system

Abstract

We provide the system. [Solution] A means for receiving user conditions and searching for real estate information based on those conditions, A means of removing false or unnecessary information from the searched real estate information, A means of evaluating the property information after removal based on the user's lifestyle and preferences, A means of presenting users with the most suitable real estate information based on the evaluation results, Methods to automate and streamline the application process for real estate contracts, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, the selection of real estate is a complex and time-consuming process, and there is a problem that it is difficult to find a property that perfectly matches the user's preferences and lifestyle. Also, there is often a problem that property information contains false or unnecessary content and the accuracy of the information is low. Furthermore, the procedures for real estate contracts are often cumbersome and burdensome for users, so it is necessary to solve these problems.

Means for Solving the Problems

[0005] This invention provides a means for receiving conditions from a user and searching for real estate information based on those conditions. By using a means to remove false or unnecessary information from the search results, only information useful to the user is presented. Furthermore, the invention includes a means for evaluating the removed real estate information based on the user's lifestyle and preferences, and by presenting the user with the most suitable real estate information based on the evaluation results, it effectively supports property selection. In addition, by providing an efficient automated procedure, the time and effort required for contract application are reduced, thereby alleviating the burden on the user. Thus, the objective of this invention is to improve the efficiency and accuracy of property selection.

[0006] A "user" is an individual who provides the system with criteria and preferences for searching for real estate properties.

[0007] "Conditions" refer to the specific wishes and requirements that the user provides, such as location, budget, number of rooms, and whether pets are allowed.

[0008] "Real estate information" refers to information that includes detailed data and attributes about the property being searched.

[0009] "False information" refers to some real estate information that contains content that is contrary to the facts or contains incorrect data.

[0010] "Unnecessary information" refers to real estate information that does not match the user's conditions or preferences.

[0011] "Lifestyle" refers to the habits, values, and characteristics of a user's lifestyle that they consider important.

[0012] "Evaluation" refers to the process of determining the suitability and advantages of a property based on the user's conditions and lifestyle.

[0013] "Automation" refers to methods of reducing human labor by performing procedures that were previously done manually, either mechanically or electronically.

[0014] "Efficiency improvement" refers to methods for reducing time and costs and carrying out tasks more effectively. [Brief explanation of the drawing]

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

Embodiments for Carrying out the Invention

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

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

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

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

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

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

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

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

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

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

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0036] This invention provides a configuration for realizing a system that proposes optimal real estate properties based on the user's conditions and lifestyle. This system consists of a user, a terminal, and a server.

[0037] First, the user uses a terminal to input their preferences and requirements for real estate properties (location, budget, number of rooms, pet-friendly, etc.). The terminal sends this information to the server. The server searches the real estate information database based on the received conditions.

[0038] Based on the search results, the server filters out false information and information that the user does not need. Furthermore, using the filtered information, the server uses an AI algorithm to evaluate properties. In the evaluation, features such as the property's location, price, facilities, and transportation access are scored in comparison to the user's lifestyle.

[0039] Based on the evaluation results, the server selects the most suitable real estate information and sends it to the terminal. The terminal displays the received property information to the user and explains the reasons for selection and the recommended points of each property.

[0040] Furthermore, if a user expresses interest in a particular property, the server initiates an automated application process. This includes generating necessary documents, obtaining digital signatures, and notifying relevant parties. The terminal monitors the user's progress and provides guidance to ensure a smooth contract process.

[0041] As a concrete example, suppose a user sets the conditions as "2LDK in a suburban area, under 20 million yen, pet-friendly." The server searches the database for candidate properties according to these conditions and uses AI to evaluate transportation access and the surrounding environment. Once a suitable property is selected, the information is presented to the user, and the process can proceed quickly without going through a real estate agent or property management company. In this way, this system reduces the burden on the user and efficiently supports property selection and contract.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user uses a device to enter their preferences and requirements for a real estate property. The entered requirements should be specific, including location, budget, number of rooms, and whether pets are allowed.

[0045] Step 2:

[0046] The terminal receives user information, formats it into digital data, and sends it to the server.

[0047] Step 3:

[0048] The server receives the user's criteria data. It generates a query against the database and searches for real estate information that matches the criteria.

[0049] Step 4:

[0050] The server filters out false and unnecessary information from the retrieved real estate data. Data cleansing techniques are used to ensure the quality of the information.

[0051] Step 5:

[0052] The server sends filtered real estate information to an AI algorithm, which scores each property by matching its characteristics with the user's lifestyle.

[0053] Step 6:

[0054] The server ranks property information based on the scoring results and selects the property that best meets the criteria.

[0055] Step 7:

[0056] The server sends the selected property information to the terminal. The terminal presents the received information to the user, displaying the evaluation points and reasons for recommendation for each property.

[0057] Step 8:

[0058] The user reviews the presented property information and selects the properties that interest them. The user's selection is notified to the server via their device.

[0059] Step 9:

[0060] The server initiates an automated application process for the selected property. It generates the necessary documents, obtains digital signatures, and submits applications to the relevant authorities.

[0061] Step 10:

[0062] The terminal displays the progress of the application process to the user and guides them through the next steps. The server confirms the completion of the process and notifies the user of the result.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] In real estate property selection, it is difficult for users to efficiently find the optimal property while considering a variety of conditions. Furthermore, the cumbersome paperwork and communication involved in the process consume time and effort. There is a need for a means to solve these problems and enable quick and efficient property selection and contract procedures.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes means for receiving user conditions via a terminal and securely transmitting them to the server, means for searching a real estate information database based on the conditions and extracting properties that match the conditions, and means for filtering and evaluating real estate information using a generation AI model. This enables the selection of optimal property information according to the user's conditions and the efficient execution of automated real estate contracts.

[0068] A "user" is an individual or organization that uses the system to search for and select real estate property information.

[0069] A "terminal" is an electronic device used by a user to access a system and input or retrieve information.

[0070] A "server" is a central computing system that searches for and evaluates real estate information based on conditions submitted by users and executes the necessary processes.

[0071] A "real estate information database" is a data storage system that stores detailed information about properties and allows users to extract and manage information according to their criteria.

[0072] A "generative AI model" is an artificial intelligence algorithm used to filter and evaluate optimal information based on input data.

[0073] "Lifestyle" refers to elements that reflect the user's preferences and values ​​related to their way of life, and is considered as part of the property evaluation.

[0074] "Evaluation" is the process of indicating the suitability of a property based on the user's criteria using numerical values ​​or indicators.

[0075] A "digital document" is an electronic document used in real estate contract procedures, serving as a substitute for paper-based documents.

[0076] "Electronic signature" is a technology used to verify and authorize the identity of a user on a digital document.

[0077] This invention is a system designed to enable users to efficiently select and contract for real estate properties. The system consists of users, terminals, and a server.

[0078] The user first uses their device to enter their real estate search criteria. Specifically, the device displays an input form where the user can enter criteria such as "budget," "location," "number of rooms," and "pets allowed" into text fields. This information is securely transmitted to the server by the device. In this process, the device encrypts the data using the HTTPS protocol and transfers it to the server's API in JSON format.

[0079] The server searches a real estate information database using the received conditions. A common SQL database system is used for database management. The server creates and executes SQL queries to retrieve property information that matches the conditions. The retrieved information is temporarily stored in the server's memory. The server then filters the real estate information using a generative AI model. The AI ​​model incorporates machine learning algorithms to remove false information and information that is not relevant to the user.

[0080] Next, an AI evaluation takes place, where the server scores properties based on the user's lifestyle. Here, the AI ​​algorithm uses a trained model to match the property's location, price, amenities, and transportation access features with the user's requirements. Properties with high scores are added to the final selection list.

[0081] The server then sends the selected property information to the terminal. The terminal displays the received information in an easy-to-understand manner for the user, highlighting the property's features and recommended points. For properties the user is interested in, the server automatically starts the application process. Digital documents and electronic signatures are used for the application, and document generation and notifications to relevant parties are handled. The terminal displays the user's progress in real time and guides them through the necessary operations to support a smooth contract process.

[0082] For example, when a prompt such as "The user sets the conditions, and the AI ​​scores the best properties and outputs the results" is entered into the system, optimized property information based on the user's conditions is provided.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users enter criteria such as "budget," "location," "number of rooms," and "pets allowed" into an input form on their device. The entered criteria are converted to JSON format by the device and sent to the server via the HTTPS protocol. During this process, the user's criteria data is encrypted and securely transferred to the server through a secure communication channel.

[0086] Step 2:

[0087] The server parses the received JSON data and searches the real estate information database based on the specified conditions. The server generates an SQL query and extracts property information that meets the conditions from the database. The input here is conditional data in JSON format, and the output is a list of property information as search results. The server stores this data in temporary memory.

[0088] Step 3:

[0089] The server filters the searched property information using a generating AI model. The AI ​​model uses machine learning algorithms to remove false or irrelevant information from the search results. The input is a list of searched property information, and the output is a filtered list of property information. The server evaluates the reliability of each property during this process.

[0090] Step 4:

[0091] Based on the filtered information, the server uses an AI algorithm to evaluate properties. The server scores each property's characteristics (location, price, amenities, transportation access, etc.) based on the user's lifestyle. The input is a filtered list of property information, and the output is a scored list of property information. This evaluation identifies the most suitable property.

[0092] Step 5:

[0093] The server sends high-scoring property information to the terminal. The terminal analyzes the received information and displays it clearly in the user interface. The display includes property details and recommended points based on AI evaluation. The input is scored property information, and the output is a visual presentation of information to the user.

[0094] Step 6:

[0095] When a user expresses interest in a particular property, the terminal sends that information to the server, which automatically initiates the application process. The server generates the necessary digital documents for the application and sends the user a link for electronic signature. The input is the property information selected by the user, and the output is the generated documents and notifications of the process's progress.

[0096] This entire process allows users to efficiently and safely select real estate properties and complete contract procedures.

[0097] (Application Example 1)

[0098] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0099] In modern urban life, efficient housing selection utilizing digital technology is required to improve convenience and quality of life. However, existing real estate information systems lack mechanisms to efficiently propose properties that meet individual needs based on user criteria, and they fail to remove false or unnecessary information. Furthermore, the current real estate contract procedures are not sufficiently efficient.

[0100] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0101] In this invention, the server includes means for receiving user conditions and searching for property information based on those conditions; means for removing false or unnecessary information; means for evaluating the remaining property information based on the user's lifestyle and preferences; and means for linking with urban infrastructure data to evaluate the overall living environment and propose the most suitable property. This makes it possible to scrutinize property information according to the user's individual conditions and efficiently proceed with the contract process.

[0102] "User requirements" refer to specific demands that users have regarding property selection, such as budget, location, number of rooms, and whether or not pets are allowed.

[0103] "Property information" refers to a collection of information that includes detailed data about real estate, such as location, price, facilities, area, and transportation access.

[0104] "False information" refers to incorrect data that differs from the actual facts about a property, and is inaccurate information that should be excluded during the selection process.

[0105] "Urban infrastructure data" refers to data related to the basic infrastructure of a city, such as public transportation, road networks, living facilities, educational institutions, and medical facilities.

[0106] "Contract procedures" refer to the various procedures, document preparation, signing, and notification processes necessary to finalize a lease or sale of a property.

[0107] "Overall living environment" refers to all factors that affect the quality of life, including not only the characteristics of individual properties but also the surrounding community and urban functions.

[0108] This invention provides a system that enables users to efficiently select housing. First, the user inputs their desired housing requirements using a device such as a smartphone. These requirements include budget, location, number of rooms, and whether pets are allowed. The device then transmits this information to a server.

[0109] The server searches the property information database using an AI model based on the received conditions. The Python Django framework is used for this process. After the search, the server filters the information in the database, removing false or unnecessary data. The removed data is then scored by an AI algorithm based on the user's lifestyle and preferences. This process utilizes either TENSORFLOW® or PyTorch.

[0110] Furthermore, the server utilizes the Google® Maps API to connect with urban infrastructure data and perform an overall assessment of the living environment. This makes it possible to select the property that best suits the user's specified conditions. The server sends the selection results to the terminal and presents the user with the most suitable property information. The terminal displays the reasons for the selection and the recommended points of each property to the user.

[0111] Furthermore, when a user expresses interest in a particular property, the server initiates an automated contract process using smart contracts. This generates digital documents and efficiently carries out the necessary procedures.

[0112] For example, if a user enters criteria such as "within 30 minutes of the city center, in a low-humidity area, close to a school, and within a budget of 30 million yen," the server will search for the property that best fits these criteria, comprehensively evaluate the surrounding environment and quality of life, and then present the user with the most suitable property information.

[0113] An example of a prompt message for the generating AI model is: "Provide real estate property data that matches the user's specified conditions and select the optimal property to evaluate its compatibility with the living environment and urban infrastructure."

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] Users enter their desired property criteria (e.g., budget, location, number of rooms, whether pets are allowed) through their device. The user's input is recorded on the device as form data. This data is then sent to the server in JSON format.

[0117] Step 2:

[0118] The server searches the property information database based on the user's conditions received from the terminal. It uses the Django framework to generate database queries and extract property information that matches the user's conditions. The search results obtained from the database are stored as an array.

