system

Abstract

We provide a system that collects, analyzes, and proposes real estate information, providing convenience to property owners and property searchers. [Solution] A system including: a means for collecting property information from the web and storing it in a database; a means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required by the market; a means for generating and notifying the property owner of an optimal improvement proposal based on the identified facilities and conditions; a means for collecting the search conditions of property searchers and storing them in a database; a means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions; a means for proposing the searcher the optimal property based on the identified desired conditions; a means for matching property owners and property searchers and facilitating personal contracts; and a means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in wizard format.

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 market, property owners were unable to provide facilities and conditions that accurately met market demand, resulting in low property turnover. Another problem was that property searchers were unable to grasp their own potential needs and were unable to find a property that satisfied them. Furthermore, there were also issues with contracts between individuals not being completed smoothly, and the need to go through a real estate agent meant that large fees were incurred. These issues need to be resolved. [Means for solving the problem]

[0005] The present invention provides a system that solves conventional problems by including means for collecting real estate property information from the web and storing it in a database, means for analyzing the stored data with an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying the property owner of an optimal improvement proposal based on the identified facilities and conditions, means for collecting the search conditions of property searchers and storing them in a database, means for analyzing the stored search condition data with an AI algorithm to identify the property searcher's potential desired conditions, means for proposing the optimal property to the searcher based on the identified desired conditions, means for matching property owners and property searchers and promoting personal contracts, and means for automatically generating contract documents using generation AI and providing input support to the user in wizard format.

[0006] "Means of collecting property information from the Web" refers to the process of automatically obtaining property information from real estate portal sites and data sources on the Internet and storing it in a database.

[0007] "Means of storing in a database" refers to a data management system that organizes collected property information and stores it for efficient search and analysis.

[0008] "Means of analysis using AI algorithms" refers to the process of using artificial intelligence and machine learning techniques to analyze large amounts of data and predict market trends and demand.

[0009] "Means to identify the equipment and conditions required by the market" refers to a method for determining current market needs from analyzed data and grasping specific equipment and conditions.

[0010] The "means of generating and notifying optimal improvement proposals to property owners" refers to the process of making specific proposals to property owners regarding improvements and facilities to be introduced based on identified market needs, and informing the property owners of the details of those proposals.

[0011] "Means for collecting search conditions from property searchers and storing them in a database" refers to a method for saving the desired conditions entered by property searchers in a database and using them as material for later analysis and proposals.

[0012] "Method of identifying potential desired conditions of property searchers through analysis using AI algorithms" refers to the process of analyzing collected search condition data to discover desired conditions that are not explicitly stated by the searcher but are likely to actually be what they are looking for.

[0013] The "means of proposing the most suitable property to the searcher" is a method for selecting and proposing the most suitable property to the property searcher based on the identified potential desired conditions.

[0014] "Means for matching property owners and property searchers to facilitate personal contracts" refers to the process of matching the requirements of property owners and property searchers, connecting the searchers with suitable properties, and facilitating personal contracts.

[0015] "Means for automatically generating contract documents and providing input support to users in wizard format" refers to a system that uses generation AI to automatically create the necessary contract documents and guides users through entering the necessary information in sequence. [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] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. The system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[0038] Collection and accumulation of property information

[0039] Gathering property information

[0040] The server periodically collects property information from the web and stores it in a database. This includes real estate portal sites and open data. Web scraping technology is used to extract the necessary data.

[0041] Accumulation of property information

[0042] The server organizes the collected data and stores it in a database, which includes detailed information such as property location, price, facilities, and floor plan.

[0043] Analyzing data and generating optimal proposals

[0044] Data analysis

[0045] The server analyzes the accumulated property information using AI algorithms, which identifies current market trends and the facilities and conditions that are in high demand.

[0046] Generating optimal proposals

[0047] Based on the identified market trends, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi. By notifying the property owner of these proposals, the property owner can increase the turnover rate.

[0048] Specific examples

[0049] The server performs web scraping to collect property information in Shinjuku Ward. The collected data is analyzed to determine that many searchers are looking for air conditioning and Wi-Fi. Based on this, the server makes recommendations to specific property owners about installing air conditioning and Wi-Fi.

[0050] Collecting and analyzing search criteria

[0051] Collecting search criteria

[0052] When a user searches for a property, the terminal sends the entered search criteria, including location, price range, floor plan, and facilities, to the server.

[0053] Data accumulation

[0054] The server stores the received search conditions in a database.

[0055] Data analysis

[0056] The server uses an AI algorithm to analyze the accumulated search criteria data, thereby identifying potential desired conditions that have not yet been suggested by the property searcher.

[0057] Specific examples

[0058] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to the server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[0059] Facilitating personal contracts and providing procedural support

[0060] matching

[0061] The server compares the conditions of property owners and property searchers and matches them with the optimal combination, making it easier for both parties to enter into a direct contract.

[0062] Automatic generation of contract documents

[0063] The server uses generation AI to automatically generate contract documents and other necessary documents, and a wizard format allows users to enter the necessary information, simplifying the contract process.

[0064] Specific examples

[0065] The server matches property owners with property searchers. It uses generation AI to automatically create contract documents and provide them to users. Users input information according to the AI's guidance, and the server supports the creation of final documents and the conclusion of the contract.

[0066] This solves the problems of the traditional real estate market, allowing property owners to increase turnover and property searchers to easily find properties based on their potential needs. Furthermore, private contracts reduce fees and simplify legal procedures.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[0070] Step 2:

[0071] The server stores the collected property information in a database, eliminates duplicate data, and cleanses the data as needed.

[0072] Step 3:

[0073] The server uses AI algorithms to analyze the property information stored in the database, analysing market demand trends, property popularity, search frequency, and other factors.

[0074] Step 4:

[0075] Based on the analysis, the server identifies the amenities and conditions the market demands. For example, it may discover that many searchers are looking for air conditioning and Wi-Fi.

[0076] Step 5:

[0077] The server generates optimal improvement proposals for each property based on the identified market needs, for example, recommending the installation of air conditioners for a specific property.

[0078] Step 6:

[0079] The server notifies the property owner of the generated improvement proposals, possibly via email or push notification.

[0080] Step 7:

[0081] When a user searches for properties, the terminal receives the search criteria entered by the user (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[0082] Step 8:

[0083] The server stores the received search criteria in a database, and also stores each user's search history.

[0084] Step 9:

[0085] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the searcher's potential desired conditions. For example, it may discover that the searcher has strict requirements regarding location.

[0086] Step 10:

[0087] The server then proposes optimal properties to the searcher based on the identified latent conditions. The proposals take into account the user's initial conditions as well as their latent conditions.

[0088] Step 11:

[0089] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[0090] Step 12:

[0091] The server uses generative AI to automatically generate the necessary contract documents, which include the contract details and legal requirements.

[0092] Step 13:

[0093] The user receives input support in a wizard format and enters the necessary information to proceed with the contract procedure. The terminal supports this process.

[0094] Step 14:

[0095] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[0096] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, and completing contract procedures, providing a convenient platform for both property owners and searchers.

[0097] Example 1

[0098] 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."

[0099] Existing real estate information systems have difficulty efficiently collecting and analyzing large amounts of property information. They also lack the means to quickly match the requirements of property owners and property searchers and automatically generate contract documents. This results in a lack of efficiency and accuracy in property searches and transactions, and presents challenges in proposing optimal properties and simplifying contract procedures.

[0100] 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.

[0101] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in a wizard format, means for automatically collecting and storing property information and search conditions on a regular basis, and means for sending notifications to the user in an optimal format depending on the device used. This enables efficient and accurate property searches and transactions.

[0102] "Property information" refers to detailed data about the property's location, price, facilities, floor plan, etc.

[0103] A "database" is a data structure for storing and managing collected property information and search conditions.

[0104] An "AI algorithm" is a computational method that uses machine learning and artificial intelligence to analyze data and identify patterns and trends.

[0105] "Property Owner" means an individual or legal entity that owns a property.

[0106] A "property searcher" is an individual or entity searching for a property.

[0107] "Improvement proposals" are specific advice provided to property owners to increase the value of their properties and improve turnover.

[0108] "Search conditions" are conditions such as location, price range, layout, and facilities that a property searcher inputs when searching for a property.

[0109] "Latent desired conditions" are conditions that property searchers do not explicitly enter but actually consider to be important.

[0110] "Matching" is the process of matching the conditions of the property owner with the conditions of the property searcher to find the optimal combination.

[0111] A "personal contract" is a transaction or contract made directly between a property owner and a property searcher.

[0112] "Generative AI" is an artificial intelligence technology for automatically generating text and documents.

[0113] "Contract documents" are documents that formally record the agreements related to a property transaction.

[0114] A "wizard format" is a guided input method that allows a user to input information step by step.

[0115] A "notification" is information or an alert sent from the system to a user.

[0116] A "terminal" is a device that a user uses to access the property information system. For example, a smartphone or a PC would be an example.

[0117] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. This system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[0118] Collection and accumulation of property information

[0119] Gathering property information

[0120] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python libraries such as BeautifulSoup and Scrapy.

[0121] Examples:

[0122] The server starts a scheduled job every day at 2:00 AM to extract property information from the specified URL, and the extracted data is temporarily stored in memory.

[0123] Accumulation of property information

[0124] The server organizes the collected property information and stores it in a database using MySQL (registered trademark) or PostgreSQL.

[0125] Examples:

[0126] The server stores the property information stored in memory in a database. The database table contains fields such as property location, price, amenities, and layout. It checks for duplicate data and inserts only new data.

[0127] Analyzing data and generating optimal proposals

[0128] Data analysis

[0129] The server analyzes the accumulated property information using AI algorithms (e.g., the Scikit-learn library).

[0130] Examples:

[0131] The server feeds the accumulated data into a data analysis pipeline, performing clustering and regression analysis to identify market trends and equipment in high demand.

[0132] Generating optimal proposals

[0133] The server generates optimal improvement proposals for the property owner based on the analysis results, using a generative AI model (e.g., GPT-4 (registered trademark)).

[0134] Examples:

[0135] The server inputs market trends and demand data into the AI ​​model and generates improvement suggestions, which are then sent to the property owner, such as suggesting the installation of air conditioners or Wi-Fi.

[0136] Collecting and analyzing search criteria

[0137] Collecting search criteria

[0138] When a user searches for a property, the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[0139] Examples:

[0140] The user launches the property search app on their smartphone and enters search criteria. The device sends the entered search criteria in JSON format to the server.

[0141] Search condition data accumulation

[0142] The server stores the received search conditions in a database.

[0143] Examples:

[0144] The server stores the search condition data in a database.

[0145] Data analysis

[0146] The server uses an AI algorithm to analyze the accumulated search criteria data to identify the potential desired conditions of property searchers.

[0147] Examples:

[0148] The server analyzes the search criteria data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[0149] Facilitating personal contracts and providing procedural support

[0150] matching

[0151] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[0152] Examples:

[0153] The server performs a filtering process to compare the property information with the search criteria and notifies both parties of the matching results.

[0154] Automatic generation of contract documents

[0155] The server uses a generative AI model (e.g., GPT-4) to automatically generate contracts and other necessary documents.

[0156] Examples:

[0157] The server inputs the contract terms into the AI ​​model and sends the generated contract documents to the user, who then enters information in a wizard format to complete the process.

[0158] Specific examples of prompts for the generative AI model to use

[0159] "Write a program to collect information on 1LDK apartments in Shinjuku Ward, organize it, and store it in a database. Next, implement a system that analyzes market trends based on the property information and generates recommendations for air conditioning and Wi-Fi."

[0160] By using this prompt sentence, it is possible to generate a program to implement the above function using a generative AI model.

[0161] By referring to these procedures and examples in practicing the present invention, property searches and transactions can be carried out efficiently and accurately.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Step 1: Gather property information

[0164] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python's BeautifulSoup and Scrapy libraries.

[0165] Input: URL of real estate portal site

[0166] Data processing: Extract specific elements (location, price, facilities, floor plan) from HTML pages.

[0167] Output: Collected property information is temporarily stored in memory.

[0168] Specific operation: The server starts a scheduled job at 2:00 AM every day, extracts property information from the specified URL, and temporarily stores it in memory.

[0169] Step 2: Accumulating property information in a database

[0170] The server organizes the collected property information and stores it in a database using MySQL or PostgreSQL.

[0171] Input: Property information in memory

[0172] Data processing: Check for duplicate data and organize it.

[0173] Output: Store the organized property information in a database.

[0174] Specific operation: The server checks the property information stored in memory for duplicate data and then stores it in the database.

[0175] Step 3: Data analysis

[0176] The server analyzes the accumulated property information using an AI algorithm (Scikit-learn library).

[0177] Input: Property information stored in the database

[0178] Data calculations: Perform clustering and regression analysis.

[0179] Output: Identify market trends and equipment / conditions with high demand.

[0180] How it works: The server feeds the data stored in the database into a data analysis pipeline, where AI algorithms are used to identify market trends and equipment in high demand.

[0181] Step 4: Generate optimal proposals

[0182] The server generates and notifies the property owner of optimal improvement proposals based on the analysis results, using a generative AI model (GPT-4).

[0183] Inputs: Market trends and demand data

[0184] Data processing: Generate specific improvement suggestions based on the AI ​​model.

[0185] Output: Send the improvement suggestions in the form of a notice to the property owner.

[0186] How it works: The server inputs market trends and demand data into the AI ​​model, and then notifies the property owner of the generated proposals for installing air conditioners and improving Wi-Fi environments.

[0187] Step 5: Collecting search criteria

[0188] The user searches for properties, and the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[0189] Input: Search criteria entered by the user

[0190] Data processing: Convert search criteria into JSON format.

[0191] Output: The search criteria is sent to the server.

[0192] Specific operation: The user launches a property search app on their smartphone, enters search criteria, and the device sends the search criteria to the server in JSON format.

[0193] Step 6: Storing search criteria in the database

[0194] The server stores the received search conditions in a database.

[0195] Input: Search criteria sent to the server

[0196] Data processing: Format the search criteria to store them in the database.

[0197] Output: The search criteria are stored in the database.

[0198] Specific operation: The server stores the received search criteria in a database in an appropriate format.

[0199] Step 7: Identify potential requirements through data analysis

[0200] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers.

[0201] Input: Accumulated search criteria data

[0202] Data crunching: Using AI algorithms to analyze data and identify potential desired conditions.

[0203] Output: Obtain the results of the identified potential desired conditions.

[0204] Specific operation: The server inputs the search criteria data into an AI algorithm and determines that the user is actually looking for a property close to the station.

[0205] Step 8: Proposal of the best property

[0206] Based on the analysis results, the server suggests the most suitable property to the user.

[0207] Input: Identified potential desires

[0208] Data processing: Generate specific property proposals.

[0209] Output: Send the best property suggestions to the device.

[0210] Specific operation: The server sends the user a notification recommending properties within a five-minute walk from the station.

[0211] Step 9: Matching property information with search criteria

[0212] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[0213] Input: Property information and search conditions

[0214] Data operations: Perform filtering and condition matching operations.

[0215] Output: Get the matching results.

[0216] Specific operation: The server compares the property information with the search criteria and notifies both parties of matching combinations.

[0217] Step 10: Automatic generation of contract documents

[0218] The server uses a generative AI model (GPT-4) to automatically generate contracts and necessary documents.

[0219] Input: Terms and Conditions

[0220] Data processing: Generate contract documents using AI models.

[0221] Output: Send the generated contract document to the user.

[0222] Specific operation: The server inputs the contract terms into the AI ​​model and sends the generated document to the user. The user enters information in a wizard format and completes the contract procedure.

[0223] (Application example 1)

[0224] 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."

[0225] Conventional real estate information systems have comprehensive functionality for collecting and analyzing property information, but they lack sufficient evaluation and proposal capabilities for property security information, making it difficult to effectively improve users' confidence in the safety of properties. Furthermore, because security information is not shared or evaluated among users, it is difficult to make the most of the information held by each user. This creates an issue in which the benefits to both property owners and property searchers are not fully realized.

[0226] 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.

[0227] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to users in a wizard format, means for collecting property security information, analyzing it using an AI algorithm, and proposing highly secure properties, and means for users to share and evaluate security information with each other, thereby improving users' confidence in the safety of properties.

[0228] "Property information" refers to information about the property, such as its location, price, layout, facilities, and security.

[0229] A "database" is a system for storing and managing collected property information and search conditions.

[0230] An "AI algorithm" is a program that analyzes property information and search criteria data based on machine learning and data analysis.

[0231] "Property Owner" means the person or entity that owns the property and provides the information.

[0232] A "Property Searcher" is a person or entity searching for a property.

[0233] "Improvement proposals" are recommendations for adding amenities or changing conditions proposed to increase the market value of the property.

[0234] "Search conditions" are the conditions and wishes specified by a property searcher when searching for a property.

[0235] "Potential desired conditions" are desired conditions that are not explicitly specified by the property searcher, but are likely to be indicated as a result of the AI ​​algorithm's analysis.

[0236] "Matching" is the process of matching the conditions of property owners and property searchers to find the optimal combination.

[0237] A "personal contract" is a direct contract between a property owner and a property searcher.

[0238] "Generative AI" is an AI technology that automatically generates contracts and other necessary documents.

[0239] A "wizard format" is a guided interface designed to guide the user through entering required information.

[0240] "Security information" refers to information about the property's security status and the security equipment installed.

[0241] "Sharing and evaluation" is a process in which users provide each other with information and then evaluate it based on that information.

[0242] MODE FOR CARRYING OUT THE INVENTION

[0243] The present invention is a system that collects, analyzes, and proposes real estate information, providing convenience to property owners and property searchers. Specifically, the system is implemented with the following configuration.

[0244] Collection and accumulation of property information

[0245] The server periodically collects property information from the web and stores it in a database. This involves using web scraping technology to extract the necessary data from real estate portal sites and open data. The software used is a Python program and the BeautifulSoup library. As a specific example, real estate information related to Shinjuku Ward is scraped, and data such as location, price, and facilities is stored in the database.

[0246] Analyzing data and generating optimal proposals

[0247] The server analyzes the collected property information using AI algorithms. This identifies market trends and facilities and conditions that are in high demand, and generates and notifies the property owner of optimal improvement proposals. This process uses machine learning algorithms. AI tools used include TENSORFLOW (registered trademark) and scikit-learn. For example, if it identifies that many searchers are looking for air conditioning and Wi-Fi, it can use this information to suggest installing air conditioning and improving Wi-Fi to specific property owners.

[0248] Collecting and analyzing search criteria

[0249] When a property searcher searches for a property on their smartphone, the device sends the search criteria entered by the user to a server. The collected data is stored in a database and analyzed using an AI algorithm. For example, if a user searches for a 1LDK property, the server will determine through analysis that the user is looking for a property close to the station and suggest properties within a 5-minute walk from the station.

[0250] Facilitating personal contracts and providing procedural support

[0251] The server compares the conditions of the property owner and the property searcher and matches the optimal combination. It also uses generation AI to automatically generate contract documents and other necessary documents, and prompts the user to enter the necessary information in a wizard format. This generation AI uses the OpenAI (registered trademark) API. An example of a specific prompt sentence that can be entered is as follows:

[0252] Property location: Shinjuku Ward

[0253] Price: 30 million yen

[0254] Security: Near station, air conditioning, Wi-Fi

[0255] Generate the contract.

[0256] Analysis, sharing and evaluation of security information

[0257] Furthermore, the server collects property security information and analyzes it using an AI algorithm to suggest highly secure properties to searchers. The system also has a function that allows users to share and rate security information with each other, which can improve the reliability of property security.

[0258] This system makes it easier for property owners to increase turnover and for property searchers to find the perfect property that meets their needs. In addition, by taking security information into consideration when making suggestions, it increases users' sense of security.

[0259] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0260] Program processing flow

[0261] Step 1: Collecting and accumulating property information

[0262] The server collects property information from the web and stores it in a database.

[0263] Input: URL of real estate portal site or open data

[0264] Data processing: Using web scraping technology, property information such as location, price, floor plan, and facilities is extracted from HTML pages.

[0265] Output: Store the collected property information in a database as structured data.

[0266] What it does: The server uses Python and the BeautifulSoup library to periodically access the specified URL, extract the necessary data, and store it in the database.

[0267] Step 2: Analyze the data and generate optimal proposals

[0268] The server analyzes the collected property information using AI algorithms and generates and notifies the property owner of optimal improvement proposals.

