system

Abstract

Provide a system. 【Solution means】 Means for obtaining and analyzing storage information and customer information, Means for providing information that matches the customer's wishes based on the analysis results, Means for calculating an appropriate price based on the information obtained from the database, Means for visually presenting information using virtual reality technology, Means for automatically processing inquiries from customers, Means for proposing individualized information using artificial intelligence, Means for enabling information browsing in a virtual space by a mobile information terminal or device, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional real estate brokerage service, there is a problem that it is difficult to accurately grasp various customer demands in a short time and propose suitable real estate information. In addition, it is not possible to efficiently perform a rapid and accurate assessment of the market price, automatically generate contract documents, and further provide visual information of the property, and there is a demand for improving convenience for customers. Therefore, means for improving the efficiency of information processing and the user experience are required.

Means for Solving the Problems

[0005] This invention provides means for collecting and analyzing customer and property information, and constructs a system that quickly provides real estate information that matches the customer's wishes based on the analysis results. Furthermore, it improves customer convenience by utilizing AI to calculate appropriate prices from market data, using virtual reality technology to visually present property information, and an automated inquiry response system. This makes it possible to provide efficient real estate brokerage services in a short period of time.

[0006] "Storage information" refers to data about the properties and conditions that customers are looking for.

[0007] "Customer information" refers to the customer's desired conditions, past behavioral history, and profile information.

[0008] "Analysis" refers to the process of analyzing trends and patterns based on collected data.

[0009] "Providing" refers to the act of presenting the analyzed results or information to the user.

[0010] A "database" refers to a system for storing and retrieving information, as well as a collection of structured information.

[0011] "Fair price" refers to a reasonable buying or selling price for a property, calculated based on market data.

[0012] "Virtual reality technology" refers to technology that uses computer technology to provide experiences that closely resemble reality in a digital space.

[0013] "Visual presentation" refers to a method of making information known to users through images and videos.

[0014] "Inquiry" refers to communication that requires a response to a customer's question or request.

[0015] "Automated processing" refers to processes in which a system independently performs tasks without human intervention.

Brief Description of the Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0017] 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.

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple 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.

[0020] 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.

[0021] 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] In this invention, to implement an AI-powered real estate brokerage system, the server receives data such as customer preferences, past behavioral history, and profile information. This data, along with real estate information in the database, is analyzed by an AI algorithm.

[0038] Based on this analysis, the server selects real estate information that matches the customer's desired conditions and generates a list of the most suitable properties. The terminal then presents the generated property list in an interface that the user can easily view and operate. Based on the presented information, the customer can select a property, obtain detailed information, or conduct a virtual viewing using virtual reality technology.

[0039] The server also uses AI to automatically calculate the fair market price of a property based on transaction history and market trends collected from the database. This allows users to obtain pricing information that reflects the latest market data.

[0040] Furthermore, the server is equipped with an automated response system that uses natural language processing technology to analyze user inquiries and respond quickly and accurately 24 hours a day. Users can ask questions and make inquiries about properties through a chat interface, and an AI chatbot will respond to them.

[0041] This system also streamlines contract-related tasks. The server automatically generates contract documents using template information and automatically inputs the necessary information, providing users with quick and accurate documents. This simplifies procedures and reduces errors.

[0042] In this way, AI-powered systems make it possible to provide efficient and customer-oriented real estate brokerage services. Specific benefits include users quickly obtaining property information that matches their preferences, receiving virtual reality-based viewings and price quotes based on accurate market information, and significantly simplifying contract procedures.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server.

[0046] Step 2:

[0047] The server retrieves user preferences and past browsing history from its database. Based on this data, it uses an AI algorithm to analyze suitable real estate information.

[0048] Step 3:

[0049] The server uses AI analysis results to select the properties best suited to the customer's preferences and generates a property list. This list is then sent to the user's device.

[0050] Step 4:

[0051] The terminal displays the received property list in a user-friendly interface and organizes it into a format that allows users to view detailed information and images of each property.

[0052] Step 5:

[0053] Users can select properties of interest via their devices and view detailed information. In some cases, they can also choose a virtual tour using virtual reality technology.

[0054] Step 6:

[0055] The server analyzes market data based on the detailed information of the selected property and uses AI to calculate a fair price.

[0056] Step 7:

[0057] The device notifies the user of detailed information, including the calculated fair price, and the user can verify the price.