[0119] Step 3:

[0120] The server filters out false and unnecessary information from the search results. A filtering algorithm is used to evaluate the accuracy of the data and its match with user criteria. The output of this filtering step is a cleaned-up list of property information.

[0121] Step 4:

[0122] The server evaluates the removed property information based on the user's lifestyle and preferences. An AI model using TensorFlow or PyTorch scores the properties by comparing their characteristics (location, price, facilities, transportation access, etc.) with the user's conditions. The evaluation results are output as a score and associated with the property information.

[0123] Step 5:

[0124] The server uses the Google Maps API to connect with urban infrastructure data and evaluate the surrounding environment of each property. Using data on public transportation and amenities obtained from the API, it determines whether the property is suitable for the user's lifestyle. The output of this process is an infrastructure evaluation score.

[0125] Step 6:

[0126] The server selects the most suitable property information based on an overall score. It compares the scores of each property and prioritizes selecting the highest-scoring property as a candidate to suggest to the user. This selection result is a list of the best properties that match the user's criteria.

[0127] Step 7:

[0128] The terminal displays optimal property information sent from the server to the user, explaining the selection criteria and recommended features. Through the user interface, detailed property information (score, evaluation reasons, surrounding facilities, etc.) is presented visually.

[0129] Step 8:

[0130] When a user expresses interest in a particular property, the server automatically initiates the contract process. Smart contracts are used to generate digital documents and manage the process. Once the process is complete, relevant notifications are sent to the user.

[0131] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0132] This invention provides a configuration for implementing a real estate information provision system that incorporates an emotion engine that recognizes user emotions. This system consists of a user, a terminal, a server, and an emotion engine.

[0133] First, the user uses their device to input their desired real estate conditions (e.g., location, budget, number of rooms, whether pets are allowed). This information is then sent from the device to the server.

[0134] The server receives the submitted conditions, searches the real estate information database, and retrieves real estate information that matches the conditions. At this stage, the server performs data cleansing to remove false information and information that is not important to the user from the real estate information.

[0135] Next, the server incorporates an emotion engine that recognizes the user's emotional state in real time. This recognition is based on the user's facial expressions, tone of voice, connection time, and preference behavior data. The emotional information analyzed by the emotion engine is used to dynamically adjust the content of the real estate information presented.

[0136] Specifically, if the emotion engine determines that the user is highly interested in or satisfied with the service, the server will present more relevant properties and provide more detailed information. On the other hand, if the user expresses stress or dissatisfaction, the server will narrow down the options and prioritize displaying properties that better match the user's criteria.

[0137] For example, if a user sets the conditions "1LDK in the city center, under 25 million yen, pet-friendly," the initial search might present 10 properties. If the emotion engine detects unfavorable emotions from the user's response, it reduces the number of properties presented and narrows them down to those that particularly match the user's conditions before re-presenting them. Furthermore, for properties that the user shows great interest in, it provides detailed explanatory videos and virtual tours.

[0138] Thus, the present invention aims to improve the user experience by providing real estate information that is adapted to the user's emotions. Furthermore, if contract procedures are required, an automated application process using digital documents is efficiently carried out by the server and guided to the user via the terminal.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] Users use their devices to enter their desired real estate criteria. These criteria can include location, budget, number of rooms, and whether pets are allowed.

[0142] Step 2:

[0143] The terminal sends the entered conditions as data to the server.

[0144] Step 3:

[0145] The server searches the real estate information database based on the conditions it receives. It then collects property information that matches those conditions.

[0146] Step 4:

[0147] The server filters out false or irrelevant information from search results, selecting only reliable information.

[0148] Step 5:

[0149] The server passes the selected real estate information to the emotion engine, which analyzes the user's emotions in real time. The emotion engine analyzes changes in the user's facial expressions and voice based on data acquired from cameras, microphones, and other sensors.

[0150] Step 6:

[0151] The emotion engine adjusts the content of the real estate information presented based on the user's emotions. If the user shows interest, it provides more detailed and relevant real estate information; conversely, if the user is not interested, it provides information more concisely.

[0152] Step 7:

[0153] The server sends the adjusted real estate information to the terminal. The terminal displays this information to the user and performs appropriate interactions.

[0154] Step 8:

[0155] The user selects properties of interest based on the information presented. The selection is then sent from the device to the server.

[0156] Step 9:

[0157] The server initiates an automated application process for the selected property. It generates the necessary documents using the selected information and proceeds with the digital signature process.

[0158] Step 10:

[0159] The terminal displays the progress of the application process to the user and guides them through the next necessary actions. Finally, the server confirms the completion of the process and notifies the user.

[0160] (Example 2)

[0161] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0162] Conventional technologies sometimes resulted in lower user satisfaction because they provided real estate information without considering the user's individual emotional state. Furthermore, too much information or information that causes confusion can hinder user decision-making. In addition, cumbersome and time-consuming contract procedures are also problematic.

[0163] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0164] In this invention, the server includes means for receiving a user's request and searching for geospatial information based on the request, means for removing false or unnecessary information from the searched geospatial information, and means for recognizing the user's emotional state and making an evaluation based on that emotional state. This enables the presentation of optimal geospatial information tailored to each user's emotional state and efficient contract procedures.

[0165] "User requirements" refer to the conditions and preferences specified by the user regarding geospatial information, including financial requirements, location, number of rooms, and animal permits.

[0166] "Geospatial information" refers to data that includes information about the location and surrounding environment of a property, and includes location information and information about related facilities.

[0167] "False information" refers to information that is not based on facts or is potentially misleading, and includes data that lacks accuracy or reliability.

[0168] "Unnecessary information" refers to information that is irrelevant or unnecessary in relation to the purpose or requirements of providing it to the user, and includes data that does not help the user make decisions.

[0169] "Emotional state" refers to the mental or emotional state a user exhibits when viewing information, and is a concept that includes various emotions such as interest, satisfaction, and dissatisfaction.

[0170] "Evaluating" refers to the process of judging the value and suitability of information based on the user's emotional state and needs, and the act of establishing criteria for presenting the most suitable information as an option.

[0171] This system aims to improve the user experience by efficiently providing geospatial information based on diverse user requests. Users first input specific requests regarding real estate using a terminal. These include financial conditions, location, number of rooms, and animal permits.

[0172] The terminal uses dedicated software to send user requests to the server. The server searches for geospatial information corresponding to the user's request on a high-performance database system. The database system used here is particularly well-suited for processing large amounts of data.

[0173] Next, the server uses its built-in emotion engine to evaluate the user's emotional state. This involves using facial recognition systems and voice analysis technologies to identify emotions from the user's facial expressions and tone of voice. The analyzed emotional information is stored by machine learning algorithms, and evaluations of user satisfaction and interest are performed.

[0174] For example, suppose a user enters the following criteria: "2LDK apartment in the city center, under 30 million yen, children allowed." Based on these criteria, the server first retrieves matching properties, and then, if it senses joy or satisfaction from the user's expression, it provides additional detailed information on related properties.

[0175] The generative AI model used in this process supports highly accurate sentiment analysis, enabling more user-friendly information delivery. An example of a specific prompt would be: "How can we build a system that determines whether a user is satisfied or dissatisfied based on their facial expressions and voice tone data, and dynamically changes the level of real estate information presented?"

[0176] If a contract application is ultimately required, the server automates the contract process using electronic documents, ensuring efficient process management. This system configuration allows users to quickly and reliably obtain real estate information and enter into contracts.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] The user uses a terminal to input property-related conditions. These conditions include financial requirements, location, number of rooms, and animal permits. This input data is packetized by the terminal and sent to the server. The condition data is then returned to the server as output.

[0180] Step 2:

[0181] The server searches for geospatial information in a high-performance database system based on the user's specified criteria. The input is user criteria data, and all geospatial information in the database is searched. As part of the data processing, information matching the criteria is filtered, and a list of matching property information is generated as output.

[0182] Step 3:

[0183] The server performs data cleansing on filtered geospatial information, removing false and duplicate information. The input is the property information list obtained above, and the output is a clean property information list. A rule-based, trained algorithm is used for operation.

[0184] Step 4:

[0185] The server uses an emotion engine on a cloud platform to evaluate the user's emotional state. Facial expressions and voice data sent from the device are input, analyzed by machine learning algorithms, and the user's emotional state is output. Specifically, image analysis and voice analysis technologies are applied.

[0186] Step 5:

[0187] Based on the acquired sentiment information, the server dynamically adjusts the property information displayed according to the user's interests and satisfaction levels. The input consists of an improved property information list and the user's sentiment state data, and the server outputs the most relevant information. For example, if the user shows interest, additional details and related properties are provided.

[0188] Step 6:

[0189] Ultimately, when necessary for a contract, the server automates the contract process using electronic documents, providing a streamlined workflow. Appropriate digital forms and contract documents are filled in, and the necessary information is output to the user. Specific features include electronic signatures and auto-fill functionality.

[0190] (Application Example 2)

[0191] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0192] There is a problem in providing optimal living space information that responds to the user's emotions. Existing systems cannot fully utilize emotional data such as the user's facial expressions and voice tone, and may not be able to provide information that meets the user's wishes. In addition, there is the challenge that the application process for living space contracts is complex and time-consuming.

[0193] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0194] In this invention, the server includes means for receiving user conditions and searching for living space information based on those conditions; means for removing false or unnecessary information from the searched living space information; and means for recognizing the user's emotional state based on facial expressions, voice tone, connection time, and preference behavior data. This not only enables the provision of appropriate living space information that corresponds to the user's emotions, but also streamlines the contract procedure.

[0195] "User" refers to a person who searches for and uses information about living spaces.

[0196] "Conditions" refers to the user's preferences or requirements regarding the living space, including costs, geographical range, number of rooms, and pet permits.

[0197] "Residential space information" refers to data related to real estate and rental properties, including details such as location, price, floor plan, and facilities.

[0198] "Emotional state" refers to emotions analyzed based on the user's facial expressions, voice tone, connection time, and preference behavior data.

[0199] A "server" refers to a computer system that manages information about living spaces and performs processes such as searching, removing, evaluating, and recognizing.

[0200] "False information" refers to information that is inaccurate, misleading, or contrary to reality.

[0201] "Unnecessary information" refers to content that is irrelevant to the user's wishes or requirements and is deemed unnecessary for providing information.

[0202] "Evaluation" refers to the process of analyzing and considering information about the living space after removal, based on the user's emotional state.

[0203] "Contract procedures" refer to the process of formally concluding an agreement regarding living space, which usually includes document review and signing.

[0204] An "electronic document" refers to an official document created and transmitted / received in digital format, and is used in contractual procedures and other similar contexts.

[0205] The embodiment of this invention begins with a user using a terminal to input conditions related to their living space. These conditions include costs, geographical range, number of rooms, and animal permit status, and this information is transmitted from the terminal to a server. The server searches a living space information database based on the transmitted conditions and collects the relevant information. In this process, the server performs data cleansing to remove false information and information that is not necessary for the user.

[0206] The server incorporates an emotion engine that utilizes machine learning libraries such as TensorFlow to recognize the user's emotional state (facial expressions, voice tone, connection time, and preference data) in real time. This emotional information is used to dynamically adjust the spatial information presented according to the user's interests and satisfaction levels. For example, if high interest is detected, more detailed information about the relevant spatial environment is provided. On the other hand, if stress or dissatisfaction is detected, the information provided is narrowed down.

[0207] Furthermore, to streamline the contract process, the server automates the application process using electronic documents and guides users through their terminals. In this process, the Python programming language and the Google Assistant API are used for speech recognition and the user interface.

[0208] As a concrete example, this system can optimize everything from property search to contract procedures based on the user's emotions. For instance, a possible prompt for the generating AI model could be, "If the user has a relaxed expression, how should we provide more detailed information about the living space?" Based on this prompt, the AI ​​model can generate the optimal way to provide information to the user.

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] The user enters their living space requirements using a terminal. The user enters their preferences, such as cost, geographical area, number of rooms, and pet permit status, and this information is sent from the terminal to the server. The user's requirements data is then generated as output.

[0212] Step 2:

[0213] The server searches the residential space information database based on the received condition data. The input is the user's condition data; the server queries the database and collects the relevant residential space information. The output is the extracted residential space information.

[0214] Step 3:

[0215] The server uses data cleansing techniques to remove false or unnecessary information from the extracted residential space information. The input is the extracted residential space information; the data's integrity and relevance are verified, and unnecessary information is eliminated. The output is the cleansed residential space information.

[0216] Step 4:

[0217] The server uses an emotion engine to recognize the user's emotional state in real time. Inputs include the user's facial expressions, voice tone, connection time, and preference behavior data. The server analyzes this data to determine the emotional state. The output is the user's emotional state data.

[0218] Step 5:

[0219] The server dynamically adjusts the content of the living space information presented based on the user's emotional state data. The input consists of emotional state data and cleansed living space information, and the server changes the level of detail according to the user's interests and satisfaction levels. The output is living space information adjusted according to the user's emotions.

[0220] Step 6:

[0221] When a user enters into a contract for a living space, the server generates electronic documents and automates the process. The input consists of the user's selections, and the server creates the necessary documents for the contract and manages the electronic signature process. The output consists of the digitized contract documents and the completed procedure.

