; means for the server to calculate a transaction fee and present it to the user; and means for the user to enter into a contract for the property. This enables optimal property proposals and payment methods to be proposed while taking the user's emotions into consideration. Furthermore, smooth transaction progress and improved user satisfaction are achieved.

[0838] "Means for inputting desired conditions for a property" refers to an interface that allows a user to specify the characteristics and requirements of a property they desire.

[0839] The "means for transmitting the input conditions to the server" refers to a communication means for transmitting the information input by the user to a remote server.

[0840] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a method in which the server finds properties from the database that meet the conditions received and presents them to the user.

[0841] "Means for the server to use a generative AI model to generate new proposals that are close to the user's conditions" refers to a system that utilizes artificial intelligence technology to automatically generate new proposals based on the user's conditions.

[0842] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a method for transferring the generated property list and suggestions to the user's device.

[0843] "Means by which the terminal displays these property listings to the user" refers to an interface for visually displaying the property listings on the user's device.

[0844] "Means for recognizing a user's emotions and suggesting payment methods based on those emotions" refers to a method for analyzing a user's emotional state and presenting appropriate payment options.

[0845] "Means for obtaining and displaying detailed information about a property selected by a user" refers to a method for obtaining specific information about a property selected by a user and displaying it.

[0846] "Means for the server to calculate transaction fees and present them to the user" refers to a method for automatically calculating fees related to real estate transactions and notifying the user of the results.

[0847] "Means by which a user enters into a contract for a property" refers to the method by which a user completes the contract procedures for the property selected by the user.

[0848] The present invention is a real estate search system that recognizes a user's emotions and suggests optimal properties and payment methods. This system is composed of multiple components, such as a server, a user terminal, an emotion recognition engine, and a generative AI model. Specific embodiments for implementing the present invention are described below.

[0849] 1. System Configuration

[0850] 1.1 User terminal

[0851] The user terminal uses a device such as a smartphone, smart glasses, or head-mounted display, and provides an interface for the user to input desired conditions for a property. Once the user enters the desired conditions, they are sent to the server.

[0852] 1.2 Server

[0853] The server searches a property database based on the received desired conditions and lists properties that match the conditions. The server also uses a generative AI model to generate new proposals that are close to the user's conditions. These proposals can include information about the property's surrounding environment and services.

[0854] 1.3 Emotion Recognition Engine

[0855] The emotion recognition engine has the ability to analyze the user's emotional state. For example, it analyzes the user's facial image and recognizes whether the user is feeling happiness, stress, surprise, etc. This emotional information is sent to the server and used to optimize property listings and payment methods.

[0856] 2. Data processing and calculation

[0857] 2.1 Data Acquisition

[0858] The user enters the desired property conditions and the terminal sends the data to the server, which analyzes the received data and searches the property database to find properties that meet the conditions.

[0859] 2.2 Emotion recognition

[0860] It uses cameras and sensors to recognize emotions from images of the user's face. The emotion recognition engine uses libraries such as OpenCV and dlib to analyze the user's facial expressions and behavior.

[0861] 2.3 Proposal Generation by AI

[0862] The server uses a generative AI model (e.g., GPT-3) to generate new property suggestions, which are optimized based on the user's desired conditions and emotional information.

[0863] 3. Specific Examples

[0864] Let's say a user is looking for a "2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month." The user enters their desired conditions, and the emotion recognition engine analyzes the user's input, facial expressions, and operation speed. As a result, the request sent to the server includes the desired conditions as well as the user's emotional data. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to make suggestions such as "areas with extensive pet services" and "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions, and then sends them.

[0865] Prompt Sentence Examples

[0866] Recognize emotions from a user's facial image and suggest payment options that optimize the user experience. For example, if a user is feeling stressed, offer a relaxation coupon and recommend credit card payment.

[0867] In this way, the present invention is a system that can provide optimal property proposals and payment methods while taking into consideration the user's feelings, making it possible to proceed with real estate transactions in a smoother and more personalized manner.

[0868] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0869] Step 1:

[0870] The user operates the terminal and inputs the desired conditions for the property. The input conditions are detailed information such as "a 2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." Once this input is complete, the desired condition data is sent to the server. The input here is the user's desired requirements and the associated fields, and the output is the transmission of that data.

[0871] Specific behavior:

[0872] The user opens the property search app and enters each item (location, rent, floor plan, etc.) along the interface. They then press the "Search" button, which sends the data to the server.

[0873] Step 2:

[0874] The server analyzes the desired conditions received and searches the property database based on them. It then lists properties that match the conditions from the property information in the database. In this process, a search query is generated based on the desired conditions entered, and data that matches the conditions is extracted based on that query. The output is a list of properties that match the conditions.

[0875] Specific behavior:

[0876] The server analyzes the received data, generates SQL queries, etc., and executes searches against the database. The resulting property list is then temporarily saved.

[0877] Step 3:

[0878] The server uses an emotion recognition engine to analyze the data to recognize the user's emotions. The emotion recognition engine takes the user's facial image data acquired from the camera as input and outputs the user's emotional state. This output is one of several emotional states, such as "happiness" or "stress."

[0879] Specific behavior:

[0880] The user takes a facial image using the device camera or streams video in real time, and the emotion recognition engine processes the video. The result is sent to the server as the user's current emotional state.

[0881] Step 4:

[0882] The server uses a generative AI model to generate new property proposals based on the desired conditions and the user's emotional information. The generative AI model, for example, uses GPT-3, receives the desired conditions and emotional information as input, and outputs proposals for optimal properties and services. This output is a new proposal list.

[0883] Specific behavior:

[0884] The server sends a request to the generative AI model using a "prompt sentence," receives the generated suggestions, and stores them (e.g., "Please suggest properties in Tokyo with good pet services for users who are feeling stressed").

[0885] Step 5:

[0886] The server sends the property list and the proposals made by the AI ​​to the terminal. The input is the property list and the new proposal list, and the output is sending these lists to the user terminal.

[0887] Specific behavior:

[0888] The server combines the property list with the AI-generated proposal list, generates a data packet to send to the user's device, and transmits it. The user's device receives this data.

[0889] Step 6:

[0890] The terminal displays these property lists to the user using a user interface that presents the information in a format that is easily understandable to the user. The input is the property list and the proposal list, and the output is the display on the user interface.

[0891] Specific behavior:

[0892] The device analyzes the data it receives and displays it in an easy-to-understand format. For example, it could display properties in a list format with a button for more detailed information.

[0893] Step 7:

[0894] The detailed information of the property selected by the user is retrieved and displayed. When the user selects a property of interest, the terminal again sends a request to the server to retrieve the detailed information. The input is the user's selection, and the output is the detailed information of that property.

[0895] Specific behavior:

[0896] When a user clicks on a property they are interested in, the device requests detailed information about that property from the server, which then receives and displays the detailed data.

[0897] Step 8:

[0898] The server calculates the transaction fee and presents it to the user. The transaction fee is calculated based on the property price and transaction details. The input is the property price and transaction terms, and the output is the calculated fee.

[0899] Specific behavior:

[0900] The server collects data related to the transaction, automatically calculates fees, and generates and transmits data to be presented to the user.

[0901] Step 9:

[0902] The user goes through the process of signing a contract for a property. When the user finally selects the property they wish to sign a contract for, the terminal assists them in proceeding with the contract procedure. The input is the user's final selection, and the output is the official completion of the contract procedure.

[0903] Specific behavior:

[0904] When the user presses the "Contract" button, the device provides an interface for entering the necessary contract information and sends a formal contract procedure request to the server. The server then generates a contract and sends it to both parties.

[0905] 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.

[0906] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0907] 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.

[0908] [Third embodiment]

[0909] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0910] 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.

[0911] 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).

[0912] 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.

[0913] 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.

[0914] 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).

[0915] 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.

[0916] 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.

[0917] 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.

[0918] 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.

[0919] 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.

[0920] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0921] ---

[0922] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[0923] First, the user accesses the property search screen. The desired conditions (e.g., floor plan, location, rent, etc.) entered by the user are sent to the server via the terminal. The terminal converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[0924] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[0925] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a further request is sent to the server, which retrieves the details and sends them to the terminal.

[0926] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server compiles all necessary information, generates a contract, and sends it to the user.

[0927] Specific examples

[0928] For example, let's say a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the device sends the information to the server. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to suggest properties such as "areas with extensive pet services" and "properties where rent is negotiable."

[0929] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[0930] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[0931] The present invention aims to provide a system that efficiently and flexibly supports property selection, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[0932] The processing flow will be explained below.

[0933] System processing steps

[0934] Step 1:

[0935] The user accesses the property search screen and enters the desired conditions (e.g., 3LDK, within 10 minutes' walk from the station, rent less than 100,000 yen).

[0936] Step 2:

[0937] The terminal converts the desired conditions entered by the user into an appropriate data format and generates a request to be sent to the server.

[0938] Step 3:

[0939] The server receives the request from the terminal and analyzes the contents.

[0940] Step 4:

[0941] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[0942] Step 5:

[0943] The server runs the generative AI model to create new proposals that closely match the user's desired conditions, such as properties in areas with good pet services or properties where rent is negotiable.

[0944] Step 6:

[0945] The server compiles the listed property information and suggestions made by the generating AI and sends them to the terminal.

[0946] Step 7:

[0947] The device displays property information and suggestions on a user interface, allowing the user to view the information and select properties that interest them.

[0948] Step 8:

[0949] To view detailed information about a particular property, the user selects the property and clicks the "View Details" button.

[0950] Step 9:

[0951] The terminal sends the user's selection to the server as a request.

[0952] Step 10:

[0953] The server receives the request and retrieves the details of the selected property from the database.

[0954] Step 11:

[0955] The server sends the acquired detailed information to the terminal.

[0956] Step 12:

[0957] The terminal displays the detailed information on the user interface so that the user can check it. The user checks the detailed information and clicks the "Contract" button if they wish to enter into a contract.

[0958] Step 13:

[0959] The device sends a contract request to the server.

[0960] Step 14:

[0961] The server receives the request and calculates the transaction fee based on the property price and contract details.

[0962] Step 15:

[0963] The server sends the calculation results to the terminal.

[0964] Step 16:

[0965] The terminal displays the calculated fee on the user interface for the user to review.

[0966] Step 17:

[0967] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[0968] Step 18:

[0969] The terminal sends the final request to the server.

[0970] Step 19:

[0971] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[0972] Step 20:

[0973] The server sends the generated contract to the user and asks for final confirmation.

[0974] The above are the processing steps of this system.