[0269] Input: Property information stored in the database

[0270] Data crunching: Using AI algorithms, we analyze property information to identify market trends and in-demand amenities and conditions.

[0271] Output: A list of improvement suggestions to send to the property owner

[0272] How it works: The server uses TensorFlow and scikit-learn to analyze property information in the database, identify high-demand facilities and conditions, and generate recommendations. The identified proposals are then notified to the property owner.

[0273] Step 3: Collecting and analyzing search criteria

[0274] The terminal collects the search conditions of property searchers and sends them to the server, which then analyzes the accumulated search condition data to identify potential desired conditions.

[0275] Input: Search criteria entered by the property searcher on their smartphone

[0276] Data processing: The terminal transfers the entered search criteria to the server.

[0277] Output: Potential desired conditions identified based on the analysis

[0278] How it works: Property searchers enter search criteria into a smartphone app, and the device sends the information to a server, which uses AI algorithms to analyze the data, identify potential preferences, and generate a list of search candidates.

[0279] Step 4: Facilitating personal contracts and providing procedural support

[0280] The server compares the conditions of property owners and property searchers to find the optimal combination. It also uses generation AI to automatically generate contract documents and provides input support to users in a wizard format.

[0281] Input: Property owner and property searcher criteria

[0282] Data calculation: Condition matching and generation Contract document generation using AI

[0283] Output: Matching results and automatically generated contract documents

[0284] Specific operation: The server matches the conditions of the property owner and the property searcher to identify the optimal combination. Then, it automatically generates the contract documents using the OpenAI API and provides input support to the user in a wizard format. The following is an example of a prompt sentence:

[0285] Property location: Shinjuku Ward

[0286] Price: 30 million yen

[0287] Security: Near station, air conditioning, Wi-Fi

[0288] Generate the contract.

[0289] Step 5: Analyze, share and evaluate security information

[0290] The server collects property security information, analyzes it with an AI algorithm, and recommends properties with high safety. It also provides a function for users to share and rate security information with each other.

[0291] Input: Property security information

[0292] Data Computing: Analyzing Security Information with AI Algorithms

[0293] Output: A list of safe property suggestions and security ratings

[0294] Specific operation: The server analyzes the collected security information using an AI algorithm (e.g., TensorFlow) and recommends highly secure properties to users. It also provides a mechanism for users to share and mutually evaluate security information, thereby increasing confidence in the safety of properties.

[0295] As described above, by performing specific processing at each step, it is possible to provide an optimal real estate information system for property owners and property searchers.

[0296] 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.

[0297] This invention relates to a system that provides new benefits to both property owners and property searchers by incorporating an emotion engine into a real estate information system. In addition to functions such as collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents, this system also includes a function that recognizes the user's emotions and provides feedback based on them.

[0298] Collection and accumulation of property information

[0299] Gathering property information

[0300] The server periodically collects property information from the web and stores it in a database. Web scraping technology is used to extract detailed information such as the property's location, price, layout, facilities, and age.

[0301] Accumulation of property information

[0302] The server organizes the collected property information and stores it in a database. Data duplication is eliminated and data cleansing is performed to maintain accurate data.

[0303] Analyzing data and generating optimal proposals

[0304] Data analysis

[0305] The server uses AI algorithms to analyze the property information stored in the database, analyzing indicators such as market demand trends, property popularity, and search frequency to identify specific market needs.

[0306] Generating optimal proposals

[0307] The server generates optimal improvement proposals based on market needs and notifies the property owner, including proposals such as installing air conditioners and improving Wi-Fi.

[0308] Specific examples

[0309] The server collects property information in Shinjuku Ward and identifies that many searchers are looking for air conditioning and Wi-Fi. Based on this, it makes proposals to specific property owners for the installation of air conditioning and Wi-Fi.

[0310] Collecting and analyzing search criteria

[0311] Collecting search criteria

[0312] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[0313] Data accumulation

[0314] The server stores the received search criteria in a database, along with the user's search history.

[0315] Data analysis

[0316] The server uses an AI algorithm to analyze the accumulated search condition data and identify the potential desired conditions of property searchers, for example, determining that the searcher places importance on location.

[0317] Specific examples

[0318] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to a server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[0319] Emotion Recognition and Feedback

[0320] Emotion engine integration

[0321] The device is equipped with a function to collect emotional data from the user's facial expressions and voice, allowing for real-time monitoring of the user's emotions as they search for properties and complete contract procedures.

[0322] Emotional Data Analysis

[0323] The server uses AI algorithms to analyze the data sent from the emotion engine, detects the user's stress or anxiety, and provides support and feedback at the appropriate time.

[0324] Optimal Feedback Generation

[0325] The server generates feedback and suggestions that are best suited to the user's situation based on the emotion data. If the user is interested in a particular property, it will provide detailed information about that property and suggest similar properties.

[0326] Specific examples

[0327] If a user is feeling stressed during a property search, the device will detect this emotion and the server will provide friendly feedback to reduce anxiety and expand options by suggesting other properties similar to the one they expressed interest in.

[0328] Facilitating personal contracts and providing procedural support

[0329] matching

[0330] The server compares the conditions of property owners and property searchers to find the best match, making it easier for both parties to enter into a direct contract.

[0331] Automatic generation of contract documents

[0332] The server uses generation AI to automatically generate contract documents and other necessary documents, and provides input support in the form of a wizard, allowing users to easily proceed with the contract procedure.

[0333] Specific examples

[0334] The system matches users with property owners and automatically creates contract documents using generation AI. The user enters information according to the AI's guidance, and the server generates the final contract documents and provides them to both parties, completing the contract procedure.

[0335] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, completing contract procedures, and recognizing emotions, providing a highly convenient platform for both property owners and searchers.

[0336] The processing flow will be explained below.

[0337] Step 1:

[0338] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[0339] Step 2:

[0340] The server stores the collected property information in a database, which also includes eliminating duplicate data and cleaning inaccurate information.

[0341] Step 3:

[0342] The server uses AI algorithms to analyze property information stored in the database, identifying current market trends and the facilities and conditions that are in high demand.

[0343] Step 4:

[0344] Based on the analysis results, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi.

[0345] Step 5:

[0346] The server notifies the property owner of the generated improvement proposals via email, push notifications, or other means.

[0347] Step 6:

[0348] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[0349] Step 7:

[0350] The server stores the received search conditions in a database. Each user's search history is also saved, enabling consistent data utilization.

[0351] Step 8:

[0352] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers, such as determining whether users place importance on location information.

[0353] Step 9:

[0354] The server then proposes the most suitable property to the user based on the identified latent conditions, taking into account the user's initial conditions as well as their latent conditions.

[0355] Step 10:

[0356] The device uses an emotion engine to analyze the user's facial expressions and voice while searching for properties, collecting emotional data in real time, thereby monitoring the stress and anxiety the user is feeling.

[0357] Step 11:

[0358] The server uses an AI algorithm to analyze the emotional data sent from the emotion engine and provides feedback according to the user's situation, such as changing the UI to help them relax or providing more information.

[0359] Step 12:

[0360] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[0361] Step 13:

[0362] The server uses generation AI to automatically generate the necessary contract documents, which include contract details and legal requirements, and provides input support to the user in a wizard format.

[0363] Step 14:

[0364] The user is guided through a wizard-style input process to input the necessary information into the system, and through this process the contract documents are completed.

[0365] Step 15:

[0366] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[0367] This allows the system to efficiently carry out a series of processes, such as collecting property information, accumulating and analyzing data, generating optimal proposals, collecting and analyzing search conditions, recognizing emotions, and completing contract procedures, thereby improving the user experience.

[0368] Example 2

[0369] 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."

[0370] While conventional real estate information systems collect property information and accumulate data, they are unable to make proposals that reflect the user's emotional state, making improving user satisfaction a challenge. Furthermore, support for improvement proposals to property owners and for personal contract procedures is insufficient, and improvements are needed, particularly in the automatic generation and updating of contract documents. Furthermore, it is difficult for property searchers to identify the conditions they actually desire, resulting in many cases where users' potential needs are overlooked.

[0371] 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.

[0372] In this invention, the server includes: means for collecting property information from the Web and storing it in a database; means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market; means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions; means for collecting search conditions from property searchers and storing them in a database; means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions; means for proposing optimal properties to the searchers based on the identified desired conditions; means for matching property owners and property searchers and facilitating personal contracts; means for automatically generating necessary documents such as contracts using a generative AI model and providing input support to the user in a wizard format; means for collecting emotional data from the user's facial expressions and voice; means for analyzing the collected emotional data using an AI algorithm to detect the user's stress or anxiety; and means for generating and providing optimal feedback and proposals based on the emotional data. This enables optimal property proposals and feedback that take the user's emotional state into consideration, thereby providing a highly convenient service for both property owners and property searchers.

[0373] "Means of collecting property information from the Web" refers to technology that automatically collects data about properties from real estate sites on the Internet.

[0374] "Means of storing data in a database" refers to the technology of organizing collected data and storing it in a database system for centralized management.

[0375] "Artificial intelligence algorithms" are computational methods that include machine learning and deep learning to analyze large amounts of data and find patterns and trends.

[0376] "Means to identify the facilities and conditions desired by the market" refers to a technology that analyzes accumulated property information and identifies the facilities and conditions that searchers highly value in the current market.

[0377] The "means for generating and notifying optimal improvement proposals to property owners" is a technology for generating improvement proposals for owned properties based on identified market needs and notifying the property owners in an appropriate manner.

[0378] "Means for collecting search conditions of property searchers" refers to technology for collecting desired conditions entered by users searching for properties.

[0379] "Means for storing search condition data in a database" refers to a technology for organizing and saving the conditions entered by property searchers in a database.

[0380] "Means for identifying the potential desired conditions of property searchers" is a technology that analyzes collected search condition data and identifies conditions that the searcher does not express but actually desires.

[0381] "Means for proposing optimal properties to searchers" refers to technology that recommends the most suitable properties to property searchers based on the specified desired conditions.

[0382] "Means of matching property owners and property searchers and facilitating personal contracts" refers to technology that matches the conditions of property owners and searchers, finds the optimal combination, and promotes direct contracts.

[0383] "Means for automatically generating necessary documents such as contracts using a generative artificial intelligence model" refers to a technology that uses artificial intelligence technology to automatically create documents necessary for contracts and transactions.

[0384] "Means for providing input support to the user in a wizard format" refers to a form of user interface that guides the user through a procedure so that the user can easily input information.

[0385] "Means for collecting emotional data from the user's facial expressions and voice" refers to technology that uses a camera or microphone to obtain data that recognizes the user's emotions.

[0386] "Means for analyzing emotional data using an artificial intelligence algorithm" refers to technology for analyzing collected emotional data and identifying the user's psychological state.

[0387] "Means for generating and providing optimal feedback and suggestions based on emotional data" refers to technology that provides appropriate advice and information to users based on the analysis results.

[0388] This invention relates to a system that integrates an emotion engine into a real estate information system to provide new benefits to both property owners and property searchers. This system has functions such as collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents, as well as a function that recognizes the user's emotions and provides feedback based on them.

[0389] Hardware and Software Configuration

[0390] 1. Collection and accumulation of property information

[0391] The server periodically collects property information from the web and stores it in a database. The technology used is web scraping, specifically Python's BeautifulSoup or Scrapy. For example, property information in Shinjuku Ward is collected and detailed information such as location, price, floor plan, facilities, and age of the building is extracted. This information is stored in a database using MySQL or PostgreSQL. The organized data undergoes data cleansing before being stored in an accurate state.

[0392] 2. Analyzing data and generating optimal proposals

[0393] The server uses artificial intelligence algorithms to analyze the property information stored in the database. It analyzes indicators such as market demand trends, property popularity, and search frequency, and uses machine learning libraries such as TensorFlow and PyTorch to identify specific market needs. For example, it can identify properties that require air conditioning or Wi-Fi and send notifications to property owners suggesting the installation of air conditioning or Wi-Fi.

[0394] 3. Collecting and analyzing search criteria

[0395] When a user searches for a property, the device receives the entered search criteria (location, price range, floor plan, facilities, etc.) and sends them to the server. The received search criteria are saved in a database and managed along with the user's search history. This allows the use of artificial intelligence algorithms to identify the user's potential desired conditions. Using Google® AutoML, it is possible to determine whether the searcher places importance on location. For example, if a user searches for a 1LDK property, the server analyzes the data and suggests properties within a 5-minute walk from the station.

[0396] 4. Emotion Recognition and Feedback

[0397] The device has the ability to collect emotional data from the user's facial expressions and voice. It uses libraries such as OpenCV and DeepFace to monitor the user's emotions in real time. The collected emotional data is analyzed using IBM Watson (registered trademark) and Amazon Rekognition. This allows it to provide optimal feedback to reduce the stress and anxiety the user feels while searching for properties. For example, it can provide detailed information about properties that the user is interested in and suggest similar properties.

[0398] 5. Facilitating personal contracts and supporting procedures

[0399] The server compares the conditions of property owners and property searchers to find the best match. To achieve this, it uses collaborative filtering and content-based filtering algorithms. It also has the ability to automatically generate contracts and other necessary documents using generative AI models. It uses generative AI technologies such as OpenAI's GPT-3 (registered trademark) and Google's BERT to provide input support to users in a wizard format. For example, the user enters information according to the AI's guidance, and the server generates the final contract documents and provides them to both parties, completing the contract process.

[0400] Examples of prompt statements

[0401] "I'm looking for a 1LDK property in Shinjuku Ward that has Wi-Fi and air conditioning. Can you recommend any properties?"

[0402] "Generate the optimal prompt sentence to make it easier for users to search for properties near stations."

[0403] This system handles everything from collecting property information to analyzing it, making optimal proposals, contract procedures, and even emotion recognition, providing a highly convenient platform for both property owners and searchers.

[0404] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0405] The flow of this system's program processing

[0406] Step 1:

[0407] Gathering property information

[0408] The server periodically collects property information from the web. The input is the URL of the target real estate website. The output is a list of the collected property information. Specifically, it uses web scraping technology (for example, Python's BeautifulSoup or Scrapy) to collect information such as property location, price, floor plan, facilities, and age. It includes the operation of crawling websites and extracting data.

[0409] Step 2:

[0410] Accumulation of property information

[0411] The server stores the collected property information in a database. The input is the list of property information collected in step 1, and the output is the information stored in the database. Specifically, a database system such as MySQL or PostgreSQL is used to eliminate duplicates and cleanse the data. If necessary, the data format is also adjusted.

[0412] Step 3:

[0413] Market Data Analysis

[0414] The server uses AI algorithms to analyze the property information stored in the database. The input is the property information in the database, and the output is indicators related to market trends and demand. Specifically, TensorFlow and PyTorch are used to analyze demand trends, property popularity, search frequency, etc., and obtain analytical results.

[0415] Step 4:

[0416] Generating optimal proposals

[0417] The server generates the optimal improvement proposal for the property owner based on the analyzed market data. The input is the analysis result of the market data obtained in step 3, and the output is the improvement proposal to be notified. Specifically, the server creates proposals such as installing air conditioners or improving the Wi-Fi environment and sends them to the property owner via email or push notification.

[0418] Step 5:

[0419] Collecting search criteria

[0420] When a user searches for a property, the terminal sends the entered search criteria (location, price range, floor plan, facilities, etc.) to the server. The input is the search criteria entered by the user, and the output is the search query sent to the server. Specifically, using web frameworks such as JavaScript (registered trademark) and PHP, the terminal receives the search criteria in real time and sends them to the server.

[0421] Step 6:

[0422] Accumulation of search condition data

[0423] The server stores the received search criteria in a database. The input is the search criteria received in step 5, and the output is the search criteria data stored in the database. For example, the search criteria and history when a user searches for a 1LDK property are stored in the database.

[0424] Step 7:

[0425] Analyzing search data

[0426] The server analyzes the accumulated search criteria data using an AI algorithm to identify the potential desired conditions of property searchers. The input is the search criteria data in the database, and the output is the user's potential desired conditions. Specifically, using Google's AutoML or similar, the analysis is performed to identify the conditions that searchers actually prioritize.

[0427] Step 8:

[0428] Collecting Emotional Data

[0429] The device collects emotion data from the user's facial expressions and voice. The input is the user's real-time facial and voice data, and the output is the collected emotion data. Specifically, emotion data is acquired using libraries such as OpenCV and DeepFace. This includes the use of a camera and microphone to read the form of emotion.

[0430] Step 9:

[0431] Emotional Data Analysis

[0432] The server uses an AI algorithm to analyze the data sent from the emotion engine. The input is the emotion data collected in step 8, and the output is the detection result of the user's stress or anxiety. IBM Watson and Amazon Rekognition are used to analyze the collected emotion data and determine the user's psychological state.

[0433] Step 10:

[0434] Optimal Feedback Generation

[0435] The server generates optimal feedback and suggestions for the user based on the emotion data. The input is the analysis results obtained in step 9, and the output is feedback and property suggestions provided to the user. For example, if the user shows a strong interest in a particular property, detailed information about that property and a list of similar properties are generated and provided to the user.

[0436] Step 11:

[0437] Matching of personal contracts

[0438] The server compares the conditions of property owners and property searchers to find the best match. The input is property information and search condition data, and the output is a matched pair of property owners and searchers. Collaborative Filtering and Content-Based Filtering algorithms are used to calculate the suitability of the conditions and find the best match.

[0439] Step 12:

[0440] Automatic generation of contract documents

[0441] The server automatically generates contracts and necessary documents using a generative artificial intelligence model. The input is the matching results and necessary contract information, and the output is the automatically generated contract document. Models such as OpenAI's GPT-3 and Google's BERT are used to collect input information in a wizard format and create the final contract document.

[0442] In this way, the system can consistently provide property information collection, configuration, analysis, personalized suggestions, emotion recognition, contract support, and more, bringing maximum benefits to both property owners and users.

[0443] (Application example 2)

[0444] 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."

[0445] Conventional real estate information systems offer many functions, such as collecting and analyzing property information, proposing optimal properties, and generating contract documents. However, they lack feedback and suggestions that take user emotions into consideration. As a result, users can feel stressed during property searches and contract procedures, making it difficult to find the perfect property. Furthermore, while property viewing using virtual reality technology is becoming more common, there are still few systems that provide real-time emotional feedback. Therefore, there is a need for a system that improves the user experience and provides optimal property suggestions and feedback based on the user's emotions.

[0446] 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 collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searchers based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in a wizard format, means for collecting the user's facial expressions and voice via a smart device and analyzing their emotions in real time, and means for providing feedback and property proposals to the user based on the analyzed emotion data. This makes it possible to analyze the user's emotions in real time and provide feedback and property proposals based on the analyzed emotion data.

[0447] "Property information" refers to detailed information about a real estate property, such as its location, price, floor plan, facilities, and age.

[0448] A "database" is a system for organizing and storing collected information, and is a medium for storing property information, search condition data, etc.

[0449] An "AI algorithm" is a program that uses machine learning and data analysis techniques to analyze data, find patterns and trends, and make optimal suggestions and predictions.

[0450] A "Property Owner" is an individual or legal entity that owns a real estate property and wishes to rent or sell the property.

[0451] A "property searcher" is an individual or corporation searching for a real estate property.

[0452] An "optimal improvement proposal" is a proposal for improvement made to a property owner based on the facilities and conditions required by the market, and includes specific advice to increase the attractiveness of the property.

[0453] "Search criteria" refers to the conditions that property searchers enter when searching for a property, and refers to elements such as location, price range, floor plan, and facilities.

[0454] "Latent desired conditions" are elements or conditions that property searchers consider particularly important; they are hidden needs that are not explicitly entered but are identified through data analysis.

[0455] "Matching" is the process of matching the conditions of property owners and property searchers to find the optimal combination that meets the wishes of both parties.

[0456] A "personal contract" refers to a direct contract between a property owner and a property searcher.

[0457] "Generative AI" is a program that uses artificial intelligence technology to automatically generate necessary documents and contract documents based on information entered by the user.

[0458] A "wizard format" is a guided interface that allows a user to obtain a final output by inputting required information step by step.

[0459] "Smart device" refers to a device with internet connectivity, including smartphones, smart glasses, and head-mounted displays.

[0460] "Facial expressions and voice" refers to data for capturing the user's emotional state in real time, including facial expressions and what is being said.

[0461] "Analyzing emotions in real time" means instantly analyzing collected facial expressions and voice data to understand the user's emotional state.

[0462] "Feedback" refers to advice and information provided to users based on analyzed emotional data.