[0222] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0223] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0224] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0228] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0229] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0230] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0231] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0232] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0233] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0234] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0235] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0236] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0237] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0238] This invention provides a configuration for realizing a system that proposes optimal real estate properties based on the user's conditions and lifestyle. This system consists of a user, a terminal, and a server.

[0239] First, the user uses a terminal to input their preferences and requirements for real estate properties (location, budget, number of rooms, pet-friendly, etc.). The terminal sends this information to the server. The server searches the real estate information database based on the received conditions.

[0240] Based on the search results, the server filters out false information and information that the user does not need. Furthermore, using the filtered information, the server uses an AI algorithm to evaluate properties. In the evaluation, features such as the property's location, price, facilities, and transportation access are scored in comparison to the user's lifestyle.

[0241] Based on the evaluation results, the server selects the most suitable real estate information and sends it to the terminal. The terminal displays the received property information to the user and explains the reasons for selection and the recommended points of each property.

[0242] Furthermore, if a user expresses interest in a particular property, the server initiates an automated application process. This includes generating necessary documents, obtaining digital signatures, and notifying relevant parties. The terminal monitors the user's progress and provides guidance to ensure a smooth contract process.

[0243] As a concrete example, suppose a user sets the conditions as "2LDK in a suburban area, under 20 million yen, pet-friendly." The server searches the database for candidate properties according to these conditions and uses AI to evaluate transportation access and the surrounding environment. Once a suitable property is selected, the information is presented to the user, and the process can proceed quickly without going through a real estate agent or property management company. In this way, this system reduces the burden on the user and efficiently supports property selection and contract.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] The user uses a device to enter their preferences and requirements for a real estate property. The entered requirements should be specific, including location, budget, number of rooms, and whether pets are allowed.

[0247] Step 2:

[0248] The terminal receives user information, formats it into digital data, and sends it to the server.

[0249] Step 3:

[0250] The server receives the user's criteria data. It generates a query against the database and searches for real estate information that matches the criteria.

[0251] Step 4:

[0252] The server filters out false and unnecessary information from the retrieved real estate data. Data cleansing techniques are used to ensure the quality of the information.

[0253] Step 5:

[0254] The server sends filtered real estate information to an AI algorithm, which scores each property by matching its characteristics with the user's lifestyle.

[0255] Step 6:

[0256] The server ranks property information based on the scoring results and selects the property that best meets the criteria.

[0257] Step 7:

[0258] The server sends the selected property information to the terminal. The terminal presents the received information to the user, displaying the evaluation points and reasons for recommendation for each property.

[0259] Step 8:

[0260] The user reviews the presented property information and selects the properties that interest them. The user's selection is notified to the server via their device.

[0261] Step 9:

[0262] The server initiates an automated application process for the selected property. It generates the necessary documents, obtains digital signatures, and submits applications to the relevant authorities.

[0263] Step 10:

[0264] The terminal displays the progress of the application process to the user and guides them through the next steps. The server confirms the completion of the process and notifies the user of the result.

[0265] (Example 1)

[0266] Next, we will describe Example 1. 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."

[0267] In real estate property selection, it is difficult for users to efficiently find the optimal property while considering a variety of conditions. Furthermore, the cumbersome paperwork and communication involved in the process consume time and effort. There is a need for a means to solve these problems and enable quick and efficient property selection and contract procedures.

[0268] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0269] In this invention, the server includes means for receiving user conditions via a terminal and securely transmitting them to the server, means for searching a real estate information database based on the conditions and extracting properties that match the conditions, and means for filtering and evaluating real estate information using a generation AI model. This enables the selection of optimal property information according to the user's conditions and the efficient execution of automated real estate contracts.

[0270] A "user" is an individual or organization that uses the system to search for and select real estate property information.

[0271] A "terminal" is an electronic device used by a user to access a system and input or retrieve information.

[0272] A "server" is a central computing system that searches for and evaluates real estate information based on conditions submitted by users and executes the necessary processes.

[0273] A "real estate information database" is a data storage system that stores detailed information about properties and allows users to extract and manage information according to their criteria.

[0274] A "generative AI model" is an artificial intelligence algorithm used to filter and evaluate optimal information based on input data.

[0275] "Lifestyle" refers to elements that reflect the user's preferences and values ​​related to their way of life, and is considered as part of the property evaluation.

[0276] "Evaluation" is the process of indicating the suitability of a property based on the user's criteria using numerical values ​​or indicators.

[0277] A "digital document" is an electronic document used in real estate contract procedures, serving as a substitute for paper-based documents.

[0278] "Electronic signature" is a technology used to verify and authorize the identity of a user on a digital document.

[0279] This invention is a system designed to enable users to efficiently select and contract for real estate properties. The system consists of users, terminals, and a server.

[0280] The user first uses their device to enter their real estate search criteria. Specifically, the device displays an input form where the user can enter criteria such as "budget," "location," "number of rooms," and "pets allowed" into text fields. This information is securely transmitted to the server by the device. In this process, the device encrypts the data using the HTTPS protocol and transfers it to the server's API in JSON format.

[0281] The server searches a real estate information database using the received conditions. A common SQL database system is used for database management. The server creates and executes SQL queries to retrieve property information that matches the conditions. The retrieved information is temporarily stored in the server's memory. The server then filters the real estate information using a generative AI model. The AI ​​model incorporates machine learning algorithms to remove false information and information that is not relevant to the user.

[0282] Next, an AI evaluation takes place, where the server scores properties based on the user's lifestyle. Here, the AI ​​algorithm uses a trained model to match the property's location, price, amenities, and transportation access features with the user's requirements. Properties with high scores are added to the final selection list.

[0283] The server then sends the selected property information to the terminal. The terminal displays the received information in an easy-to-understand manner for the user, highlighting the property's features and recommended points. For properties the user is interested in, the server automatically starts the application process. Digital documents and electronic signatures are used for the application, and document generation and notifications to relevant parties are handled. The terminal displays the user's progress in real time and guides them through the necessary operations to support a smooth contract process.

[0284] For example, when a prompt such as "The user sets the conditions, and the AI ​​scores the best properties and outputs the results" is entered into the system, optimized property information based on the user's conditions is provided.

[0285] The process of the specific process in Example 1 will be described using FIG. 11.

[0286] Step 1:

[0287] The user inputs conditions such as "budget", "location", "number of rooms", "pet allowance" etc. into the input form of the terminal. The input conditions are converted into JSON format by the terminal and sent to the server via the HTTPS protocol. In this process, the user's condition data is encrypted and securely transferred to the server through a secure communication channel.

[0288] Step 2:

[0289] The server analyzes the received JSON-formatted data and searches the real estate information database based on the conditions. The server generates an SQL query and extracts property information that meets the conditions from the database. The input here is the JSON-formatted condition data, and the output is a list of property information as the search result. The server stores these data in temporary memory.

[0290] Step 3:

[0291] The server filters the retrieved property information using the generated AI model. The AI model uses machine learning algorithms to remove false information and information unnecessary for the user from the search results. The input is the list of retrieved property information, and the output is the filtered list of property information. The server evaluates the reliability of each property during this process.

[0292] Step 4:

[0293] Based on the filtered information, the server uses an AI algorithm to evaluate properties. The server scores each property's characteristics (location, price, amenities, transportation access, etc.) based on the user's lifestyle. The input is a filtered list of property information, and the output is a scored list of property information. This evaluation identifies the most suitable property.

[0294] Step 5:

[0295] The server sends high-scoring property information to the terminal. The terminal analyzes the received information and displays it clearly in the user interface. The display includes property details and recommended points based on AI evaluation. The input is scored property information, and the output is a visual presentation of information to the user.

[0296] Step 6:

[0297] When a user expresses interest in a particular property, the terminal sends that information to the server, which automatically initiates the application process. The server generates the necessary digital documents for the application and sends the user a link for electronic signature. The input is the property information selected by the user, and the output is the generated documents and notifications of the process's progress.

[0298] This entire process allows users to efficiently and safely select real estate properties and complete contract procedures.

[0299] (Application Example 1)

[0300] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0301] In modern urban life, in order to improve convenience and the quality of life, an efficient housing selection using digital technology is required. However, existing real estate information systems lack a mechanism to efficiently propose properties that meet individual needs based on user conditions, and are lacking in removing false information and unnecessary information. In addition, there is a current situation where the efficiency of real estate contract procedures is not sufficient.

[0302] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0303] In this invention, the server includes means for receiving user conditions and searching for property information based on the conditions, means for removing false information and unnecessary information, means for evaluating the property information after removal based on the user's lifestyle and preferences, and means for coordinating with urban infrastructure data, evaluating the overall living environment, and proposing an optimal property. As a result, it becomes possible to scrutinize property information according to individual user conditions and efficiently proceed with the contract process.

[0304] "User conditions" refers to specific requirements such as the budget, location, number of rooms, and pet-friendliness that the user desires regarding housing selection.

[0305] "Property information" refers to a set of information including detailed data such as the location, price, facilities, area, and transportation access of real estate.

[0306] "False information" refers to incorrect data that is different from the facts regarding the actual property, and is inaccurate information that should be excluded during selection.

[0307] "Urban infrastructure data" refers to data related to the basic living infrastructure in the city, such as public transportation, road networks, living facilities, educational institutions, and medical facilities.

[0308] "Contract procedures" refers to various procedures, document preparation, signature, notification, and other operations necessary to conclude a lease or sale of a property.

[0309] "Overall living environment" refers to all factors that affect the quality of life, including not only the characteristics of individual properties but also the surrounding community and urban functions.

[0310] This invention provides a system that enables users to efficiently select housing. First, the user inputs their desired housing requirements using a device such as a smartphone. These requirements include budget, location, number of rooms, and whether pets are allowed. The device then transmits this information to a server.

[0311] The server searches a property information database using an AI model based on the received conditions. The Python Django framework is used for this process. After the search, the server filters the information in the database, removing false or unnecessary data. The removed data is then scored by an AI algorithm based on the user's lifestyle and preferences. TensorFlow or PyTorch is used for this process.

[0312] Furthermore, the server utilizes the Google Maps API to connect with urban infrastructure data and perform an overall assessment of the living environment. This makes it possible to select the property that best suits the user's specified criteria. The server sends the selection results to the terminal and presents the user with the most suitable property information. The terminal displays the reasons for the selection and the recommended points of each property to the user.

[0313] Furthermore, when a user expresses interest in a particular property, the server initiates an automated contract process using smart contracts. This generates digital documents and efficiently carries out the necessary procedures.

[0314] For example, if a user enters criteria such as "within 30 minutes of the city center, in a low-humidity area, close to a school, and within a budget of 30 million yen," the server will search for the property that best fits these criteria, comprehensively evaluate the surrounding environment and quality of life, and then present the user with the most suitable property information.

[0315] An example of a prompt message for the generating AI model is: "Provide real estate property data that matches the user's specified conditions and select the optimal property to evaluate its compatibility with the living environment and urban infrastructure."

[0316] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0317] Step 1:

[0318] Users enter their desired property criteria (e.g., budget, location, number of rooms, whether pets are allowed) through their device. The user's input is recorded on the device as form data. This data is then sent to the server in JSON format.

[0319] Step 2:

[0320] The server searches the property information database based on the user's conditions received from the terminal. It uses the Django framework to generate database queries and extract property information that matches the user's conditions. The search results obtained from the database are stored as an array.

[0321] Step 3:

[0322] The server filters out false and unnecessary information from the search results. A filtering algorithm is used to evaluate the accuracy of the data and its match with user criteria. The output of this filtering step is a cleaned-up list of property information.

[0323] Step 4:

[0324] The server evaluates the removed property information based on the user's lifestyle and preferences. An AI model using TensorFlow or PyTorch scores the properties by comparing their characteristics (location, price, facilities, transportation access, etc.) with the user's conditions. The evaluation results are output as a score and associated with the property information.

[0325] Step 5:

[0326] The server uses the Google Maps API to connect with urban infrastructure data and evaluate the surrounding environment of each property. Using data on public transportation and amenities obtained from the API, it determines whether the property is suitable for the user's lifestyle. The output of this process is an infrastructure evaluation score.

[0327] Step 6:

[0328] The server selects the most suitable property information based on an overall score. It compares the scores of each property and prioritizes selecting the highest-scoring property as a candidate to suggest to the user. This selection result is a list of the best properties that match the user's criteria.

[0329] Step 7:

[0330] The terminal displays optimal property information sent from the server to the user, explaining the selection criteria and recommended features. Through the user interface, detailed property information (score, evaluation reasons, surrounding facilities, etc.) is presented visually.

[0331] Step 8:

[0332] When a user expresses interest in a particular property, the server automatically initiates the contract process. Smart contracts are used to generate digital documents and manage the process. Once the process is complete, relevant notifications are sent to the user.

[0333] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0334] This invention provides a configuration for implementing a real estate information provision system that incorporates an emotion engine that recognizes user emotions. This system consists of a user, a terminal, a server, and an emotion engine.

[0335] First, the user uses their device to input their desired real estate conditions (e.g., location, budget, number of rooms, whether pets are allowed). This information is then sent from the device to the server.