[0975] Example 1

[0976] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0977] Conventional real estate search systems make it difficult for users to efficiently find the property they desire. They also lack the mechanisms to provide new suggestions based on users' desired conditions or to support the smooth progress of contract procedures. As a result, users have to compare and consider many properties themselves, which takes time and effort.

[0978] 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.

[0979] In this invention, the server includes means for a user to input desired conditions for a property, means for transmitting the input conditions to the server, means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions, means for the server to generate new proposals that are close to the user's conditions using a generative AI model, means for the server to transmit the property list and proposals made by the generative AI to a terminal, means for the terminal to display these property lists to the user, means for the server to obtain and display detailed information about a property selected by the user, means for the server to calculate a transaction fee and present it to the user, and means for the user to enter into a contract for the property. This enables users to efficiently search for properties, receive new proposals for those properties, and smoothly proceed with the contract procedure.

[0980] The "means for the user to input desired conditions for a property" is a system component that provides an interface for the user to input the conditions for the property they desire.

[0981] The "means for transmitting input conditions to a server" is a system component that has the function of converting the desired conditions input by the user into an appropriate data format and transmitting the converted data to the server.

[0982] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a system component that has the function of the server analyzing the desired conditions received from the user, searching the property database based on those conditions, and listing properties that meet the conditions.

[0983] The "means for generating new proposals that are close to the user's conditions using a generative AI model" is a system component that has the function of using a generative AI model to generate new proposals based on the user's input conditions.

[0984] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a system component that has the function of sending the listed property information and suggestions made by the generating AI model to the terminal.

[0985] The "means by which the terminal displays these property listings to the user" refers to a system component that has the functionality to display the received property listings to the user.

[0986] The "means for obtaining and displaying detailed information about a property selected by the user" is a system component that has the function of obtaining detailed information about a property in which the user is interested from the server and displaying it to the user.

[0987] The "means for the server to calculate the transaction fee and present it to the user" is a system component that has the function of calculating the transaction fee required for a property contract and presenting that information to the user.

[0988] The "means for users to enter into a contract for a property" is a system component that provides an interface and functions for users to proceed with the contract procedure for a property.

[0989] A "property database" is a data storage system that stores various information about real estate properties.

[0990] A "generative AI model" is an artificial intelligence model used to generate new suggestions based on a user's desired criteria.

[0991] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[0992] First, a user accesses the URL of the real estate search system using a web browser. At this time, the user enters their desired conditions for the property (e.g., floor plan, location, rent, etc.) in an input form. The entered conditions are converted into an appropriate data format (e.g., JSON) by the terminal and sent to the server via the Internet.

[0993] The server receives the request sent from the device and analyzes the desired conditions. Based on this analysis, the server searches a property database (e.g., MySQL or PostgreSQL) and lists properties that match the conditions. The server then uses a generative AI model (e.g., GPT-4) to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that includes not only properties that match the conditions, but also proposals made by the generative AI model.

[0994] Next, the server sends these property lists and the generated proposals to the terminal. The terminal receives them and displays them in a list format on the user interface. The user can check the displayed property list and click on a property that interests them to view its detailed information. In this case, the terminal sends a request for detailed information to the server, and the server retrieves the property's detailed information from the database and sends it to the terminal.

[0995] If the user wishes to enter into a contract for a property, they indicate their intention by clicking the "Contract" button. The device sends this information to the server, which then calculates the fees required for the transaction and displays them on the device. If the user agrees to the fees, they click the "Confirm" button to proceed with the contract. The server then compiles all the information required for the contract, generates a formal contract, and sends it to the user. The contract is sent by email, and a link is also provided for the user to download.

[0996] Specific examples

[0997] Below is a specific example. If a user searches for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen," the user enters their desired criteria into the search screen. The device sends this information to the server, which then searches its database. It lists properties that match the criteria and uses a generative AI model to generate suggestions such as "areas with extensive pet services" and "properties where rent is negotiable."

[0998] This information is sent to the terminal and displayed on the user interface. The user can view the displayed property list, select a property that interests them, and check its detailed information. Finally, if the user wishes to enter into a contract, the server calculates the fee and presents it to the user. Once the user confirms the fee and proceeds with the contract procedure, the server generates a contract and sends it to the user.

[0999] In this way, the present invention is a system that enables users to efficiently search and select properties, receive new proposals, and smoothly proceed with contracts.

[1000] Prompt Sentence Examples

[1001] "Search for pet-friendly 2LDK apartments in Tokyo for less than 150,000 yen per month."

[1002] This system greatly improves user convenience and provides groundbreaking support for efficiently conducting real estate transactions.

[1003] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1004] Step 1:

[1005] The user accesses the property search screen.

[1006] Input: A user accesses the URL of the real estate search system in a web browser.

[1007] Specific behavior: A user opens a browser, enters the system's URL, and arrives at the search screen.

[1008] Output: Property search screen will be displayed.

[1009] Step 2:

[1010] The user inputs the desired conditions.

[1011] Input: The user enters desired conditions (e.g., floor plan, location, rent, etc.) into the input form on the search screen.

[1012] Specific operation: The user enters conditions such as "2LDK," "Tokyo," "under 150,000 yen," and "pets allowed" into the input form and clicks the search button.

[1013] Output: The desired conditions are retained in the input form.

[1014] Step 3:

[1015] The terminal sends the input information to the server.

[1016] Input: The desired conditions entered by the user.

[1017] Specific operation: The device converts the input desired conditions into an appropriate data format such as JSON and sends a request to the server via the Internet.

[1018] Output: The request data sent to the server.

[1019] Step 4:

[1020] The server analyzes the conditions and searches the database.

[1021] Input: Desired conditions sent from the terminal.

[1022] What happens: The server analyzes the request and searches the property database using a SQL query, such as "SELECT FROM properties WHERE location="Tokyo" AND rent <= 150000 AND type="2LDK" AND pet_friendly=True."

[1023] Output: A list of properties that match the criteria.

[1024] Step 5:

[1025] The server generates suggestions using a generative AI model.

[1026] Input: A list of properties that match your criteria.

[1027] How it works: The server uses a generative AI model (e.g., GPT-4) to generate new proposals based on the user's desired conditions. For example, it creates proposals such as "areas with extensive pet services" or "properties where rent is negotiable."

[1028] Output: The new list of suggestions generated.

[1029] Step 6:

[1030] The server sends property information and suggestions to the device.

[1031] Input: A list of properties that fit your criteria and a list of suggestions generated by a generative AI model.

[1032] Specific operation: The server sends this information to the terminal.

[1033] Output: Property and proposal information sent to your device.

[1034] Step 7:

[1035] The terminal displays the property listing to the user.

[1036] Input: Property information and proposal information received from the server.

[1037] Specific operation: The terminal displays this information in a list format on the user interface.

[1038] Output: The property list and proposal list displayed to the user.

[1039] Step 8:

[1040] A user views property details.

[1041] Input: Property listings in which the user is interested.

[1042] Specific operation: The user clicks on a property they are interested in and views detailed information. A request for detailed information is sent from the device to the server.

[1043] Output: A request is sent to the server for more information.

[1044] Step 9:

[1045] The server retrieves the details and sends them to the device.

[1046] Input: Request for more information.

[1047] Specific operation: The server retrieves detailed information about the property from the database and sends it to the terminal.

[1048] Output: Detailed information sent to the terminal.

[1049] Step 10:

[1050] A user requests a contract and the terminal transmits the information to the server.

[1051] Input: The property the user wishes to contract for and their intentions.

[1052] Specific operation: The user clicks the "Contract" button, and the information is sent from the device to the server.

[1053] Output: The contract request information sent to the server.

[1054] Step 11:

[1055] The server calculates the fee and displays it on the terminal.

[1056] Input: Contract information and property details.

[1057] Specific operation: The server calculates the fee required for the transaction and sends that information to the terminal.

[1058] Output: Fee information displayed on the terminal.

[1059] Step 12:

[1060] The user confirms the fee and proceeds with the contract.

[1061] Input: Fee information confirmed by the user.

[1062] Specific behavior: The user agrees to the fee and clicks the "Confirm" button.

[1063] Output: Fee confirmation information is sent to the server.

[1064] Step 13:

[1065] The server generates a contract and sends it to the user.

[1066] Input: Fee verification information and all information required for the contract.

[1067] What happens: The server generates a formal contract and sends it to the user via email, along with a link for the user to download it.

[1068] Output: The contract and download link sent to the user.

[1069] (Application example 1)

[1070] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1071] Conventional real estate search systems limit the means by which users can visually check property information in detail, making it difficult to understand properties from a realistic perspective. Furthermore, the contract procedures, from property selection to contract signing, are cumbersome, and improvements are needed to improve the user experience.

[1072] 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.

[1073] In this invention, the server includes a means for displaying detailed information about a property selected in a virtual space as a 360-degree virtual tour when the user wears a head-mounted display, and a means for the user to enter into a contract for the property, which allows the user to check the property in detail from a realistic perspective and realize a smooth contract procedure.

[1074] A "user" is an entity that searches for real estate properties and carries out procedures such as contracts.

[1075] "Property" refers to real estate, including residential properties such as apartments, condominiums, and detached houses.

[1076] "Desired conditions" are specific requests such as floor plan, location, rent, etc. that a user sets when searching for a property.

[1077] A "server" is a computer system that receives requests from users, searches a property database, and provides the results.

[1078] "Terminal" means a device on which a user inputs desired search criteria and receives and displays search results from the server, and includes smartphones, tablets, computers, etc.

[1079] A "property database" refers to a database that stores information on various real estate properties.

[1080] A "generative AI model" is an artificial intelligence model that generates new proposals that are close to the user's desired conditions.

[1081] A "head-mounted display" is a device that allows users to visually experience a virtual reality space by wearing it on their head.

[1082] "Virtual space" refers to a virtual three-dimensional space constructed using a computer system.

[1083] A "360-degree virtual tour" is a video technology that provides an environment in which users can view detailed information about a property from any angle within a virtual space.

[1084] "Transaction fees" are fees incurred when entering into a property contract and are calculated based on the property price and transaction details.

[1085] "Contract" refers to the formal procedure for the property selected by the user.

[1086] The present invention is a real estate search system that allows users to check real estate properties in detail in a virtual space using a head-mounted display and proceed to a contract. The system operates through the interaction between the user, the terminal, and the server.

[1087] First, the user puts on a head-mounted display and accesses a virtual real estate store. The user then controls a virtual avatar, moves to a property search terminal, and enters their desired conditions. These desired conditions (e.g., floor plan, location, rent, etc.) are sent to a server via the terminal. The terminal then converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[1088] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[1089] The device organizes the property information and proposals received from the server and displays them on a visual interface in the virtual space. Users can review the displayed property list and select a property they are interested in, and detailed information about it is displayed as a 360-degree virtual tour. This allows users to view the property in detail as if they were in person.