[0463] "Property suggestion" refers to recommending properties that are deemed appropriate based on the user's wishes and emotional state.

[0464] An embodiment of this invention is based on a real estate information system that integrates property information collection, data analysis, optimal proposal generation, search condition collection and analysis, emotion recognition and feedback, and interpersonal contract promotion and procedure support. This system allows users to tour properties using virtual reality technology using smart devices (smartphones, smart glasses, head-mounted displays, etc.), analyzes the user's emotions, and provides feedback in real time.

[0465] Program processing and technology used

[0466] The server first uses web scraping technology to collect property information from various real estate websites. The collected data is then stored in a database. Data duplication is eliminated and data cleansing is performed to ensure accurate data. This data is then analyzed using AI algorithms (e.g., machine learning models) to identify the facilities and conditions desired by the market.

[0467] When a user searches for a property, the device receives the search criteria entered and sends them to the server. The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of the property searcher. Based on this, the system suggests the most suitable property.

[0468] During a property viewing, the smart device collects the user's facial expressions and voice. This data is analyzed in real time using facial expression analysis software (e.g., Emotion API) and voice analysis software (e.g., Google Cloud Speech-to-Text + Sentiment Analysis API). Based on the emotion data, the server provides optimal feedback to the user and suggests detailed information about properties that interest them and similar properties.

[0469] When the contract is to proceed, the server uses a generative AI (e.g., OpenAI GPT-3) to automatically generate the contract documents and other necessary documents. It provides input support in the form of a wizard, allowing the user to easily follow the instructions to proceed with the contract procedure.

[0470] Examples of concrete examples and prompts

[0471] For example, if a user is using smart glasses to take a virtual tour and expresses interest in a property, if the user smiles or makes a positive comment, their facial expression and voice data will be analyzed and real-time feedback such as, "It seems you're interested in this property. More information is available here. Also, please check out similar properties."

[0472] Example prompt sentence:

[0473] Analyze the emotions users feel when viewing properties and generate feedback that provides details about properties that interest them and suggests similar properties.

[0474] Input data: User facial expressions (e.g., happy expressions), voice transcripts (e.g., positive comments)

[0475] Output data: Feedback based on user sentiment (e.g., "You seem interested in this property. More information here.")

[0476] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0477] Step 1:

[0478] The server uses web scraping technology to collect property information from various real estate websites. The input is the URL and HTML structure information of the real estate website, and the output is detailed information such as the property's location, price, layout, facilities, and age, which is stored in a database. Specifically, a script that runs periodically crawls through websites, extracts the necessary data, and stores it in the database.

[0479] Step 2:

[0480] The server stores the collected property information in a database. The input is property information obtained through web scraping, and the output is accurate property data after deduplication and data cleansing. Specifically, the database engine is used to organize, de-dupe, and cleanse the data.

[0481] Step 3:

[0482] The server uses AI algorithms to analyze the property information stored in the database. It uses organized property data as input and identifies the amenities and conditions the market demands as output. Specifically, it uses machine learning models to analyze the dataset and identify trends and popular amenities.

[0483] Step 4:

[0484] The server generates and notifies the property owner of optimal improvement proposals based on the identified market demand. The input is market demand data obtained by the AI ​​algorithm, and the output is specific improvement proposals (e.g., installing an air conditioner or improving the Wi-Fi environment) that are generated and notified to the property owner. Specifically, the improvement proposals are sent to the property owner's email or app via the notification system.

[0485] Step 5:

[0486] When a user searches for a property, the device receives the search criteria (e.g., location, price range, layout, facilities, etc.) entered and sends them to the server. The input uses the search criteria entered by the user into the app or website, and the output sends these search criteria to the server. Specifically, the device accepts search interactions through the device interface and sends the data to the server.

[0487] Step 6:

[0488] The server uses an AI algorithm to analyze the accumulated search condition data and identify the potential desired conditions of the property searcher. The input is the user's search history and condition data, and the output is the user's potential desired conditions. Specifically, it uses a machine learning model to analyze past data and discover the user's hidden needs.

[0489] Step 7:

[0490] The server then suggests properties that best suit the searcher based on the searcher's desired conditions. The input is the user's desired conditions as determined by the AI ​​algorithm, and the output is a list of properties that best suit the user. Specifically, the server searches the database for properties that match the user's desired conditions and displays them as a recommended list on the app or website.

[0491] Step 8:

[0492] The device collects the user's facial expressions and voice and transmits them to the server in real time. The input is facial expression and voice data acquired from the user's camera and microphone, and the output is transmission of these data to the server. Specifically, the device's camera and microphone capture data in real time and transmit it to the server using a communication protocol.

[0493] Step 9:

[0494] The server analyzes the transmitted emotional data using an AI algorithm to identify the user's emotional state. The input is the facial expression and voice data transmitted from the device, and the output is the user's emotional state (e.g., stress, anxiety, interest). Specific operations include analyzing the data using facial expression analysis software and voice analysis APIs.

[0495] Step 10:

[0496] The server provides feedback and property suggestions to the user based on the emotional data. It uses the analyzed emotional data as input and generates appropriate feedback and property suggestions as output, which it provides to the user. Specifically, it uses a feedback generation AI model to create feedback messages and property information according to the user's emotional state and sends them to the device.

[0497] Step 11:

[0498] The server matches property owners and property searchers and automatically generates the necessary documents to facilitate interpersonal contracts using generative AI. It uses the contract information of the property owner and property searcher as input, and generates complete contract documents as output, providing them to both parties. Specifically, it creates contract documents using a generative AI model based on the contract information obtained from the user, and provides input support through a wizard-style interface.

[0499] 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.

[0500] 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.

[0501] 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.

[0502] [Second embodiment]

[0503] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0504] 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.

[0505] 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).

[0506] 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.

[0507] 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.

[0508] 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).

[0509] 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.

[0510] 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.

[0511] 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.

[0512] 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.

[0513] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0514] 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."

[0515] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. The system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[0516] Collection and accumulation of property information

[0517] Gathering property information

[0518] The server periodically collects property information from the web and stores it in a database. This includes real estate portal sites and open data. Web scraping technology is used to extract the necessary data.

[0519] Accumulation of property information

[0520] The server organizes the collected data and stores it in a database, which includes detailed information such as property location, price, facilities, and floor plan.

[0521] Analyzing data and generating optimal proposals

[0522] Data analysis

[0523] The server analyzes the accumulated property information using AI algorithms, which identifies current market trends and the facilities and conditions that are in high demand.

[0524] Generating optimal proposals

[0525] Based on the identified market trends, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi. By notifying the property owner of these proposals, the property owner can increase the turnover rate.

[0526] Specific examples

[0527] The server performs web scraping to collect property information in Shinjuku Ward. The collected data is analyzed to determine that many searchers are looking for air conditioning and Wi-Fi. Based on this, the server makes recommendations to specific property owners about installing air conditioning and Wi-Fi.

[0528] Collecting and analyzing search criteria

[0529] Collecting search criteria

[0530] When a user searches for a property, the terminal sends the entered search criteria, including location, price range, floor plan, and facilities, to the server.

[0531] Data accumulation

[0532] The server stores the received search conditions in a database.

[0533] Data analysis

[0534] The server uses an AI algorithm to analyze the accumulated search criteria data, thereby identifying potential desired conditions that have not yet been suggested by the property searcher.

[0535] Specific examples

[0536] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to the server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[0537] Facilitating personal contracts and providing procedural support

[0538] matching

[0539] The server compares the conditions of property owners and property searchers and matches them with the optimal combination, making it easier for both parties to enter into a direct contract.

[0540] Automatic generation of contract documents

[0541] The server uses generation AI to automatically generate contract documents and other necessary documents, and a wizard format allows users to enter the necessary information, simplifying the contract process.

[0542] Specific examples

[0543] The server matches property owners with property searchers. It uses generation AI to automatically create contract documents and provide them to users. Users input information according to the AI's guidance, and the server supports the creation of final documents and the conclusion of the contract.

[0544] This solves the problems of the traditional real estate market, allowing property owners to increase turnover and property searchers to easily find properties based on their potential needs. Furthermore, private contracts reduce fees and simplify legal procedures.

[0545] The processing flow will be explained below.

[0546] Step 1:

[0547] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[0548] Step 2:

[0549] The server stores the collected property information in a database, eliminates duplicate data, and cleanses the data as needed.

[0550] Step 3:

[0551] The server uses AI algorithms to analyze the property information stored in the database, analysing market demand trends, property popularity, search frequency, and other factors.

[0552] Step 4:

[0553] Based on the analysis, the server identifies the amenities and conditions the market demands. For example, it may discover that many searchers are looking for air conditioning and Wi-Fi.

[0554] Step 5:

[0555] The server generates optimal improvement proposals for each property based on the identified market needs, for example, recommending the installation of air conditioners for a specific property.

[0556] Step 6:

[0557] The server notifies the property owner of the generated improvement proposals, possibly via email or push notification.

[0558] Step 7:

[0559] When a user searches for properties, the terminal receives the search criteria entered by the user (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[0560] Step 8:

[0561] The server stores the received search criteria in a database, and also stores each user's search history.

[0562] Step 9:

[0563] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the searcher's potential desired conditions. For example, it may discover that the searcher has strict requirements regarding location.

[0564] Step 10:

[0565] The server then proposes optimal properties to the searcher based on the identified latent conditions. The proposals take into account the user's initial conditions as well as their latent conditions.

[0566] Step 11:

[0567] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[0568] Step 12:

[0569] The server uses generative AI to automatically generate the necessary contract documents, which include the contract details and legal requirements.

[0570] Step 13:

[0571] The user receives input support in a wizard format and enters the necessary information to proceed with the contract procedure. The terminal supports this process.

[0572] Step 14:

[0573] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[0574] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, and completing contract procedures, providing a convenient platform for both property owners and searchers.

[0575] Example 1

[0576] 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."

[0577] Existing real estate information systems have difficulty efficiently collecting and analyzing large amounts of property information. They also lack the means to quickly match the requirements of property owners and property searchers and automatically generate contract documents. This results in a lack of efficiency and accuracy in property searches and transactions, and presents challenges in proposing optimal properties and simplifying contract procedures.

[0578] 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.

[0579] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in a wizard format, means for automatically collecting and storing property information and search conditions on a regular basis, and means for sending notifications to the user in an optimal format depending on the device used. This enables efficient and accurate property searches and transactions.

[0580] "Property information" refers to detailed data about the property's location, price, facilities, floor plan, etc.

[0581] A "database" is a data structure for storing and managing collected property information and search conditions.

[0582] An "AI algorithm" is a computational method that uses machine learning and artificial intelligence to analyze data and identify patterns and trends.

[0583] "Property Owner" means an individual or legal entity that owns a property.

[0584] A "property searcher" is an individual or entity searching for a property.

[0585] "Improvement proposals" are specific advice provided to property owners to increase the value of their properties and improve turnover.

[0586] "Search conditions" are conditions such as location, price range, layout, and facilities that a property searcher inputs when searching for a property.

[0587] "Latent desired conditions" are conditions that property searchers do not explicitly enter but actually consider to be important.

[0588] "Matching" is the process of matching the conditions of the property owner with the conditions of the property searcher to find the optimal combination.

[0589] A "personal contract" is a transaction or contract made directly between a property owner and a property searcher.

[0590] "Generative AI" is an artificial intelligence technology for automatically generating text and documents.

[0591] "Contract documents" are documents that formally record the agreements related to a property transaction.

[0592] A "wizard format" is a guided input method that allows a user to input information step by step.

[0593] A "notification" is information or an alert sent from the system to a user.

[0594] A "terminal" is a device that a user uses to access the property information system. For example, a smartphone or a PC would be an example.

[0595] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. This system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[0596] Collection and accumulation of property information

[0597] Gathering property information

[0598] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python libraries such as BeautifulSoup and Scrapy.

[0599] Examples:

[0600] The server starts a scheduled job every day at 2:00 AM to extract property information from the specified URL, and the extracted data is temporarily stored in memory.

[0601] Accumulation of property information

[0602] The server organizes the collected property information and stores it in a database using MySQL, PostgreSQL, or similar.

[0603] Examples:

[0604] The server stores the property information stored in memory in a database. The database table contains fields such as property location, price, amenities, and layout. It checks for duplicate data and inserts only new data.

[0605] Analyzing data and generating optimal proposals

[0606] Data analysis

[0607] The server analyzes the accumulated property information using AI algorithms (e.g., the Scikit-learn library).

[0608] Examples:

[0609] The server feeds the accumulated data into a data analysis pipeline, performing clustering and regression analysis to identify market trends and equipment in high demand.

[0610] Generating optimal proposals

[0611] The server generates optimal improvement proposals for property owners based on the analysis results, using a generative AI model (e.g., GPT-4).

[0612] Examples:

[0613] The server inputs market trends and demand data into the AI ​​model and generates improvement suggestions, which are then sent to the property owner, such as suggesting the installation of air conditioners or Wi-Fi.

[0614] Collecting and analyzing search criteria

[0615] Collecting search criteria

[0616] When a user searches for a property, the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[0617] Examples:

[0618] The user launches the property search app on their smartphone and enters search criteria. The device sends the entered search criteria in JSON format to the server.

[0619] Search condition data accumulation

[0620] The server stores the received search conditions in a database.

[0621] Examples:

[0622] The server stores the search condition data in a database.

[0623] Data analysis

[0624] The server uses an AI algorithm to analyze the accumulated search criteria data to identify the potential desired conditions of property searchers.

[0625] Examples:

[0626] The server analyzes the search criteria data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[0627] Facilitating personal contracts and providing procedural support

[0628] matching

[0629] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[0630] Examples:

[0631] The server performs a filtering process to compare the property information with the search criteria and notifies both parties of the matching results.

[0632] Automatic generation of contract documents

[0633] The server uses a generative AI model (e.g., GPT-4) to automatically generate contracts and other necessary documents.

[0634] Examples:

[0635] The server inputs the contract terms into the AI ​​model and sends the generated contract documents to the user, who then enters information in a wizard format to complete the process.

[0636] Specific examples of prompts for the generative AI model to use

[0637] "Write a program to collect information on 1LDK apartments in Shinjuku Ward, organize it, and store it in a database. Next, implement a system that analyzes market trends based on the property information and generates recommendations for air conditioning and Wi-Fi."

[0638] By using this prompt sentence, it is possible to generate a program to implement the above function using a generative AI model.

[0639] By referring to these procedures and examples in practicing the present invention, property searches and transactions can be carried out efficiently and accurately.

[0640] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0641] Step 1: Gather property information

[0642] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python's BeautifulSoup and Scrapy libraries.

[0643] Input: URL of real estate portal site

[0644] Data processing: Extract specific elements (location, price, facilities, floor plan) from HTML pages.

[0645] Output: Collected property information is temporarily stored in memory.

[0646] Specific operation: The server starts a scheduled job at 2:00 AM every day, extracts property information from the specified URL, and temporarily stores it in memory.

[0647] Step 2: Accumulating property information in a database

[0648] The server organizes the collected property information and stores it in a database using MySQL or PostgreSQL.

[0649] Input: Property information in memory

[0650] Data processing: Check for duplicate data and organize it.

[0651] Output: Store the organized property information in a database.

[0652] Specific operation: The server checks the property information stored in memory for duplicate data and then stores it in the database.

[0653] Step 3: Data analysis

[0654] The server analyzes the accumulated property information using an AI algorithm (Scikit-learn library).

[0655] Input: Property information stored in the database

[0656] Data calculations: Perform clustering and regression analysis.

[0657] Output: Identify market trends and equipment / conditions with high demand.

[0658] How it works: The server feeds the data stored in the database into a data analysis pipeline, where AI algorithms are used to identify market trends and equipment in high demand.

[0659] Step 4: Generate optimal proposals

[0660] The server generates and notifies the property owner of optimal improvement proposals based on the analysis results, using a generative AI model (GPT-4).

[0661] Inputs: Market trends and demand data

[0662] Data processing: Generate specific improvement suggestions based on the AI ​​model.

[0663] Output: Send the improvement suggestions in the form of a notice to the property owner.

[0664] How it works: The server inputs market trends and demand data into the AI ​​model, and then notifies the property owner of the generated proposals for installing air conditioners and improving Wi-Fi environments.

[0665] Step 5: Collecting search criteria

[0666] The user searches for properties, and the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[0667] Input: Search criteria entered by the user

[0668] Data processing: Convert search criteria into JSON format.

[0669] Output: The search criteria is sent to the server.

[0670] Specific operation: The user launches a property search app on their smartphone, enters search criteria, and the device sends the search criteria to the server in JSON format.

[0671] Step 6: Storing search criteria in the database

[0672] The server stores the received search conditions in a database.

[0673] Input: Search criteria sent to the server

[0674] Data processing: Format the search criteria to store them in the database.

[0675] Output: The search criteria are stored in the database.

[0676] Specific operation: The server stores the received search criteria in a database in an appropriate format.

[0677] Step 7: Identify potential requirements through data analysis

[0678] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers.

[0679] Input: Accumulated search criteria data

[0680] Data crunching: Using AI algorithms to analyze data and identify potential desired conditions.

[0681] Output: Obtain the results of the identified potential desired conditions.

[0682] Specific operation: The server inputs the search criteria data into an AI algorithm and determines that the user is actually looking for a property close to the station.

[0683] Step 8: Proposal of the best property

[0684] Based on the analysis results, the server suggests the most suitable property to the user.

[0685] Input: Identified potential desires

[0686] Data processing: Generate specific property proposals.

[0687] Output: Send the best property suggestions to the device.

[0688] Specific operation: The server sends the user a notification recommending properties within a five-minute walk from the station.

[0689] Step 9: Matching property information with search criteria

[0690] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[0691] Input: Property information and search conditions

[0692] Data operations: Perform filtering and condition matching operations.

[0693] Output: Get the matching results.

[0694] Specific operation: The server compares the property information with the search criteria and notifies both parties of matching combinations.

[0695] Step 10: Automatic generation of contract documents

[0696] The server uses a generative AI model (GPT-4) to automatically generate contracts and necessary documents.

[0697] Input: Terms and Conditions

[0698] Data processing: Generate contract documents using AI models.

[0699] Output: Send the generated contract document to the user.

[0700] Specific operation: The server inputs the contract terms into the AI ​​model and sends the generated document to the user. The user enters information in a wizard format and completes the contract procedure.

[0701] (Application example 1)

[0702] 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."

[0703] Conventional real estate information systems have comprehensive functionality for collecting and analyzing property information, but they lack sufficient evaluation and proposal capabilities for property security information, making it difficult to effectively improve users' confidence in the safety of properties. Furthermore, because security information is not shared or evaluated among users, it is difficult to make the most of the information held by each user. This creates an issue in which the benefits to both property owners and property searchers are not fully realized.

[0704] 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.

[0705] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to users in a wizard format, means for collecting property security information, analyzing it using an AI algorithm, and proposing highly secure properties, and means for users to share and evaluate security information with each other, thereby improving users' confidence in the safety of properties.

[0706] "Property information" refers to information about the property, such as its location, price, layout, facilities, and security.

[0707] A "database" is a system for storing and managing collected property information and search conditions.

[0708] An "AI algorithm" is a program that analyzes property information and search criteria data based on machine learning and data analysis.

[0709] "Property Owner" means the person or entity that owns the property and provides the information.

[0710] A "Property Searcher" is a person or entity searching for a property.

[0711] "Improvement proposals" are recommendations for adding amenities or changing conditions proposed to increase the market value of the property.

[0712] "Search conditions" are the conditions and wishes specified by a property searcher when searching for a property.

[0713] "Potential desired conditions" are desired conditions that are not explicitly specified by the property searcher, but are likely to be indicated as a result of the AI ​​algorithm's analysis.

[0714] "Matching" is the process of matching the conditions of property owners and property searchers to find the optimal combination.

[0715] A "personal contract" is a direct contract between a property owner and a property searcher.

[0716] "Generative AI" is an AI technology that automatically generates contracts and other necessary documents.

[0717] A "wizard format" is a guided interface designed to guide the user through entering required information.

[0718] "Security information" refers to information about the property's security status and the security equipment installed.

[0719] "Sharing and evaluation" is a process in which users provide each other with information and then evaluate it based on that information.

[0720] MODE FOR CARRYING OUT THE INVENTION

[0721] The present invention is a system that collects, analyzes, and proposes real estate information, providing convenience to property owners and property searchers. Specifically, the system is implemented with the following configuration.