[0058] Step 8:

[0059] The user enters their question using the chat interface on their device.

[0060] Step 9:

[0061] The server analyzes the received question using natural language processing technology, and the AI ​​chatbot generates an appropriate answer.

[0062] Step 10:

[0063] The server generates a response, which is then sent to the user's device, allowing the user to immediately see the response.

[0064] Step 11:

[0065] When a user decides to purchase a property, the server runs a template-based automated contract creation program to generate a contract with the necessary information automatically entered.

[0066] Step 12:

[0067] The terminal presents the generated contract to the user, enabling online confirmation and approval.

[0068] (Example 1)

[0069] 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."

[0070] Conventional information systems struggled to provide detailed information that responded immediately to individual user requests, resulting in significant time and effort spent on manual information gathering and inquiry handling. Furthermore, there were challenges in accuracy and efficiency in properly valuing goods and creating contract documents, highlighting the need for new technological solutions to improve the user experience.

[0071] 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.

[0072] In this invention, the server includes means for receiving and analyzing input data acquired from a communication terminal, means for extracting and providing information suitable for a specific request based on the analysis results, and means for calculating a price using information acquired from a data storage unit. This enables accurate and prompt responses to diverse user requests, as well as efficient price evaluation and contract document creation.

[0073] A "communication terminal" is a device used to send and receive information, and is used by users to input or view data.

[0074] "Input data" refers to the information provided by users when specifying particular requests or conditions, and it forms the basis for the system's analysis.

[0075] "Means of analysis" refers to a function that performs a process of calculating or evaluating information that matches the user's requests and conditions using the received data.

[0076] The "data storage unit" is a component for accumulating related information such as product information and market data, and is a data storage that is referenced during analysis and information provision.

[0077] "Virtual reality technology" refers to technologies that use virtual reality to provide users with visual information, and is a technique for digitally recreating real-life experiences.

[0078] "Natural language processing technology" is a computer technology that understands inquiries entered in human language and responds appropriately, and it is a method of processing human language using AI.

[0079] "Means for automatically generating document information" refers to a function that efficiently and accurately creates necessary documents based on pre-configured templates and provided data.

[0080] A description of embodiments for carrying out this invention will be given.

[0081] This real estate brokerage system comprises a communication terminal, a server, a data storage unit, and an analysis engine utilizing AI technology. The server receives data such as desired conditions and profile information entered by the user via the communication terminal. This data is analyzed by a generative AI model using machine learning frameworks such as TENSORFLOW®. The AI ​​model matches real estate information stored in a large database with user information to identify property information that suits the user's preferences.

[0082] The server uses data analysis libraries such as scikit-learn to analyze information obtained from historical market data and transaction history in order to calculate the fair price of an asset. This allows it to provide users with information based on objective and up-to-date market analysis.

[0083] The device is built using front-end technologies such as React and Vue.js, providing users with an intuitive interface. Through this interface, users can virtually tour properties using virtual reality technology. Using a VR headset, users can examine the property in detail from a 360-degree perspective.

[0084] Furthermore, the server utilizes natural language processing technology to interpret user inquiries and has an automated response function for quick responses. By using an AI chatbot, the server can handle inquiries 24 hours a day. For example, if a user enters the question "Can I keep pets in this property?" into the chat interface, the server will check its database and provide the relevant information immediately.

[0085] Regarding the automated generation of contract documents, the server utilizes template information and integrates with electronic contract services such as DocuSign to establish a process for accurately and quickly creating the necessary documents. This allows users to complete contract procedures smoothly online.

[0086] As a concrete example of a prompt, you can use a command such as, "Please find a 3LDK property that is within a 10-minute walk from the station and allows pets." Based on this command, the AI ​​will filter relevant real estate information and present suitable properties to the user.

[0087] This system configuration allows for a more efficient real estate brokerage process and significantly improves the user experience.

[0088] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0089] Step 1:

[0090] The server receives user preferences, behavioral history, and profile information via a communication terminal. This data is stored in a database as input. The data is used as foundational information to identify user needs.

[0091] Step 2:

[0092] The server analyzes the received data using generative AI models such as TensorFlow. This step uses machine learning algorithms to generate prompts and identify real estate information that matches them. The output is a list of properties that best match the user's preferences. This list is then ranked by scoring.