[1090] When the user finally selects the property they wish to sign a contract for, the server calculates the transaction fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server collects all necessary information, generates a contract, and sends it to the user.

[1091] This processing is performed using the following hardware and software:

[1092] Hardware: Head-mounted display (HMD), high-performance personal computer (PC)

[1093] Software: Virtual reality (VR) engines (Unity, Unreal Engine), generative AI models (OpenAI GPT-4, HuggingFace's Transformers), web application frameworks (Flask, Django), database management systems (MySQL, PostgreSQL)

[1094] For example, let's say a user is looking for a "2LDK apartment in Shibuya Ward, with a monthly fee of less than 200,000 yen, and within a 10-minute walk from the station." The user enters their desired conditions and sends them to the server. The server receives this information, searches its database, and uses a generative AI model to suggest properties in popular areas or newly built properties. This information is displayed in the virtual space, and when the user selects a property that interests them, a 360-degree virtual tour of that property begins. The user can then check the property in detail and proceed with the contract process.

[1095] Example prompts to input to the generative AI model:

[1096] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[1097] The present invention allows the user to check the property in detail from a realistic perspective and smoothly proceed with the contract procedure.

[1098] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1099] Step 1:

[1100] The user wears a head-mounted display and accesses a virtual real estate store. The user operates a virtual avatar, moves to a property search terminal, and enters desired conditions. Specifically, information such as floor plan, location, and rent is entered into a dedicated input form, and the terminal receives this as data. This data is then sent to the server.

[1101] Step 2:

[1102] The terminal converts the desired condition data entered by the user into an appropriate data format and sends a request to the server via the Internet. Here, the input data is the desired conditions, and the output is the request data converted into the appropriate data format. Data serialization technology is used for the conversion.

[1103] Step 3:

[1104] The server receives the request data sent from the terminal and analyzes the desired conditions. Based on the analysis results, the server searches the property database. The input data are the desired conditions, and the output data is a list of properties that meet the conditions. The database search is performed using an SQL query.

[1105] Step 4:

[1106] The server uses a generative AI model to generate new proposals that are close to the user's desired conditions. The input data is the desired conditions and a property list, and a prompt for the generative AI model is also generated. Specifically, the following prompt is used:

[1107] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[1108] The output data is a list of proposed properties generated by the generative AI. The generative AI model is run using OpenAI GPT-4 and HuggingFace's Transformers.

[1109] Step 5:

[1110] The server compiles search results from the property database and proposed properties based on the generative AI model, and sends them to the terminal. The input data is the property list and proposed properties, and the output data is a list of real estate information that integrates these. This data is sent in JSON format.

[1111] Step 6:

[1112] The terminal organizes the real estate information received from the server and displays it on a visual interface in the virtual space. The input data is a consolidated real estate information list, and the output is the visual information displayed on the user interface. This is done using a VR engine (Unity, Unreal Engine).

[1113] Step 7:

[1114] The user selects a property that interests them from the displayed property list and checks its detailed information as a 360-degree virtual tour. At this time, the ID of the selected property is used as input data, and a request is sent to the server. The output data is the video data of the 360-degree virtual tour.

[1115] Step 8:

[1116] The server acquires detailed information about the selected property and sends it to the terminal as video data for a 360-degree virtual tour. The input data is the property ID, and the output data is the 360-degree video data. High-resolution video files are used to acquire the data.

[1117] Step 9:

[1118] When a user checks the 360-degree virtual tour and selects a property they wish to purchase, the server calculates the transaction fee and presents it to the user via their terminal. The input data are property information and user information, and the output data is the transaction fee. Basic arithmetic operations are used for this calculation.

[1119] Step 10:

[1120] When the user confirms the fees and presses the "Contract" button, the server officially starts the contract procedure, gathers all the necessary information, generates a contract, and sends it to the user. The input data is a set of contract information, and the output data is the generated contract. Document generation software is used for this process.

[1121] 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.

[1122] ---

[1123] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[1124] First, the user accesses the property search screen and enters their desired conditions (e.g., floor plan, location, rent, etc.). Based on the user's input and operations, the emotion engine analyzes the user's emotions. The device converts the desired conditions entered by the user and the results of the emotion analysis into an appropriate data format and generates a request to send to the server.

[1125] The server receives requests from the device and analyzes their contents. Based on the analysis, the server searches its property database and lists properties that meet the user's requirements. The server then uses a generative AI model to generate new proposals that are close to the user's desired conditions. These proposals may include, for example, properties in areas with extensive pet services or properties where rent is negotiable.

[1126] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby transmitting the optimal property listing based on the user's emotional data to the terminal.

[1127] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the details and sends them to the terminal.

[1128] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[1129] Specific examples

[1130] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[1131] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[1132] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[1133] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[1134] The present invention aims to provide a system that recognizes a user's emotions and supports the selection of the most suitable property based on those emotions, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[1135] The processing flow will be explained below.

[1136] System processing steps

[1137] Step 1:

[1138] The user accesses the property search screen and enters the desired conditions (e.g., floor plan, location, rent, etc.).

[1139] Step 2:

[1140] The emotion engine analyzes the user's input and operation methods (e.g., keyboard typing speed, mouse movements, etc.) and generates the user's emotion data.

[1141] Step 3:

[1142] The terminal transmits a request to the server, which includes the desired conditions input by the user and the emotion data analyzed by the emotion engine.

[1143] Step 4:

[1144] The server receives the request from the terminal and analyzes its contents (desired conditions and emotional data).

[1145] Step 5:

[1146] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[1147] Step 6:

[1148] The server runs the generative AI model and generates new proposals that are close to the user's desired conditions (e.g., properties with good surrounding environments, properties with extensive pet services, etc.).

[1149] Step 7:

[1150] The server adjusts the display order of property listings and proposals based on the user's emotional data analyzed by the emotion engine.

[1151] Step 8:

[1152] The server compiles the listed property information and suggestions from the emotion engine and sends them to the terminal.

[1153] Step 9:

[1154] The terminal organizes the property information and proposals received from the server and displays them on the user interface.

[1155] Step 10:

[1156] The user reviews the displayed property list and clicks to view details of the property that interests them.

[1157] Step 11:

[1158] The terminal sends the user's selection to the server as a request.

[1159] Step 12:

[1160] The server receives the request and retrieves the details of the selected property from the database.

[1161] Step 13:

[1162] The server sends the acquired detailed information to the terminal.

[1163] Step 14:

[1164] The terminal displays the detailed information on the user interface so that the user can check it.

[1165] Step 15:

[1166] The user checks the detailed information and, if he wishes to enter into a contract, clicks the "Contract" button.

[1167] Step 16:

[1168] The device sends a contract request to the server.

[1169] Step 17:

[1170] The server receives the request and calculates the transaction fee based on the property price and contract details.

[1171] Step 18:

[1172] The server sends the calculation results to the terminal.

[1173] Step 19:

[1174] The terminal displays the calculated fee on the user interface for the user to review.

[1175] Step 20:

[1176] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[1177] Step 21:

[1178] The terminal sends the final request to the server.

[1179] Step 22:

[1180] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[1181] Step 23:

[1182] The server sends the generated contract to the user and asks for final confirmation.

[1183] The above are the processing steps of this system.

[1184] Example 2

[1185] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1186] Conventional real estate search systems simply listed properties based on the user's input criteria without considering the user's feelings, making it difficult to fully meet the user's needs. Furthermore, the inability to make suggestions based on the user's feelings narrowed the range of choices, making it difficult to find the perfect property. Furthermore, the process of entering into a property contract was complicated, creating the problem of stress for users.

[1187] 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.

[1188] In this invention, the server includes a means for transmitting input conditions and emotion data to the server, a means for searching a property database based on the transmitted conditions and emotion data to list properties that meet the conditions, and a means for optimizing the property list and generated proposals using an emotion engine. This enables optimal property proposals based on the user's emotions, thereby increasing user satisfaction. Furthermore, by taking emotion data into consideration, properties that interest the user can be efficiently proposed, and contract procedures can proceed smoothly.

[1189] "Input conditions" refers to the desired conditions (e.g., location, layout, rent, etc.) specified by the user when searching for a property.

[1190] "Emotion data" refers to data that represents the user's emotional state, and refers to information acquired based on facial expression recognition, operation speed, and the like.

[1191] "Server" refers to a computer system that receives conditions and emotional data entered by users, searches a property database, and generates and optimizes optimal proposals using a generative AI model.

[1192] A "property database" is a database that stores information about properties, and refers to an information source that can be searched based on the user's desired conditions.

[1193] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates new proposals based on a user's desired conditions.

[1194] An "emotion engine" refers to a technology that analyzes users' emotional data and optimizes property listings and proposals based on the results.

[1195] "Terminal" refers to the device (e.g., PC, smartphone, tablet) used by a user to search for properties and view detailed information.

[1196] "Transaction fee" refers to the fee incurred when a user proceeds with a property contract, and is calculated based on the property price and transaction details.

[1197] "Detailed information" refers to additional information about the property (e.g., specific facilities, surrounding environment, contract terms, etc.).

[1198] "Means of entering into a contract" refers to a series of processes and procedures for the user to proceed with the contract procedure for the property they desire.

[1199] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[1200] System configuration

[1201] This system is configured using the following main hardware and software:

[1202] 1. Device: The device on which a user searches for properties and views detailed information. Examples include computers, smartphones, and tablets.

[1203] 2. Server: A remote computer system that processes user requests, searches a property database, and uses an emotion engine. The server manages a database such as MySQL and uses a generative AI model (e.g., OpenAI GPT-4) and an emotion engine (e.g., IBM Watson Tone Analyzer).

[1204] 3. Property database: A database that stores information about properties. It provides the necessary property information based on search criteria.

[1205] 4. Emotion Engine: Software that analyzes user emotional data and optimizes property listings and offers based on the results.

[1206] System Operation

[1207] The user accesses the real estate search screen and enters their desired conditions (for example, floor plan, location, rent, etc.). Specifically, they enter "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[1208] The terminal converts the desired conditions and emotion data entered by the user into an appropriate data format and generates a request to send to the server. The emotion data includes the user's facial expression, operation speed, etc., and the resulting emotion analysis data.

[1209] The server receives requests from the device and analyzes the content. The analyzed information includes, for example, desired conditions and emotional data. The server searches the property database and lists properties that match the conditions. The server then uses a generative AI model to generate new proposals that are closer to the user's desired conditions. These proposals include, for example, "areas with extensive pet services" and "properties where rent is negotiable."