[0722] Collection and accumulation of property information

[0723] The server periodically collects property information from the web and stores it in a database. This involves using web scraping technology to extract the necessary data from real estate portal sites and open data. The software used is a Python program and the BeautifulSoup library. As a specific example, real estate information related to Shinjuku Ward is scraped, and data such as location, price, and facilities is stored in the database.

[0724] Analyzing data and generating optimal proposals

[0725] The server analyzes the collected property information using AI algorithms. This identifies market trends and facilities and conditions that are in high demand, and generates and notifies property owners of optimal improvement proposals. This process uses machine learning algorithms. AI tools used include TensorFlow and scikit-learn. For example, if it identifies that many searchers are looking for air conditioning and Wi-Fi, it can use this information to suggest installing air conditioning and improving Wi-Fi to specific property owners.

[0726] Collecting and analyzing search criteria

[0727] When a property searcher searches for a property on their smartphone, the device sends the search criteria entered by the user to a server. The collected data is stored in a database and analyzed using an AI algorithm. For example, if a user searches for a 1LDK property, the server will determine through analysis that the user is looking for a property close to the station and suggest properties within a 5-minute walk from the station.

[0728] Facilitating personal contracts and providing procedural support

[0729] The server compares the conditions of the property owner and the property searcher and matches the optimal combination. It also uses generation AI to automatically generate contract documents and other necessary documents, and prompts the user to enter the necessary information in a wizard format. This generation AI uses OpenAI's API. An example of a specific prompt sentence that can be entered is as follows:

[0730] Property location: Shinjuku Ward

[0731] Price: 30 million yen

[0732] Security: Near station, air conditioning, Wi-Fi

[0733] Generate the contract.

[0734] Analysis, sharing and evaluation of security information

[0735] Furthermore, the server collects property security information and analyzes it using an AI algorithm to suggest highly secure properties to searchers. The system also has a function that allows users to share and rate security information with each other, which can improve the reliability of property security.

[0736] This system makes it easier for property owners to increase turnover and for property searchers to find the perfect property that meets their needs. In addition, by taking security information into consideration when making suggestions, it increases users' sense of security.

[0737] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0738] Program processing flow

[0739] Step 1: Collecting and accumulating property information

[0740] The server collects property information from the web and stores it in a database.

[0741] Input: URL of real estate portal site or open data

[0742] Data processing: Using web scraping technology, property information such as location, price, floor plan, and facilities is extracted from HTML pages.

[0743] Output: Store the collected property information in a database as structured data.

[0744] What it does: The server uses Python and the BeautifulSoup library to periodically access the specified URL, extract the necessary data, and store it in the database.

[0745] Step 2: Analyze the data and generate optimal proposals

[0746] The server analyzes the collected property information using AI algorithms and generates and notifies the property owner of optimal improvement proposals.

[0747] Input: Property information stored in the database

[0748] Data crunching: Using AI algorithms, we analyze property information to identify market trends and in-demand amenities and conditions.

[0749] Output: A list of improvement suggestions to send to the property owner

[0750] How it works: The server uses TensorFlow and scikit-learn to analyze property information in the database, identify high-demand facilities and conditions, and generate recommendations. The identified proposals are then notified to the property owner.

[0751] Step 3: Collecting and analyzing search criteria

[0752] The terminal collects the search conditions of property searchers and sends them to the server, which then analyzes the accumulated search condition data to identify potential desired conditions.

[0753] Input: Search criteria entered by the property searcher on their smartphone

[0754] Data processing: The terminal transfers the entered search criteria to the server.

[0755] Output: Potential desired conditions identified based on the analysis

[0756] How it works: Property searchers enter search criteria into a smartphone app, and the device sends the information to a server, which uses AI algorithms to analyze the data, identify potential preferences, and generate a list of search candidates.

[0757] Step 4: Facilitating personal contracts and providing procedural support

[0758] The server compares the conditions of property owners and property searchers to find the optimal combination. It also uses generation AI to automatically generate contract documents and provides input support to users in a wizard format.

[0759] Input: Property owner and property searcher criteria

[0760] Data calculation: Condition matching and generation Contract document generation using AI

[0761] Output: Matching results and automatically generated contract documents

[0762] Specific operation: The server matches the conditions of the property owner and the property searcher to identify the optimal combination. Then, it automatically generates the contract documents using the OpenAI API and provides input support to the user in a wizard format. The following is an example of a prompt sentence:

[0763] Property location: Shinjuku Ward

[0764] Price: 30 million yen

[0765] Security: Near station, air conditioning, Wi-Fi

[0766] Generate the contract.

[0767] Step 5: Analyze, share and evaluate security information

[0768] The server collects property security information, analyzes it with an AI algorithm, and recommends properties with high safety. It also provides a function for users to share and rate security information with each other.

[0769] Input: Property security information

[0770] Data Computing: Analyzing Security Information with AI Algorithms

[0771] Output: A list of safe property suggestions and security ratings

[0772] Specific operation: The server analyzes the collected security information using an AI algorithm (e.g., TensorFlow) and recommends highly secure properties to users. It also provides a mechanism for users to share and mutually evaluate security information, thereby increasing confidence in the safety of properties.

[0773] As described above, by performing specific processing at each step, it is possible to provide an optimal real estate information system for property owners and property searchers.

[0774] 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.

[0775] This invention relates to a system that provides new benefits to both property owners and property searchers by incorporating an emotion engine into a real estate information system. In addition to functions such as collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents, this system also includes a function that recognizes the user's emotions and provides feedback based on them.

[0776] Collection and accumulation of property information

[0777] Gathering property information

[0778] The server periodically collects property information from the web and stores it in a database. Web scraping technology is used to extract detailed information such as the property's location, price, layout, facilities, and age.

[0779] Accumulation of property information

[0780] The server organizes the collected property information and stores it in a database. Data duplication is eliminated and data cleansing is performed to maintain accurate data.

[0781] Analyzing data and generating optimal proposals

[0782] Data analysis

[0783] The server uses AI algorithms to analyze the property information stored in the database, analyzing indicators such as market demand trends, property popularity, and search frequency to identify specific market needs.

[0784] Generating optimal proposals

[0785] The server generates optimal improvement proposals based on market needs and notifies the property owner, including proposals such as installing air conditioners and improving Wi-Fi.

[0786] Specific examples

[0787] The server collects property information in Shinjuku Ward and identifies that many searchers are looking for air conditioning and Wi-Fi. Based on this, it makes proposals to specific property owners for the installation of air conditioning and Wi-Fi.

[0788] Collecting and analyzing search criteria

[0789] Collecting search criteria

[0790] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[0791] Data accumulation

[0792] The server stores the received search criteria in a database, along with the user's search history.

[0793] Data analysis

[0794] The server uses an AI algorithm to analyze the accumulated search condition data and identify the potential desired conditions of property searchers, for example, determining that the searcher places importance on location.

[0795] Specific examples

[0796] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to a server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[0797] Emotion Recognition and Feedback

[0798] Emotion engine integration

[0799] The device is equipped with a function to collect emotional data from the user's facial expressions and voice, allowing for real-time monitoring of the user's emotions as they search for properties and complete contract procedures.

[0800] Emotional Data Analysis

[0801] The server uses AI algorithms to analyze the data sent from the emotion engine, detects the user's stress or anxiety, and provides support and feedback at the appropriate time.

[0802] Optimal Feedback Generation

[0803] The server generates feedback and suggestions that are best suited to the user's situation based on the emotion data. If the user is interested in a particular property, it will provide detailed information about that property and suggest similar properties.

[0804] Specific examples

[0805] If a user is feeling stressed during a property search, the device will detect this emotion and the server will provide friendly feedback to reduce anxiety and expand options by suggesting other properties similar to the one they expressed interest in.

[0806] Facilitating personal contracts and providing procedural support

[0807] matching

[0808] The server compares the conditions of property owners and property searchers to find the best match, making it easier for both parties to enter into a direct contract.

[0809] Automatic generation of contract documents

[0810] The server uses generation AI to automatically generate contract documents and other necessary documents, and provides input support in the form of a wizard, allowing users to easily proceed with the contract procedure.

[0811] Specific examples

[0812] The system matches users with property owners and automatically creates contract documents using generation AI. The user enters information according to the AI's guidance, and the server generates the final contract documents and provides them to both parties, completing the contract procedure.

[0813] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, completing contract procedures, and recognizing emotions, providing a highly convenient platform for both property owners and searchers.

[0814] The processing flow will be explained below.

[0815] Step 1:

[0816] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[0817] Step 2:

[0818] The server stores the collected property information in a database, which also includes eliminating duplicate data and cleaning inaccurate information.

[0819] Step 3:

[0820] The server uses AI algorithms to analyze property information stored in the database, identifying current market trends and the facilities and conditions that are in high demand.

[0821] Step 4:

[0822] Based on the analysis results, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi.

[0823] Step 5:

[0824] The server notifies the property owner of the generated improvement proposals via email, push notifications, or other means.

[0825] Step 6:

[0826] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[0827] Step 7:

[0828] The server stores the received search conditions in a database. Each user's search history is also saved, enabling consistent data utilization.

[0829] Step 8:

[0830] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers, such as determining whether users place importance on location information.

[0831] Step 9:

[0832] The server then proposes the most suitable property to the user based on the identified latent conditions, taking into account the user's initial conditions as well as their latent conditions.

[0833] Step 10:

[0834] The device uses an emotion engine to analyze the user's facial expressions and voice while searching for properties, collecting emotional data in real time, thereby monitoring the stress and anxiety the user is feeling.

[0835] Step 11:

[0836] The server uses an AI algorithm to analyze the emotional data sent from the emotion engine and provides feedback according to the user's situation, such as changing the UI to help them relax or providing more information.

[0837] Step 12:

[0838] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[0839] Step 13:

[0840] The server uses generation AI to automatically generate the necessary contract documents, which include contract details and legal requirements, and provides input support to the user in a wizard format.

[0841] Step 14:

[0842] The user is guided through a wizard-style input process to input the necessary information into the system, and through this process the contract documents are completed.

[0843] Step 15:

[0844] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[0845] This allows the system to efficiently carry out a series of processes, such as collecting property information, accumulating and analyzing data, generating optimal proposals, collecting and analyzing search conditions, recognizing emotions, and completing contract procedures, thereby improving the user experience.

[0846] Example 2

[0847] 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."

[0848] While conventional real estate information systems collect property information and accumulate data, they are unable to make proposals that reflect the user's emotional state, making improving user satisfaction a challenge. Furthermore, support for improvement proposals to property owners and for personal contract procedures is insufficient, and improvements are needed, particularly in the automatic generation and updating of contract documents. Furthermore, it is difficult for property searchers to identify the conditions they actually desire, resulting in many cases where users' potential needs are overlooked.

[0849] 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.

[0850] In this invention, the server includes: means for collecting property information from the Web and storing it in a database; means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market; means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions; means for collecting search conditions from property searchers and storing them in a database; means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions; means for proposing optimal properties to the searchers based on the identified desired conditions; means for matching property owners and property searchers and facilitating personal contracts; means for automatically generating necessary documents such as contracts using a generative AI model and providing input support to the user in a wizard format; means for collecting emotional data from the user's facial expressions and voice; means for analyzing the collected emotional data using an AI algorithm to detect the user's stress or anxiety; and means for generating and providing optimal feedback and proposals based on the emotional data. This enables optimal property proposals and feedback that take the user's emotional state into consideration, thereby providing a highly convenient service for both property owners and property searchers.

[0851] "Means of collecting property information from the Web" refers to technology that automatically collects data about properties from real estate sites on the Internet.

[0852] "Means of storing data in a database" refers to the technology of organizing collected data and storing it in a database system for centralized management.

[0853] "Artificial intelligence algorithms" are computational methods that include machine learning and deep learning to analyze large amounts of data and find patterns and trends.

[0854] "Means to identify the facilities and conditions desired by the market" refers to a technology that analyzes accumulated property information and identifies the facilities and conditions that searchers highly value in the current market.

[0855] The "means for generating and notifying optimal improvement proposals to property owners" is a technology for generating improvement proposals for owned properties based on identified market needs and notifying the property owners in an appropriate manner.

[0856] "Means for collecting search conditions of property searchers" refers to technology for collecting desired conditions entered by users searching for properties.

[0857] "Means for storing search condition data in a database" refers to a technology for organizing and saving the conditions entered by property searchers in a database.

[0858] "Means for identifying the potential desired conditions of property searchers" is a technology that analyzes collected search condition data and identifies conditions that the searcher does not express but actually desires.

[0859] "Means for proposing optimal properties to searchers" refers to technology that recommends the most suitable properties to property searchers based on the specified desired conditions.

[0860] "Means of matching property owners and property searchers and facilitating personal contracts" refers to technology that matches the conditions of property owners and searchers, finds the optimal combination, and promotes direct contracts.

[0861] "Means for automatically generating necessary documents such as contracts using a generative artificial intelligence model" refers to a technology that uses artificial intelligence technology to automatically create documents necessary for contracts and transactions.

[0862] "Means for providing input support to the user in a wizard format" refers to a form of user interface that guides the user through a procedure so that the user can easily input information.

[0863] "Means for collecting emotional data from the user's facial expressions and voice" refers to technology that uses a camera or microphone to obtain data that recognizes the user's emotions.

[0864] "Means for analyzing emotional data using an artificial intelligence algorithm" refers to technology for analyzing collected emotional data and identifying the user's psychological state.

[0865] "Means for generating and providing optimal feedback and suggestions based on emotional data" refers to technology that provides appropriate advice and information to users based on the analysis results.

[0866] This invention relates to a system that integrates an emotion engine into a real estate information system to provide new benefits to both property owners and property searchers. This system has functions such as collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents, as well as a function that recognizes the user's emotions and provides feedback based on them.

[0867] Hardware and Software Configuration

[0868] 1. Collection and accumulation of property information

[0869] The server periodically collects property information from the web and stores it in a database. The technology used is web scraping, specifically Python's BeautifulSoup or Scrapy. For example, property information in Shinjuku Ward is collected and detailed information such as location, price, floor plan, facilities, and age of the building is extracted. This information is stored in a database using MySQL or PostgreSQL. The organized data undergoes data cleansing before being stored in an accurate state.

[0870] 2. Analyzing data and generating optimal proposals

[0871] The server uses artificial intelligence algorithms to analyze the property information stored in the database. It analyzes indicators such as market demand trends, property popularity, and search frequency, and uses machine learning libraries such as TensorFlow and PyTorch to identify specific market needs. For example, it can identify properties that require air conditioning or Wi-Fi and send notifications to property owners suggesting the installation of air conditioning or Wi-Fi.

[0872] 3. Collecting and analyzing search criteria

[0873] When a user searches for a property, the device receives the entered search criteria (location, price range, floor plan, facilities, etc.) and sends them to the server. The received search criteria are saved in a database and managed along with the user's search history. This makes it possible to use an artificial intelligence algorithm to identify the user's potential desired conditions. Using Google's AutoML, it is possible to determine whether the searcher places importance on location. For example, if a user searches for a 1LDK property, the server analyzes the data and suggests properties within a 5-minute walk from the station.

[0874] 4. Emotion Recognition and Feedback

[0875] The device has the ability to collect emotional data from the user's facial expressions and voice. It uses libraries such as OpenCV and DeepFace to monitor the user's emotions in real time. The collected emotional data is analyzed using IBM Watson and Amazon Rekognition. This allows it to provide optimal feedback to reduce the stress and anxiety the user feels while searching for properties. For example, it can provide detailed information about properties the user is interested in and suggest similar properties.

[0876] 5. Facilitating personal contracts and supporting procedures

[0877] The server compares the conditions of property owners and property searchers to find the best match. To do this, it uses collaborative filtering and content-based filtering algorithms. It also has the ability to automatically generate contracts and other necessary documents using generative AI models. It uses generative AI technologies such as OpenAI's GPT-3 and Google's BERT to provide input support to users in a wizard format. For example, the user enters information according to the AI's guidance, and the server generates the final contract documents and provides them to both parties, completing the contract process.

[0878] Examples of prompt statements

[0879] "I'm looking for a 1LDK property in Shinjuku Ward that has Wi-Fi and air conditioning. Can you recommend any properties?"

[0880] "Generate the optimal prompt sentence to make it easier for users to search for properties near stations."

[0881] This system handles everything from collecting property information to analyzing it, making optimal proposals, contract procedures, and even emotion recognition, providing a highly convenient platform for both property owners and searchers.

[0882] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0883] The flow of this system's program processing

[0884] Step 1:

[0885] Gathering property information

[0886] The server periodically collects property information from the web. The input is the URL of the target real estate website. The output is a list of the collected property information. Specifically, it uses web scraping technology (for example, Python's BeautifulSoup or Scrapy) to collect information such as property location, price, floor plan, facilities, and age. It includes the operation of crawling websites and extracting data.

[0887] Step 2:

[0888] Accumulation of property information

[0889] The server stores the collected property information in a database. The input is the list of property information collected in step 1, and the output is the information stored in the database. Specifically, a database system such as MySQL or PostgreSQL is used to eliminate duplicates and cleanse the data. If necessary, the data format is also adjusted.

[0890] Step 3:

[0891] Market Data Analysis

[0892] The server uses AI algorithms to analyze the property information stored in the database. The input is the property information in the database, and the output is indicators related to market trends and demand. Specifically, TensorFlow and PyTorch are used to analyze demand trends, property popularity, search frequency, etc., and obtain analytical results.

[0893] Step 4:

[0894] Generating optimal proposals

[0895] The server generates the optimal improvement proposal for the property owner based on the analyzed market data. The input is the analysis result of the market data obtained in step 3, and the output is the improvement proposal to be notified. Specifically, the server creates proposals such as installing air conditioners or improving the Wi-Fi environment and sends them to the property owner via email or push notification.

[0896] Step 5:

[0897] Collecting search criteria

[0898] When a user searches for a property, the device sends the entered search criteria (location, price range, floor plan, facilities, etc.) to the server. The input is the search criteria entered by the user, and the output is the search query sent to the server. Specifically, using web frameworks such as JavaScript and PHP, the search criteria are received in real time and sent to the server.

[0899] Step 6:

[0900] Accumulation of search condition data

[0901] The server stores the received search criteria in a database. The input is the search criteria received in step 5, and the output is the search criteria data stored in the database. For example, the search criteria and history when a user searches for a 1LDK property are stored in the database.

[0902] Step 7:

[0903] Analyzing search data

[0904] The server analyzes the accumulated search criteria data using an AI algorithm to identify the potential desired conditions of property searchers. The input is the search criteria data in the database, and the output is the user's potential desired conditions. Specifically, using Google's AutoML or similar, the analysis is performed to identify the conditions that searchers actually prioritize.

[0905] Step 8:

[0906] Collecting Emotional Data

[0907] The device collects emotion data from the user's facial expressions and voice. The input is the user's real-time facial and voice data, and the output is the collected emotion data. Specifically, emotion data is acquired using libraries such as OpenCV and DeepFace. This includes the use of a camera and microphone to read the form of emotion.

[0908] Step 9:

[0909] Emotional Data Analysis

[0910] The server uses an AI algorithm to analyze the data sent from the emotion engine. The input is the emotion data collected in step 8, and the output is the detection result of the user's stress or anxiety. IBM Watson and Amazon Rekognition are used to analyze the collected emotion data and determine the user's psychological state.

[0911] Step 10:

[0912] Optimal Feedback Generation

[0913] The server generates optimal feedback and suggestions for the user based on the emotion data. The input is the analysis results obtained in step 9, and the output is feedback and property suggestions provided to the user. For example, if the user shows a strong interest in a particular property, detailed information about that property and a list of similar properties are generated and provided to the user.

[0914] Step 11:

[0915] Matching of personal contracts

[0916] The server compares the conditions of property owners and property searchers to find the best match. The input is property information and search condition data, and the output is a matched pair of property owners and searchers. Collaborative Filtering and Content-Based Filtering algorithms are used to calculate the suitability of the conditions and find the best match.

[0917] Step 12:

[0918] Automatic generation of contract documents

[0919] The server automatically generates contracts and necessary documents using a generative artificial intelligence model. The input is the matching results and necessary contract information, and the output is the automatically generated contract document. Models such as OpenAI's GPT-3 and Google's BERT are used to collect input information in a wizard format and create the final contract document.

[0920] In this way, the system can consistently provide property information collection, configuration, analysis, personalized suggestions, emotion recognition, contract support, and more, bringing maximum benefits to both property owners and users.