[0093] Step 3:

[0094] The server formats the generated property list into an intuitive user interface using React or Vue.js. The terminal displays the property list to the user through this interface. The input is the property list, and the output is a screen formatted for easy viewing by the user.

[0095] Step 4:

[0096] Users view property details and conduct virtual tours through their devices. This step utilizes virtual space technology to allow users to experience the property's interior from a 360-degree perspective. The input is the property information selected by the user, and the output is a real-time generated virtual tour video.

[0097] Step 5:

[0098] The server calculates the fair market value of a property using data analysis techniques such as scikit-learn, based on past transaction history and market trends. The input is market transaction data, and the output is the calculated price information. This allows users to verify prices based on market value.

[0099] Step 6:

[0100] Questions and inquiries from users are sent to the server via a chat interface. The server analyzes these inquiries using natural language processing, and an AI chatbot provides an appropriate answer. The input is the user's inquiry, and the output is the analyzed answer information.

[0101] Step 7:

[0102] In contract procedures, the server automatically generates contract documents using template information. Necessary information is retrieved from a database, and the document is accurately created in conjunction with electronic contract services such as DocuSign. Input consists of the necessary contract template and user information, while output is the automatically generated contract.

[0103] (Application Example 1)

[0104] 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."

[0105] In today's real estate market, it is difficult for customers to quickly and accurately obtain property information that matches their preferences. Furthermore, there is a growing demand for fair pricing based on market trends and streamlined contract procedures. At the same time, customers increasingly desire to view properties virtually without visiting in person. Against this backdrop, providing customers with personalized experiences while efficiently presenting property information has become a crucial challenge.

[0106] 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.

[0107] In this invention, the server includes means for acquiring and analyzing storage information and customer information; means for providing information that matches the customer's wishes based on the analysis results; means for calculating a fair price based on information acquired from a database; means for visually presenting information using virtual reality technology; means for automatically processing customer inquiries; means for suggesting personalized information using artificial intelligence; and means for enabling viewing of information in a virtual space using a mobile information terminal or device. As a result, customers can efficiently acquire property information that matches their wishes and visually confirm properties through virtual reality.

[0108] "Storage information" refers to data collected to understand the user's wishes and needs, and is an important factor when selecting a property.

[0109] "Customer information" refers to information necessary to respond to individual requests, such as user profiles and behavioral history.

[0110] "Analysis" is the process of processing collected information using AI algorithms to select properties that match the user's preferences.

[0111] "Fair price" refers to a reasonable property price calculated by AI based on market trends and past transactions.

[0112] "Virtual reality technology" is a technology that uses 3D technology to visualize the interior of a property, making users feel as if they are actually viewing it.

[0113] "Automated inquiry processing" is a function in which AI understands user questions and requests through natural language processing and responds quickly.

[0114] "Artificial intelligence" is an advanced processing technology that analyzes customer information and provides property information tailored to individual needs.

[0115] "Personal information terminals" refer to smartphones and head-mounted displays used by users to access virtual stores and information.

[0116] A "virtual space" is a computer-generated area where users can view and manipulate property information within a digital environment.

[0117] This system is designed to allow users to efficiently acquire real estate information and provide a realistic experience through virtual reality. The server uses artificial intelligence to analyze customer and storage information and generate personalized property information. Machine learning frameworks such as Python's TensorFlow and PyTorch are used for this analysis.

[0118] The acquired property information is visualized in a virtual reality environment using Unity. Users can experience these virtual properties via smartphones or head-mounted displays such as Oculus Quest. When users view properties in the virtual space, the server calculates and displays a fair price in real time based on market trend data and past transaction information. A database management system assists in this price calculation.

[0119] On the device, natural language processing technology using Google's Dialogflow is implemented, allowing users to input questions and uncertainties about properties via a chat interface. An AI chatbot then responds quickly, supporting the user's decision-making. Furthermore, a template engine is used for the automatic generation of contract documents, enabling simple and accurate document creation.

[0120] For example, if a user enters criteria such as "I'm looking for a 3LDK apartment in Tokyo where pets are allowed," the system will list the properties that best match those criteria. The user can then virtually tour multiple properties and experience the process of selecting the one they like best.

[0121] An example of a prompt to input into the generating AI model is as follows: "Visualize the most suitable property information based on the user's desired conditions for a virtual viewing. Utilize VR technology to present detailed property information as well."