[1210] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby generating an optimal property listing based on the user's emotional data and sending it to the terminal.

[1211] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the detailed information and sends it to the terminal.

[1212] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[1213] Specific examples

[1214] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[1215] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[1216] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[1217] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[1218] Prompt Sentence Examples

[1219] "A user is looking for a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month. The user enters search criteria, and emotional data is also collected. The server should generate a list of properties that match the criteria, suggesting areas with good pet services and properties where the rent is negotiable. Generate an optimal list of properties based on the user's emotional data, and send that list to the device."

[1220] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1221] Step 1:

[1222] The user accesses the property search screen and enters the desired conditions.

[1223] Specific operation: The user opens a real estate search screen via a web browser or app and enters specific criteria, such as "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[1224] Input: Desired conditions

[1225] Output: Data format of the desired conditions entered

[1226] Step 2:

[1227] The terminal converts the user's desired conditions and emotional data into an appropriate data format.

[1228] Specific operation: The device collects the desired conditions entered by the user and emotional data from sensors such as the camera and microphone, analyzes them, and converts them into an appropriate data format such as JSON.

[1229] Input: Desired conditions, emotional data

[1230] Output: Converted desired conditions and emotion data

[1231] Step 3:

[1232] The device sends a request to the server.

[1233] Specific operation: The device sends the converted desired conditions and emotion data to the server as an HTTP request.

[1234] Input: Converted desired condition data and emotion data

[1235] Output: Request sent to the server

[1236] Step 4:

[1237] The server receives the request and parses it.

[1238] Specific operation: The server receives an HTTP request, analyzes it, and obtains the desired conditions and emotion data. It then separates the desired conditions for database search and the emotion data for emotion analysis.

[1239] Input: The request sent to the server

[1240] Output: Analyzed desired conditions and emotion data

[1241] Step 5:

[1242] The server searches the property database and lists properties that match the criteria.

[1243] Specific operation: The server searches a property database (e.g., MySQL) based on the analyzed desired conditions, and filters and lists properties that match the conditions.

[1244] Input: Parsed desired conditions

[1245] Output: Listed property data

[1246] Step 6:

[1247] The server generates new proposals using a generative AI model.

[1248] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) to add suggestions to the listed property data, such as "areas with extensive pet services" and "properties where rent is negotiable."

[1249] Input: Listed property data

[1250] Output: The newly generated proposal

[1251] Step 7:

[1252] The server uses an emotion engine to optimize property listings and offers.

[1253] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotion data. Based on the results, it prioritizes the listed properties and generated suggestions to create an optimized listing.

[1254] Input: emotion data, newly generated suggestions

[1255] Output: Optimized property listings and recommendations

[1256] Step 8:

[1257] The server sends the optimized property listings and suggestions to the device.

[1258] Specific operation: The server converts the optimized property listings and proposals into an appropriate data format, such as JSON, and sends it to the terminal as an HTTP response.

[1259] Input: Optimized property listings and proposals

[1260] Output: Property list and proposals sent to the device

[1261] Step 9:

[1262] The device displays the property information and allows the user to view the details.

[1263] Specific operation: The terminal displays the property information and suggestions received from the server on the user interface. The user can check the displayed property list and click to view detailed information on the property that interests them.

[1264] Input: Property listings and offers sent to your device

[1265] Output: Property list and details displayed in a user interface

[1266] Step 10:

[1267] The user selects the property they wish to contract for and confirms the transaction fee.

[1268] Specific operation: When a user presses the "Contract" button for a specific property, the terminal sends a request to the server again. The server calculates the transaction fee for this property and returns it to the terminal.

[1269] Input: User selection information

[1270] Output: Calculated transaction fee

[1271] Step 11:

[1272] The server initiates the contract procedure and sends the necessary information to the user.

[1273] Specific operation: When the user checks the fees and property details and presses the "Contract" button, the server responds to this action and starts the contract procedure, collating the necessary information and sending it to the user.

[1274] Input: User's contract intention confirmation information

[1275] Output: Information required for contract procedures and contract

[1276] (Application example 2)

[1277] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1278] Conventional real estate search systems simply list properties based on the user's desired conditions, but are unable to make recommendations that are optimized for the user's emotions and circumstances. This leaves them lacking in ingenuity to improve user satisfaction. There is also room for improvement in proposing payment methods that take the user's emotions into account, and in calculating transaction fees. Furthermore, there is a need for a system that can facilitate a series of real estate transactions in a smoother and more personalized manner.

[1279] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input desired property conditions; means for transmitting the input conditions to the server; means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions; means for the server to generate new proposals that are close to the user's conditions using a generative AI model; means for the server to transmit the property list and the generative AI proposals to a terminal; means for the terminal to display these property lists to the user; means for recognizing the user's emotions and proposing a payment method based on the emotions; means for acquiring and displaying detailed information about the property selected by the user; means for the server to calculate a transaction fee and present it to the user; and means for the user to enter into a contract for the property. This enables optimal property proposals and payment methods to be proposed while taking the user's emotions into consideration. Furthermore, smooth transaction progress and improved user satisfaction are achieved.

[1280] "Means for inputting desired conditions for a property" refers to an interface that allows a user to specify the characteristics and requirements of a property they desire.

[1281] The "means for transmitting the input conditions to the server" refers to a communication means for transmitting the information input by the user to a remote server.

[1282] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a method in which the server finds properties from the database that meet the conditions received and presents them to the user.

[1283] "Means for the server to use a generative AI model to generate new proposals that are close to the user's conditions" refers to a system that utilizes artificial intelligence technology to automatically generate new proposals based on the user's conditions.

[1284] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a method for transferring the generated property list and suggestions to the user's device.

[1285] "Means by which the terminal displays these property listings to the user" refers to an interface for visually displaying the property listings on the user's device.

[1286] "Means for recognizing a user's emotions and suggesting payment methods based on those emotions" refers to a method for analyzing a user's emotional state and presenting appropriate payment options.

[1287] "Means for obtaining and displaying detailed information about a property selected by a user" refers to a method for obtaining specific information about a property selected by a user and displaying it.

[1288] "Means for the server to calculate transaction fees and present them to the user" refers to a method for automatically calculating fees related to real estate transactions and notifying the user of the results.

[1289] "Means by which a user enters into a contract for a property" refers to the method by which a user completes the contract procedures for the property selected by the user.

[1290] The present invention is a real estate search system that recognizes a user's emotions and suggests optimal properties and payment methods. This system is composed of multiple components, such as a server, a user terminal, an emotion recognition engine, and a generative AI model. Specific embodiments for implementing the present invention are described below.

[1291] 1. System Configuration

[1292] 1.1 User terminal

[1293] The user terminal uses a device such as a smartphone, smart glasses, or head-mounted display, and provides an interface for the user to input desired conditions for a property. Once the user enters the desired conditions, they are sent to the server.

[1294] 1.2 Server

[1295] The server searches a property database based on the received desired conditions and lists properties that match the conditions. The server also uses a generative AI model to generate new proposals that are close to the user's conditions. These proposals can include information about the property's surrounding environment and services.

[1296] 1.3 Emotion Recognition Engine

[1297] The emotion recognition engine has the ability to analyze the user's emotional state. For example, it analyzes the user's facial image and recognizes whether the user is feeling happiness, stress, surprise, etc. This emotional information is sent to the server and used to optimize property listings and payment methods.

[1298] 2. Data processing and calculation

[1299] 2.1 Data Acquisition

[1300] The user enters the desired property conditions and the terminal sends the data to the server, which analyzes the received data and searches the property database to find properties that meet the conditions.

[1301] 2.2 Emotion recognition

[1302] It uses cameras and sensors to recognize emotions from images of the user's face. The emotion recognition engine uses libraries such as OpenCV and dlib to analyze the user's facial expressions and behavior.

[1303] 2.3 Proposal Generation by AI

[1304] The server uses a generative AI model (e.g., GPT-3) to generate new property suggestions, which are optimized based on the user's desired conditions and emotional information.

[1305] 3. Specific Examples

[1306] Let's say a user is looking for a "2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month." The user enters their desired conditions, and the emotion recognition engine analyzes the user's input, facial expressions, and operation speed. As a result, the request sent to the server includes the desired conditions as well as the user's emotional data. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to make suggestions such as "areas with extensive pet services" and "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions, and then sends them.

[1307] Prompt Sentence Examples

[1308] Recognize emotions from a user's facial image and suggest payment options that optimize the user experience. For example, if a user is feeling stressed, offer a relaxation coupon and recommend credit card payment.

[1309] In this way, the present invention is a system that can provide optimal property proposals and payment methods while taking into consideration the user's feelings, making it possible to proceed with real estate transactions in a smoother and more personalized manner.

[1310] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1311] Step 1:

[1312] The user operates the terminal and inputs the desired conditions for the property. The input conditions are detailed information such as "a 2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." Once this input is complete, the desired condition data is sent to the server. The input here is the user's desired requirements and the associated fields, and the output is the transmission of that data.

[1313] Specific behavior:

[1314] The user opens the property search app and enters each item (location, rent, floor plan, etc.) along the interface. They then press the "Search" button, which sends the data to the server.

[1315] Step 2:

[1316] The server analyzes the desired conditions received and searches the property database based on them. It then lists properties that match the conditions from the property information in the database. In this process, a search query is generated based on the desired conditions entered, and data that matches the conditions is extracted based on that query. The output is a list of properties that match the conditions.

[1317] Specific behavior:

[1318] The server analyzes the received data, generates SQL queries, etc., and executes searches against the database. The resulting property list is then temporarily saved.

[1319] Step 3:

[1320] The server uses an emotion recognition engine to analyze the data to recognize the user's emotions. The emotion recognition engine takes the user's facial image data acquired from the camera as input and outputs the user's emotional state. This output is one of several emotional states, such as "happiness" or "stress."

[1321] Specific behavior:

[1322] The user takes a facial image using the device camera or streams video in real time, and the emotion recognition engine processes the video. The result is sent to the server as the user's current emotional state.

[1323] Step 4:

[1324] The server uses a generative AI model to generate new property proposals based on the desired conditions and the user's emotional information. The generative AI model, for example, uses GPT-3, receives the desired conditions and emotional information as input, and outputs proposals for optimal properties and services. This output is a new proposal list.

[1325] Specific behavior:

[1326] The server sends a request to the generative AI model using a "prompt sentence," receives the generated suggestions, and stores them (e.g., "Please suggest properties in Tokyo with good pet services for users who are feeling stressed").

[1327] Step 5:

[1328] The server sends the property list and the proposals made by the AI ​​to the terminal. The input is the property list and the new proposal list, and the output is sending these lists to the user terminal.