[0921] (Application example 2)

[0922] 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."

[0923] Conventional real estate information systems offer many functions, such as collecting and analyzing property information, proposing optimal properties, and generating contract documents. However, they lack feedback and suggestions that take user emotions into consideration. As a result, users can feel stressed during property searches and contract procedures, making it difficult to find the perfect property. Furthermore, while property viewing using virtual reality technology is becoming more common, there are still few systems that provide real-time emotional feedback. Therefore, there is a need for a system that improves the user experience and provides optimal property suggestions and feedback based on the user's emotions.

[0924] 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 collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searchers based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in a wizard format, means for collecting the user's facial expressions and voice via a smart device and analyzing their emotions in real time, and means for providing feedback and property proposals to the user based on the analyzed emotion data. This makes it possible to analyze the user's emotions in real time and provide feedback and property proposals based on the analyzed emotion data.

[0925] "Property information" refers to detailed information about a real estate property, such as its location, price, floor plan, facilities, and age.

[0926] A "database" is a system for organizing and storing collected information, and is a medium for storing property information, search condition data, etc.

[0927] An "AI algorithm" is a program that uses machine learning and data analysis techniques to analyze data, find patterns and trends, and make optimal suggestions and predictions.

[0928] A "Property Owner" is an individual or legal entity that owns a real estate property and wishes to rent or sell the property.

[0929] A "property searcher" is an individual or corporation searching for a real estate property.

[0930] An "optimal improvement proposal" is a proposal for improvement made to a property owner based on the facilities and conditions required by the market, and includes specific advice to increase the attractiveness of the property.

[0931] "Search criteria" refers to the conditions that property searchers enter when searching for a property, and refers to elements such as location, price range, floor plan, and facilities.

[0932] "Latent desired conditions" are elements or conditions that property searchers consider particularly important; they are hidden needs that are not explicitly entered but are identified through data analysis.

[0933] "Matching" is the process of matching the conditions of property owners and property searchers to find the optimal combination that meets the wishes of both parties.

[0934] A "personal contract" refers to a direct contract between a property owner and a property searcher.

[0935] "Generative AI" is a program that uses artificial intelligence technology to automatically generate necessary documents and contract documents based on information entered by the user.

[0936] A "wizard format" is a guided interface that allows a user to obtain a final output by inputting required information step by step.

[0937] "Smart device" refers to a device with internet connectivity, including smartphones, smart glasses, and head-mounted displays.

[0938] "Facial expressions and voice" refers to data for capturing the user's emotional state in real time, including facial expressions and what is being said.

[0939] "Analyzing emotions in real time" means instantly analyzing collected facial expressions and voice data to understand the user's emotional state.

[0940] "Feedback" refers to advice and information provided to users based on analyzed emotional data.

[0941] "Property suggestion" refers to recommending properties that are deemed appropriate based on the user's wishes and emotional state.

[0942] An embodiment of this invention is based on a real estate information system that integrates property information collection, data analysis, optimal proposal generation, search condition collection and analysis, emotion recognition and feedback, and interpersonal contract promotion and procedure support. This system allows users to tour properties using virtual reality technology using smart devices (smartphones, smart glasses, head-mounted displays, etc.), analyzes the user's emotions, and provides feedback in real time.

[0943] Program processing and technology used

[0944] The server first uses web scraping technology to collect property information from various real estate websites. The collected data is then stored in a database. Data duplication is eliminated and data cleansing is performed to ensure accurate data. This data is then analyzed using AI algorithms (e.g., machine learning models) to identify the facilities and conditions desired by the market.

[0945] When a user searches for a property, the device receives the search criteria entered and sends them to the server. The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of the property searcher. Based on this, the system suggests the most suitable property.

[0946] During a property viewing, the smart device collects the user's facial expressions and voice. This data is analyzed in real time using facial expression analysis software (e.g., Emotion API) and voice analysis software (e.g., Google Cloud Speech-to-Text + Sentiment Analysis API). Based on the emotion data, the server provides optimal feedback to the user and suggests detailed information about properties that interest them and similar properties.

[0947] When the contract is to proceed, the server uses a generative AI (e.g., OpenAI GPT-3) to automatically generate the contract documents and other necessary documents. It provides input support in the form of a wizard, allowing the user to easily follow the instructions to proceed with the contract procedure.

[0948] Examples of concrete examples and prompts

[0949] For example, if a user is using smart glasses to take a virtual tour and expresses interest in a property, if the user smiles or makes a positive comment, their facial expression and voice data will be analyzed and real-time feedback such as, "It seems you're interested in this property. More information is available here. Also, please check out similar properties."

[0950] Example prompt sentence:

[0951] Analyze the emotions users feel when viewing properties and generate feedback that provides details about properties that interest them and suggests similar properties.

[0952] Input data: User facial expressions (e.g., happy expressions), voice transcripts (e.g., positive comments)

[0953] Output data: Feedback based on user sentiment (e.g., "You seem interested in this property. More information here.")

[0954] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0955] Step 1:

[0956] The server uses web scraping technology to collect property information from various real estate websites. The input is the URL and HTML structure information of the real estate website, and the output is detailed information such as the property's location, price, layout, facilities, and age, which is stored in a database. Specifically, a script that runs periodically crawls through websites, extracts the necessary data, and stores it in the database.

[0957] Step 2:

[0958] The server stores the collected property information in a database. The input is property information obtained through web scraping, and the output is accurate property data after deduplication and data cleansing. Specifically, the database engine is used to organize, de-dupe, and cleanse the data.

[0959] Step 3:

[0960] The server uses AI algorithms to analyze the property information stored in the database. It uses organized property data as input and identifies the amenities and conditions the market demands as output. Specifically, it uses machine learning models to analyze the dataset and identify trends and popular amenities.

[0961] Step 4:

[0962] The server generates and notifies the property owner of optimal improvement proposals based on the identified market demand. The input is market demand data obtained by the AI ​​algorithm, and the output is specific improvement proposals (e.g., installing an air conditioner or improving the Wi-Fi environment) that are generated and notified to the property owner. Specifically, the improvement proposals are sent to the property owner's email or app via the notification system.

[0963] Step 5:

[0964] When a user searches for a property, the device receives the search criteria (e.g., location, price range, layout, facilities, etc.) entered and sends them to the server. The input uses the search criteria entered by the user into the app or website, and the output sends these search criteria to the server. Specifically, the device accepts search interactions through the device interface and sends the data to the server.

[0965] Step 6:

[0966] The server uses an AI algorithm to analyze the accumulated search condition data and identify the potential desired conditions of the property searcher. The input is the user's search history and condition data, and the output is the user's potential desired conditions. Specifically, it uses a machine learning model to analyze past data and discover the user's hidden needs.

[0967] Step 7:

[0968] The server then suggests properties that best suit the searcher based on the searcher's desired conditions. The input is the user's desired conditions as determined by the AI ​​algorithm, and the output is a list of properties that best suit the user. Specifically, the server searches the database for properties that match the user's desired conditions and displays them as a recommended list on the app or website.

[0969] Step 8:

[0970] The device collects the user's facial expressions and voice and transmits them to the server in real time. The input is facial expression and voice data acquired from the user's camera and microphone, and the output is transmission of these data to the server. Specifically, the device's camera and microphone capture data in real time and transmit it to the server using a communication protocol.

[0971] Step 9:

[0972] The server analyzes the transmitted emotional data using an AI algorithm to identify the user's emotional state. The input is the facial expression and voice data transmitted from the device, and the output is the user's emotional state (e.g., stress, anxiety, interest). Specific operations include analyzing the data using facial expression analysis software and voice analysis APIs.

[0973] Step 10:

[0974] The server provides feedback and property suggestions to the user based on the emotional data. It uses the analyzed emotional data as input and generates appropriate feedback and property suggestions as output, which it provides to the user. Specifically, it uses a feedback generation AI model to create feedback messages and property information according to the user's emotional state and sends them to the device.

[0975] Step 11:

[0976] The server matches property owners and property searchers and automatically generates the necessary documents to facilitate interpersonal contracts using generative AI. It uses the contract information of the property owner and property searcher as input, and generates complete contract documents as output, providing them to both parties. Specifically, it creates contract documents using a generative AI model based on the contract information obtained from the user, and provides input support through a wizard-style interface.

[0977] 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.

[0978] 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.

[0979] 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.

[0980] [Third embodiment]

[0981] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0982] 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.

[0983] 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).

[0984] 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.

[0985] 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.

[0986] 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).

[0987] 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.

[0988] 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.

[0989] 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.

[0990] 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.

[0991] 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.

[0992] 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."

[0993] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. The system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[0994] Collection and accumulation of property information

[0995] Gathering property information

[0996] The server periodically collects property information from the web and stores it in a database. This includes real estate portal sites and open data. Web scraping technology is used to extract the necessary data.

[0997] Accumulation of property information

[0998] The server organizes the collected data and stores it in a database, which includes detailed information such as property location, price, facilities, and floor plan.

[0999] Analyzing data and generating optimal proposals

[1000] Data analysis

[1001] The server analyzes the accumulated property information using AI algorithms, which identifies current market trends and the facilities and conditions that are in high demand.

[1002] Generating optimal proposals

[1003] Based on the identified market trends, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi. By notifying the property owner of these proposals, the property owner can increase the turnover rate.

[1004] Specific examples

[1005] The server performs web scraping to collect property information in Shinjuku Ward. The collected data is analyzed to determine that many searchers are looking for air conditioning and Wi-Fi. Based on this, the server makes recommendations to specific property owners about installing air conditioning and Wi-Fi.

[1006] Collecting and analyzing search criteria

[1007] Collecting search criteria

[1008] When a user searches for a property, the terminal sends the entered search criteria, including location, price range, floor plan, and facilities, to the server.

[1009] Data accumulation

[1010] The server stores the received search conditions in a database.

[1011] Data analysis

[1012] The server uses an AI algorithm to analyze the accumulated search criteria data, thereby identifying potential desired conditions that have not yet been suggested by the property searcher.

[1013] Specific examples

[1014] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to the server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[1015] Facilitating personal contracts and providing procedural support

[1016] matching

[1017] The server compares the conditions of property owners and property searchers and matches them with the optimal combination, making it easier for both parties to enter into a direct contract.

[1018] Automatic generation of contract documents

[1019] The server uses generation AI to automatically generate contract documents and other necessary documents, and a wizard format allows users to enter the necessary information, simplifying the contract process.

[1020] Specific examples

[1021] The server matches property owners with property searchers. It uses generation AI to automatically create contract documents and provide them to users. Users input information according to the AI's guidance, and the server supports the creation of final documents and the conclusion of the contract.

[1022] This solves the problems of the traditional real estate market, allowing property owners to increase turnover and property searchers to easily find properties based on their potential needs. Furthermore, private contracts reduce fees and simplify legal procedures.

[1023] The processing flow will be explained below.

[1024] Step 1:

[1025] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[1026] Step 2:

[1027] The server stores the collected property information in a database, eliminates duplicate data, and cleanses the data as needed.

[1028] Step 3:

[1029] The server uses AI algorithms to analyze the property information stored in the database, analysing market demand trends, property popularity, search frequency, and other factors.

[1030] Step 4:

[1031] Based on the analysis, the server identifies the amenities and conditions the market demands. For example, it may discover that many searchers are looking for air conditioning and Wi-Fi.

[1032] Step 5:

[1033] The server generates optimal improvement proposals for each property based on the identified market needs, for example, recommending the installation of air conditioners for a specific property.

[1034] Step 6:

[1035] The server notifies the property owner of the generated improvement proposals, possibly via email or push notification.

[1036] Step 7:

[1037] When a user searches for properties, the terminal receives the search criteria entered by the user (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[1038] Step 8:

[1039] The server stores the received search criteria in a database, and also stores each user's search history.

[1040] Step 9:

[1041] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the searcher's potential desired conditions. For example, it may discover that the searcher has strict requirements regarding location.

[1042] Step 10:

[1043] The server then proposes optimal properties to the searcher based on the identified latent conditions. The proposals take into account the user's initial conditions as well as their latent conditions.

[1044] Step 11:

[1045] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[1046] Step 12:

[1047] The server uses generative AI to automatically generate the necessary contract documents, which include the contract details and legal requirements.

[1048] Step 13:

[1049] The user receives input support in a wizard format and enters the necessary information to proceed with the contract procedure. The terminal supports this process.

[1050] Step 14:

[1051] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[1052] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, and completing contract procedures, providing a convenient platform for both property owners and searchers.

[1053] Example 1

[1054] 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."

[1055] Existing real estate information systems have difficulty efficiently collecting and analyzing large amounts of property information. They also lack the means to quickly match the requirements of property owners and property searchers and automatically generate contract documents. This results in a lack of efficiency and accuracy in property searches and transactions, and presents challenges in proposing optimal properties and simplifying contract procedures.

[1056] 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.

[1057] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in a wizard format, means for automatically collecting and storing property information and search conditions on a regular basis, and means for sending notifications to the user in an optimal format depending on the device used. This enables efficient and accurate property searches and transactions.

[1058] "Property information" refers to detailed data about the property's location, price, facilities, floor plan, etc.

[1059] A "database" is a data structure for storing and managing collected property information and search conditions.

[1060] An "AI algorithm" is a computational method that uses machine learning and artificial intelligence to analyze data and identify patterns and trends.

[1061] "Property Owner" means an individual or legal entity that owns a property.

[1062] A "property searcher" is an individual or entity searching for a property.

[1063] "Improvement proposals" are specific advice provided to property owners to increase the value of their properties and improve turnover.

[1064] "Search conditions" are conditions such as location, price range, layout, and facilities that a property searcher inputs when searching for a property.

[1065] "Latent desired conditions" are conditions that property searchers do not explicitly enter but actually consider to be important.

[1066] "Matching" is the process of matching the conditions of the property owner with the conditions of the property searcher to find the optimal combination.

[1067] A "personal contract" is a transaction or contract made directly between a property owner and a property searcher.

[1068] "Generative AI" is an artificial intelligence technology for automatically generating text and documents.

[1069] "Contract documents" are documents that formally record the agreements related to a property transaction.

[1070] A "wizard format" is a guided input method that allows a user to input information step by step.

[1071] A "notification" is information or an alert sent from the system to a user.

[1072] A "terminal" is a device that a user uses to access the property information system. For example, a smartphone or a PC would be an example.

[1073] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. This system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[1074] Collection and accumulation of property information

[1075] Gathering property information

[1076] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python libraries such as BeautifulSoup and Scrapy.

[1077] Examples:

[1078] The server starts a scheduled job every day at 2:00 AM to extract property information from the specified URL, and the extracted data is temporarily stored in memory.

[1079] Accumulation of property information

[1080] The server organizes the collected property information and stores it in a database using MySQL, PostgreSQL, or similar.

[1081] Examples:

[1082] The server stores the property information stored in memory in a database. The database table contains fields such as property location, price, amenities, and layout. It checks for duplicate data and inserts only new data.

[1083] Analyzing data and generating optimal proposals

[1084] Data analysis

[1085] The server analyzes the accumulated property information using AI algorithms (e.g., the Scikit-learn library).

[1086] Examples:

[1087] The server feeds the accumulated data into a data analysis pipeline, performing clustering and regression analysis to identify market trends and equipment in high demand.

[1088] Generating optimal proposals

[1089] The server generates optimal improvement proposals for property owners based on the analysis results, using a generative AI model (e.g., GPT-4).

[1090] Examples:

[1091] The server inputs market trends and demand data into the AI ​​model and generates improvement suggestions, which are then sent to the property owner, such as suggesting the installation of air conditioners or Wi-Fi.

[1092] Collecting and analyzing search criteria

[1093] Collecting search criteria

[1094] When a user searches for a property, the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[1095] Examples:

[1096] The user launches the property search app on their smartphone and enters search criteria. The device sends the entered search criteria in JSON format to the server.

[1097] Search condition data accumulation

[1098] The server stores the received search conditions in a database.

[1099] Examples:

[1100] The server stores the search condition data in a database.

[1101] Data analysis

[1102] The server uses an AI algorithm to analyze the accumulated search criteria data to identify the potential desired conditions of property searchers.

[1103] Examples:

[1104] The server analyzes the search criteria data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[1105] Facilitating personal contracts and providing procedural support

[1106] matching

[1107] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[1108] Examples:

[1109] The server performs a filtering process to compare the property information with the search criteria and notifies both parties of the matching results.

[1110] Automatic generation of contract documents

[1111] The server uses a generative AI model (e.g., GPT-4) to automatically generate contracts and other necessary documents.

[1112] Examples:

[1113] The server inputs the contract terms into the AI ​​model and sends the generated contract documents to the user, who then enters information in a wizard format to complete the process.

[1114] Specific examples of prompts for the generative AI model to use

[1115] "Write a program to collect information on 1LDK apartments in Shinjuku Ward, organize it, and store it in a database. Next, implement a system that analyzes market trends based on the property information and generates recommendations for air conditioning and Wi-Fi."

[1116] By using this prompt sentence, it is possible to generate a program to implement the above function using a generative AI model.

[1117] By referring to these procedures and examples in practicing the present invention, property searches and transactions can be carried out efficiently and accurately.

[1118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1119] Step 1: Gather property information

[1120] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python's BeautifulSoup and Scrapy libraries.

[1121] Input: URL of real estate portal site

[1122] Data processing: Extract specific elements (location, price, facilities, floor plan) from HTML pages.

[1123] Output: Collected property information is temporarily stored in memory.

[1124] Specific operation: The server starts a scheduled job at 2:00 AM every day, extracts property information from the specified URL, and temporarily stores it in memory.

[1125] Step 2: Accumulating property information in a database

[1126] The server organizes the collected property information and stores it in a database using MySQL or PostgreSQL.

[1127] Input: Property information in memory

[1128] Data processing: Check for duplicate data and organize it.

[1129] Output: Store the organized property information in a database.

[1130] Specific operation: The server checks the property information stored in memory for duplicate data and then stores it in the database.

[1131] Step 3: Data analysis

[1132] The server analyzes the accumulated property information using an AI algorithm (Scikit-learn library).

[1133] Input: Property information stored in the database

[1134] Data calculations: Perform clustering and regression analysis.

[1135] Output: Identify market trends and equipment / conditions with high demand.

[1136] How it works: The server feeds the data stored in the database into a data analysis pipeline, where AI algorithms are used to identify market trends and equipment in high demand.

[1137] Step 4: Generate optimal proposals

[1138] The server generates and notifies the property owner of optimal improvement proposals based on the analysis results, using a generative AI model (GPT-4).

[1139] Inputs: Market trends and demand data

[1140] Data processing: Generate specific improvement suggestions based on the AI ​​model.

[1141] Output: Send the improvement suggestions in the form of a notice to the property owner.

[1142] How it works: The server inputs market trends and demand data into the AI ​​model, and then notifies the property owner of the generated proposals for installing air conditioners and improving Wi-Fi environments.

[1143] Step 5: Collecting search criteria

[1144] The user searches for properties, and the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[1145] Input: Search criteria entered by the user

[1146] Data processing: Convert search criteria into JSON format.

[1147] Output: The search criteria is sent to the server.

[1148] Specific operation: The user launches a property search app on their smartphone, enters search criteria, and the device sends the search criteria to the server in JSON format.

[1149] Step 6: Storing search criteria in the database

[1150] The server stores the received search conditions in a database.

[1151] Input: Search criteria sent to the server

[1152] Data processing: Format the search criteria to store them in the database.

[1153] Output: The search criteria are stored in the database.

[1154] Specific operation: The server stores the received search criteria in a database in an appropriate format.

[1155] Step 7: Identify potential requirements through data analysis

[1156] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers.

[1157] Input: Accumulated search criteria data

[1158] Data crunching: Using AI algorithms to analyze data and identify potential desired conditions.

[1159] Output: Obtain the results of the identified potential desired conditions.

[1160] Specific operation: The server inputs the search criteria data into an AI algorithm and determines that the user is actually looking for a property close to the station.

[1161] Step 8: Proposal of the best property

[1162] Based on the analysis results, the server suggests the most suitable property to the user.

[1163] Input: Identified potential desires

[1164] Data processing: Generate specific property proposals.

[1165] Output: Send the best property suggestions to the device.

[1166] Specific operation: The server sends the user a notification recommending properties within a five-minute walk from the station.

[1167] Step 9: Matching property information with search criteria

[1168] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[1169] Input: Property information and search conditions

[1170] Data operations: Perform filtering and condition matching operations.