[0336] The server receives the submitted conditions, searches the real estate information database, and retrieves real estate information that matches the conditions. At this stage, the server performs data cleansing to remove false information and information that is not important to the user from the real estate information.

[0337] Next, the server incorporates an emotion engine that recognizes the user's emotional state in real time. This recognition is based on the user's facial expressions, tone of voice, connection time, and preference behavior data. The emotional information analyzed by the emotion engine is used to dynamically adjust the content of the real estate information presented.

[0338] Specifically, if the emotion engine determines that the user is highly interested in or satisfied with the service, the server will present more relevant properties and provide more detailed information. On the other hand, if the user expresses stress or dissatisfaction, the server will narrow down the options and prioritize displaying properties that better match the user's criteria.

[0339] For example, if a user sets the conditions "1LDK in the city center, under 25 million yen, pet-friendly," the initial search might present 10 properties. If the emotion engine detects unfavorable emotions from the user's response, it reduces the number of properties presented and narrows them down to those that particularly match the user's conditions before re-presenting them. Furthermore, for properties that the user shows great interest in, it provides detailed explanatory videos and virtual tours.

[0340] Thus, the present invention aims to improve the user experience by providing real estate information that is adapted to the user's emotions. Furthermore, if contract procedures are required, an automated application process using digital documents is efficiently carried out by the server and guided to the user via the terminal.

[0341] The following describes the processing flow.

[0342] Step 1:

[0343] Users use their devices to enter their desired real estate criteria. These criteria can include location, budget, number of rooms, and whether pets are allowed.

[0344] Step 2:

[0345] The terminal sends the entered conditions as data to the server.

[0346] Step 3:

[0347] The server searches the real estate information database based on the conditions it receives. It then collects property information that matches those conditions.

[0348] Step 4:

[0349] The server filters out false or irrelevant information from search results, selecting only reliable information.

[0350] Step 5:

[0351] The server passes the selected real estate information to the emotion engine, which analyzes the user's emotions in real time. The emotion engine analyzes changes in the user's facial expressions and voice based on data acquired from cameras, microphones, and other sensors.

[0352] Step 6:

[0353] The emotion engine adjusts the content of the real estate information presented based on the user's emotions. If the user shows interest, it provides more detailed and relevant real estate information; conversely, if the user is not interested, it provides information more concisely.

[0354] Step 7:

[0355] The server sends the adjusted real estate information to the terminal. The terminal displays this information to the user and performs appropriate interactions.

[0356] Step 8:

[0357] The user selects properties of interest based on the information presented. The selection is then sent from the device to the server.

[0358] Step 9:

[0359] The server initiates an automated application process for the selected property. It generates the necessary documents using the selected information and proceeds with the digital signature process.

[0360] Step 10:

[0361] The terminal displays the progress of the application process to the user and guides them through the next necessary actions. Finally, the server confirms the completion of the process and notifies the user.

[0362] (Example 2)

[0363] Next, we will describe Example 2. 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".

[0364] Conventional technologies sometimes resulted in lower user satisfaction because they provided real estate information without considering the user's individual emotional state. Furthermore, too much information or information that causes confusion can hinder user decision-making. In addition, cumbersome and time-consuming contract procedures are also problematic.

[0365] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0366] In this invention, the server includes means for receiving a user's request and searching for geospatial information based on the request, means for removing false or unnecessary information from the searched geospatial information, and means for recognizing the user's emotional state and making an evaluation based on that emotional state. This enables the presentation of optimal geospatial information tailored to each user's emotional state and efficient contract procedures.

[0367] "User requirements" refer to the conditions and preferences specified by the user regarding geospatial information, including financial requirements, location, number of rooms, and animal permits.

[0368] "Geospatial information" refers to data that includes information about the location and surrounding environment of a property, and includes location information and information about related facilities.

[0369] "False information" refers to information that is not based on facts or is potentially misleading, and includes data that lacks accuracy or reliability.

[0370] "Unnecessary information" refers to information that is irrelevant or unnecessary in relation to the purpose or requirements of providing it to the user, and includes data that does not help the user make decisions.

[0371] "Emotional state" refers to the mental or emotional state a user exhibits when viewing information, and is a concept that includes various emotions such as interest, satisfaction, and dissatisfaction.

[0372] "Evaluating" refers to the process of judging the value and suitability of information based on the user's emotional state and needs, and the act of establishing criteria for presenting the most suitable information as an option.

[0373] This system aims to improve the user experience by efficiently providing geospatial information based on diverse user requests. Users first input specific requests regarding real estate using a terminal. These include financial conditions, location, number of rooms, and animal permits.

[0374] The terminal uses dedicated software to send user requests to the server. The server searches for geospatial information corresponding to the user's request on a high-performance database system. The database system used here is particularly well-suited for processing large amounts of data.

[0375] Next, the server uses its built-in emotion engine to evaluate the user's emotional state. This involves using facial recognition systems and voice analysis technologies to identify emotions from the user's facial expressions and tone of voice. The analyzed emotional information is stored by machine learning algorithms, and evaluations of user satisfaction and interest are performed.

[0376] For example, suppose a user enters the following criteria: "2LDK apartment in the city center, under 30 million yen, children allowed." Based on these criteria, the server first retrieves matching properties, and then, if it senses joy or satisfaction from the user's expression, it provides additional detailed information on related properties.

[0377] The generative AI model used in this process supports highly accurate sentiment analysis, enabling more user-friendly information delivery. An example of a specific prompt would be: "How can we build a system that determines whether a user is satisfied or dissatisfied based on their facial expressions and voice tone data, and dynamically changes the level of real estate information presented?"

[0378] If a contract application is ultimately required, the server automates the contract process using electronic documents, ensuring efficient process management. This system configuration allows users to quickly and reliably obtain real estate information and enter into contracts.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] The user uses a terminal to input property-related conditions. These conditions include financial requirements, location, number of rooms, and animal permits. This input data is packetized by the terminal and sent to the server. The condition data is then returned to the server as output.

[0382] Step 2:

[0383] The server searches for geospatial information in a high-performance database system based on the user's specified criteria. The input is user criteria data, and all geospatial information in the database is searched. As part of the data processing, information matching the criteria is filtered, and a list of matching property information is generated as output.

[0384] Step 3:

[0385] The server performs data cleansing on filtered geospatial information, removing false and duplicate information. The input is the property information list obtained above, and the output is a clean property information list. A rule-based, trained algorithm is used for operation.

[0386] Step 4:

[0387] The server uses an emotion engine on a cloud platform to evaluate the user's emotional state. Facial expressions and voice data sent from the device are input, analyzed by machine learning algorithms, and the user's emotional state is output. Specifically, image analysis and voice analysis technologies are applied.

[0388] Step 5:

[0389] Based on the acquired sentiment information, the server dynamically adjusts the property information displayed according to the user's interests and satisfaction levels. The input consists of an improved property information list and the user's sentiment state data, and the server outputs the most relevant information. For example, if the user shows interest, additional details and related properties are provided.

[0390] Step 6:

[0391] Ultimately, when necessary for a contract, the server automates the contract process using electronic documents, providing a streamlined workflow. Appropriate digital forms and contract documents are filled in, and the necessary information is output to the user. Specific features include electronic signatures and auto-fill functionality.

[0392] (Application Example 2)

[0393] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0394] There is a problem in providing optimal living space information that responds to the user's emotions. Existing systems cannot fully utilize emotional data such as the user's facial expressions and voice tone, and may not be able to provide information that meets the user's wishes. In addition, there is the challenge that the application process for living space contracts is complex and time-consuming.

[0395] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0396] In this invention, the server includes means for receiving user conditions and searching for living space information based on those conditions; means for removing false or unnecessary information from the searched living space information; and means for recognizing the user's emotional state based on facial expressions, voice tone, connection time, and preference behavior data. This not only enables the provision of appropriate living space information that corresponds to the user's emotions, but also streamlines the contract procedure.

[0397] "User" refers to a person who searches for and uses information about living spaces.

[0398] "Conditions" refers to the user's preferences or requirements regarding the living space, including costs, geographical range, number of rooms, and pet permits.

[0399] "Residential space information" refers to data related to real estate and rental properties, including details such as location, price, floor plan, and facilities.

[0400] "Emotional state" refers to emotions analyzed based on the user's facial expressions, voice tone, connection time, and preference behavior data.

[0401] A "server" refers to a computer system that manages information about living spaces and performs processes such as searching, removing, evaluating, and recognizing.

[0402] "False information" refers to information that is inaccurate, misleading, or contrary to reality.

[0403] "Unnecessary information" refers to content that is irrelevant to the user's wishes or requirements and is deemed unnecessary for providing information.

[0404] "Evaluation" refers to the process of analyzing and considering information about the living space after removal, based on the user's emotional state.

[0405] "Contract procedures" refer to the process of formally concluding an agreement regarding living space, which usually includes document review and signing.

[0406] An "electronic document" refers to an official document created and transmitted / received in digital format, and is used in contractual procedures and other similar contexts.

[0407] The embodiment of this invention begins with a user using a terminal to input conditions related to their living space. These conditions include costs, geographical range, number of rooms, and animal permit status, and this information is transmitted from the terminal to a server. The server searches a living space information database based on the transmitted conditions and collects the relevant information. In this process, the server performs data cleansing to remove false information and information that is not necessary for the user.

[0408] The server incorporates an emotion engine that utilizes machine learning libraries such as TensorFlow to recognize the user's emotional state (facial expressions, voice tone, connection time, and preference data) in real time. This emotional information is used to dynamically adjust the spatial information presented according to the user's interests and satisfaction levels. For example, if high interest is detected, more detailed information about the relevant spatial environment is provided. On the other hand, if stress or dissatisfaction is detected, the information provided is narrowed down.

[0409] Furthermore, to streamline the contract process, the server automates the application process using electronic documents and guides users through their terminals. In this process, the Python programming language and the Google Assistant API are used for speech recognition and the user interface.

[0410] As a concrete example, this system can optimize everything from property search to contract procedures based on the user's emotions. For instance, a possible prompt for the generating AI model could be, "If the user has a relaxed expression, how should we provide more detailed information about the living space?" Based on this prompt, the AI ​​model can generate the optimal way to provide information to the user.

[0411] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0412] Step 1:

[0413] The user enters their living space requirements using a terminal. The user enters their preferences, such as cost, geographical area, number of rooms, and pet permit status, and this information is sent from the terminal to the server. The user's requirements data is then generated as output.

[0414] Step 2:

[0415] The server searches the residential space information database based on the received condition data. The input is the user's condition data; the server queries the database and collects the relevant residential space information. The output is the extracted residential space information.

[0416] Step 3:

[0417] The server uses data cleansing techniques to remove false or unnecessary information from the extracted residential space information. The input is the extracted residential space information; the data's integrity and relevance are verified, and unnecessary information is eliminated. The output is the cleansed residential space information.

[0418] Step 4:

[0419] The server uses an emotion engine to recognize the user's emotional state in real time. Inputs include the user's facial expressions, voice tone, connection time, and preference behavior data. The server analyzes this data to determine the emotional state. The output is the user's emotional state data.

[0420] Step 5:

[0421] The server dynamically adjusts the content of the living space information presented based on the user's emotional state data. The input consists of emotional state data and cleansed living space information, and the server changes the level of detail according to the user's interests and satisfaction levels. The output is living space information adjusted according to the user's emotions.

[0422] Step 6:

[0423] When a user enters into a contract for a living space, the server generates electronic documents and automates the process. The input consists of the user's selections, and the server creates the necessary documents for the contract and manages the electronic signature process. The output consists of the digitized contract documents and the completed procedure.

[0424] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0425] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0426] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0427] [Third Embodiment]

[0428] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0429] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0430] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0431] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0432] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0433] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0434] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0435] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0436] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0437] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0438] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0439] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0440] This invention provides a configuration for realizing a system that proposes optimal real estate properties based on the user's conditions and lifestyle. This system consists of a user, a terminal, and a server.

[0441] First, the user uses a terminal to input their preferences and requirements for real estate properties (location, budget, number of rooms, pet-friendly, etc.). The terminal sends this information to the server. The server searches the real estate information database based on the received conditions.

[0442] Based on the search results, the server filters out false information and information that the user does not need. Furthermore, using the filtered information, the server uses an AI algorithm to evaluate properties. In the evaluation, features such as the property's location, price, facilities, and transportation access are scored in comparison to the user's lifestyle.

[0443] Based on the evaluation results, the server selects the most suitable real estate information and sends it to the terminal. The terminal displays the received property information to the user and explains the reasons for selection and the recommended points of each property.

[0444] Furthermore, if a user expresses interest in a particular property, the server initiates an automated application process. This includes generating necessary documents, obtaining digital signatures, and notifying relevant parties. The terminal monitors the user's progress and provides guidance to ensure a smooth contract process.

[0445] As a concrete example, suppose a user sets the conditions as "2LDK in a suburban area, under 20 million yen, pet-friendly." The server searches the database for candidate properties according to these conditions and uses AI to evaluate transportation access and the surrounding environment. Once a suitable property is selected, the information is presented to the user, and the process can proceed quickly without going through a real estate agent or property management company. In this way, this system reduces the burden on the user and efficiently supports property selection and contract.