[1329] Specific behavior:

[1330] The server combines the property list with the AI-generated proposal list, generates a data packet to send to the user's device, and transmits it. The user's device receives this data.

[1331] Step 6:

[1332] The terminal displays these property lists to the user using a user interface that presents the information in a format that is easily understandable to the user. The input is the property list and the proposal list, and the output is the display on the user interface.

[1333] Specific behavior:

[1334] The device analyzes the data it receives and displays it in an easy-to-understand format. For example, it could display properties in a list format with a button for more detailed information.

[1335] Step 7:

[1336] The detailed information of the property selected by the user is retrieved and displayed. When the user selects a property of interest, the terminal again sends a request to the server to retrieve the detailed information. The input is the user's selection, and the output is the detailed information of that property.

[1337] Specific behavior:

[1338] When a user clicks on a property they are interested in, the device requests detailed information about that property from the server, which then receives and displays the detailed data.

[1339] Step 8:

[1340] The server calculates the transaction fee and presents it to the user. The transaction fee is calculated based on the property price and transaction details. The input is the property price and transaction terms, and the output is the calculated fee.

[1341] Specific behavior:

[1342] The server collects data related to the transaction, automatically calculates fees, and generates and transmits data to be presented to the user.

[1343] Step 9:

[1344] The user goes through the process of signing a contract for a property. When the user finally selects the property they wish to sign a contract for, the terminal assists them in proceeding with the contract procedure. The input is the user's final selection, and the output is the official completion of the contract procedure.

[1345] Specific behavior:

[1346] When the user presses the "Contract" button, the device provides an interface for entering the necessary contract information and sends a formal contract procedure request to the server. The server then generates a contract and sends it to both parties.

[1347] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1348] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1349] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1350] [Fourth embodiment]

[1351] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1352] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1353] 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).

[1354] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1355] 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.

[1356] 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).

[1357] 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.

[1358] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1359] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1360] 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.

[1361] 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.

[1362] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1363] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1364] ---

[1365] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[1366] First, the user accesses the property search screen. The desired conditions (e.g., floor plan, location, rent, etc.) entered by the user are sent to the server via the terminal. The terminal converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[1367] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[1368] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a further request is sent to the server, which retrieves the details and sends them to the terminal.

[1369] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server compiles all necessary information, generates a contract, and sends it to the user.

[1370] Specific examples

[1371] For example, let's say a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the device sends the information to the server. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to suggest properties such as "areas with extensive pet services" and "properties where rent is negotiable."

[1372] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[1373] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[1374] The present invention aims to provide a system that efficiently and flexibly supports property selection, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[1375] The processing flow will be explained below.

[1376] System processing steps

[1377] Step 1:

[1378] The user accesses the property search screen and enters the desired conditions (e.g., 3LDK, within 10 minutes' walk from the station, rent less than 100,000 yen).

[1379] Step 2:

[1380] The terminal converts the desired conditions entered by the user into an appropriate data format and generates a request to be sent to the server.

[1381] Step 3:

[1382] The server receives the request from the terminal and analyzes the contents.

[1383] Step 4:

[1384] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[1385] Step 5:

[1386] The server runs the generative AI model to create new proposals that closely match the user's desired conditions, such as properties in areas with good pet services or properties where rent is negotiable.

[1387] Step 6:

[1388] The server compiles the listed property information and suggestions made by the generating AI and sends them to the terminal.

[1389] Step 7:

[1390] The device displays property information and suggestions on a user interface, allowing the user to view the information and select properties that interest them.

[1391] Step 8:

[1392] To view detailed information about a particular property, the user selects the property and clicks the "View Details" button.

[1393] Step 9:

[1394] The terminal sends the user's selection to the server as a request.

[1395] Step 10:

[1396] The server receives the request and retrieves the details of the selected property from the database.

[1397] Step 11:

[1398] The server sends the acquired detailed information to the terminal.

[1399] Step 12:

[1400] The terminal displays the detailed information on the user interface so that the user can check it. The user checks the detailed information and clicks the "Contract" button if they wish to enter into a contract.

[1401] Step 13:

[1402] The device sends a contract request to the server.

[1403] Step 14:

[1404] The server receives the request and calculates the transaction fee based on the property price and contract details.

[1405] Step 15:

[1406] The server sends the calculation results to the terminal.

[1407] Step 16:

[1408] The terminal displays the calculated fee on the user interface for the user to review.

[1409] Step 17:

[1410] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[1411] Step 18:

[1412] The terminal sends the final request to the server.

[1413] Step 19:

[1414] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[1415] Step 20:

[1416] The server sends the generated contract to the user and asks for final confirmation.

[1417] The above are the processing steps of this system.

[1418] Example 1

[1419] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1420] Conventional real estate search systems make it difficult for users to efficiently find the property they desire. They also lack the mechanisms to provide new suggestions based on users' desired conditions or to support the smooth progress of contract procedures. As a result, users have to compare and consider many properties themselves, which takes time and effort.

[1421] 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.

[1422] In this invention, the server includes means for a user to input desired conditions for a property, means for transmitting the input conditions to the server, means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions, means for the server to generate new proposals that are close to the user's conditions using a generative AI model, means for the server to transmit the property list and proposals made by the generative AI to a terminal, means for the terminal to display these property lists to the user, means for the server to obtain and display detailed information about a property selected by the user, means for the server to calculate a transaction fee and present it to the user, and means for the user to enter into a contract for the property. This enables users to efficiently search for properties, receive new proposals for those properties, and smoothly proceed with the contract procedure.

[1423] The "means for the user to input desired conditions for a property" is a system component that provides an interface for the user to input the conditions for the property they desire.

[1424] The "means for transmitting input conditions to a server" is a system component that has the function of converting the desired conditions input by the user into an appropriate data format and transmitting the converted data to the server.

[1425] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a system component that has the function of the server analyzing the desired conditions received from the user, searching the property database based on those conditions, and listing properties that meet the conditions.

[1426] The "means for generating new proposals that are close to the user's conditions using a generative AI model" is a system component that has the function of using a generative AI model to generate new proposals based on the user's input conditions.

[1427] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a system component that has the function of sending the listed property information and suggestions made by the generating AI model to the terminal.

[1428] The "means by which the terminal displays these property listings to the user" refers to a system component that has the functionality to display the received property listings to the user.

[1429] The "means for obtaining and displaying detailed information about a property selected by the user" is a system component that has the function of obtaining detailed information about a property in which the user is interested from the server and displaying it to the user.

[1430] The "means for the server to calculate the transaction fee and present it to the user" is a system component that has the function of calculating the transaction fee required for a property contract and presenting that information to the user.

[1431] The "means for users to enter into a contract for a property" is a system component that provides an interface and functions for users to proceed with the contract procedure for a property.

[1432] A "property database" is a data storage system that stores various information about real estate properties.

[1433] A "generative AI model" is an artificial intelligence model used to generate new suggestions based on a user's desired criteria.

[1434] The present invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract. The system operates through the interaction of users, terminals, and a server.

[1435] First, a user accesses the URL of the real estate search system using a web browser. At this time, the user enters their desired conditions for the property (e.g., floor plan, location, rent, etc.) in an input form. The entered conditions are converted into an appropriate data format (e.g., JSON) by the terminal and sent to the server via the Internet.

[1436] The server receives the request sent from the device and analyzes the desired conditions. Based on this analysis, the server searches a property database (e.g., MySQL or PostgreSQL) and lists properties that match the conditions. The server then uses a generative AI model (e.g., GPT-4) to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that includes not only properties that match the conditions, but also proposals made by the generative AI model.

[1437] Next, the server sends these property lists and the generated proposals to the terminal. The terminal receives them and displays them in a list format on the user interface. The user can check the displayed property list and click on a property that interests them to view its detailed information. In this case, the terminal sends a request for detailed information to the server, and the server retrieves the property's detailed information from the database and sends it to the terminal.

[1438] If the user wishes to enter into a contract for a property, they indicate their intention by clicking the "Contract" button. The device sends this information to the server, which then calculates the fees required for the transaction and displays them on the device. If the user agrees to the fees, they click the "Confirm" button to proceed with the contract. The server then compiles all the information required for the contract, generates a formal contract, and sends it to the user. The contract is sent by email, and a link is also provided for the user to download.

[1439] Specific examples

[1440] Below is a specific example. If a user searches for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen," the user enters their desired criteria into the search screen. The device sends this information to the server, which then searches its database. It lists properties that match the criteria and uses a generative AI model to generate suggestions such as "areas with extensive pet services" and "properties where rent is negotiable."

[1441] This information is sent to the terminal and displayed on the user interface. The user can view the displayed property list, select a property that interests them, and check its detailed information. Finally, if the user wishes to enter into a contract, the server calculates the fee and presents it to the user. Once the user confirms the fee and proceeds with the contract procedure, the server generates a contract and sends it to the user.

[1442] In this way, the present invention is a system that enables users to efficiently search and select properties, receive new proposals, and smoothly proceed with contracts.

[1443] Prompt Sentence Examples

[1444] "Search for pet-friendly 2LDK apartments in Tokyo for less than 150,000 yen per month."

[1445] This system greatly improves user convenience and provides groundbreaking support for efficiently conducting real estate transactions.

[1446] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1447] Step 1:

[1448] The user accesses the property search screen.

[1449] Input: A user accesses the URL of the real estate search system in a web browser.

[1450] Specific behavior: A user opens a browser, enters the system's URL, and arrives at the search screen.

[1451] Output: Property search screen will be displayed.

[1452] Step 2:

[1453] The user inputs the desired conditions.

[1454] Input: The user enters desired conditions (e.g., floor plan, location, rent, etc.) into the input form on the search screen.

[1455] Specific operation: The user enters conditions such as "2LDK," "Tokyo," "under 150,000 yen," and "pets allowed" into the input form and clicks the search button.

[1456] Output: The desired conditions are retained in the input form.

[1457] Step 3:

[1458] The terminal sends the input information to the server.

[1459] Input: The desired conditions entered by the user.

[1460] Specific operation: The device converts the input desired conditions into an appropriate data format such as JSON and sends a request to the server via the Internet.

[1461] Output: The request data sent to the server.

[1462] Step 4:

[1463] The server analyzes the conditions and searches the database.

[1464] Input: Desired conditions sent from the terminal.

[1465] What happens: The server analyzes the request and searches the property database using a SQL query, such as "SELECT FROM properties WHERE location="Tokyo" AND rent <= 150000 AND type="2LDK" AND pet_friendly=True."

[1466] Output: A list of properties that match the criteria.