[1171] Output: Get the matching results.

[1172] Specific operation: The server compares the property information with the search criteria and notifies both parties of matching combinations.

[1173] Step 10: Automatic generation of contract documents

[1174] The server uses a generative AI model (GPT-4) to automatically generate contracts and necessary documents.

[1175] Input: Terms and Conditions

[1176] Data processing: Generate contract documents using AI models.

[1177] Output: Send the generated contract document to the user.

[1178] Specific operation: The server inputs the contract terms into the AI ​​model and sends the generated document to the user. The user enters information in a wizard format and completes the contract procedure.

[1179] (Application example 1)

[1180] 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."

[1181] Conventional real estate information systems have comprehensive functionality for collecting and analyzing property information, but they lack sufficient evaluation and proposal capabilities for property security information, making it difficult to effectively improve users' confidence in the safety of properties. Furthermore, because security information is not shared or evaluated among users, it is difficult to make the most of the information held by each user. This creates an issue in which the benefits to both property owners and property searchers are not fully realized.

[1182] 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.

[1183] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to users in a wizard format, means for collecting property security information, analyzing it using an AI algorithm, and proposing highly secure properties, and means for users to share and evaluate security information with each other, thereby improving users' confidence in the safety of properties.

[1184] "Property information" refers to information about the property, such as its location, price, layout, facilities, and security.

[1185] A "database" is a system for storing and managing collected property information and search conditions.

[1186] An "AI algorithm" is a program that analyzes property information and search criteria data based on machine learning and data analysis.

[1187] "Property Owner" means the person or entity that owns the property and provides the information.

[1188] A "Property Searcher" is a person or entity searching for a property.

[1189] "Improvement proposals" are recommendations for adding amenities or changing conditions proposed to increase the market value of the property.

[1190] "Search conditions" are the conditions and wishes specified by a property searcher when searching for a property.

[1191] "Potential desired conditions" are desired conditions that are not explicitly specified by the property searcher, but are likely to be indicated as a result of the AI ​​algorithm's analysis.

[1192] "Matching" is the process of matching the conditions of property owners and property searchers to find the optimal combination.

[1193] A "personal contract" is a direct contract between a property owner and a property searcher.

[1194] "Generative AI" is an AI technology that automatically generates contracts and other necessary documents.

[1195] A "wizard format" is a guided interface designed to guide the user through entering required information.

[1196] "Security information" refers to information about the property's security status and the security equipment installed.

[1197] "Sharing and evaluation" is a process in which users provide each other with information and then evaluate it based on that information.

[1198] MODE FOR CARRYING OUT THE INVENTION

[1199] The present invention is a system that collects, analyzes, and proposes real estate information, providing convenience to property owners and property searchers. Specifically, the system is implemented with the following configuration.

[1200] Collection and accumulation of property information

[1201] The server periodically collects property information from the web and stores it in a database. This involves using web scraping technology to extract the necessary data from real estate portal sites and open data. The software used is a Python program and the BeautifulSoup library. As a specific example, real estate information related to Shinjuku Ward is scraped, and data such as location, price, and facilities is stored in the database.

[1202] Analyzing data and generating optimal proposals

[1203] The server analyzes the collected property information using AI algorithms. This identifies market trends and facilities and conditions that are in high demand, and generates and notifies property owners of optimal improvement proposals. This process uses machine learning algorithms. AI tools used include TensorFlow and scikit-learn. For example, if it identifies that many searchers are looking for air conditioning and Wi-Fi, it can use this information to suggest installing air conditioning and improving Wi-Fi to specific property owners.

[1204] Collecting and analyzing search criteria

[1205] When a property searcher searches for a property on their smartphone, the device sends the search criteria entered by the user to a server. The collected data is stored in a database and analyzed using an AI algorithm. For example, if a user searches for a 1LDK property, the server will determine through analysis that the user is looking for a property close to the station and suggest properties within a 5-minute walk from the station.

[1206] Facilitating personal contracts and providing procedural support

[1207] The server compares the conditions of the property owner and the property searcher and matches the optimal combination. It also uses generation AI to automatically generate contract documents and other necessary documents, and prompts the user to enter the necessary information in a wizard format. This generation AI uses OpenAI's API. An example of a specific prompt sentence that can be entered is as follows:

[1208] Property location: Shinjuku Ward

[1209] Price: 30 million yen

[1210] Security: Near station, air conditioning, Wi-Fi

[1211] Generate the contract.

[1212] Analysis, sharing and evaluation of security information

[1213] Furthermore, the server collects property security information and analyzes it using an AI algorithm to suggest highly secure properties to searchers. The system also has a function that allows users to share and rate security information with each other, which can improve the reliability of property security.

[1214] This system makes it easier for property owners to increase turnover and for property searchers to find the perfect property that meets their needs. In addition, by taking security information into consideration when making suggestions, it increases users' sense of security.

[1215] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1216] Program processing flow

[1217] Step 1: Collecting and accumulating property information

[1218] The server collects property information from the web and stores it in a database.

[1219] Input: URL of real estate portal site or open data

[1220] Data processing: Using web scraping technology, property information such as location, price, floor plan, and facilities is extracted from HTML pages.

[1221] Output: Store the collected property information in a database as structured data.

[1222] What it does: The server uses Python and the BeautifulSoup library to periodically access the specified URL, extract the necessary data, and store it in the database.

[1223] Step 2: Analyze the data and generate optimal proposals

[1224] The server analyzes the collected property information using AI algorithms and generates and notifies the property owner of optimal improvement proposals.

[1225] Input: Property information stored in the database

[1226] Data crunching: Using AI algorithms, we analyze property information to identify market trends and in-demand amenities and conditions.

[1227] Output: A list of improvement suggestions to send to the property owner

[1228] How it works: The server uses TensorFlow and scikit-learn to analyze property information in the database, identify high-demand facilities and conditions, and generate recommendations. The identified proposals are then notified to the property owner.

[1229] Step 3: Collecting and analyzing search criteria

[1230] The terminal collects the search conditions of property searchers and sends them to the server, which then analyzes the accumulated search condition data to identify potential desired conditions.

[1231] Input: Search criteria entered by the property searcher on their smartphone

[1232] Data processing: The terminal transfers the entered search criteria to the server.

[1233] Output: Potential desired conditions identified based on the analysis

[1234] How it works: Property searchers enter search criteria into a smartphone app, and the device sends the information to a server, which uses AI algorithms to analyze the data, identify potential preferences, and generate a list of search candidates.

[1235] Step 4: Facilitating personal contracts and providing procedural support

[1236] The server compares the conditions of property owners and property searchers to find the optimal combination. It also uses generation AI to automatically generate contract documents and provides input support to users in a wizard format.

[1237] Input: Property owner and property searcher criteria

[1238] Data calculation: Condition matching and generation Contract document generation using AI

[1239] Output: Matching results and automatically generated contract documents

[1240] Specific operation: The server matches the conditions of the property owner and the property searcher to identify the optimal combination. Then, it automatically generates the contract documents using the OpenAI API and provides input support to the user in a wizard format. The following is an example of a prompt sentence:

[1241] Property location: Shinjuku Ward

[1242] Price: 30 million yen

[1243] Security: Near station, air conditioning, Wi-Fi

[1244] Generate the contract.

[1245] Step 5: Analyze, share and evaluate security information

[1246] The server collects property security information, analyzes it with an AI algorithm, and recommends properties with high safety. It also provides a function for users to share and rate security information with each other.

[1247] Input: Property security information

[1248] Data Computing: Analyzing Security Information with AI Algorithms

[1249] Output: A list of safe property suggestions and security ratings

[1250] Specific operation: The server analyzes the collected security information using an AI algorithm (e.g., TensorFlow) and recommends highly secure properties to users. It also provides a mechanism for users to share and mutually evaluate security information, thereby increasing confidence in the safety of properties.

[1251] As described above, by performing specific processing at each step, it is possible to provide an optimal real estate information system for property owners and property searchers.

[1252] 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.

[1253] This invention relates to a system that provides new benefits to both property owners and property searchers by incorporating an emotion engine into a real estate information system. In addition to functions such as collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents, this system also includes a function that recognizes the user's emotions and provides feedback based on them.

[1254] Collection and accumulation of property information

[1255] Gathering property information

[1256] The server periodically collects property information from the web and stores it in a database. Web scraping technology is used to extract detailed information such as the property's location, price, layout, facilities, and age.

[1257] Accumulation of property information

[1258] The server organizes the collected property information and stores it in a database. Data duplication is eliminated and data cleansing is performed to maintain accurate data.

[1259] Analyzing data and generating optimal proposals

[1260] Data analysis

[1261] The server uses AI algorithms to analyze the property information stored in the database, analyzing indicators such as market demand trends, property popularity, and search frequency to identify specific market needs.

[1262] Generating optimal proposals

[1263] The server generates optimal improvement proposals based on market needs and notifies the property owner, including proposals such as installing air conditioners and improving Wi-Fi.

[1264] Specific examples

[1265] The server collects property information in Shinjuku Ward and identifies that many searchers are looking for air conditioning and Wi-Fi. Based on this, it makes proposals to specific property owners for the installation of air conditioning and Wi-Fi.

[1266] Collecting and analyzing search criteria

[1267] Collecting search criteria

[1268] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[1269] Data accumulation

[1270] The server stores the received search criteria in a database, along with the user's search history.

[1271] Data analysis

[1272] The server uses an AI algorithm to analyze the accumulated search condition data and identify the potential desired conditions of property searchers, for example, determining that the searcher places importance on location.

[1273] Specific examples

[1274] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to a server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[1275] Emotion Recognition and Feedback

[1276] Emotion engine integration

[1277] The device is equipped with a function to collect emotional data from the user's facial expressions and voice, allowing for real-time monitoring of the user's emotions as they search for properties and complete contract procedures.

[1278] Emotional Data Analysis

[1279] The server uses AI algorithms to analyze the data sent from the emotion engine, detects the user's stress or anxiety, and provides support and feedback at the appropriate time.

[1280] Optimal Feedback Generation

[1281] The server generates feedback and suggestions that are best suited to the user's situation based on the emotion data. If the user is interested in a particular property, it will provide detailed information about that property and suggest similar properties.

[1282] Specific examples

[1283] If a user is feeling stressed during a property search, the device will detect this emotion and the server will provide friendly feedback to reduce anxiety and expand options by suggesting other properties similar to the one they expressed interest in.

[1284] Facilitating personal contracts and providing procedural support

[1285] matching

[1286] The server compares the conditions of property owners and property searchers to find the best match, making it easier for both parties to enter into a direct contract.

[1287] Automatic generation of contract documents

[1288] The server uses generation AI to automatically generate contract documents and other necessary documents, and provides input support in the form of a wizard, allowing users to easily proceed with the contract procedure.

[1289] Specific examples

[1290] The system matches users with property owners and automatically creates contract documents using generation AI. The user enters information according to the AI's guidance, and the server generates the final contract documents and provides them to both parties, completing the contract procedure.

[1291] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, completing contract procedures, and recognizing emotions, providing a highly convenient platform for both property owners and searchers.

[1292] The processing flow will be explained below.

[1293] Step 1:

[1294] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[1295] Step 2:

[1296] The server stores the collected property information in a database, which also includes eliminating duplicate data and cleaning inaccurate information.

[1297] Step 3:

[1298] The server uses AI algorithms to analyze property information stored in the database, identifying current market trends and the facilities and conditions that are in high demand.

[1299] Step 4:

[1300] Based on the analysis results, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi.

[1301] Step 5:

[1302] The server notifies the property owner of the generated improvement proposals via email, push notifications, or other means.

[1303] Step 6:

[1304] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[1305] Step 7:

[1306] The server stores the received search conditions in a database. Each user's search history is also saved, enabling consistent data utilization.

[1307] Step 8:

[1308] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers, such as determining whether users place importance on location information.

[1309] Step 9:

[1310] The server then proposes the most suitable property to the user based on the identified latent conditions, taking into account the user's initial conditions as well as their latent conditions.

[1311] Step 10:

[1312] The device uses an emotion engine to analyze the user's facial expressions and voice while searching for properties, collecting emotional data in real time, thereby monitoring the stress and anxiety the user is feeling.

[1313] Step 11:

[1314] The server uses an AI algorithm to analyze the emotional data sent from the emotion engine and provides feedback according to the user's situation, such as changing the UI to help them relax or providing more information.

[1315] Step 12:

[1316] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[1317] Step 13:

[1318] The server uses generation AI to automatically generate the necessary contract documents, which include contract details and legal requirements, and provides input support to the user in a wizard format.

[1319] Step 14:

[1320] The user is guided through a wizard-style input process to input the necessary information into the system, and through this process the contract documents are completed.

[1321] Step 15:

[1322] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[1323] This allows the system to efficiently carry out a series of processes, such as collecting property information, accumulating and analyzing data, generating optimal proposals, collecting and analyzing search conditions, recognizing emotions, and completing contract procedures, thereby improving the user experience.

[1324] Example 2

[1325] 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."

[1326] While conventional real estate information systems collect property information and accumulate data, they are unable to make proposals that reflect the user's emotional state, making improving user satisfaction a challenge. Furthermore, support for improvement proposals to property owners and for personal contract procedures is insufficient, and improvements are needed, particularly in the automatic generation and updating of contract documents. Furthermore, it is difficult for property searchers to identify the conditions they actually desire, resulting in many cases where users' potential needs are overlooked.

[1327] 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.

[1328] In this invention, the server includes: means for collecting property information from the Web and storing it in a database; means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market; means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions; means for collecting search conditions from property searchers and storing them in a database; means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions; means for proposing optimal properties to the searchers based on the identified desired conditions; means for matching property owners and property searchers and facilitating personal contracts; means for automatically generating necessary documents such as contracts using a generative AI model and providing input support to the user in a wizard format; means for collecting emotional data from the user's facial expressions and voice; means for analyzing the collected emotional data using an AI algorithm to detect the user's stress or anxiety; and means for generating and providing optimal feedback and proposals based on the emotional data. This enables optimal property proposals and feedback that take the user's emotional state into consideration, thereby providing a highly convenient service for both property owners and property searchers.

[1329] "Means of collecting property information from the Web" refers to technology that automatically collects data about properties from real estate sites on the Internet.

[1330] "Means of storing data in a database" refers to the technology of organizing collected data and storing it in a database system for centralized management.

[1331] "Artificial intelligence algorithms" are computational methods that include machine learning and deep learning to analyze large amounts of data and find patterns and trends.

[1332] "Means to identify the facilities and conditions desired by the market" refers to a technology that analyzes accumulated property information and identifies the facilities and conditions that searchers highly value in the current market.

[1333] The "means for generating and notifying optimal improvement proposals to property owners" is a technology for generating improvement proposals for owned properties based on identified market needs and notifying the property owners in an appropriate manner.

[1334] "Means for collecting search conditions of property searchers" refers to technology for collecting desired conditions entered by users searching for properties.

[1335] "Means for storing search condition data in a database" refers to a technology for organizing and saving the conditions entered by property searchers in a database.

[1336] "Means for identifying the potential desired conditions of property searchers" is a technology that analyzes collected search condition data and identifies conditions that the searcher does not express but actually desires.

[1337] "Means for proposing optimal properties to searchers" refers to technology that recommends the most suitable properties to property searchers based on the specified desired conditions.

[1338] "Means of matching property owners and property searchers and facilitating personal contracts" refers to technology that matches the conditions of property owners and searchers, finds the optimal combination, and promotes direct contracts.

[1339] "Means for automatically generating necessary documents such as contracts using a generative artificial intelligence model" refers to a technology that uses artificial intelligence technology to automatically create documents necessary for contracts and transactions.

[1340] "Means for providing input support to the user in a wizard format" refers to a form of user interface that guides the user through a procedure so that the user can easily input information.

[1341] "Means for collecting emotional data from the user's facial expressions and voice" refers to technology that uses a camera or microphone to obtain data that recognizes the user's emotions.

[1342] "Means for analyzing emotional data using an artificial intelligence algorithm" refers to technology for analyzing collected emotional data and identifying the user's psychological state.

[1343] "Means for generating and providing optimal feedback and suggestions based on emotional data" refers to technology that provides appropriate advice and information to users based on the analysis results.

[1344] This invention relates to a system that integrates an emotion engine into a real estate information system to provide new benefits to both property owners and property searchers. This system has functions such as collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents, as well as a function that recognizes the user's emotions and provides feedback based on them.

[1345] Hardware and Software Configuration

[1346] 1. Collection and accumulation of property information

[1347] The server periodically collects property information from the web and stores it in a database. The technology used is web scraping, specifically Python's BeautifulSoup or Scrapy. For example, property information in Shinjuku Ward is collected and detailed information such as location, price, floor plan, facilities, and age of the building is extracted. This information is stored in a database using MySQL or PostgreSQL. The organized data undergoes data cleansing before being stored in an accurate state.

[1348] 2. Analyzing data and generating optimal proposals

[1349] The server uses artificial intelligence algorithms to analyze the property information stored in the database. It analyzes indicators such as market demand trends, property popularity, and search frequency, and uses machine learning libraries such as TensorFlow and PyTorch to identify specific market needs. For example, it can identify properties that require air conditioning or Wi-Fi and send notifications to property owners suggesting the installation of air conditioning or Wi-Fi.

[1350] 3. Collecting and analyzing search criteria

[1351] When a user searches for a property, the device receives the entered search criteria (location, price range, floor plan, facilities, etc.) and sends them to the server. The received search criteria are saved in a database and managed along with the user's search history. This makes it possible to use an artificial intelligence algorithm to identify the user's potential desired conditions. Using Google's AutoML, it is possible to determine whether the searcher places importance on location. For example, if a user searches for a 1LDK property, the server analyzes the data and suggests properties within a 5-minute walk from the station.

[1352] 4. Emotion Recognition and Feedback

[1353] The device has the ability to collect emotional data from the user's facial expressions and voice. It uses libraries such as OpenCV and DeepFace to monitor the user's emotions in real time. The collected emotional data is analyzed using IBM Watson and Amazon Rekognition. This allows it to provide optimal feedback to reduce the stress and anxiety the user feels while searching for properties. For example, it can provide detailed information about properties the user is interested in and suggest similar properties.

[1354] 5. Facilitating personal contracts and supporting procedures

[1355] The server compares the conditions of property owners and property searchers to find the best match. To do this, it uses collaborative filtering and content-based filtering algorithms. It also has the ability to automatically generate contracts and other necessary documents using generative AI models. It uses generative AI technologies such as OpenAI's GPT-3 and Google's BERT to provide input support to users in a wizard format. For example, the user enters information according to the AI's guidance, and the server generates the final contract documents and provides them to both parties, completing the contract process.

[1356] Examples of prompt statements

[1357] "I'm looking for a 1LDK property in Shinjuku Ward that has Wi-Fi and air conditioning. Can you recommend any properties?"

[1358] "Generate the optimal prompt sentence to make it easier for users to search for properties near stations."

[1359] This system handles everything from collecting property information to analyzing it, making optimal proposals, contract procedures, and even emotion recognition, providing a highly convenient platform for both property owners and searchers.

[1360] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1361] The flow of this system's program processing

[1362] Step 1:

[1363] Gathering property information

[1364] The server periodically collects property information from the web. The input is the URL of the target real estate website. The output is a list of the collected property information. Specifically, it uses web scraping technology (for example, Python's BeautifulSoup or Scrapy) to collect information such as property location, price, floor plan, facilities, and age. It includes the operation of crawling websites and extracting data.

[1365] Step 2:

[1366] Accumulation of property information

[1367] The server stores the collected property information in a database. The input is the list of property information collected in step 1, and the output is the information stored in the database. Specifically, a database system such as MySQL or PostgreSQL is used to eliminate duplicates and cleanse the data. If necessary, the data format is also adjusted.

[1368] Step 3:

[1369] Market Data Analysis

[1370] The server uses AI algorithms to analyze the property information stored in the database. The input is the property information in the database, and the output is indicators related to market trends and demand. Specifically, TensorFlow and PyTorch are used to analyze demand trends, property popularity, search frequency, etc., and obtain analytical results.

[1371] Step 4:

[1372] Generating optimal proposals

[1373] The server generates the optimal improvement proposal for the property owner based on the analyzed market data. The input is the analysis result of the market data obtained in step 3, and the output is the improvement proposal to be notified. Specifically, the server creates proposals such as installing air conditioners or improving the Wi-Fi environment and sends them to the property owner via email or push notification.