[0446] The following describes the processing flow.

[0447] Step 1:

[0448] The user uses a device to enter their preferences and requirements for a real estate property. The entered requirements should be specific, including location, budget, number of rooms, and whether pets are allowed.

[0449] Step 2:

[0450] The terminal receives user information, formats it into digital data, and sends it to the server.

[0451] Step 3:

[0452] The server receives the user's criteria data. It generates a query against the database and searches for real estate information that matches the criteria.

[0453] Step 4:

[0454] The server filters out false and unnecessary information from the retrieved real estate data. Data cleansing techniques are used to ensure the quality of the information.

[0455] Step 5:

[0456] The server sends filtered real estate information to an AI algorithm, which scores each property by matching its characteristics with the user's lifestyle.

[0457] Step 6:

[0458] The server ranks property information based on the scoring results and selects the property that best meets the criteria.

[0459] Step 7:

[0460] The server sends the selected property information to the terminal. The terminal presents the received information to the user, displaying the evaluation points and reasons for recommendation for each property.

[0461] Step 8:

[0462] The user reviews the presented property information and selects the properties that interest them. The user's selection is notified to the server via their device.

[0463] Step 9:

[0464] The server initiates an automated application process for the selected property. It generates the necessary documents, obtains digital signatures, and submits applications to the relevant authorities.

[0465] Step 10:

[0466] The terminal displays the progress of the application process to the user and guides them through the next steps. The server confirms the completion of the process and notifies the user of the result.

[0467] (Example 1)

[0468] Next, we will describe Example 1. 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."

[0469] In real estate property selection, it is difficult for users to efficiently find the optimal property while considering a variety of conditions. Furthermore, the cumbersome paperwork and communication involved in the process consume time and effort. There is a need for a means to solve these problems and enable quick and efficient property selection and contract procedures.

[0470] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0471] In this invention, the server includes means for receiving user conditions via a terminal and securely transmitting them to the server, means for searching a real estate information database based on the conditions and extracting properties that match the conditions, and means for filtering and evaluating real estate information using a generation AI model. This enables the selection of optimal property information according to the user's conditions and the efficient execution of automated real estate contracts.

[0472] A "user" is an individual or organization that uses the system to search for and select real estate property information.

[0473] A "terminal" is an electronic device used by a user to access a system and input or retrieve information.

[0474] A "server" is a central computing system that searches for and evaluates real estate information based on conditions submitted by users and executes the necessary processes.

[0475] A "real estate information database" is a data storage system that stores detailed information about properties and allows users to extract and manage information according to their criteria.

[0476] A "generative AI model" is an artificial intelligence algorithm used to filter and evaluate optimal information based on input data.

[0477] "Lifestyle" refers to elements that reflect the user's preferences and values ​​related to their way of life, and is considered as part of the property evaluation.

[0478] "Evaluation" is the process of indicating the suitability of a property based on the user's criteria using numerical values ​​or indicators.

[0479] A "digital document" is an electronic document used in real estate contract procedures, serving as a substitute for paper-based documents.

[0480] "Electronic signature" is a technology used to verify and authorize the identity of a user on a digital document.

[0481] This invention is a system designed to enable users to efficiently select and contract for real estate properties. The system consists of users, terminals, and a server.

[0482] The user first uses their device to enter their real estate search criteria. Specifically, the device displays an input form where the user can enter criteria such as "budget," "location," "number of rooms," and "pets allowed" into text fields. This information is securely transmitted to the server by the device. In this process, the device encrypts the data using the HTTPS protocol and transfers it to the server's API in JSON format.

[0483] The server searches a real estate information database using the received conditions. A common SQL database system is used for database management. The server creates and executes SQL queries to retrieve property information that matches the conditions. The retrieved information is temporarily stored in the server's memory. The server then filters the real estate information using a generative AI model. The AI ​​model incorporates machine learning algorithms to remove false information and information that is not relevant to the user.

[0484] Next, an AI evaluation takes place, where the server scores properties based on the user's lifestyle. Here, the AI ​​algorithm uses a trained model to match the property's location, price, amenities, and transportation access features with the user's requirements. Properties with high scores are added to the final selection list.

[0485] The server then sends the selected property information to the terminal. The terminal displays the received information in an easy-to-understand manner for the user, highlighting the property's features and recommended points. For properties the user is interested in, the server automatically starts the application process. Digital documents and electronic signatures are used for the application, and document generation and notifications to relevant parties are handled. The terminal displays the user's progress in real time and guides them through the necessary operations to support a smooth contract process.

[0486] For example, when a prompt such as "The user sets the conditions, and the AI ​​scores the best properties and outputs the results" is entered into the system, optimized property information based on the user's conditions is provided.

[0487] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0488] Step 1:

[0489] Users enter criteria such as "budget," "location," "number of rooms," and "pets allowed" into an input form on their device. The entered criteria are converted to JSON format by the device and sent to the server via the HTTPS protocol. During this process, the user's criteria data is encrypted and securely transferred to the server through a secure communication channel.

[0490] Step 2:

[0491] The server parses the received JSON data and searches the real estate information database based on the specified conditions. The server generates an SQL query and extracts property information that meets the conditions from the database. The input here is conditional data in JSON format, and the output is a list of property information as search results. The server stores this data in temporary memory.

[0492] Step 3:

[0493] The server filters the searched property information using a generating AI model. The AI ​​model uses machine learning algorithms to remove false or irrelevant information from the search results. The input is a list of searched property information, and the output is a filtered list of property information. The server evaluates the reliability of each property during this process.

[0494] Step 4:

[0495] Based on the filtered information, the server uses an AI algorithm to evaluate properties. The server scores each property's characteristics (location, price, amenities, transportation access, etc.) based on the user's lifestyle. The input is a filtered list of property information, and the output is a scored list of property information. This evaluation identifies the most suitable property.

[0496] Step 5:

[0497] The server sends high-scoring property information to the terminal. The terminal analyzes the received information and displays it clearly in the user interface. The display includes property details and recommended points based on AI evaluation. The input is scored property information, and the output is a visual presentation of information to the user.

[0498] Step 6:

[0499] When a user expresses interest in a particular property, the terminal sends that information to the server, which automatically initiates the application process. The server generates the necessary digital documents for the application and sends the user a link for electronic signature. The input is the property information selected by the user, and the output is the generated documents and notifications of the process's progress.

[0500] This entire process allows users to efficiently and safely select real estate properties and complete contract procedures.

[0501] (Application Example 1)

[0502] Next, we will explain Application Example 1. In the following explanation, 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."

[0503] In modern urban life, efficient housing selection utilizing digital technology is required to improve convenience and quality of life. However, existing real estate information systems lack mechanisms to efficiently propose properties that meet individual needs based on user criteria, and they fail to remove false or unnecessary information. Furthermore, the current real estate contract procedures are not sufficiently efficient.

[0504] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0505] In this invention, the server includes means for receiving user conditions and searching for property information based on those conditions; means for removing false or unnecessary information; means for evaluating the remaining property information based on the user's lifestyle and preferences; and means for linking with urban infrastructure data to evaluate the overall living environment and propose the most suitable property. This makes it possible to scrutinize property information according to the user's individual conditions and efficiently proceed with the contract process.

[0506] "User requirements" refer to specific demands that users have regarding property selection, such as budget, location, number of rooms, and whether or not pets are allowed.

[0507] "Property information" refers to a collection of information that includes detailed data about real estate, such as location, price, facilities, area, and transportation access.

[0508] "False information" refers to incorrect data that differs from the actual facts about a property, and is inaccurate information that should be excluded during the selection process.

[0509] "Urban infrastructure data" refers to data related to the basic infrastructure of a city, such as public transportation, road networks, living facilities, educational institutions, and medical facilities.

[0510] "Contract procedures" refer to the various procedures, document preparation, signing, and notification processes necessary to finalize a lease or sale of a property.

[0511] "Overall living environment" refers to all factors that affect the quality of life, including not only the characteristics of individual properties but also the surrounding community and urban functions.

[0512] This invention provides a system that enables users to efficiently select housing. First, the user inputs their desired housing requirements using a device such as a smartphone. These requirements include budget, location, number of rooms, and whether pets are allowed. The device then transmits this information to a server.

[0513] The server searches a property information database using an AI model based on the received conditions. The Python Django framework is used for this process. After the search, the server filters the information in the database, removing false or unnecessary data. The removed data is then scored by an AI algorithm based on the user's lifestyle and preferences. TensorFlow or PyTorch is used for this process.

[0514] Furthermore, the server utilizes the Google Maps API to connect with urban infrastructure data and perform an overall assessment of the living environment. This makes it possible to select the property that best suits the user's specified criteria. The server sends the selection results to the terminal and presents the user with the most suitable property information. The terminal displays the reasons for the selection and the recommended points of each property to the user.

[0515] Furthermore, when a user expresses interest in a particular property, the server initiates an automated contract process using smart contracts. This generates digital documents and efficiently carries out the necessary procedures.

[0516] For example, if a user enters criteria such as "within 30 minutes of the city center, in a low-humidity area, close to a school, and within a budget of 30 million yen," the server will search for the property that best fits these criteria, comprehensively evaluate the surrounding environment and quality of life, and then present the user with the most suitable property information.

[0517] An example of a prompt message for the generating AI model is: "Provide real estate property data that matches the user's specified conditions and select the optimal property to evaluate its compatibility with the living environment and urban infrastructure."

[0518] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0519] Step 1:

[0520] Users enter their desired property criteria (e.g., budget, location, number of rooms, whether pets are allowed) through their device. The user's input is recorded on the device as form data. This data is then sent to the server in JSON format.

[0521] Step 2:

[0522] The server searches the property information database based on the user's conditions received from the terminal. It uses the Django framework to generate database queries and extract property information that matches the user's conditions. The search results obtained from the database are stored as an array.

[0523] Step 3:

[0524] The server filters out false and unnecessary information from the search results. A filtering algorithm is used to evaluate the accuracy of the data and its match with user criteria. The output of this filtering step is a cleaned-up list of property information.

[0525] Step 4:

[0526] The server evaluates the removed property information based on the user's lifestyle and preferences. An AI model using TensorFlow or PyTorch scores the properties by comparing their characteristics (location, price, facilities, transportation access, etc.) with the user's conditions. The evaluation results are output as a score and associated with the property information.

[0527] Step 5:

[0528] The server uses the Google Maps API to connect with urban infrastructure data and evaluate the surrounding environment of each property. Using data on public transportation and amenities obtained from the API, it determines whether the property is suitable for the user's lifestyle. The output of this process is an infrastructure evaluation score.

[0529] Step 6:

[0530] The server selects the most suitable property information based on an overall score. It compares the scores of each property and prioritizes selecting the highest-scoring property as a candidate to suggest to the user. This selection result is a list of the best properties that match the user's criteria.

[0531] Step 7:

[0532] The terminal displays optimal property information sent from the server to the user, explaining the selection criteria and recommended features. Through the user interface, detailed property information (score, evaluation reasons, surrounding facilities, etc.) is presented visually.

[0533] Step 8:

[0534] When a user expresses interest in a particular property, the server automatically initiates the contract process. Smart contracts are used to generate digital documents and manage the process. Once the process is complete, relevant notifications are sent to the user.

[0535] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0536] This invention provides a configuration for implementing a real estate information provision system that incorporates an emotion engine that recognizes user emotions. This system consists of a user, a terminal, a server, and an emotion engine.

[0537] First, the user uses their device to input their desired real estate conditions (e.g., location, budget, number of rooms, whether pets are allowed). This information is then sent from the device to the server.

[0538] The server receives the submitted conditions, searches the real estate information database, and retrieves real estate information that matches the conditions. At this stage, the server performs data cleansing to remove false information and information that is not important to the user from the real estate information.

[0539] Next, the server incorporates an emotion engine that recognizes the user's emotional state in real time. This recognition is based on the user's facial expressions, tone of voice, connection time, and preference behavior data. The emotional information analyzed by the emotion engine is used to dynamically adjust the content of the real estate information presented.

[0540] Specifically, if the emotion engine determines that the user is highly interested in or satisfied with the service, the server will present more relevant properties and provide more detailed information. On the other hand, if the user expresses stress or dissatisfaction, the server will narrow down the options and prioritize displaying properties that better match the user's criteria.

[0541] For example, if a user sets the conditions "1LDK in the city center, under 25 million yen, pet-friendly," the initial search might present 10 properties. If the emotion engine detects unfavorable emotions from the user's response, it reduces the number of properties presented and narrows them down to those that particularly match the user's conditions before re-presenting them. Furthermore, for properties that the user shows great interest in, it provides detailed explanatory videos and virtual tours.

[0542] Thus, the present invention aims to improve the user experience by providing real estate information that is adapted to the user's emotions. Furthermore, if contract procedures are required, an automated application process using digital documents is efficiently carried out by the server and guided to the user via the terminal.

[0543] The following describes the processing flow.

[0544] Step 1:

[0545] Users use their devices to enter their desired real estate criteria. These criteria can include location, budget, number of rooms, and whether pets are allowed.