[1467] Step 5:

[1468] The server generates suggestions using a generative AI model.

[1469] Input: A list of properties that match your criteria.

[1470] How it works: The server uses a generative AI model (e.g., GPT-4) to generate new proposals based on the user's desired conditions. For example, it creates proposals such as "areas with extensive pet services" or "properties where rent is negotiable."

[1471] Output: The new list of suggestions generated.

[1472] Step 6:

[1473] The server sends property information and suggestions to the device.

[1474] Input: A list of properties that fit your criteria and a list of suggestions generated by a generative AI model.

[1475] Specific operation: The server sends this information to the terminal.

[1476] Output: Property and proposal information sent to your device.

[1477] Step 7:

[1478] The terminal displays the property listing to the user.

[1479] Input: Property information and proposal information received from the server.

[1480] Specific operation: The terminal displays this information in a list format on the user interface.

[1481] Output: The property list and proposal list displayed to the user.

[1482] Step 8:

[1483] A user views property details.

[1484] Input: Property listings in which the user is interested.

[1485] Specific operation: The user clicks on a property they are interested in and views detailed information. A request for detailed information is sent from the device to the server.

[1486] Output: A request is sent to the server for more information.

[1487] Step 9:

[1488] The server retrieves the details and sends them to the device.

[1489] Input: Request for more information.

[1490] Specific operation: The server retrieves detailed information about the property from the database and sends it to the terminal.

[1491] Output: Detailed information sent to the terminal.

[1492] Step 10:

[1493] A user requests a contract and the terminal transmits the information to the server.

[1494] Input: The property the user wishes to contract for and their intentions.

[1495] Specific operation: The user clicks the "Contract" button, and the information is sent from the device to the server.

[1496] Output: The contract request information sent to the server.

[1497] Step 11:

[1498] The server calculates the fee and displays it on the terminal.

[1499] Input: Contract information and property details.

[1500] Specific operation: The server calculates the fee required for the transaction and sends that information to the terminal.

[1501] Output: Fee information displayed on the terminal.

[1502] Step 12:

[1503] The user confirms the fee and proceeds with the contract.

[1504] Input: Fee information confirmed by the user.

[1505] Specific behavior: The user agrees to the fee and clicks the "Confirm" button.

[1506] Output: Fee confirmation information is sent to the server.

[1507] Step 13:

[1508] The server generates a contract and sends it to the user.

[1509] Input: Fee verification information and all information required for the contract.

[1510] What happens: The server generates a formal contract and sends it to the user via email, along with a link for the user to download it.

[1511] Output: The contract and download link sent to the user.

[1512] (Application example 1)

[1513] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1514] Conventional real estate search systems limit the means by which users can visually check property information in detail, making it difficult to understand properties from a realistic perspective. Furthermore, the contract procedures, from property selection to contract signing, are cumbersome, and improvements are needed to improve the user experience.

[1515] 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.

[1516] In this invention, the server includes a means for displaying detailed information about a property selected in a virtual space as a 360-degree virtual tour when the user wears a head-mounted display, and a means for the user to enter into a contract for the property, which allows the user to check the property in detail from a realistic perspective and realize a smooth contract procedure.

[1517] A "user" is an entity that searches for real estate properties and carries out procedures such as contracts.

[1518] "Property" refers to real estate, including residential properties such as apartments, condominiums, and detached houses.

[1519] "Desired conditions" are specific requests such as floor plan, location, rent, etc. that a user sets when searching for a property.

[1520] A "server" is a computer system that receives requests from users, searches a property database, and provides the results.

[1521] "Terminal" means a device on which a user inputs desired search criteria and receives and displays search results from the server, and includes smartphones, tablets, computers, etc.

[1522] A "property database" refers to a database that stores information on various real estate properties.

[1523] A "generative AI model" is an artificial intelligence model that generates new proposals that are close to the user's desired conditions.

[1524] A "head-mounted display" is a device that allows users to visually experience a virtual reality space by wearing it on their head.

[1525] "Virtual space" refers to a virtual three-dimensional space constructed using a computer system.

[1526] A "360-degree virtual tour" is a video technology that provides an environment in which users can view detailed information about a property from any angle within a virtual space.

[1527] "Transaction fees" are fees incurred when entering into a property contract and are calculated based on the property price and transaction details.

[1528] "Contract" refers to the formal procedure for the property selected by the user.

[1529] The present invention is a real estate search system that allows users to check real estate properties in detail in a virtual space using a head-mounted display and proceed to a contract. The system operates through the interaction between the user, the terminal, and the server.

[1530] First, the user puts on a head-mounted display and accesses a virtual real estate store. The user then controls a virtual avatar, moves to a property search terminal, and enters their desired conditions. These desired conditions (e.g., floor plan, location, rent, etc.) are sent to a server via the terminal. The terminal then converts the conditions entered by the user into an appropriate data format and sends a request to the server via the Internet.

[1531] The server receives the request sent from the terminal and analyzes the conditions. Based on the analysis, the server searches the property database and lists properties that meet the conditions. At the same time, the server uses a generative AI model to generate new proposals that are close to the user's desired conditions. This allows the user to obtain a property list that not only meets their desired conditions but also includes several other proposals.

[1532] The device organizes the property information and proposals received from the server and displays them on a visual interface in the virtual space. Users can review the displayed property list and select a property they are interested in, and detailed information about it is displayed as a 360-degree virtual tour. This allows users to view the property in detail as if they were in person.

[1533] When the user finally selects the property they wish to sign a contract for, the server calculates the transaction fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract process officially begins. The server collects all necessary information, generates a contract, and sends it to the user.

[1534] This processing is performed using the following hardware and software:

[1535] Hardware: Head-mounted display (HMD), high-performance personal computer (PC)

[1536] Software: Virtual reality (VR) engines (Unity, Unreal Engine), generative AI models (OpenAI GPT-4, HuggingFace's Transformers), web application frameworks (Flask, Django), database management systems (MySQL, PostgreSQL)

[1537] For example, let's say a user is looking for a "2LDK apartment in Shibuya Ward, with a monthly fee of less than 200,000 yen, and within a 10-minute walk from the station." The user enters their desired conditions and sends them to the server. The server receives this information, searches its database, and uses a generative AI model to suggest properties in popular areas or newly built properties. This information is displayed in the virtual space, and when the user selects a property that interests them, a 360-degree virtual tour of that property begins. The user can then check the property in detail and proceed with the contract process.

[1538] Example prompts to input to a generative AI model:

[1539] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[1540] The present invention allows the user to check the property in detail from a realistic perspective and smoothly proceed with the contract procedure.

[1541] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1542] Step 1:

[1543] The user wears a head-mounted display and accesses a virtual real estate store. The user operates a virtual avatar, moves to a property search terminal, and enters desired conditions. Specifically, information such as floor plan, location, and rent is entered into a dedicated input form, and the terminal receives this as data. This data is then sent to the server.

[1544] Step 2:

[1545] The terminal converts the desired condition data entered by the user into an appropriate data format and sends a request to the server via the Internet. Here, the input data is the desired conditions, and the output is the request data converted into the appropriate data format. Data serialization technology is used for the conversion.

[1546] Step 3:

[1547] The server receives the request data sent from the terminal and analyzes the desired conditions. Based on the analysis results, the server searches the property database. The input data are the desired conditions, and the output data is a list of properties that meet the conditions. The database search is performed using an SQL query.

[1548] Step 4:

[1549] The server uses a generative AI model to generate new proposals that are close to the user's desired conditions. The input data is the desired conditions and a property list, and a prompt for the generative AI model is also generated. Specifically, the following prompt is used:

[1550] Please search for properties in Shibuya Ward that meet the following criteria: 2LDK, monthly rent under 200,000 yen, within a 10-minute walk from the station. In addition, please also suggest popular areas and newly built properties within Shibuya Ward with the same criteria.

[1551] The output data is a list of proposed properties generated by the generative AI. The generative AI model is run using OpenAI GPT-4 and HuggingFace's Transformers.

[1552] Step 5:

[1553] The server compiles search results from the property database and proposed properties based on the generative AI model, and sends them to the terminal. The input data is the property list and proposed properties, and the output data is a list of real estate information that integrates these. This data is sent in JSON format.

[1554] Step 6:

[1555] The terminal organizes the real estate information received from the server and displays it on a visual interface in the virtual space. The input data is a consolidated real estate information list, and the output is the visual information displayed on the user interface. This is done using a VR engine (Unity, Unreal Engine).

[1556] Step 7:

[1557] The user selects a property that interests them from the displayed property list and checks its detailed information as a 360-degree virtual tour. At this time, the ID of the selected property is used as input data, and a request is sent to the server. The output data is the video data of the 360-degree virtual tour.

[1558] Step 8:

[1559] The server acquires detailed information about the selected property and sends it to the terminal as video data for a 360-degree virtual tour. The input data is the property ID, and the output data is the 360-degree video data. High-resolution video files are used to acquire the data.

[1560] Step 9:

[1561] When a user checks the 360-degree virtual tour and selects a property they wish to purchase, the server calculates the transaction fee and presents it to the user via their terminal. The input data are property information and user information, and the output data is the transaction fee. Basic arithmetic operations are used for this calculation.

[1562] Step 10:

[1563] When the user confirms the fees and presses the "Contract" button, the server officially starts the contract procedure, gathers all the necessary information, generates a contract, and sends it to the user. The input data is a set of contract information, and the output data is the generated contract. Document generation software is used for this process.

[1564] 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.

[1565] ---

[1566] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[1567] First, the user accesses the property search screen and enters their desired conditions (e.g., floor plan, location, rent, etc.). Based on the user's input and operations, the emotion engine analyzes the user's emotions. The device converts the desired conditions entered by the user and the results of the emotion analysis into an appropriate data format and generates a request to send to the server.

[1568] The server receives requests from the device and analyzes their contents. Based on the analysis, the server searches its property database and lists properties that meet the user's requirements. The server then uses a generative AI model to generate new proposals that are close to the user's desired conditions. These proposals may include, for example, properties in areas with extensive pet services or properties where rent is negotiable.

[1569] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby transmitting the optimal property listing based on the user's emotional data to the terminal.

[1570] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the details and sends them to the terminal.

[1571] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[1572] Specific examples

[1573] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[1574] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[1575] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[1576] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[1577] The present invention aims to provide a system that recognizes a user's emotions and supports the selection of the most suitable property based on those emotions, thereby ensuring smooth progress in real estate transactions and improving user satisfaction.

[1578] The processing flow will be explained below.

[1579] System processing steps

[1580] Step 1:

[1581] The user accesses the property search screen and enters the desired conditions (e.g., floor plan, location, rent, etc.).