[0122] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0123] Step 1:

[0124] The server collects user preferences and profile information. The entered data is formatted as preprocessing for analysis by an AI algorithm. This prepares the system to gain a detailed understanding of the user's individual needs.

[0125] Step 2:

[0126] The server analyzes the collected user data using Python's TensorFlow. Based on the analysis, property information that best matches the user's preferences is selected. This output is a property list based on the user's desired conditions.

[0127] Step 3:

[0128] The server uses Unity to visualize selected property information within a 3D virtual reality environment. Based on the input data, the structure and interior of the property are realistically rendered in the virtual space, which the user views using a head-mounted display.

[0129] Step 4:

[0130] Users tour properties in a virtual space using a smartphone or head-mounted display. Depending on the user's selection, the server switches scenes or loads information on other properties as needed.

[0131] Step 5:

[0132] The server retrieves market trends and historical transaction information from the database and calculates a fair price in real time using Python. The calculation results are presented to users during virtual viewings and serve as useful price information.

[0133] Step 6:

[0134] User inquiries are sent via a text chat interface. The device uses Google's Dialogflow to analyze the natural language input, and an AI chatbot generates an appropriate response.

[0135] Step 7:

[0136] The server uses a template engine to automatically generate contract documents for the property selected by the user. This process automatically populates the template document with the necessary information, ensuring accurate and rapid document creation.

[0137] 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.

[0138] This invention implements a system that provides more personalized information by combining a conventional property information provision system with an emotion engine that recognizes the user's emotions. The server uses not only the desired conditions and behavioral history received from the user, but also emotion data acquired from the user's terminal for analysis. The emotion engine detects emotions from the user's voice, text, facial expressions, etc., and quantifies their state.

[0139] The server uses this sentiment data to optimize the user experience by making adjustments when suggesting properties and providing information. For example, if a user is experiencing stress, the number of suggested properties will be reduced to lessen the visual burden. Furthermore, properties deemed to be of high interest will receive priority in displaying detailed information and additional content.

[0140] By incorporating user emotions obtained through an emotion engine into price predictions, more appropriate price information is presented to users. This allows for pricing that is psychologically acceptable to users.

[0141] Furthermore, when a user asks a question through the chat interface, the server uses an emotion engine to understand the user's emotional state and generate an appropriate response based on that. For example, if the user is feeling anxious, the server will respond using clearer and more polite language.

[0142] This emotional data is also used in the contract document generation process to adjust the process so that users can proceed with the contract in a calm state. This enables the real estate brokerage service to be flexible and effective, tailored to the user's psychological state.

[0143] This system allows users to have an experience that goes beyond mere information provision, enabling them to make more suitable choices based on their individual needs and emotions.

[0144] The following describes the processing flow.

[0145] Step 1:

[0146] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server. The device also captures the user's facial expressions and tone of voice as emotional data through voice and camera.

[0147] Step 2:

[0148] The server comprehensively analyzes the user's desired conditions, past search history, and emotional data analyzed by the emotion engine. In this process, the AI ​​algorithm selects properties by taking into account information corresponding to the user's emotional state.

[0149] Step 3:

[0150] Based on the analysis results, the server selects the most suitable properties for the user and generates a list of selected properties. The number and display format of these properties are adjusted according to the user's emotional state.

[0151] Step 4:

[0152] The terminal displays a generated list of properties to the user. The user can view property details through an emotion-optimized interface. Furthermore, for properties of interest, a virtual tour using virtual reality technology is available.

[0153] Step 5:

[0154] The server analyzes market data related to the selected property and calculates a fair price using an AI model. This price information is then adjusted based on sentiment data to make it psychologically more acceptable to the user.

[0155] Step 6:

[0156] The device notifies the user of detailed information, including the calculated fair price. This allows the user to fully understand the property's price and details, enabling them to confidently choose a property.

[0157] Step 7:

[0158] When a user enters an inquiry via the chat interface from their device, the server uses an emotion engine to analyze the user's emotional state.

[0159] Step 8:

[0160] Based on the results of sentiment analysis, the server generates a response to the user in an appropriate tone and content. For example, if the user is feeling stressed, the response will be organized clearly and reassuringly.

[0161] Step 9:

[0162] When a user decides to purchase a property, the server uses a template-based automatic contract generation function to create a contract and automatically inputs the necessary information.