[0546] Step 2:

[0547] The terminal sends the entered conditions as data to the server.

[0548] Step 3:

[0549] The server searches the real estate information database based on the conditions it receives. It then collects property information that matches those conditions.

[0550] Step 4:

[0551] The server filters out false or irrelevant information from search results, selecting only reliable information.

[0552] Step 5:

[0553] The server passes the selected real estate information to the emotion engine, which analyzes the user's emotions in real time. The emotion engine analyzes changes in the user's facial expressions and voice based on data acquired from cameras, microphones, and other sensors.

[0554] Step 6:

[0555] The emotion engine adjusts the content of the real estate information presented based on the user's emotions. If the user shows interest, it provides more detailed and relevant real estate information; conversely, if the user is not interested, it provides information more concisely.

[0556] Step 7:

[0557] The server sends the adjusted real estate information to the terminal. The terminal displays this information to the user and performs appropriate interactions.

[0558] Step 8:

[0559] The user selects properties of interest based on the information presented. The selection is then sent from the device to the server.

[0560] Step 9:

[0561] The server initiates an automated application process for the selected property. It generates the necessary documents using the selected information and proceeds with the digital signature process.

[0562] Step 10:

[0563] The terminal displays the progress of the application process to the user and guides them through the next necessary actions. Finally, the server confirms the completion of the process and notifies the user.

[0564] (Example 2)

[0565] Next, we will describe Example 2. 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."

[0566] Conventional technologies sometimes resulted in lower user satisfaction because they provided real estate information without considering the user's individual emotional state. Furthermore, too much information or information that causes confusion can hinder user decision-making. In addition, cumbersome and time-consuming contract procedures are also problematic.

[0567] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0568] In this invention, the server includes means for receiving a user's request and searching for geospatial information based on the request, means for removing false or unnecessary information from the searched geospatial information, and means for recognizing the user's emotional state and making an evaluation based on that emotional state. This enables the presentation of optimal geospatial information tailored to each user's emotional state and efficient contract procedures.

[0569] "User requirements" refer to the conditions and preferences specified by the user regarding geospatial information, including financial requirements, location, number of rooms, and animal permits.

[0570] "Geospatial information" refers to data that includes information about the location and surrounding environment of a property, and includes location information and information about related facilities.

[0571] "False information" refers to information that is not based on facts or is potentially misleading, and includes data that lacks accuracy or reliability.

[0572] "Unnecessary information" refers to information that is irrelevant or unnecessary in relation to the purpose or requirements of providing it to the user, and includes data that does not help the user make decisions.

[0573] "Emotional state" refers to the mental or emotional state a user exhibits when viewing information, and is a concept that includes various emotions such as interest, satisfaction, and dissatisfaction.

[0574] "Evaluating" refers to the process of judging the value and suitability of information based on the user's emotional state and needs, and the act of establishing criteria for presenting the most suitable information as an option.

[0575] This system aims to improve the user experience by efficiently providing geospatial information based on diverse user requests. Users first input specific requests regarding real estate using a terminal. These include financial conditions, location, number of rooms, and animal permits.

[0576] The terminal uses dedicated software to send user requests to the server. The server searches for geospatial information corresponding to the user's request on a high-performance database system. The database system used here is particularly well-suited for processing large amounts of data.

[0577] Next, the server uses its built-in emotion engine to evaluate the user's emotional state. This involves using facial recognition systems and voice analysis technologies to identify emotions from the user's facial expressions and tone of voice. The analyzed emotional information is stored by machine learning algorithms, and evaluations of user satisfaction and interest are performed.

[0578] For example, suppose a user enters the following criteria: "2LDK apartment in the city center, under 30 million yen, children allowed." Based on these criteria, the server first retrieves matching properties, and then, if it senses joy or satisfaction from the user's expression, it provides additional detailed information on related properties.

[0579] The generative AI model used in this process supports highly accurate sentiment analysis, enabling more user-friendly information delivery. An example of a specific prompt would be: "How can we build a system that determines whether a user is satisfied or dissatisfied based on their facial expressions and voice tone data, and dynamically changes the level of real estate information presented?"

[0580] If a contract application is ultimately required, the server automates the contract process using electronic documents, ensuring efficient process management. This system configuration allows users to quickly and reliably obtain real estate information and enter into contracts.

[0581] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0582] Step 1:

[0583] The user uses a terminal to input property-related conditions. These conditions include financial requirements, location, number of rooms, and animal permits. This input data is packetized by the terminal and sent to the server. The condition data is then returned to the server as output.

[0584] Step 2:

[0585] The server searches for geospatial information in a high-performance database system based on the user's specified criteria. The input is user criteria data, and all geospatial information in the database is searched. As part of the data processing, information matching the criteria is filtered, and a list of matching property information is generated as output.

[0586] Step 3:

[0587] The server performs data cleansing on filtered geospatial information, removing false and duplicate information. The input is the property information list obtained above, and the output is a clean property information list. A rule-based, trained algorithm is used for operation.

[0588] Step 4:

[0589] The server uses an emotion engine on a cloud platform to evaluate the user's emotional state. Facial expressions and voice data sent from the device are input, analyzed by machine learning algorithms, and the user's emotional state is output. Specifically, image analysis and voice analysis technologies are applied.

[0590] Step 5:

[0591] Based on the acquired sentiment information, the server dynamically adjusts the property information displayed according to the user's interests and satisfaction levels. The input consists of an improved property information list and the user's sentiment state data, and the server outputs the most relevant information. For example, if the user shows interest, additional details and related properties are provided.

[0592] Step 6:

[0593] Ultimately, when necessary for a contract, the server automates the contract process using electronic documents, providing a streamlined workflow. Appropriate digital forms and contract documents are filled in, and the necessary information is output to the user. Specific features include electronic signatures and auto-fill functionality.

[0594] (Application Example 2)

[0595] Next, we will explain application example 2. In the following explanation, 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."

[0596] There is a problem in providing optimal living space information that responds to the user's emotions. Existing systems cannot fully utilize emotional data such as the user's facial expressions and voice tone, and may not be able to provide information that meets the user's wishes. In addition, there is the challenge that the application process for living space contracts is complex and time-consuming.

[0597] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0598] In this invention, the server includes means for receiving user conditions and searching for living space information based on those conditions; means for removing false or unnecessary information from the searched living space information; and means for recognizing the user's emotional state based on facial expressions, voice tone, connection time, and preference behavior data. This not only enables the provision of appropriate living space information that corresponds to the user's emotions, but also streamlines the contract procedure.

[0599] "User" refers to a person who searches for and uses information about living spaces.

[0600] "Conditions" refers to the user's preferences or requirements regarding the living space, including costs, geographical range, number of rooms, and pet permits.

[0601] "Residential space information" refers to data related to real estate and rental properties, including details such as location, price, floor plan, and facilities.

[0602] "Emotional state" refers to emotions analyzed based on the user's facial expressions, voice tone, connection time, and preference behavior data.

[0603] A "server" refers to a computer system that manages information about living spaces and performs processes such as searching, removing, evaluating, and recognizing.

[0604] "False information" refers to information that is inaccurate, misleading, or contrary to reality.

[0605] "Unnecessary information" refers to content that is irrelevant to the user's wishes or requirements and is deemed unnecessary for providing information.

[0606] "Evaluation" refers to the process of analyzing and considering information about the living space after removal, based on the user's emotional state.

[0607] "Contract procedures" refer to the process of formally concluding an agreement regarding living space, which usually includes document review and signing.

[0608] An "electronic document" refers to an official document created and transmitted / received in digital format, and is used in contractual procedures and other similar contexts.

[0609] The embodiment of this invention begins with a user using a terminal to input conditions related to their living space. These conditions include costs, geographical range, number of rooms, and animal permit status, and this information is transmitted from the terminal to a server. The server searches a living space information database based on the transmitted conditions and collects the relevant information. In this process, the server performs data cleansing to remove false information and information that is not necessary for the user.

[0610] The server incorporates an emotion engine that utilizes machine learning libraries such as TensorFlow to recognize the user's emotional state (facial expressions, voice tone, connection time, and preference data) in real time. This emotional information is used to dynamically adjust the spatial information presented according to the user's interests and satisfaction levels. For example, if high interest is detected, more detailed information about the relevant spatial environment is provided. On the other hand, if stress or dissatisfaction is detected, the information provided is narrowed down.

[0611] Furthermore, to streamline the contract process, the server automates the application process using electronic documents and guides users through their terminals. In this process, the Python programming language and the Google Assistant API are used for speech recognition and the user interface.

[0612] As a concrete example, this system can optimize everything from property search to contract procedures based on the user's emotions. For instance, a possible prompt for the generating AI model could be, "If the user has a relaxed expression, how should we provide more detailed information about the living space?" Based on this prompt, the AI ​​model can generate the optimal way to provide information to the user.

[0613] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0614] Step 1:

[0615] The user enters their living space requirements using a terminal. The user enters their preferences, such as cost, geographical area, number of rooms, and pet permit status, and this information is sent from the terminal to the server. The user's requirements data is then generated as output.

[0616] Step 2:

[0617] The server searches the residential space information database based on the received condition data. The input is the user's condition data; the server queries the database and collects the relevant residential space information. The output is the extracted residential space information.

[0618] Step 3:

[0619] The server uses data cleansing techniques to remove false or unnecessary information from the extracted residential space information. The input is the extracted residential space information; the data's integrity and relevance are verified, and unnecessary information is eliminated. The output is the cleansed residential space information.

[0620] Step 4:

[0621] The server uses an emotion engine to recognize the user's emotional state in real time. Inputs include the user's facial expressions, voice tone, connection time, and preference behavior data. The server analyzes this data to determine the emotional state. The output is the user's emotional state data.

[0622] Step 5:

[0623] The server dynamically adjusts the content of the living space information presented based on the user's emotional state data. The input consists of emotional state data and cleansed living space information, and the server changes the level of detail according to the user's interests and satisfaction levels. The output is living space information adjusted according to the user's emotions.

[0624] Step 6:

[0625] When a user enters into a contract for a living space, the server generates electronic documents and automates the process. The input consists of the user's selections, and the server creates the necessary documents for the contract and manages the electronic signature process. The output consists of the digitized contract documents and the completed procedure.

[0626] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0627] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0628] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0629] [Fourth Embodiment]

[0630] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0631] As shown in Figure 7, the 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.

[0632] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0633] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0634] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0635] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0636] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0637] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0638] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0639] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0640] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0641] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0642] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0643] This invention provides a configuration for realizing a system that proposes optimal real estate properties based on the user's conditions and lifestyle. This system consists of a user, a terminal, and a server.

[0644] First, the user uses a terminal to input their preferences and requirements for real estate properties (location, budget, number of rooms, pet-friendly, etc.). The terminal sends this information to the server. The server searches the real estate information database based on the received conditions.

[0645] Based on the search results, the server filters out false information and information that the user does not need. Furthermore, using the filtered information, the server uses an AI algorithm to evaluate properties. In the evaluation, features such as the property's location, price, facilities, and transportation access are scored in comparison to the user's lifestyle.

[0646] Based on the evaluation results, the server selects the most suitable real estate information and sends it to the terminal. The terminal displays the received property information to the user and explains the reasons for selection and the recommended points of each property.

[0647] Furthermore, if a user expresses interest in a particular property, the server initiates an automated application process. This includes generating necessary documents, obtaining digital signatures, and notifying relevant parties. The terminal monitors the user's progress and provides guidance to ensure a smooth contract process.

[0648] As a concrete example, suppose a user sets the conditions as "2LDK in a suburban area, under 20 million yen, pet-friendly." The server searches the database for candidate properties according to these conditions and uses AI to evaluate transportation access and the surrounding environment. Once a suitable property is selected, the information is presented to the user, and the process can proceed quickly without going through a real estate agent or property management company. In this way, this system reduces the burden on the user and efficiently supports property selection and contract.

[0649] The following describes the processing flow.

[0650] Step 1:

[0651] The user uses a device to enter their preferences and requirements for a real estate property. The entered requirements should be specific, including location, budget, number of rooms, and whether pets are allowed.

[0652] Step 2:

[0653] The terminal receives user information, formats it into digital data, and sends it to the server.

[0654] Step 3:

[0655] The server receives the user's criteria data. It generates a query against the database and searches for real estate information that matches the criteria.

[0656] Step 4:

[0657] The server filters out false and unnecessary information from the retrieved real estate data. Data cleansing techniques are used to ensure the quality of the information.

[0658] Step 5:

[0659] The server sends filtered real estate information to an AI algorithm, which scores each property by matching its characteristics with the user's lifestyle.

[0660] Step 6:

[0661] The server ranks property information based on the scoring results and selects the property that best meets the criteria.

[0662] Step 7:

[0663] The server sends the selected property information to the terminal. The terminal presents the received information to the user, displaying the evaluation points and reasons for recommendation for each property.

[0664] Step 8:

[0665] The user reviews the presented property information and selects the properties that interest them. The user's selection is notified to the server via their device.

[0666] Step 9:

[0667] The server initiates an automated application process for the selected property. It generates the necessary documents, obtains digital signatures, and submits applications to the relevant authorities.