[1582] Step 2:

[1583] The emotion engine analyzes the user's input and operation methods (e.g., keyboard typing speed, mouse movements, etc.) and generates the user's emotion data.

[1584] Step 3:

[1585] The terminal transmits a request to the server, which includes the desired conditions input by the user and the emotion data analyzed by the emotion engine.

[1586] Step 4:

[1587] The server receives the request from the terminal and analyzes its contents (desired conditions and emotional data).

[1588] Step 5:

[1589] The server searches the database based on the analysis results and lists properties that meet the user's desired conditions.

[1590] Step 6:

[1591] The server runs the generative AI model and generates new proposals that are close to the user's desired conditions (e.g., properties with good surrounding environments, properties with extensive pet services, etc.).

[1592] Step 7:

[1593] The server adjusts the display order of property listings and proposals based on the user's emotional data analyzed by the emotion engine.

[1594] Step 8:

[1595] The server compiles the listed property information and suggestions from the emotion engine and sends them to the terminal.

[1596] Step 9:

[1597] The terminal organizes the property information and proposals received from the server and displays them on the user interface.

[1598] Step 10:

[1599] The user reviews the displayed property list and clicks to view details of the property that interests them.

[1600] Step 11:

[1601] The terminal sends the user's selection to the server as a request.

[1602] Step 12:

[1603] The server receives the request and retrieves the details of the selected property from the database.

[1604] Step 13:

[1605] The server sends the acquired detailed information to the terminal.

[1606] Step 14:

[1607] The terminal displays the detailed information on the user interface so that the user can check it.

[1608] Step 15:

[1609] The user checks the detailed information and, if he wishes to enter into a contract, clicks the "Contract" button.

[1610] Step 16:

[1611] The device sends a contract request to the server.

[1612] Step 17:

[1613] The server receives the request and calculates the transaction fee based on the property price and contract details.

[1614] Step 18:

[1615] The server sends the calculation results to the terminal.

[1616] Step 19:

[1617] The terminal displays the calculated fee on the user interface for the user to review.

[1618] Step 20:

[1619] The user confirms the proposed fee and clicks the "Proceed with the contract" button.

[1620] Step 21:

[1621] The terminal sends the final request to the server.

[1622] Step 22:

[1623] The server receives the request, verifies and compiles all necessary information, and generates the contract.

[1624] Step 23:

[1625] The server sends the generated contract to the user and asks for final confirmation.

[1626] The above are the processing steps of this system.

[1627] Example 2

[1628] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1629] Conventional real estate search systems simply listed properties based on the user's input criteria without considering the user's feelings, making it difficult to fully meet the user's needs. Furthermore, the inability to make suggestions based on the user's feelings narrowed the range of choices, making it difficult to find the perfect property. Furthermore, the process of entering into a property contract was complicated, creating the problem of stress for users.

[1630] 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.

[1631] In this invention, the server includes a means for transmitting input conditions and emotion data to the server, a means for searching a property database based on the transmitted conditions and emotion data to list properties that meet the conditions, and a means for optimizing the property list and generated proposals using an emotion engine. This enables optimal property proposals based on the user's emotions, thereby increasing user satisfaction. Furthermore, by taking emotion data into consideration, properties that interest the user can be efficiently proposed, and contract procedures can proceed smoothly.

[1632] "Input conditions" refers to the desired conditions (e.g., location, layout, rent, etc.) specified by the user when searching for a property.

[1633] "Emotion data" refers to data that represents the user's emotional state, and refers to information acquired based on facial expression recognition, operation speed, and the like.

[1634] "Server" refers to a computer system that receives conditions and emotional data entered by users, searches a property database, and generates and optimizes optimal proposals using a generative AI model.

[1635] A "property database" is a database that stores information about properties, and refers to an information source that can be searched based on the user's desired conditions.

[1636] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates new proposals based on a user's desired conditions.

[1637] An "emotion engine" refers to a technology that analyzes users' emotional data and optimizes property listings and proposals based on the results.

[1638] "Terminal" refers to the device (e.g., PC, smartphone, tablet) used by a user to search for properties and view detailed information.

[1639] "Transaction fee" refers to the fee incurred when a user proceeds with a property contract, and is calculated based on the property price and transaction details.

[1640] "Detailed information" refers to additional information about the property (e.g., specific facilities, surrounding environment, contract terms, etc.).

[1641] "Means of entering into a contract" refers to a series of processes and procedures for the user to proceed with the contract procedure for the property they desire.

[1642] This invention is a real estate search system that enables users to efficiently search for properties and ultimately proceed to a contract, and is particularly configured to incorporate an emotion engine that recognizes the user's emotions and optimizes proposals and property display based on those emotions. This system operates through the interaction between the user, terminal, server, and emotion engine.

[1643] System configuration

[1644] This system is configured using the following main hardware and software:

[1645] 1. Device: The device on which a user searches for properties and views detailed information. Examples include computers, smartphones, and tablets.

[1646] 2. Server: A remote computer system that processes user requests, searches a property database, and uses an emotion engine. The server manages a database such as MySQL and uses a generative AI model (e.g., OpenAI GPT-4) and an emotion engine (e.g., IBM Watson Tone Analyzer).

[1647] 3. Property database: A database that stores information about properties. It provides the necessary property information based on search criteria.

[1648] 4. Emotion Engine: Software that analyzes user emotional data and optimizes property listings and offers based on the results.

[1649] System Operation

[1650] The user accesses the real estate search screen and enters their desired conditions (for example, floor plan, location, rent, etc.). Specifically, they enter "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[1651] The terminal converts the desired conditions and emotion data entered by the user into an appropriate data format and generates a request to send to the server. The emotion data includes the user's facial expression, operation speed, etc., and the resulting emotion analysis data.

[1652] The server receives requests from the device and analyzes the content. The analyzed information includes, for example, desired conditions and emotional data. The server searches the property database and lists properties that match the conditions. The server then uses a generative AI model to generate new proposals that are closer to the user's desired conditions. These proposals include, for example, "areas with extensive pet services" and "properties where rent is negotiable."

[1653] Based on the user's emotional data analyzed by the emotion engine, the server adjusts the display order of property listings and new proposals, thereby generating an optimal property listing based on the user's emotional data and sending it to the terminal.

[1654] The terminal organizes the property information and proposals received from the server and displays them on the user interface. The user can check the displayed property list and click to view the details of the property they are interested in. To view the detailed information, a request is sent to the server, and the server retrieves the detailed information and sends it to the terminal.

[1655] If the user finally selects the property they wish to sign a contract for, a transaction fee will be charged. The server calculates this fee and presents it to the user via their terminal. If the user confirms the fee and proceeds with the contract, the contract procedure officially begins. Based on the collected user emotion data, the emotion engine will make optimal suggestions the next time they search for a property.

[1656] Specific examples

[1657] For example, suppose a user is looking for a "2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." The user enters their desired conditions, and the emotion engine analyzes the user's input, facial expressions, operation speed, etc. As a result, the request sent to the server includes the user's emotional data along with the desired conditions.

[1658] The server receives this information and searches its database. It lists properties that match the criteria and even uses generative AI to suggest properties such as "areas with extensive pet services" or "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions and sends them.

[1659] This information is sent to the terminal and displayed on the user interface. When the user looks at the displayed property list and selects a property that interests them, detailed information about that property is displayed. At this time, the server acquires additional detailed information and sends it to the terminal.

[1660] When a user decides they like a property and wishes to sign a contract, the server automatically calculates the fee and sends that information to the terminal. When the user confirms the fee and property details and presses the "Contract" button, the server compiles all the necessary information, generates a formal contract, and sends it to the user.

[1661] Prompt Sentence Examples

[1662] "A user is looking for a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month. The user enters search criteria, and emotional data is also collected. The server should generate a list of properties that match the criteria, suggesting areas with good pet services and properties where the rent is negotiable. Generate an optimal list of properties based on the user's emotional data, and send that list to the device."

[1663] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1664] Step 1:

[1665] The user accesses the property search screen and enters the desired conditions.

[1666] Specific operation: The user opens a real estate search screen via a web browser or app and enters specific criteria such as "a 2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month."

[1667] Input: Desired conditions

[1668] Output: Data format of the desired conditions entered

[1669] Step 2:

[1670] The terminal converts the user's desired conditions and emotional data into an appropriate data format.

[1671] Specific operation: The device collects the desired conditions entered by the user and emotional data from sensors such as the camera and microphone, analyzes them, and converts them into an appropriate data format such as JSON.

[1672] Input: Desired conditions, emotional data

[1673] Output: Converted desired conditions and emotion data

[1674] Step 3:

[1675] The device sends a request to the server.

[1676] Specific operation: The device sends the converted desired conditions and emotion data to the server as an HTTP request.

[1677] Input: Converted desired condition data and emotion data

[1678] Output: Request sent to the server

[1679] Step 4:

[1680] The server receives the request and parses it.

[1681] Specific operation: The server receives an HTTP request, analyzes it, and obtains the desired conditions and emotion data. It then separates the desired conditions for database search and the emotion data for emotion analysis.

[1682] Input: The request sent to the server

[1683] Output: Analyzed desired conditions and emotion data

[1684] Step 5:

[1685] The server searches the property database and lists properties that match the criteria.

[1686] Specific operation: The server searches a property database (e.g., MySQL) based on the analyzed desired conditions, and filters and lists properties that match the conditions.

[1687] Input: Parsed desired conditions

[1688] Output: Listed property data

[1689] Step 6:

[1690] The server generates new proposals using a generative AI model.

[1691] Specific operation: The server uses a generative AI model (e.g., OpenAI GPT-4) to add suggestions to the listed property data, such as "areas with extensive pet services" and "properties where rent is negotiable."

[1692] Input: Listed property data

[1693] Output: The newly generated proposal

[1694] Step 7:

[1695] The server uses an emotion engine to optimize property listings and offers.

[1696] Specific operation: The server uses an emotion engine (e.g., IBM Watson Tone Analyzer) to analyze the user's emotion data. Based on the results, it prioritizes the listed properties and generated suggestions to create an optimized listing.

[1697] Input: emotion data, newly generated suggestions

[1698] Output: Optimized property listings and recommendations

[1699] Step 8:

[1700] The server sends the optimized property listings and suggestions to the device.

[1701] Specific operation: The server converts the optimized property listings and proposals into an appropriate data format, such as JSON, and sends it to the device as an HTTP response.

[1702] Input: Optimized property listings and proposals

[1703] Output: Property list and offers sent to the device

[1704] Step 9:

[1705] The device displays the property information and allows the user to view the details.