[0163] Step 10:

[0164] The terminal presents the generated contract to the user and provides a confirmation and approval process, including notes regarding the user's psychological state. This allows the user to proceed with the contract process in a calm and composed manner.

[0165] (Example 2)

[0166] 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".

[0167] Conventional information systems provide uniform information and pricing data without adequately considering the emotional state of individual users, making it difficult to provide information optimized to users' needs and psychological conditions. As a result, particularly in real estate transactions, users sometimes experienced stress and dissatisfaction due to information overload and a lack of appropriate pricing.

[0168] 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.

[0169] In this invention, the server includes means for recognizing and acquiring the user's emotional state, means for adjusting the content of information provided using the results of the emotional analysis, and means for considering emotional data in the process of generating contract documents. This enables flexible and personalized information provision and optimization of the contract process in accordance with the user's emotional state.

[0170] "Storage information" refers to information about the content and conditions related to specific services or products that users are seeking.

[0171] "User information" refers to information including the attributes, preferences, and past behavioral history of an individual using the service.

[0172] "Analyzing" means extracting meaning from acquired data and processing it to provide useful information.

[0173] A "data set" is a collection of information in which multiple data points or records are aggregated.

[0174] "Virtual environment technology" is a technology that uses computer technology to provide users with a visual experience that differs from the real world.

[0175] "Emotional state" refers to the psychological and sensory state that a user is experiencing at a particular moment.

[0176] "Emotional analysis" is a technology that quantifies or classifies a user's psychological state based on data such as voice and facial expressions provided by the user.

[0177] The "contract document generation process" refers to the process of creating the documents necessary for a legal agreement or transaction to be concluded.

[0178] "Template information" refers to template information that defines the standard format for documents and data.

[0179] This invention is a system that utilizes emotion recognition technology to provide information and real estate brokerage services optimized for the user. The main components of the system are a server, a terminal, and a user.

[0180] First, the device is equipped with a camera and microphone to acquire data such as the user's voice, facial expressions, and entered preferences. This data is sent to a server that performs emotion analysis. The server uses general emotion analysis software to quantify the emotional state from this data. Specifically, it is possible to use emotion analysis tools from cloud services such as Microsoft® Azure®.

[0181] The server analyzes real estate property information retrieved from the database based on emotional data and provides information tailored to each user's emotional state. For example, if the analysis indicates that a user is feeling stressed, the server reduces the number of suggested properties to lessen the visual burden. On the other hand, for properties that the user has shown interest in, detailed information and additional content are displayed preferentially.

[0182] In addition, emotional data is input into AI models and used in price prediction and contract document creation processes. At the contract stage, the system checks the user's relaxed state and adjusts the content and wording of the contract documents to reduce psychological burden.

[0183] As a concrete example of the system, suppose a user is looking for a new place to live. If the stress or anxiety the user feels while reviewing the properties is detected through emotion analysis, the server will simplify the information about the suggested properties and adjust it so that the user can make a selection in a relaxed state. An example of a prompt message generated by the AI ​​model would be, "If the user is feeling anxious, how should the suggested property information be simplified?"

[0184] In this way, by implementing this invention, users can receive personalized real estate brokerage services that respond to their emotions.

[0185] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0186] Step 1:

[0187] The device acquires voice and facial expression data from the user and also accepts text input such as region and budget as desired conditions. This data is sent to the server as input data for sentiment analysis. Specifically, the device captures voice and video in real time using a microphone and camera and prepares a text input form.

[0188] Step 2:

[0189] The server receives voice, facial expression, and text data transmitted from the terminal and inputs it into the emotion analysis engine. The input data is processed by the emotion analysis engine and output as numerical data representing the user's emotional state. Specifically, it analyzes changes in voice tone and facial expression to quantify emotions such as joy, stress, and anxiety.

[0190] Step 3:

[0191] The server analyzes real estate property information based on quantified emotional data. It filters property information retrieved from the database according to each user's emotional state and desired conditions, and creates tailored suggestions. Specifically, when a user is feeling stressed, it extracts only the most important properties from the database and reduces the suggestion list.

[0192] Step 4:

[0193] The server uses a generative AI model to predict the price information to be provided to the user. Using sentiment data and historical transaction data as input, it runs the price prediction model and outputs a price range that the user finds acceptable. Specifically, if the sentiment state is positive, it broadens the user's options by suggesting a wider range of price points.