[1374] Step 5:

[1375] Collecting search criteria

[1376] When a user searches for a property, the device sends the entered search criteria (location, price range, floor plan, facilities, etc.) to the server. The input is the search criteria entered by the user, and the output is the search query sent to the server. Specifically, using web frameworks such as JavaScript and PHP, the search criteria are received in real time and sent to the server.

[1377] Step 6:

[1378] Accumulation of search condition data

[1379] The server stores the received search criteria in a database. The input is the search criteria received in step 5, and the output is the search criteria data stored in the database. For example, the search criteria and history when a user searches for a 1LDK property are stored in the database.

[1380] Step 7:

[1381] Analyzing search data

[1382] The server analyzes the accumulated search criteria data using an AI algorithm to identify the potential desired conditions of property searchers. The input is the search criteria data in the database, and the output is the user's potential desired conditions. Specifically, using Google's AutoML or similar, the analysis is performed to identify the conditions that searchers actually prioritize.

[1383] Step 8:

[1384] Collecting Emotional Data

[1385] The device collects emotion data from the user's facial expressions and voice. The input is the user's real-time facial and voice data, and the output is the collected emotion data. Specifically, emotion data is acquired using libraries such as OpenCV and DeepFace. This includes the use of a camera and microphone to read the form of emotion.

[1386] Step 9:

[1387] Emotional Data Analysis

[1388] The server uses an AI algorithm to analyze the data sent from the emotion engine. The input is the emotion data collected in step 8, and the output is the detection result of the user's stress or anxiety. IBM Watson and Amazon Rekognition are used to analyze the collected emotion data and determine the user's psychological state.

[1389] Step 10:

[1390] Optimal Feedback Generation

[1391] The server generates optimal feedback and suggestions for the user based on the emotion data. The input is the analysis results obtained in step 9, and the output is feedback and property suggestions provided to the user. For example, if the user shows a strong interest in a particular property, detailed information about that property and a list of similar properties are generated and provided to the user.

[1392] Step 11:

[1393] Matching of personal contracts

[1394] The server compares the conditions of property owners and property searchers to find the best match. The input is property information and search condition data, and the output is a matched pair of property owners and searchers. Collaborative Filtering and Content-Based Filtering algorithms are used to calculate the suitability of the conditions and find the best match.

[1395] Step 12:

[1396] Automatic generation of contract documents

[1397] The server automatically generates contracts and necessary documents using a generative artificial intelligence model. The input is the matching results and necessary contract information, and the output is the automatically generated contract document. Models such as OpenAI's GPT-3 and Google's BERT are used to collect input information in a wizard format and create the final contract document.

[1398] In this way, the system can consistently provide property information collection, configuration, analysis, personalized suggestions, emotion recognition, contract support, and more, bringing maximum benefits to both property owners and users.

[1399] (Application example 2)

[1400] 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."

[1401] Conventional real estate information systems offer many functions, such as collecting and analyzing property information, proposing optimal properties, and generating contract documents. However, they lack feedback and suggestions that take user emotions into consideration. As a result, users can feel stressed during property searches and contract procedures, making it difficult to find the perfect property. Furthermore, while property viewing using virtual reality technology is becoming more common, there are still few systems that provide real-time emotional feedback. Therefore, there is a need for a system that improves the user experience and provides optimal property suggestions and feedback based on the user's emotions.

[1402] 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 collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searchers based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in a wizard format, means for collecting the user's facial expressions and voice via a smart device and analyzing their emotions in real time, and means for providing feedback and property proposals to the user based on the analyzed emotion data. This makes it possible to analyze the user's emotions in real time and provide feedback and property proposals based on the analyzed emotion data.

[1403] "Property information" refers to detailed information about a real estate property, such as its location, price, floor plan, facilities, and age.

[1404] A "database" is a system for organizing and storing collected information, and is a medium for storing property information, search condition data, etc.

[1405] An "AI algorithm" is a program that uses machine learning and data analysis techniques to analyze data, find patterns and trends, and make optimal suggestions and predictions.

[1406] A "Property Owner" is an individual or legal entity that owns a real estate property and wishes to rent or sell the property.

[1407] A "property searcher" is an individual or corporation searching for a real estate property.

[1408] An "optimal improvement proposal" is a proposal for improvement made to a property owner based on the facilities and conditions required by the market, and includes specific advice to increase the attractiveness of the property.

[1409] "Search criteria" refers to the conditions that property searchers enter when searching for a property, and refers to elements such as location, price range, floor plan, and facilities.

[1410] "Latent desired conditions" are elements or conditions that property searchers consider particularly important; they are hidden needs that are not explicitly entered but are identified through data analysis.

[1411] "Matching" is the process of matching the conditions of property owners and property searchers to find the optimal combination that meets the wishes of both parties.

[1412] A "personal contract" refers to a direct contract between a property owner and a property searcher.

[1413] "Generative AI" is a program that uses artificial intelligence technology to automatically generate necessary documents and contract documents based on information entered by the user.

[1414] A "wizard format" is a guided interface that allows a user to obtain a final output by inputting required information step by step.

[1415] "Smart device" refers to a device with internet connectivity, including smartphones, smart glasses, and head-mounted displays.

[1416] "Facial expressions and voice" refers to data for capturing the user's emotional state in real time, including facial expressions and what is being said.

[1417] "Analyzing emotions in real time" means instantly analyzing collected facial expressions and voice data to understand the user's emotional state.

[1418] "Feedback" refers to advice and information provided to users based on analyzed emotional data.

[1419] "Property suggestion" refers to recommending properties that are deemed appropriate based on the user's wishes and emotional state.

[1420] An embodiment of this invention is based on a real estate information system that integrates property information collection, data analysis, optimal proposal generation, search condition collection and analysis, emotion recognition and feedback, and interpersonal contract promotion and procedure support. This system allows users to tour properties using virtual reality technology using smart devices (smartphones, smart glasses, head-mounted displays, etc.), analyzes the user's emotions, and provides feedback in real time.

[1421] Program processing and technology used

[1422] The server first uses web scraping technology to collect property information from various real estate websites. The collected data is then stored in a database. Data duplication is eliminated and data cleansing is performed to ensure accurate data. This data is then analyzed using AI algorithms (e.g., machine learning models) to identify the facilities and conditions desired by the market.

[1423] When a user searches for a property, the device receives the search criteria entered and sends them to the server. The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of the property searcher. Based on this, the system suggests the most suitable property.

[1424] During a property viewing, the smart device collects the user's facial expressions and voice. This data is analyzed in real time using facial expression analysis software (e.g., Emotion API) and voice analysis software (e.g., Google Cloud Speech-to-Text + Sentiment Analysis API). Based on the emotion data, the server provides optimal feedback to the user and suggests detailed information about properties that interest them and similar properties.

[1425] When the contract is to proceed, the server uses a generative AI (e.g., OpenAI GPT-3) to automatically generate the contract documents and other necessary documents. It provides input support in the form of a wizard, allowing the user to easily follow the instructions to proceed with the contract procedure.

[1426] Examples of concrete examples and prompts

[1427] For example, if a user is using smart glasses to take a virtual tour and expresses interest in a property, if the user smiles or makes a positive comment, their facial expression and voice data will be analyzed and real-time feedback such as, "It seems you're interested in this property. More information is available here. Also, please check out similar properties."

[1428] Example prompt sentence:

[1429] Analyze the emotions users feel when viewing properties and generate feedback that provides details about properties that interest them and suggests similar properties.

[1430] Input data: User facial expressions (e.g., happy expressions), voice transcripts (e.g., positive comments)

[1431] Output data: Feedback based on user sentiment (e.g., "You seem interested in this property. More information here.")

[1432] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1433] Step 1:

[1434] The server uses web scraping technology to collect property information from various real estate websites. The input is the URL and HTML structure information of the real estate website, and the output is detailed information such as the property's location, price, layout, facilities, and age, which is stored in a database. Specifically, a script that runs periodically crawls through websites, extracts the necessary data, and stores it in the database.

[1435] Step 2:

[1436] The server stores the collected property information in a database. The input is property information obtained through web scraping, and the output is accurate property data after deduplication and data cleansing. Specifically, the database engine is used to organize, de-dupe, and cleanse the data.

[1437] Step 3:

[1438] The server uses AI algorithms to analyze the property information stored in the database. It uses organized property data as input and identifies the amenities and conditions the market demands as output. Specifically, it uses machine learning models to analyze the dataset and identify trends and popular amenities.

[1439] Step 4:

[1440] The server generates and notifies the property owner of optimal improvement proposals based on the identified market demand. The input is market demand data obtained by the AI ​​algorithm, and the output is specific improvement proposals (e.g., installing an air conditioner or improving the Wi-Fi environment) that are generated and notified to the property owner. Specifically, the improvement proposals are sent to the property owner's email or app via the notification system.

[1441] Step 5:

[1442] When a user searches for a property, the device receives the search criteria (e.g., location, price range, layout, facilities, etc.) entered and sends them to the server. The input uses the search criteria entered by the user into the app or website, and the output sends these search criteria to the server. Specifically, the device accepts search interactions through the device interface and sends the data to the server.

[1443] Step 6:

[1444] The server uses an AI algorithm to analyze the accumulated search condition data and identify the potential desired conditions of the property searcher. The input is the user's search history and condition data, and the output is the user's potential desired conditions. Specifically, it uses a machine learning model to analyze past data and discover the user's hidden needs.

[1445] Step 7:

[1446] The server then suggests properties that best suit the searcher based on the searcher's desired conditions. The input is the user's desired conditions as determined by the AI ​​algorithm, and the output is a list of properties that best suit the user. Specifically, the server searches the database for properties that match the user's desired conditions and displays them as a recommended list on the app or website.

[1447] Step 8:

[1448] The device collects the user's facial expressions and voice and transmits them to the server in real time. The input is facial expression and voice data acquired from the user's camera and microphone, and the output is transmission of these data to the server. Specifically, the device's camera and microphone capture data in real time and transmit it to the server using a communication protocol.

[1449] Step 9:

[1450] The server analyzes the transmitted emotional data using an AI algorithm to identify the user's emotional state. The input is the facial expression and voice data transmitted from the device, and the output is the user's emotional state (e.g., stress, anxiety, interest). Specific operations include analyzing the data using facial expression analysis software and voice analysis APIs.

[1451] Step 10:

[1452] The server provides feedback and property suggestions to the user based on the emotional data. It uses the analyzed emotional data as input and generates appropriate feedback and property suggestions as output, which it provides to the user. Specifically, it uses a feedback generation AI model to create feedback messages and property information according to the user's emotional state and sends them to the device.

[1453] Step 11:

[1454] The server matches property owners and property searchers and automatically generates the necessary documents to facilitate interpersonal contracts using generative AI. It uses the contract information of the property owner and property searcher as input, and generates complete contract documents as output, providing them to both parties. Specifically, it creates contract documents using a generative AI model based on the contract information obtained from the user, and provides input support through a wizard-style interface.

[1455] 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.

[1456] 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.

[1457] 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.

[1458] [Fourth embodiment]

[1459] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1460] 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.

[1461] 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).

[1462] 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.

[1463] 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.

[1464] 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).

[1465] 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.

[1466] 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.

[1467] 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.

[1468] 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.

[1469] 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.

[1470] 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.

[1471] 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."

[1472] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. The system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[1473] Collection and accumulation of property information

[1474] Gathering property information

[1475] The server periodically collects property information from the web and stores it in a database. This includes real estate portal sites and open data. Web scraping technology is used to extract the necessary data.

[1476] Accumulation of property information

[1477] The server organizes the collected data and stores it in a database, which includes detailed information such as property location, price, facilities, and floor plan.

[1478] Analyzing data and generating optimal proposals

[1479] Data analysis

[1480] The server analyzes the accumulated property information using AI algorithms, which identifies current market trends and the facilities and conditions that are in high demand.

[1481] Generating optimal proposals

[1482] Based on the identified market trends, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi. By notifying the property owner of these proposals, the property owner can increase the turnover rate.

[1483] Specific examples

[1484] The server performs web scraping to collect property information in Shinjuku Ward. The collected data is analyzed to determine that many searchers are looking for air conditioning and Wi-Fi. Based on this, the server makes recommendations to specific property owners about installing air conditioning and Wi-Fi.

[1485] Collecting and analyzing search criteria

[1486] Collecting search criteria

[1487] When a user searches for a property, the terminal sends the entered search criteria, including location, price range, floor plan, and facilities, to the server.

[1488] Data accumulation

[1489] The server stores the received search conditions in a database.

[1490] Data analysis

[1491] The server uses an AI algorithm to analyze the accumulated search criteria data, thereby identifying potential desired conditions that have not yet been suggested by the property searcher.

[1492] Specific examples

[1493] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to the server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[1494] Facilitating personal contracts and providing procedural support

[1495] matching

[1496] The server compares the conditions of property owners and property searchers and matches them with the optimal combination, making it easier for both parties to enter into a direct contract.

[1497] Automatic generation of contract documents

[1498] The server uses generation AI to automatically generate contract documents and other necessary documents, and a wizard format allows users to enter the necessary information, simplifying the contract process.

[1499] Specific examples

[1500] The server matches property owners with property searchers. It uses generation AI to automatically create contract documents and provide them to users. Users input information according to the AI's guidance, and the server supports the creation of final documents and the conclusion of the contract.

[1501] This solves the problems of the traditional real estate market, allowing property owners to increase turnover and property searchers to easily find properties based on their potential needs. Furthermore, private contracts reduce fees and simplify legal procedures.

[1502] The processing flow will be explained below.

[1503] Step 1:

[1504] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[1505] Step 2:

[1506] The server stores the collected property information in a database, eliminates duplicate data, and cleanses the data as needed.

[1507] Step 3:

[1508] The server uses AI algorithms to analyze the property information stored in the database, analysing market demand trends, property popularity, search frequency, and other factors.

[1509] Step 4:

[1510] Based on the analysis, the server identifies the amenities and conditions the market demands. For example, it may discover that many searchers are looking for air conditioning and Wi-Fi.

[1511] Step 5:

[1512] The server generates optimal improvement proposals for each property based on the identified market needs, for example, recommending the installation of air conditioners for a specific property.

[1513] Step 6:

[1514] The server notifies the property owner of the generated improvement proposals, possibly via email or push notification.

[1515] Step 7:

[1516] When a user searches for properties, the terminal receives the search criteria entered by the user (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[1517] Step 8:

[1518] The server stores the received search criteria in a database, and also stores each user's search history.

[1519] Step 9:

[1520] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the searcher's potential desired conditions. For example, it may discover that the searcher has strict requirements regarding location.

[1521] Step 10:

[1522] The server then proposes optimal properties to the searcher based on the identified latent conditions. The proposals take into account the user's initial conditions as well as their latent conditions.

[1523] Step 11:

[1524] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[1525] Step 12:

[1526] The server uses generative AI to automatically generate the necessary contract documents, which include the contract details and legal requirements.

[1527] Step 13:

[1528] The user receives input support in a wizard format and enters the necessary information to proceed with the contract procedure. The terminal supports this process.

[1529] Step 14:

[1530] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[1531] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, and completing contract procedures, providing a convenient platform for both property owners and searchers.

[1532] Example 1

[1533] 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."

[1534] Existing real estate information systems have difficulty efficiently collecting and analyzing large amounts of property information. They also lack the means to quickly match the requirements of property owners and property searchers and automatically generate contract documents. This results in a lack of efficiency and accuracy in property searches and transactions, and presents challenges in proposing optimal properties and simplifying contract procedures.

[1535] 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.

[1536] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to the user in a wizard format, means for automatically collecting and storing property information and search conditions on a regular basis, and means for sending notifications to the user in an optimal format depending on the device used. This enables efficient and accurate property searches and transactions.

[1537] "Property information" refers to detailed data about the property's location, price, facilities, floor plan, etc.

[1538] A "database" is a data structure for storing and managing collected property information and search conditions.

[1539] An "AI algorithm" is a computational method that uses machine learning and artificial intelligence to analyze data and identify patterns and trends.

[1540] "Property Owner" means an individual or legal entity that owns a property.

[1541] A "property searcher" is an individual or entity searching for a property.

[1542] "Improvement proposals" are specific advice provided to property owners to increase the value of their properties and improve turnover.

[1543] "Search conditions" are conditions such as location, price range, layout, and facilities that a property searcher inputs when searching for a property.

[1544] "Latent desired conditions" are conditions that property searchers do not explicitly enter but actually consider to be important.

[1545] "Matching" is the process of matching the conditions of the property owner with the conditions of the property searcher to find the optimal combination.

[1546] A "personal contract" is a transaction or contract made directly between a property owner and a property searcher.

[1547] "Generative AI" is an artificial intelligence technology for automatically generating text and documents.

[1548] "Contract documents" are documents that formally record the agreements related to a property transaction.

[1549] A "wizard format" is a guided input method that allows a user to input information step by step.

[1550] A "notification" is information or an alert sent from the system to a user.

[1551] A "terminal" is a device that a user uses to access the property information system. For example, a smartphone or a PC would be an example.

[1552] This invention relates to a real estate information system that provides benefits to both property owners and property searchers. This system has a variety of functions, including collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents.

[1553] Collection and accumulation of property information

[1554] Gathering property information

[1555] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python libraries such as BeautifulSoup and Scrapy.

[1556] Examples:

[1557] The server starts a scheduled job every day at 2:00 AM to extract property information from the specified URL, and the extracted data is temporarily stored in memory.

[1558] Accumulation of property information

[1559] The server organizes the collected property information and stores it in a database using MySQL, PostgreSQL, or similar.

[1560] Examples:

[1561] The server stores the property information stored in memory in a database. The database table contains fields such as property location, price, amenities, and layout. It checks for duplicate data and inserts only new data.

[1562] Analyzing data and generating optimal proposals

[1563] Data analysis

[1564] The server analyzes the accumulated property information using AI algorithms (e.g., the Scikit-learn library).

[1565] Examples:

[1566] The server feeds the accumulated data into a data analysis pipeline, performing clustering and regression analysis to identify market trends and equipment in high demand.

[1567] Generating optimal proposals

[1568] The server generates optimal improvement proposals for property owners based on the analysis results, using a generative AI model (e.g., GPT-4).

[1569] Examples:

[1570] The server inputs market trends and demand data into the AI ​​model and generates improvement suggestions, which are then sent to the property owner, such as suggesting the installation of air conditioners or Wi-Fi.

[1571] Collecting and analyzing search criteria

[1572] Collecting search criteria

[1573] When a user searches for a property, the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[1574] Examples:

[1575] The user launches the property search app on their smartphone and enters search criteria. The device sends the entered search criteria in JSON format to the server.

[1576] Search condition data accumulation

[1577] The server stores the received search conditions in a database.

[1578] Examples:

[1579] The server stores the search condition data in a database.

[1580] Data analysis

[1581] The server uses an AI algorithm to analyze the accumulated search criteria data to identify the potential desired conditions of property searchers.

[1582] Examples:

[1583] The server analyzes the search criteria data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[1584] Facilitating personal contracts and providing procedural support

[1585] matching

[1586] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[1587] Examples:

[1588] The server performs a filtering process to compare the property information with the search criteria and notifies both parties of the matching results.

[1589] Automatic generation of contract documents

[1590] The server uses a generative AI model (e.g., GPT-4) to automatically generate contracts and other necessary documents.

[1591] Examples:

[1592] The server inputs the contract terms into the AI ​​model and sends the generated contract documents to the user, who then enters information in a wizard format to complete the process.

[1593] Specific examples of prompts for the generative AI model to use

[1594] "Write a program to collect information on 1LDK apartments in Shinjuku Ward, organize it, and store it in a database. Next, implement a system that analyzes market trends based on the property information and generates recommendations for air conditioning and Wi-Fi."

[1595] By using this prompt sentence, it is possible to generate a program to implement the above function using a generative AI model.

[1596] By referring to these procedures and examples in practicing the present invention, property searches and transactions can be carried out efficiently and accurately.

[1597] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1598] Step 1: Gather property information

[1599] The server uses web scraping technology to periodically collect property information from real estate portal sites and open data, using Python's BeautifulSoup and Scrapy libraries.

[1600] Input: URL of real estate portal site

[1601] Data processing: Extract specific elements (location, price, facilities, floor plan) from HTML pages.

[1602] Output: Collected property information is temporarily stored in memory.