[0668] Step 10:

[0669] The terminal displays the progress of the application process to the user and guides them through the next steps. The server confirms the completion of the process and notifies the user of the result.

[0670] (Example 1)

[0671] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0672] In real estate property selection, it is difficult for users to efficiently find the optimal property while considering a variety of conditions. Furthermore, the cumbersome paperwork and communication involved in the process consume time and effort. There is a need for a means to solve these problems and enable quick and efficient property selection and contract procedures.

[0673] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0674] In this invention, the server includes means for receiving user conditions via a terminal and securely transmitting them to the server, means for searching a real estate information database based on the conditions and extracting properties that match the conditions, and means for filtering and evaluating real estate information using a generation AI model. This enables the selection of optimal property information according to the user's conditions and the efficient execution of automated real estate contracts.

[0675] A "user" is an individual or organization that uses the system to search for and select real estate property information.

[0676] A "terminal" is an electronic device used by a user to access a system and input or retrieve information.

[0677] A "server" is a central computing system that searches for and evaluates real estate information based on conditions submitted by users and executes the necessary processes.

[0678] A "real estate information database" is a data storage system that stores detailed information about properties and allows users to extract and manage information according to their criteria.

[0679] A "generative AI model" is an artificial intelligence algorithm used to filter and evaluate optimal information based on input data.

[0680] "Lifestyle" refers to elements that reflect the user's preferences and values ​​related to their way of life, and is considered as part of the property evaluation.

[0681] "Evaluation" is the process of indicating the suitability of a property based on the user's criteria using numerical values ​​or indicators.

[0682] A "digital document" is an electronic document used in real estate contract procedures, serving as a substitute for paper-based documents.

[0683] "Electronic signature" is a technology used to verify and authorize the identity of a user on a digital document.

[0684] This invention is a system designed to enable users to efficiently select and contract for real estate properties. The system consists of users, terminals, and a server.

[0685] The user first uses their device to enter their real estate search criteria. Specifically, the device displays an input form where the user can enter criteria such as "budget," "location," "number of rooms," and "pets allowed" into text fields. This information is securely transmitted to the server by the device. In this process, the device encrypts the data using the HTTPS protocol and transfers it to the server's API in JSON format.

[0686] The server searches a real estate information database using the received conditions. A common SQL database system is used for database management. The server creates and executes SQL queries to retrieve property information that matches the conditions. The retrieved information is temporarily stored in the server's memory. The server then filters the real estate information using a generative AI model. The AI ​​model incorporates machine learning algorithms to remove false information and information that is not relevant to the user.

[0687] Next, an AI evaluation takes place, where the server scores properties based on the user's lifestyle. Here, the AI ​​algorithm uses a trained model to match the property's location, price, amenities, and transportation access features with the user's requirements. Properties with high scores are added to the final selection list.

[0688] The server then sends the selected property information to the terminal. The terminal displays the received information in an easy-to-understand manner for the user, highlighting the property's features and recommended points. For properties the user is interested in, the server automatically starts the application process. Digital documents and electronic signatures are used for the application, and document generation and notifications to relevant parties are handled. The terminal displays the user's progress in real time and guides them through the necessary operations to support a smooth contract process.

[0689] For example, when a prompt such as "The user sets the conditions, and the AI ​​scores the best properties and outputs the results" is entered into the system, optimized property information based on the user's conditions is provided.

[0690] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0691] Step 1:

[0692] Users enter criteria such as "budget," "location," "number of rooms," and "pets allowed" into an input form on their device. The entered criteria are converted to JSON format by the device and sent to the server via the HTTPS protocol. During this process, the user's criteria data is encrypted and securely transferred to the server through a secure communication channel.

[0693] Step 2:

[0694] The server parses the received JSON data and searches the real estate information database based on the specified conditions. The server generates an SQL query and extracts property information that meets the conditions from the database. The input here is conditional data in JSON format, and the output is a list of property information as search results. The server stores this data in temporary memory.

[0695] Step 3:

[0696] The server filters the searched property information using a generating AI model. The AI ​​model uses machine learning algorithms to remove false or irrelevant information from the search results. The input is a list of searched property information, and the output is a filtered list of property information. The server evaluates the reliability of each property during this process.

[0697] Step 4:

[0698] Based on the filtered information, the server uses an AI algorithm to evaluate properties. The server scores each property's characteristics (location, price, amenities, transportation access, etc.) based on the user's lifestyle. The input is a filtered list of property information, and the output is a scored list of property information. This evaluation identifies the most suitable property.

[0699] Step 5:

[0700] The server sends high-scoring property information to the terminal. The terminal analyzes the received information and displays it clearly in the user interface. The display includes property details and recommended points based on AI evaluation. The input is scored property information, and the output is a visual presentation of information to the user.

[0701] Step 6:

[0702] When a user expresses interest in a particular property, the terminal sends that information to the server, which automatically initiates the application process. The server generates the necessary digital documents for the application and sends the user a link for electronic signature. The input is the property information selected by the user, and the output is the generated documents and notifications of the process's progress.

[0703] This entire process allows users to efficiently and safely select real estate properties and complete contract procedures.

[0704] (Application Example 1)

[0705] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] In modern urban life, efficient housing selection utilizing digital technology is required to improve convenience and quality of life. However, existing real estate information systems lack mechanisms to efficiently propose properties that meet individual needs based on user criteria, and they fail to remove false or unnecessary information. Furthermore, the current real estate contract procedures are not sufficiently efficient.

[0707] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0708] In this invention, the server includes means for receiving user conditions and searching for property information based on those conditions; means for removing false or unnecessary information; means for evaluating the remaining property information based on the user's lifestyle and preferences; and means for linking with urban infrastructure data to evaluate the overall living environment and propose the most suitable property. This makes it possible to scrutinize property information according to the user's individual conditions and efficiently proceed with the contract process.

[0709] "User requirements" refer to specific demands that users have regarding property selection, such as budget, location, number of rooms, and whether or not pets are allowed.

[0710] "Property information" refers to a collection of information that includes detailed data about real estate, such as location, price, facilities, area, and transportation access.

[0711] "False information" refers to incorrect data that differs from the actual facts about a property, and is inaccurate information that should be excluded during the selection process.

[0712] "Urban infrastructure data" refers to data related to the basic infrastructure of a city, such as public transportation, road networks, living facilities, educational institutions, and medical facilities.

[0713] "Contract procedures" refer to the various procedures, document preparation, signing, and notification processes necessary to finalize a lease or sale of a property.

[0714] "Overall living environment" refers to all factors that affect the quality of life, including not only the characteristics of individual properties but also the surrounding community and urban functions.

[0715] This invention provides a system that enables users to efficiently select housing. First, the user inputs their desired housing requirements using a device such as a smartphone. These requirements include budget, location, number of rooms, and whether pets are allowed. The device then transmits this information to a server.

[0716] The server searches a property information database using an AI model based on the received conditions. The Python Django framework is used for this process. After the search, the server filters the information in the database, removing false or unnecessary data. The removed data is then scored by an AI algorithm based on the user's lifestyle and preferences. TensorFlow or PyTorch is used for this process.

[0717] Furthermore, the server utilizes the Google Maps API to connect with urban infrastructure data and perform an overall assessment of the living environment. This makes it possible to select the property that best suits the user's specified criteria. The server sends the selection results to the terminal and presents the user with the most suitable property information. The terminal displays the reasons for the selection and the recommended points of each property to the user.

[0718] Furthermore, when a user expresses interest in a particular property, the server initiates an automated contract process using smart contracts. This generates digital documents and efficiently carries out the necessary procedures.

[0719] For example, if a user enters criteria such as "within 30 minutes of the city center, in a low-humidity area, close to a school, and within a budget of 30 million yen," the server will search for the property that best fits these criteria, comprehensively evaluate the surrounding environment and quality of life, and then present the user with the most suitable property information.

[0720] An example of a prompt message for the generating AI model is: "Provide real estate property data that matches the user's specified conditions and select the optimal property to evaluate its compatibility with the living environment and urban infrastructure."

[0721] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0722] Step 1:

[0723] Users enter their desired property criteria (e.g., budget, location, number of rooms, whether pets are allowed) through their device. The user's input is recorded on the device as form data. This data is then sent to the server in JSON format.

[0724] Step 2:

[0725] The server searches the property information database based on the user's conditions received from the terminal. It uses the Django framework to generate database queries and extract property information that matches the user's conditions. The search results obtained from the database are stored as an array.

[0726] Step 3:

[0727] The server filters out false and unnecessary information from the search results. A filtering algorithm is used to evaluate the accuracy of the data and its match with user criteria. The output of this filtering step is a cleaned-up list of property information.

[0728] Step 4:

[0729] The server evaluates the removed property information based on the user's lifestyle and preferences. An AI model using TensorFlow or PyTorch scores the properties by comparing their characteristics (location, price, facilities, transportation access, etc.) with the user's conditions. The evaluation results are output as a score and associated with the property information.

[0730] Step 5:

[0731] The server uses the Google Maps API to connect with urban infrastructure data and evaluate the surrounding environment of each property. Using data on public transportation and amenities obtained from the API, it determines whether the property is suitable for the user's lifestyle. The output of this process is an infrastructure evaluation score.

[0732] Step 6:

[0733] The server selects the most suitable property information based on an overall score. It compares the scores of each property and prioritizes selecting the highest-scoring property as a candidate to suggest to the user. This selection result is a list of the best properties that match the user's criteria.

[0734] Step 7:

[0735] The terminal displays optimal property information sent from the server to the user, explaining the selection criteria and recommended features. Through the user interface, detailed property information (score, evaluation reasons, surrounding facilities, etc.) is presented visually.

[0736] Step 8:

[0737] When a user expresses interest in a particular property, the server automatically initiates the contract process. Smart contracts are used to generate digital documents and manage the process. Once the process is complete, relevant notifications are sent to the user.

[0738] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0739] This invention provides a configuration for implementing a real estate information provision system that incorporates an emotion engine that recognizes user emotions. This system consists of a user, a terminal, a server, and an emotion engine.

[0740] First, the user uses their device to input their desired real estate conditions (e.g., location, budget, number of rooms, whether pets are allowed). This information is then sent from the device to the server.

[0741] The server receives the submitted conditions, searches the real estate information database, and retrieves real estate information that matches the conditions. At this stage, the server performs data cleansing to remove false information and information that is not important to the user from the real estate information.

[0742] Next, the server incorporates an emotion engine that recognizes the user's emotional state in real time. This recognition is based on the user's facial expressions, tone of voice, connection time, and preference behavior data. The emotional information analyzed by the emotion engine is used to dynamically adjust the content of the real estate information presented.

[0743] Specifically, if the emotion engine determines that the user is highly interested in or satisfied with the service, the server will present more relevant properties and provide more detailed information. On the other hand, if the user expresses stress or dissatisfaction, the server will narrow down the options and prioritize displaying properties that better match the user's criteria.

[0744] For example, if a user sets the conditions "1LDK in the city center, under 25 million yen, pet-friendly," the initial search might present 10 properties. If the emotion engine detects unfavorable emotions from the user's response, it reduces the number of properties presented and narrows them down to those that particularly match the user's conditions before re-presenting them. Furthermore, for properties that the user shows great interest in, it provides detailed explanatory videos and virtual tours.

[0745] Thus, the present invention aims to improve the user experience by providing real estate information that is adapted to the user's emotions. Furthermore, if contract procedures are required, an automated application process using digital documents is efficiently carried out by the server and guided to the user via the terminal.

[0746] The following describes the processing flow.

[0747] Step 1:

[0748] Users use their devices to enter their desired real estate criteria. These criteria can include location, budget, number of rooms, and whether pets are allowed.

[0749] Step 2:

[0750] The terminal sends the entered conditions as data to the server.

[0751] Step 3:

[0752] The server searches the real estate information database based on the conditions it receives. It then collects property information that matches those conditions.

[0753] Step 4:

[0754] The server filters out false or irrelevant information from search results, selecting only reliable information.

[0755] Step 5:

[0756] The server passes the selected real estate information to the emotion engine, which analyzes the user's emotions in real time. The emotion engine analyzes changes in the user's facial expressions and voice based on data acquired from cameras, microphones, and other sensors.

[0757] Step 6:

[0758] The emotion engine adjusts the content of the real estate information presented based on the user's emotions. If the user shows interest, it provides more detailed and relevant real estate information; conversely, if the user is not interested, it provides information more concisely.

[0759] Step 7:

[0760] The server sends the adjusted real estate information to the terminal. The terminal displays this information to the user and performs appropriate interactions.

[0761] Step 8:

[0762] The user selects properties of interest based on the information presented. The selection is then sent from the device to the server.

[0763] Step 9:

[0764] The server initiates an automated application process for the selected property. It generates the necessary documents using the selected information and proceeds with the digital signature process.

[0765] Step 10:

[0766] The terminal displays the progress of the application process to the user and guides them through the next necessary actions. Finally, the server confirms the completion of the process and notifies the user.

[0767] (Example 2)

[0768] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0769] Conventional technologies sometimes resulted in lower user satisfaction because they provided real estate information without considering the user's individual emotional state. Furthermore, too much information or information that causes confusion can hinder user decision-making. In addition, cumbersome and time-consuming contract procedures are also problematic.