[0194] Step 5:

[0195] The terminal presents the user with adjusted property information, price predictions, and additional information generated by the server. The information is displayed in a visually intuitive interface, making it easy for the user to understand and make selections. Specifically, it dynamically adjusts colors and font sizes according to the user's emotions.

[0196] Step 6:

[0197] If the user wishes to enter into a contract, the server starts the contract document generation process. Based on sentiment data, it adjusts the elements and wording of the contract to help the user enter into the contract calmly, and then outputs the final contract. Specifically, it simplifies or elaborates on template selections and item descriptions according to the user's sentiment.

[0198] This trend will allow users to receive real estate brokerage services that are tailored to their own needs and preferences.

[0199] (Application Example 2)

[0200] 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".

[0201] Current information provision systems struggle to provide appropriate information that takes into account the user's emotional state, and especially in electronic payments, there is a lack of means to reduce user stress and anxiety. As a result, the user experience is not satisfactory, and there are challenges in maintaining service use and improving customer satisfaction.

[0202] 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.

[0203] In this invention, the server includes means for analyzing user emotional data in addition to acquired storage information and customer information; means for providing information that matches the customer's wishes and emotional state based on the analysis results; and means for visually presenting the information through an interface dynamically adjusted based on the emotional data. This enables the provision of information and optimization of the payment experience in accordance with the user's emotional state.

[0204] "Storage information" is a general term for data related to customers and numerical information collected in transactions.

[0205] "Customer information" refers to specific data about customers, such as personal information and past transaction history.

[0206] "User emotional data" refers to information that quantifies the emotional state of users, collected through voice, text, facial expressions, etc.

[0207] "Means of analysis" refers to devices and software that perform calculations and processing to derive useful information from collected data.

[0208] "Means of provision" refers to mechanisms and methods for appropriately and effectively conveying information to users based on the analysis results.

[0209] A "dynamically responsive interface" is a flexible interface that changes its screen layout and operation methods according to the user's emotions and how they use it.

[0210] "Means of visual presentation" refers to technologies and devices that visually present information to users using images, diagrams, and other visual means.

[0211] This invention is a system that optimizes the electronic payment experience by utilizing user emotional data. The server first receives emotional data acquired from the user's smartphone or smart glasses. This emotional data is analyzed by an emotion engine based on voice, facial expressions, and text data. This analysis uses a machine learning model such as Firebase ML Kit to quantify emotions in real time.

[0212] The server evaluates the user's psychological state based on acquired emotional data and dynamically provides optimal information. For example, if the user is feeling stressed, the UI design and operation methods are simplified. This is achieved using Flutter® to build a visually superior interface. As a result, users are not exposed to excessive information on the payment screen and can complete transactions smoothly.

[0213] Furthermore, the server optimizes its pricing based on user sentiment, presenting prices that are appropriate for the user. The pricing is calculated using an algorithm that combines historical transaction data with real-time sentiment data.

[0214] As a concrete example, consider a payment scenario in a shopping mall. If the app detects stress due to congestion while the user is selecting items and heading to the checkout, it automatically opens a shortcut menu and presents an option to quickly complete the payment using a registered payment method. This significantly improves the user experience.

[0215] An example of a prompt would be: "The emotion engine is currently detecting how frustrated the user is with the waiting time at the checkout. Based on this data, what customer support measures do you think would be effective?" This prompt can be input into a generating AI model to obtain more specific action suggestions.

[0216] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0217] Step 1:

[0218] The device collects the user's voice, facial expressions, and text data in real time. This raw data is acquired as input and converted into a digital format using speech recognition software and a camera application. The device then transmits this input data to an emotion engine.

[0219] Step 2:

[0220] The server uses an emotion engine to analyze the acquired voice, facial expressions, and text data to quantify the user's emotional state. This process employs machine learning models such as Firebase ML Kit to output a score for a specific emotion based on the input data.

[0221] Step 3:

[0222] The server evaluates the user's psychological state based on quantified emotion data and dynamically adjusts the interface. Specifically, it uses Flutter to modify UI elements and simplifies information if it indicates stress. This results in an optimized user interface.

[0223] Step 4:

[0224] Users conduct transactions through a customized UI. During this process, user selections and inputs are sent back to the server and processed as new input data.