[1603] Specific operation: The server starts a scheduled job at 2:00 AM every day, extracts property information from the specified URL, and temporarily stores it in memory.

[1604] Step 2: Accumulating property information in a database

[1605] The server organizes the collected property information and stores it in a database using MySQL or PostgreSQL.

[1606] Input: Property information in memory

[1607] Data processing: Check for duplicate data and organize it.

[1608] Output: Store the organized property information in a database.

[1609] Specific operation: The server checks the property information stored in memory for duplicate data and then stores it in the database.

[1610] Step 3: Data analysis

[1611] The server analyzes the accumulated property information using an AI algorithm (Scikit-learn library).

[1612] Input: Property information stored in the database

[1613] Data calculations: Perform clustering and regression analysis.

[1614] Output: Identify market trends and equipment / conditions with high demand.

[1615] How it works: The server feeds the data stored in the database into a data analysis pipeline, where AI algorithms are used to identify market trends and equipment in high demand.

[1616] Step 4: Generate optimal proposals

[1617] The server generates and notifies the property owner of optimal improvement proposals based on the analysis results, using a generative AI model (GPT-4).

[1618] Inputs: Market trends and demand data

[1619] Data processing: Generate specific improvement suggestions based on the AI ​​model.

[1620] Output: Send the improvement suggestions in the form of a notice to the property owner.

[1621] How it works: The server inputs market trends and demand data into the AI ​​model, and then notifies the property owner of the generated proposals for installing air conditioners and improving Wi-Fi environments.

[1622] Step 5: Collecting search criteria

[1623] The user searches for properties, and the terminal sends the search criteria (location, price range, floor plan, facilities) to the server.

[1624] Input: Search criteria entered by the user

[1625] Data processing: Convert search criteria into JSON format.

[1626] Output: The search criteria is sent to the server.

[1627] Specific operation: The user launches a property search app on their smartphone, enters search criteria, and the device sends the search criteria to the server in JSON format.

[1628] Step 6: Storing search criteria in the database

[1629] The server stores the received search conditions in a database.

[1630] Input: Search criteria sent to the server

[1631] Data processing: Format the search criteria to store them in the database.

[1632] Output: The search criteria are stored in the database.

[1633] Specific operation: The server stores the received search criteria in a database in an appropriate format.

[1634] Step 7: Identify potential requirements through data analysis

[1635] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers.

[1636] Input: Accumulated search criteria data

[1637] Data crunching: Using AI algorithms to analyze data and identify potential desired conditions.

[1638] Output: Obtain the results of the identified potential desired conditions.

[1639] Specific operation: The server inputs the search criteria data into an AI algorithm and determines that the user is actually looking for a property close to the station.

[1640] Step 8: Proposal of the best property

[1641] Based on the analysis results, the server suggests the most suitable property to the user.

[1642] Input: Identified potential desires

[1643] Data processing: Generate specific property proposals.

[1644] Output: Send the best property suggestions to the device.

[1645] Specific operation: The server sends the user a notification recommending properties within a five-minute walk from the station.

[1646] Step 9: Matching property information with search criteria

[1647] The server compares the conditions of the property owner and the property searcher and matches the optimal combination.

[1648] Input: Property information and search conditions

[1649] Data operations: Perform filtering and condition matching operations.

[1650] Output: Get the matching results.

[1651] Specific operation: The server compares the property information with the search criteria and notifies both parties of matching combinations.

[1652] Step 10: Automatic generation of contract documents

[1653] The server uses a generative AI model (GPT-4) to automatically generate contracts and necessary documents.

[1654] Input: Terms and Conditions

[1655] Data processing: Generate contract documents using AI models.

[1656] Output: Send the generated contract document to the user.

[1657] Specific operation: The server inputs the contract terms into the AI ​​model and sends the generated document to the user. The user enters information in a wizard format and completes the contract procedure.

[1658] (Application example 1)

[1659] 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."

[1660] Conventional real estate information systems have comprehensive functionality for collecting and analyzing property information, but they lack sufficient evaluation and proposal capabilities for property security information, making it difficult to effectively improve users' confidence in the safety of properties. Furthermore, because security information is not shared or evaluated among users, it is difficult to make the most of the information held by each user. This creates an issue in which the benefits to both property owners and property searchers are not fully realized.

[1661] 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.

[1662] In this invention, the server includes means for collecting property information from the web and storing it in a database, means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market, means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions, means for collecting search conditions from property searchers and storing them in a database, means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions, means for proposing optimal properties to the searcher based on the identified desired conditions, means for matching property owners and property searchers and facilitating personal contracts, means for automatically generating necessary documents such as contracts using a generation AI and providing input support to users in a wizard format, means for collecting property security information, analyzing it using an AI algorithm, and proposing highly secure properties, and means for users to share and evaluate security information with each other, thereby improving users' confidence in the safety of properties.

[1663] "Property information" refers to information about the property, such as its location, price, layout, facilities, and security.

[1664] A "database" is a system for storing and managing collected property information and search conditions.

[1665] An "AI algorithm" is a program that analyzes property information and search criteria data based on machine learning and data analysis.

[1666] "Property Owner" means the person or entity that owns the property and provides the information.

[1667] A "Property Searcher" is a person or entity searching for a property.

[1668] "Improvement proposals" are recommendations for adding amenities or changing conditions proposed to increase the market value of the property.

[1669] "Search conditions" are the conditions and wishes specified by a property searcher when searching for a property.

[1670] "Potential desired conditions" are desired conditions that are not explicitly specified by the property searcher, but are likely to be indicated as a result of the AI ​​algorithm's analysis.

[1671] "Matching" is the process of matching the conditions of property owners and property searchers to find the optimal combination.

[1672] A "personal contract" is a direct contract between a property owner and a property searcher.

[1673] "Generative AI" is an AI technology that automatically generates contracts and other necessary documents.

[1674] A "wizard format" is a guided interface designed to guide the user through entering required information.

[1675] "Security information" refers to information about the property's security status and the security equipment installed.

[1676] "Sharing and evaluation" is a process in which users provide each other with information and then evaluate it based on that information.

[1677] MODE FOR CARRYING OUT THE INVENTION

[1678] The present invention is a system that collects, analyzes, and proposes real estate information, providing convenience to property owners and property searchers. Specifically, the system is implemented with the following configuration.

[1679] Collection and accumulation of property information

[1680] The server periodically collects property information from the web and stores it in a database. This involves using web scraping technology to extract the necessary data from real estate portal sites and open data. The software used is a Python program and the BeautifulSoup library. As a specific example, real estate information related to Shinjuku Ward is scraped, and data such as location, price, and facilities is stored in the database.

[1681] Analyzing data and generating optimal proposals

[1682] The server analyzes the collected property information using AI algorithms. This identifies market trends and facilities and conditions that are in high demand, and generates and notifies property owners of optimal improvement proposals. This process uses machine learning algorithms. AI tools used include TensorFlow and scikit-learn. For example, if it identifies that many searchers are looking for air conditioning and Wi-Fi, it can use this information to suggest installing air conditioning and improving Wi-Fi to specific property owners.

[1683] Collecting and analyzing search criteria

[1684] When a property searcher searches for a property on their smartphone, the device sends the search criteria entered by the user to a server. The collected data is stored in a database and analyzed using an AI algorithm. For example, if a user searches for a 1LDK property, the server will determine through analysis that the user is looking for a property close to the station and suggest properties within a 5-minute walk from the station.

[1685] Facilitating personal contracts and providing procedural support

[1686] The server compares the conditions of the property owner and the property searcher and matches the optimal combination. It also uses generation AI to automatically generate contract documents and other necessary documents, and prompts the user to enter the necessary information in a wizard format. This generation AI uses OpenAI's API. An example of a specific prompt sentence that can be entered is as follows:

[1687] Property location: Shinjuku Ward

[1688] Price: 30 million yen

[1689] Security: Near station, air conditioning, Wi-Fi

[1690] Generate the contract.

[1691] Analysis, sharing and evaluation of security information

[1692] Furthermore, the server collects property security information and analyzes it using an AI algorithm to suggest highly secure properties to searchers. The system also has a function that allows users to share and rate security information with each other, which can improve the reliability of property security.

[1693] This system makes it easier for property owners to increase turnover and for property searchers to find the perfect property that meets their needs. In addition, by taking security information into consideration when making suggestions, it increases users' sense of security.

[1694] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1695] Program processing flow

[1696] Step 1: Collecting and accumulating property information

[1697] The server collects property information from the web and stores it in a database.

[1698] Input: URL of real estate portal site or open data

[1699] Data processing: Using web scraping technology, property information such as location, price, floor plan, and facilities is extracted from HTML pages.

[1700] Output: Store the collected property information in a database as structured data.

[1701] What it does: The server uses Python and the BeautifulSoup library to periodically access the specified URL, extract the necessary data, and store it in the database.

[1702] Step 2: Analyze the data and generate optimal proposals

[1703] The server analyzes the collected property information using AI algorithms and generates and notifies the property owner of optimal improvement proposals.

[1704] Input: Property information stored in the database

[1705] Data crunching: Using AI algorithms, we analyze property information to identify market trends and in-demand amenities and conditions.

[1706] Output: A list of improvement suggestions to send to the property owner

[1707] How it works: The server uses TensorFlow and scikit-learn to analyze property information in the database, identify high-demand facilities and conditions, and generate recommendations. The identified proposals are then notified to the property owner.

[1708] Step 3: Collecting and analyzing search criteria

[1709] The terminal collects the search conditions of property searchers and sends them to the server, which then analyzes the accumulated search condition data to identify potential desired conditions.

[1710] Input: Search criteria entered by the property searcher on their smartphone

[1711] Data processing: The terminal transfers the entered search criteria to the server.

[1712] Output: Potential desired conditions identified based on the analysis

[1713] How it works: Property searchers enter search criteria into a smartphone app, and the device sends the information to a server, which uses AI algorithms to analyze the data, identify potential preferences, and generate a list of search candidates.

[1714] Step 4: Facilitating personal contracts and providing procedural support

[1715] The server compares the conditions of property owners and property searchers to find the optimal combination. It also uses generation AI to automatically generate contract documents and provides input support to users in a wizard format.

[1716] Input: Property owner and property searcher criteria

[1717] Data calculation: Condition matching and generation Contract document generation using AI

[1718] Output: Matching results and automatically generated contract documents

[1719] Specific operation: The server matches the conditions of the property owner and the property searcher to identify the optimal combination. Then, it automatically generates the contract documents using the OpenAI API and provides input support to the user in a wizard format. The following is an example of a prompt sentence:

[1720] Property location: Shinjuku Ward

[1721] Price: 30 million yen

[1722] Security: Near station, air conditioning, Wi-Fi

[1723] Generate the contract.

[1724] Step 5: Analyze, share and evaluate security information

[1725] The server collects property security information, analyzes it with an AI algorithm, and recommends properties with high safety. It also provides a function for users to share and rate security information with each other.

[1726] Input: Property security information

[1727] Data Computing: Analyzing Security Information with AI Algorithms

[1728] Output: A list of safe property suggestions and security ratings

[1729] Specific operation: The server analyzes the collected security information using an AI algorithm (e.g., TensorFlow) and recommends highly secure properties to users. It also provides a mechanism for users to share and mutually evaluate security information, thereby increasing confidence in the safety of properties.

[1730] As described above, by performing specific processing at each step, it is possible to provide an optimal real estate information system for property owners and property searchers.

[1731] 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.

[1732] This invention relates to a system that provides new benefits to both property owners and property searchers by incorporating an emotion engine into a real estate information system. In addition to functions such as collecting property information, storing and analyzing data, generating optimal proposals, collecting and analyzing search conditions, and automatically generating contract documents, this system also includes a function that recognizes the user's emotions and provides feedback based on them.

[1733] Collection and accumulation of property information

[1734] Gathering property information

[1735] The server periodically collects property information from the web and stores it in a database. Web scraping technology is used to extract detailed information such as the property's location, price, layout, facilities, and age.

[1736] Accumulation of property information

[1737] The server organizes the collected property information and stores it in a database. Data duplication is eliminated and data cleansing is performed to maintain accurate data.

[1738] Analyzing data and generating optimal proposals

[1739] Data analysis

[1740] The server uses AI algorithms to analyze the property information stored in the database, analyzing indicators such as market demand trends, property popularity, and search frequency to identify specific market needs.

[1741] Generating optimal proposals

[1742] The server generates optimal improvement proposals based on market needs and notifies the property owner, including proposals such as installing air conditioners and improving Wi-Fi.

[1743] Specific examples

[1744] The server collects property information in Shinjuku Ward and identifies that many searchers are looking for air conditioning and Wi-Fi. Based on this, it makes proposals to specific property owners for the installation of air conditioning and Wi-Fi.

[1745] Collecting and analyzing search criteria

[1746] Collecting search criteria

[1747] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[1748] Data accumulation

[1749] The server stores the received search criteria in a database, along with the user's search history.

[1750] Data analysis

[1751] The server uses an AI algorithm to analyze the accumulated search condition data and identify the potential desired conditions of property searchers, for example, determining that the searcher places importance on location.

[1752] Specific examples

[1753] A user searches for a 1LDK property on their smartphone. The device sends the search criteria to a server. The server analyzes the data and determines that the user is actually looking for a property close to the station. Based on this, it suggests properties within a five-minute walk from the station.

[1754] Emotion Recognition and Feedback

[1755] Emotion engine integration

[1756] The device is equipped with a function to collect emotional data from the user's facial expressions and voice, allowing for real-time monitoring of the user's emotions as they search for properties and complete contract procedures.

[1757] Emotional Data Analysis

[1758] The server uses AI algorithms to analyze the data sent from the emotion engine, detects the user's stress or anxiety, and provides support and feedback at the appropriate time.

[1759] Optimal Feedback Generation

[1760] The server generates feedback and suggestions that are best suited to the user's situation based on the emotion data. If the user is interested in a particular property, it will provide detailed information about that property and suggest similar properties.

[1761] Specific examples

[1762] If a user is feeling stressed during a property search, the device will detect this emotion and the server will provide friendly feedback to reduce anxiety and expand options by suggesting other properties similar to the one they expressed interest in.

[1763] Facilitating personal contracts and providing procedural support

[1764] matching

[1765] The server compares the conditions of property owners and property searchers to find the best match, making it easier for both parties to enter into a direct contract.

[1766] Automatic generation of contract documents

[1767] The server uses generation AI to automatically generate contract documents and other necessary documents, and provides input support in the form of a wizard, allowing users to easily proceed with the contract procedure.

[1768] Specific examples

[1769] The system matches users with property owners and automatically creates contract documents using generation AI. The user enters information according to the AI's guidance, and the server generates the final contract documents and provides them to both parties, completing the contract procedure.

[1770] This allows the system to consistently handle everything from collecting property information to analyzing it, making optimal proposals, completing contract procedures, and recognizing emotions, providing a highly convenient platform for both property owners and searchers.

[1771] The processing flow will be explained below.

[1772] Step 1:

[1773] The server periodically collects property information from designated real estate portal sites and other data sources using web scraping technology, extracting detailed information such as property location, price, floor plan, facilities, and age.

[1774] Step 2:

[1775] The server stores the collected property information in a database, which also includes eliminating duplicate data and cleaning inaccurate information.

[1776] Step 3:

[1777] The server uses AI algorithms to analyze property information stored in the database, identifying current market trends and the facilities and conditions that are in high demand.

[1778] Step 4:

[1779] Based on the analysis results, the server generates optimal improvement proposals for the property owner, such as installing air conditioners or improving Wi-Fi.

[1780] Step 5:

[1781] The server notifies the property owner of the generated improvement proposals via email, push notifications, or other means.

[1782] Step 6:

[1783] When a user searches for a property, the terminal receives the entered search criteria (e.g., location, price range, floor plan, facilities, etc.) and sends them to the server.

[1784] Step 7:

[1785] The server stores the received search conditions in a database. Each user's search history is also saved, enabling consistent data utilization.

[1786] Step 8:

[1787] The server uses an AI algorithm to analyze the accumulated search criteria data and identify the potential desired conditions of property searchers, such as determining whether users place importance on location information.

[1788] Step 9:

[1789] The server then proposes the most suitable property to the user based on the identified latent conditions, taking into account the user's initial conditions as well as their latent conditions.

[1790] Step 10:

[1791] The device uses an emotion engine to analyze the user's facial expressions and voice while searching for properties, collecting emotional data in real time, thereby monitoring the stress and anxiety the user is feeling.

[1792] Step 11:

[1793] The server uses an AI algorithm to analyze the emotional data sent from the emotion engine and provides feedback according to the user's situation, such as changing the UI to help them relax or providing more information.

[1794] Step 12:

[1795] The server compares the conditions of the property owner and the property searcher to find the best match, connecting the two based on the property information and the user's desired conditions.

[1796] Step 13:

[1797] The server uses generation AI to automatically generate the necessary contract documents, which include contract details and legal requirements, and provides input support to the user in a wizard format.

[1798] Step 14:

[1799] The user is guided through a wizard-style input process to input the necessary information into the system, and through this process the contract documents are completed.

[1800] Step 15:

[1801] The server generates the final contract documents and provides them to both the property owner and the property searcher, which can then be digitally signed or emailed.

[1802] This allows the system to efficiently carry out a series of processes, such as collecting property information, accumulating and analyzing data, generating optimal proposals, collecting and analyzing search conditions, recognizing emotions, and completing contract procedures, thereby improving the user experience.

[1803] Example 2

[1804] 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."

[1805] While conventional real estate information systems collect property information and accumulate data, they are unable to make proposals that reflect the user's emotional state, making improving user satisfaction a challenge. Furthermore, support for improvement proposals to property owners and for personal contract procedures is insufficient, and improvements are needed, particularly in the automatic generation and updating of contract documents. Furthermore, it is difficult for property searchers to identify the conditions they actually desire, resulting in many cases where users' potential needs are overlooked.

[1806] 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.

[1807] In this invention, the server includes: means for collecting property information from the Web and storing it in a database; means for analyzing the stored data using an AI algorithm to identify the facilities and conditions required in the market; means for generating and notifying optimal improvement proposals to property owners based on the identified facilities and conditions; means for collecting search conditions from property searchers and storing them in a database; means for analyzing the stored search condition data using an AI algorithm to identify the property searcher's potential desired conditions; means for proposing optimal properties to the searchers based on the identified desired conditions; means for matching property owners and property searchers and facilitating personal contracts; means for automatically generating necessary documents such as contracts using a generative AI model and providing input support to the user in a wizard format; means for collecting emotional data from the user's facial expressions and voice; means for analyzing the collected emotional data using an AI algorithm to detect the user's stress or anxiety; and means for generating and providing optimal feedback and proposals based on the emotional data. This enables optimal property proposals and feedback that take the user's emotional state into consideration, thereby providing a highly convenient service for both property owners and property searchers.

[1808] "Means of collecting property information from the Web" refers to technology that automatically collects data about properties from real estate sites on the Internet.

[1809] "Means of storing data in a database" refers to the technology of organizing collected data and storing it in a database system for centralized management.

[1810] "Artificial intelligence algorithms" are computational methods that include machine learning and deep learning to analyze large amounts of data and find patterns and trends.

[1811] "Means to identify the facilities and conditions desired by the market" refers to a technology that analyzes accumulated property information and identifies the facilities and conditions that searchers highly value in the current market.

[1812] The "means for generating and notifying optimal improvement proposals to property owners" is a technology for generating improvement proposals for owned properties based on identified market needs and notifying the property owners in an appropriate manner.

[1813] "Means for collecting search conditions of property searchers" refers to technology for collecting desired conditions entered by users searching for properties. ...

Claims

1. A means of collecting property information from the web and storing it in a database, The accumulated data is analyzed using AI algorithms to identify the equipment and conditions required by the market. A means for generating and communicating optimal improvement proposals to the property owner based on the identified facilities and conditions; and A means for collecting search conditions of property searchers and storing them in a database; A method to analyze accumulated search condition data using AI algorithms to identify potential desired conditions of property searchers, A means of suggesting the best properties to searchers based on their specified desired criteria; A means of matching property owners with property searchers and facilitating personal transactions; A means to automatically generate necessary documents such as contracts using generation AI and provide input support to users in a wizard format. A system including:

2. 10. The system of claim 1, further comprising means for tracking the implementation of the proposed improvements to the property owner and evaluating the effectiveness of the improvements.

3. 10. The system of claim 1, further comprising means for automatically updating the contract documents to conform to current legal requirements when changes or updates to the contract are notified.

Images