[1706] Specific operation: The terminal displays the property information and suggestions received from the server on the user interface. The user can check the displayed property list and click to view detailed information on the property that interests them.

[1707] Input: Property listings and offers sent to your device

[1708] Output: Property list and details displayed in a user interface

[1709] Step 10:

[1710] The user selects the property they wish to contract for and confirms the transaction fee.

[1711] Specific operation: When a user presses the "Contract" button for a specific property, the terminal sends a request to the server again. The server calculates the transaction fee for this property and returns it to the terminal.

[1712] Input: User selection information

[1713] Output: Calculated transaction fee

[1714] Step 11:

[1715] The server initiates the contract procedure and sends the necessary information to the user.

[1716] Specific operation: When the user checks the fees and property details and presses the "Contract" button, the server responds to this action and starts the contract procedure, collating the necessary information and sending it to the user.

[1717] Input: User's contract intention confirmation information

[1718] Output: Information required for contract procedures and contract

[1719] (Application example 2)

[1720] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1721] Conventional real estate search systems simply list properties based on the user's desired conditions, but are unable to make recommendations that are optimized for the user's emotions and circumstances. This leaves them lacking in ingenuity to improve user satisfaction. There is also room for improvement in proposing payment methods that take the user's emotions into account, and in calculating transaction fees. Furthermore, there is a need for a system that can facilitate a series of real estate transactions in a smoother and more personalized manner.

[1722] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input desired property conditions; means for transmitting the input conditions to the server; means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions; means for the server to generate new proposals that are close to the user's conditions using a generative AI model; means for the server to transmit the property list and the generative AI proposals to a terminal; means for the terminal to display these property lists to the user; means for recognizing the user's emotions and proposing a payment method based on the emotions; means for acquiring and displaying detailed information about the property selected by the user; means for the server to calculate a transaction fee and present it to the user; and means for the user to enter into a contract for the property. This enables optimal property proposals and payment methods to be proposed while taking the user's emotions into consideration. Furthermore, smooth transaction progress and improved user satisfaction are achieved.

[1723] "Means for inputting desired conditions for a property" refers to an interface that allows a user to specify the characteristics and requirements of a property they desire.

[1724] The "means for transmitting the input conditions to the server" refers to a communication means for transmitting the information input by the user to a remote server.

[1725] "Means for the server to search the property database based on the conditions sent and list properties that meet the conditions" refers to a method in which the server finds properties from the database that meet the conditions received and presents them to the user.

[1726] "Means for the server to use a generative AI model to generate new proposals that are close to the user's conditions" refers to a system that utilizes artificial intelligence technology to automatically generate new proposals based on the user's conditions.

[1727] "Means for the server to send the above-mentioned property list and suggestions made by the generating AI to the terminal" refers to a method for transferring the generated property list and suggestions to the user's device.

[1728] "Means by which the terminal displays these property listings to the user" refers to an interface for visually displaying the property listings on the user's device.

[1729] "Means for recognizing a user's emotions and suggesting payment methods based on those emotions" refers to a method for analyzing a user's emotional state and presenting appropriate payment options.

[1730] "Means for obtaining and displaying detailed information about a property selected by a user" refers to a method for obtaining specific information about a property selected by a user and displaying it.

[1731] "Means for the server to calculate transaction fees and present them to the user" refers to a method for automatically calculating fees related to real estate transactions and notifying the user of the results.

[1732] "Means by which a user enters into a contract for a property" refers to the method by which a user completes the contract procedures for the property selected by the user.

[1733] The present invention is a real estate search system that recognizes a user's emotions and suggests optimal properties and payment methods. This system is composed of multiple components, such as a server, a user terminal, an emotion recognition engine, and a generative AI model. Specific embodiments for implementing the present invention are described below.

[1734] 1. System Configuration

[1735] 1.1 User terminal

[1736] The user terminal uses a device such as a smartphone, smart glasses, or head-mounted display, and provides an interface for the user to input desired conditions for a property. Once the user enters the desired conditions, they are sent to the server.

[1737] 1.2 Server

[1738] The server searches a property database based on the received desired conditions and lists properties that match the conditions. The server also uses a generative AI model to generate new proposals that are close to the user's conditions. These proposals can include information about the property's surrounding environment and services.

[1739] 1.3 Emotion Recognition Engine

[1740] The emotion recognition engine has the ability to analyze the user's emotional state. For example, it analyzes the user's facial image and recognizes whether the user is feeling happiness, stress, surprise, etc. This emotional information is sent to the server and used to optimize property listings and payment methods.

[1741] 2. Data processing and calculation

[1742] 2.1 Data Acquisition

[1743] The user enters the desired property conditions and the terminal sends the data to the server, which analyzes the received data and searches the property database to find properties that meet the conditions.

[1744] 2.2 Emotion recognition

[1745] It uses cameras and sensors to recognize emotions from images of the user's face. The emotion recognition engine uses libraries such as OpenCV and dlib to analyze the user's facial expressions and behavior.

[1746] 2.3 Proposal Generation by AI

[1747] The server uses a generative AI model (e.g., GPT-3) to generate new property suggestions, which are optimized based on the user's desired conditions and emotional information.

[1748] 3. Specific Examples

[1749] Let's say a user is looking for a "2LDK apartment in Tokyo that allows pets and costs less than 150,000 yen per month." The user enters their desired conditions, and the emotion recognition engine analyzes the user's input, facial expressions, and operation speed. As a result, the request sent to the server includes the desired conditions as well as the user's emotional data. The server receives this information and searches its database. It lists properties that match the conditions, and also uses generative AI to make suggestions such as "areas with extensive pet services" and "properties where rent is negotiable." Based on the analysis results of the emotion engine, the server optimizes the property list and suggestions to best match the user's interests and emotions, and then sends them.

[1750] Prompt Sentence Examples

[1751] Recognize emotions from a user's facial image and suggest payment options that optimize the user experience. For example, if a user is feeling stressed, offer a relaxation coupon and recommend credit card payment.

[1752] In this way, the present invention is a system that can provide optimal property proposals and payment methods while taking into consideration the user's feelings, making it possible to proceed with real estate transactions in a smoother and more personalized manner.

[1753] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1754] Step 1:

[1755] The user operates the terminal and inputs the desired conditions for the property. The input conditions are detailed information such as "a 2LDK apartment in Tokyo where pets are allowed and the monthly fee is less than 150,000 yen." Once this input is complete, the desired condition data is sent to the server. The input here is the user's desired requirements and the associated fields, and the output is the transmission of that data.

[1756] Specific behavior:

[1757] The user opens the property search app and enters each item (location, rent, floor plan, etc.) along the interface. They then press the "Search" button, which sends the data to the server.

[1758] Step 2:

[1759] The server analyzes the desired conditions received and searches the property database based on them. It then lists properties that match the conditions from the property information in the database. In this process, a search query is generated based on the desired conditions entered, and data that matches the conditions is extracted based on that query. The output is a list of properties that match the conditions.

[1760] Specific behavior:

[1761] The server analyzes the received data, generates SQL queries, etc., and executes searches against the database. The resulting property list is then temporarily stored.

[1762] Step 3:

[1763] The server uses an emotion recognition engine to analyze the data to recognize the user's emotions. The emotion recognition engine takes the user's facial image data acquired from the camera as input and outputs the user's emotional state. This output is one of several emotional states, such as "happiness" or "stress."

[1764] Specific behavior:

[1765] The user takes a facial image using the device camera or streams video in real time, and the emotion recognition engine processes the video. The result is sent to the server as the user's current emotional state.

[1766] Step 4:

[1767] The server uses a generative AI model to generate new property proposals based on the desired conditions and the user's emotional information. The generative AI model, for example, uses GPT-3, receives the desired conditions and emotional information as input, and outputs proposals for optimal properties and services. This output is a new proposal list.

[1768] Specific behavior:

[1769] The server sends a request to the generative AI model using a "prompt sentence," receives the generated suggestions, and stores them (e.g., "Please suggest properties in Tokyo with good pet services for users who are feeling stressed").

[1770] Step 5:

[1771] The server sends the property list and the proposals made by the AI ​​to the terminal. The input is the property list and the new proposal list, and the output is sending these lists to the user terminal.

[1772] Specific behavior:

[1773] The server combines the property list with the AI-generated proposal list, generates a data packet to send to the user's device, and transmits it. The user's device receives this data.

[1774] Step 6:

[1775] The terminal displays these property lists to the user using a user interface that presents the information in a format that is easily understandable to the user. The input is the property list and the proposal list, and the output is the display on the user interface.

[1776] Specific behavior:

[1777] The device analyzes the data it receives and displays it in an easy-to-understand format. For example, it could display properties in a list format with a button for more detailed information.

[1778] Step 7:

[1779] The detailed information of the property selected by the user is retrieved and displayed. When the user selects a property of interest, the terminal again sends a request to the server to retrieve the detailed information. The input is the user's selection, and the output is the detailed information of that property.

[1780] Specific behavior:

[1781] When a user clicks on a property they are interested in, the device requests detailed information about that property from the server, which then receives and displays the detailed data.

[1782] Step 8:

[1783] The server calculates the transaction fee and presents it to the user. The transaction fee is calculated based on the property price and transaction details. The input is the property price and transaction terms, and the output is the calculated fee.

[1784] Specific behavior:

[1785] The server collects data related to the transaction, automatically calculates fees, and generates and transmits data to be presented to the user.

[1786] Step 9:

[1787] The user goes through the process of signing a contract for a property. When the user finally selects the property they wish to sign a contract for, the terminal assists them in proceeding with the contract procedure. The input is the user's final selection, and the output is the official completion of the contract procedure.

[1788] Specific behavior:

[1789] When the user presses the "Contract" button, the device provides an interface for entering the necessary contract information and sends a formal contract procedure request to the server. The server then generates a contract and sends it to both parties.

[1790] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1791] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1792] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1793] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1794] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1795] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awar...

Claims

1. A means for a user to input desired conditions for a property; means for transmitting the input conditions to a server; A means for the server to search a property database based on the transmitted conditions and list properties that meet the conditions; A means for the server to generate new proposals that are close to the user's requirements using a generative AI model; A means for the server to transmit the property list and the proposals made by the generating AI to the terminal; means by which the terminal displays these property listings to the user; A means for obtaining and displaying detailed information about a property selected by a user; A means for the server to calculate and present to the user a transaction fee; A means for users to enter into a contract for a property; A system including:

2. The system of claim 1 , wherein the property price and transaction details are included when the server calculates the transaction fee.

3. The system of claim 1, wherein the generative AI model also makes suggestions about the property's surrounding environment and service information.

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