[0225] Step 5:

[0226] The server combines user sentiment data with past transaction information to calculate and present the most suitable price. As a result, optimized price information is output and visually presented to the user.

[0227] Step 6:

[0228] When the server interacts with the user, it generates appropriate responses based on emotional data. Using a generative AI model, it processes prompts and generates suggestions such as, "Based on this data, what customer support measures do you think would be effective?" and outputs them.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] [Second Embodiment]

[0233] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0234] 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.

[0235] 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).

[0236] 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.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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".

[0245] In this invention, to implement an AI-powered real estate brokerage system, the server receives data such as customer preferences, past behavioral history, and profile information. This data, along with real estate information in the database, is analyzed by an AI algorithm.

[0246] Based on this analysis, the server selects real estate information that matches the customer's desired conditions and generates a list of the most suitable properties. The terminal then presents the generated property list in an interface that the user can easily view and operate. Based on the presented information, the customer can select a property, obtain detailed information, or conduct a virtual viewing using virtual reality technology.

[0247] The server also uses AI to automatically calculate the fair market price of a property based on transaction history and market trends collected from the database. This allows users to obtain pricing information that reflects the latest market data.

[0248] Furthermore, the server is equipped with an automated response system that uses natural language processing technology to analyze user inquiries and respond quickly and accurately 24 hours a day. Users can ask questions and make inquiries about properties through a chat interface, and an AI chatbot will respond to them.

[0249] This system also streamlines contract-related tasks. The server automatically generates contract documents using template information and automatically inputs the necessary information, providing users with quick and accurate documents. This simplifies procedures and reduces errors.

[0250] In this way, AI-powered systems make it possible to provide efficient and customer-oriented real estate brokerage services. Specific benefits include users quickly obtaining property information that matches their preferences, receiving virtual reality-based viewings and price quotes based on accurate market information, and significantly simplifying contract procedures.

[0251] The following describes the processing flow.

[0252] Step 1:

[0253] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server.

[0254] Step 2:

[0255] The server retrieves user preferences and past browsing history from its database. Based on this data, it uses an AI algorithm to analyze suitable real estate information.

[0256] Step 3:

[0257] The server uses AI analysis results to select the properties best suited to the customer's preferences and generates a property list. This list is then sent to the user's device.

[0258] Step 4:

[0259] The terminal displays the received property list in a user-friendly interface and organizes it into a format that allows users to view detailed information and images of each property.

[0260] Step 5:

[0261] Users can select properties of interest via their devices and view detailed information. In some cases, they can also choose a virtual tour using virtual reality technology.

[0262] Step 6:

[0263] The server analyzes market data based on the detailed information of the selected property and uses AI to calculate a fair price.

[0264] Step 7:

[0265] The device notifies the user of detailed information, including the calculated fair price, and the user can verify the price.

[0266] Step 8:

[0267] The user enters their question using the chat interface on their device.

[0268] Step 9:

[0269] The server analyzes the received question using natural language processing technology, and the AI ​​chatbot generates an appropriate answer.

[0270] Step 10:

[0271] The server generates a response, which is then sent to the user's device, allowing the user to immediately see the response.

[0272] Step 11:

[0273] When a user decides to purchase a property, the server runs a template-based automated contract creation program to generate a contract with the necessary information automatically entered.

[0274] Step 12:

[0275] The terminal presents the generated contract to the user, enabling online confirmation and approval.

[0276] (Example 1)

[0277] 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."

[0278] Conventional information systems struggled to provide detailed information that responded immediately to individual user requests, resulting in significant time and effort spent on manual information gathering and inquiry handling. Furthermore, there were challenges in accuracy and efficiency in properly valuing goods and creating contract documents, highlighting the need for new technological solutions to improve the user experience.

[0279] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Example 1 is realized by the following means.

[0280] In this invention, the server includes means for receiving input data acquired from a communication terminal and analyzing it, means for extracting and providing information suitable for a specific request based on the analysis result, and means for calculating a price using information acquired from a data storage unit. Thereby, while quickly and accurately responding to various requests of the user, it becomes possible to appropriately evaluate the price and efficiently create contract documents.

[0281] A "communication terminal" is a device used for transmitting and receiving information, and is what a user uses to input or view data.

[0282] "Input data" refers to information provided by a user when specifying a specific request or condition, and is the basis for system analysis.

[0283] "Means for analyzing" refers to a function that executes a process of calculating or evaluating information that matches the user's request or condition using the received data.