[0770] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0771] In this invention, the server includes means for receiving a user's request and searching for geospatial information based on the request, means for removing false or unnecessary information from the searched geospatial information, and means for recognizing the user's emotional state and making an evaluation based on that emotional state. This enables the presentation of optimal geospatial information tailored to each user's emotional state and efficient contract procedures.

[0772] "User requirements" refer to the conditions and preferences specified by the user regarding geospatial information, including financial requirements, location, number of rooms, and animal permits.

[0773] "Geospatial information" refers to data that includes information about the location and surrounding environment of a property, and includes location information and information about related facilities.

[0774] "False information" refers to information that is not based on facts or is potentially misleading, and includes data that lacks accuracy or reliability.

[0775] "Unnecessary information" refers to information that is irrelevant or unnecessary in relation to the purpose or requirements of providing it to the user, and includes data that does not help the user make decisions.

[0776] "Emotional state" refers to the mental or emotional state a user exhibits when viewing information, and is a concept that includes various emotions such as interest, satisfaction, and dissatisfaction.

[0777] "Evaluating" refers to the process of judging the value and suitability of information based on the user's emotional state and needs, and the act of establishing criteria for presenting the most suitable information as an option.

[0778] This system aims to improve the user experience by efficiently providing geospatial information based on diverse user requests. Users first input specific requests regarding real estate using a terminal. These include financial conditions, location, number of rooms, and animal permits.

[0779] The terminal uses dedicated software to send user requests to the server. The server searches for geospatial information corresponding to the user's request on a high-performance database system. The database system used here is particularly well-suited for processing large amounts of data.

[0780] Next, the server uses its built-in emotion engine to evaluate the user's emotional state. This involves using facial recognition systems and voice analysis technologies to identify emotions from the user's facial expressions and tone of voice. The analyzed emotional information is stored by machine learning algorithms, and evaluations of user satisfaction and interest are performed.

[0781] For example, suppose a user enters the following criteria: "2LDK apartment in the city center, under 30 million yen, children allowed." Based on these criteria, the server first retrieves matching properties, and then, if it senses joy or satisfaction from the user's expression, it provides additional detailed information on related properties.

[0782] The generative AI model used in this process supports highly accurate sentiment analysis, enabling more user-friendly information delivery. An example of a specific prompt would be: "How can we build a system that determines whether a user is satisfied or dissatisfied based on their facial expressions and voice tone data, and dynamically changes the level of real estate information presented?"

[0783] If a contract application is ultimately required, the server automates the contract process using electronic documents, ensuring efficient process management. This system configuration allows users to quickly and reliably obtain real estate information and enter into contracts.

[0784] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0785] Step 1:

[0786] The user uses a terminal to input property-related conditions. These conditions include financial requirements, location, number of rooms, and animal permits. This input data is packetized by the terminal and sent to the server. The condition data is then returned to the server as output.

[0787] Step 2:

[0788] The server searches for geospatial information in a high-performance database system based on the user's specified criteria. The input is user criteria data, and all geospatial information in the database is searched. As part of the data processing, information matching the criteria is filtered, and a list of matching property information is generated as output.

[0789] Step 3:

[0790] The server performs data cleansing on filtered geospatial information, removing false and duplicate information. The input is the property information list obtained above, and the output is a clean property information list. A rule-based, trained algorithm is used for operation.

[0791] Step 4:

[0792] The server uses an emotion engine on a cloud platform to evaluate the user's emotional state. Facial expressions and voice data sent from the device are input, analyzed by machine learning algorithms, and the user's emotional state is output. Specifically, image analysis and voice analysis technologies are applied.

[0793] Step 5:

[0794] Based on the acquired sentiment information, the server dynamically adjusts the property information displayed according to the user's interests and satisfaction levels. The input consists of an improved property information list and the user's sentiment state data, and the server outputs the most relevant information. For example, if the user shows interest, additional details and related properties are provided.

[0795] Step 6:

[0796] Ultimately, when necessary for a contract, the server automates the contract process using electronic documents, providing a streamlined workflow. Appropriate digital forms and contract documents are filled in, and the necessary information is output to the user. Specific features include electronic signatures and auto-fill functionality.

[0797] (Application Example 2)

[0798] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0799] There is a problem in providing optimal living space information that responds to the user's emotions. Existing systems cannot fully utilize emotional data such as the user's facial expressions and voice tone, and may not be able to provide information that meets the user's wishes. In addition, there is the challenge that the application process for living space contracts is complex and time-consuming.

[0800] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0801] In this invention, the server includes means for receiving user conditions and searching for living space information based on those conditions; means for removing false or unnecessary information from the searched living space information; and means for recognizing the user's emotional state based on facial expressions, voice tone, connection time, and preference behavior data. This not only enables the provision of appropriate living space information that corresponds to the user's emotions, but also streamlines the contract procedure.

[0802] "User" refers to a person who searches for and uses information about living spaces.

[0803] "Conditions" refers to the user's preferences or requirements regarding the living space, including costs, geographical range, number of rooms, and pet permits.

[0804] "Residential space information" refers to data related to real estate and rental properties, including details such as location, price, floor plan, and facilities.

[0805] "Emotional state" refers to emotions analyzed based on the user's facial expressions, voice tone, connection time, and preference behavior data.

[0806] A "server" refers to a computer system that manages information about living spaces and performs processes such as searching, removing, evaluating, and recognizing.

[0807] "False information" refers to information that is inaccurate, misleading, or contrary to reality.

[0808] "Unnecessary information" refers to content that is irrelevant to the user's wishes or requirements and is deemed unnecessary for providing information.

[0809] "Evaluation" refers to the process of analyzing and considering information about the living space after removal, based on the user's emotional state.

[0810] "Contract procedures" refer to the process of formally concluding an agreement regarding living space, which usually includes document review and signing.

[0811] An "electronic document" refers to an official document created and transmitted / received in digital format, and is used in contractual procedures and other similar contexts.

[0812] The embodiment of this invention begins with a user using a terminal to input conditions related to their living space. These conditions include costs, geographical range, number of rooms, and animal permit status, and this information is transmitted from the terminal to a server. The server searches a living space information database based on the transmitted conditions and collects the relevant information. In this process, the server performs data cleansing to remove false information and information that is not necessary for the user.

[0813] The server incorporates an emotion engine that utilizes machine learning libraries such as TensorFlow to recognize the user's emotional state (facial expressions, voice tone, connection time, and preference data) in real time. This emotional information is used to dynamically adjust the spatial information presented according to the user's interests and satisfaction levels. For example, if high interest is detected, more detailed information about the relevant spatial environment is provided. On the other hand, if stress or dissatisfaction is detected, the information provided is narrowed down.

[0814] Furthermore, to streamline the contract process, the server automates the application process using electronic documents and guides users through their terminals. In this process, the Python programming language and the Google Assistant API are used for speech recognition and the user interface.

[0815] As a concrete example, this system can optimize everything from property search to contract procedures based on the user's emotions. For instance, a possible prompt for the generating AI model could be, "If the user has a relaxed expression, how should we provide more detailed information about the living space?" Based on this prompt, the AI ​​model can generate the optimal way to provide information to the user.

[0816] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0817] Step 1:

[0818] The user enters their living space requirements using a terminal. The user enters their preferences, such as cost, geographical area, number of rooms, and pet permit status, and this information is sent from the terminal to the server. The user's requirements data is then generated as output.

[0819] Step 2:

[0820] The server searches the residential space information database based on the received condition data. The input is the user's condition data; the server queries the database and collects the relevant residential space information. The output is the extracted residential space information.

[0821] Step 3:

[0822] The server uses data cleansing techniques to remove false or unnecessary information from the extracted residential space information. The input is the extracted residential space information; the data's integrity and relevance are verified, and unnecessary information is eliminated. The output is the cleansed residential space information.

[0823] Step 4:

[0824] The server uses an emotion engine to recognize the user's emotional state in real time. Inputs include the user's facial expressions, voice tone, connection time, and preference behavior data. The server analyzes this data to determine the emotional state. The output is the user's emotional state data.

[0825] Step 5:

[0826] The server dynamically adjusts the content of the living space information presented based on the user's emotional state data. The input consists of emotional state data and cleansed living space information, and the server changes the level of detail according to the user's interests and satisfaction levels. The output is living space information adjusted according to the user's emotions.

[0827] Step 6:

[0828] When a user enters into a contract for a living space, the server generates electronic documents and automates the process. The input consists of the user's selections, and the server creates the necessary documents for the contract and manages the electronic signature process. The output consists of the digitized contract documents and the completed procedure.

[0829] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0830] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0831] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0832] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0833] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0834] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0835] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0836] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0837] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0838] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0839] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0840] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0841] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0842] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0843] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0844] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0845] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0846] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0847] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0848] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0849] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0850] The following is further disclosed regarding the embodiments described above.

[0851] (Claim 1)

[0852] A means for receiving user conditions and searching for real estate information based on those conditions,

[0853] A means of removing false or unnecessary information from the searched real estate information,

[0854] A means of evaluating the property information after removal based on the user's lifestyle and preferences,

[0855] A means of presenting users with the most suitable real estate information based on the evaluation results,

[0856] Methods to automate and streamline the application process for real estate contracts,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, including budget, location, number of rooms, and whether pets are allowed as user conditions.

[0860] (Claim 3)

[0861] The system according to claim 1, which uses digital documents to perform application procedures in an automated process.

[0862] "Example 1"

[0863] (Claim 1)

[0864] A means of receiving user conditions via the device and securely transmitting them to the server,

[0865] A means for searching a real estate information database based on the conditions and extracting properties that match the conditions,

[0866] A means of using a generative AI model to filter out false information and information unnecessary to the user from the searched real estate information,

[0867] A method for using an AI algorithm to evaluate filtered real estate information based on the user's lifestyle and generate scoring information,

[0868] A means of selecting the most suitable real estate information based on the evaluation results, sending it to the terminal, and presenting it to the user,

[0869] A means to automate and streamline the application process for real estate contracts using digital documents and electronic signatures,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, which uses AI to evaluate properties, with user conditions including budget, location, number of rooms, and whether pets are allowed.

[0873] (Claim 3)

[0874] The system according to claim 1, which enables the transmission of electronic notifications to relevant parties in an automated procedure and allows the progress of the procedure to be tracked on a terminal.

[0875] "Application Example 1"

[0876] (Claim 1)

[0877] A means for receiving user criteria and searching for property information based on those criteria,

[0878] A means of removing false or unnecessary information from the searched property information,

[0879] A means of evaluating property information after removal based on the user's lifestyle and preferences,

[0880] A means of presenting users with the most suitable property information based on the evaluation results,

[0881] Methods to automate and streamline the application process for property contracts,

[0882] A method that integrates with urban infrastructure data to evaluate the overall living environment and propose the most suitable properties,

[0883] A system that includes this.

[0884] (Claim 2)

[0885] The system according to claim 1, including budget, region, number of rooms, and whether or not pets are allowed as user conditions.

[0886] (Claim 3)

[0887] The system according to claim 1, which uses digital documents to perform application procedures in an automated process.

[0888] "Example 2 of combining an emotion engine"

[0889] (Claim 1)

[0890] A means for receiving a user's request and searching for geospatial information based on said request,

[0891] A means for removing false or unnecessary information from the retrieved geospatial information,

[0892] A means for recognizing the emotional state of a user and making an evaluation based on that emotional state,

[0893] A means of presenting users with optimal geospatial information based on evaluation results,

[0894] Methods to automate and streamline the application process for geospatial contracts,

[0895] A system that includes this.

[0896] (Claim 2)

[0897] The system according to claim 1, including financial conditions, location, number of rooms, and animal permits as user requirements.

[0898] (Claim 3)

[0899] The system according to claim 1, which uses electronic documents to perform application procedures in an automated process.

[0900] "Application example 2 when combining with an emotional engine"

[0901] (Claim 1)

[0902] A means for receiving user conditions and searching for living space information based on those conditions,

[0903] A means for removing false or unnecessary information from the searched residential space information,

[0904] A means of evaluating the living space information after removal based on the user's emotional state,

[0905] A means of presenting users with optimal living space information based on evaluation results,

[0906] A means for recognizing a user's emotional state based on facial expressions, voice tone, connection time, and preference behavior data,

[0907] Methods to automate and streamline the application process for residential space contracts,

[0908] A system that includes this.

[0909] (Claim 2)

[0910] The system according to claim 1, including user conditions such as cost, geographical range, number of rooms, and animal permit status.

[0911] (Claim 3)

[0912] The system according to claim 1, which uses electronic documents to perform application procedures in an automated process. [Explanation of Symbols]

[0913] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving user conditions and searching for real estate information based on those conditions, A means of removing false or unnecessary information from the searched real estate information, A means of evaluating the property information after removal based on the user's lifestyle and preferences, A means of presenting users with the most suitable real estate information based on the evaluation results, Methods to automate and streamline the application process for real estate contracts, A system that includes this.

2. The system according to claim 1, including budget, location, number of rooms, and whether pets are allowed as user conditions.

3. The system according to claim 1, which uses digital documents to perform application procedures in an automated process.

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