[0284] A "data storage unit" is a component for accumulating related information such as item information and market data, and is a data storage referred to during analysis and information provision.

[0285] "Virtual space technology" refers to a technology that uses virtual reality to provide visual information to a user, and is a technique for digitally reproducing a real experience.

[0286] "Natural language processing technology" is a computer technology for understanding inquiries input in human language and appropriately responding, and is a method of processing human language using AI.

[0287] "Means for automatically generating document information" refers to a function for efficiently and accurately creating necessary documents based on a preset template and provided data.

[0288] A description of embodiments for carrying out this invention will be given.

[0289] This real estate brokerage system consists of a communication terminal, a server, a data storage unit, and an analysis engine utilizing AI technology. The server receives data such as desired conditions and profile information entered by the user via the communication terminal. This data is analyzed by a generative AI model using machine learning frameworks such as TensorFlow. The AI ​​model matches real estate information stored in a large database with user information to identify property information that suits the user's preferences.

[0290] The server uses data analysis libraries such as scikit-learn to analyze information obtained from historical market data and transaction history in order to calculate the fair price of an asset. This allows it to provide users with information based on objective and up-to-date market analysis.

[0291] The device is built using front-end technologies such as React and Vue.js, providing users with an intuitive interface. Through this interface, users can virtually tour properties using virtual reality technology. Using a VR headset, users can examine the property in detail from a 360-degree perspective.

[0292] Furthermore, the server utilizes natural language processing technology to interpret user inquiries and has an automated response function for quick responses. By using an AI chatbot, the server can handle inquiries 24 hours a day. For example, if a user enters the question "Can I keep pets in this property?" into the chat interface, the server will check its database and provide the relevant information immediately.

[0293] Regarding the automated generation of contract documents, the server utilizes template information and integrates with electronic contract services such as DocuSign to establish a process for accurately and quickly creating the necessary documents. This allows users to complete contract procedures smoothly online.

[0294] As a concrete example of a prompt, you can use a command such as, "Please find a 3LDK property that is within a 10-minute walk from the station and allows pets." Based on this command, the AI ​​will filter relevant real estate information and present suitable properties to the user.

[0295] This system configuration allows for a more efficient real estate brokerage process and significantly improves the user experience.

[0296] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0297] Step 1:

[0298] The server receives user preferences, behavioral history, and profile information via a communication terminal. This data is stored in a database as input. The data is used as foundational information to identify user needs.

[0299] Step 2:

[0300] The server analyzes the received data using generative AI models such as TensorFlow. This step uses machine learning algorithms to generate prompts and identify real estate information that matches them. The output is a list of properties that best match the user's preferences. This list is then ranked by scoring.

[0301] Step 3:

[0302] The server formats the generated property list into a user interface that can be intuitively operated using React or Vue.js. The terminal displays the property list to the user via this interface. The input is the property list, and the output is a screen arranged in a user-friendly format.

[0303] Step 4:

[0304] The user browses the details of the property and conducts a virtual interior view through the terminal. In this step, virtual space technology can be utilized to experience the interior of the property from a 360-degree perspective. The input is the property information selected by the user, and the output is the video of the virtual interior view generated in real time.

[0305] Step 5:

[0306] The server calculates the appropriate price of the property using data analysis techniques such as scikit-learn based on past transaction histories and market trends. The input is the market transaction data, and the output is the calculated price information. This enables the user to confirm the price based on the market value.

[0307] Step 6:

[0308] Questions and inquiries from the user are sent to the server through the chat interface. The server analyzes this inquiry using natural language processing, and the AI chatbot provides an appropriate answer. The input is the user's inquiry sentence, and the output is the analyzed answer information.

[0309] Step 7:

[0310] In the procedures related to the contract, the server automatically generates contract documents using template information. The necessary information is obtained from the database, and the documents are accurately created in cooperation with an electronic contract service such as DocuSign. The input is the template and user information required for the contract, and the output is the automatically generated contract document.

[0311] (Application Example 1)

[0312] 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."

[0313] In today's real estate market, it is difficult for customers to quickly and accurately obtain property information that matches their preferences. Furthermore, there is a growing demand for fair pricing based on market trends and streamlined contract procedures. At the same time, customers increasingly desire to view properties virtually without visiting in person. Against this backdrop, providing customers with personalized experiences while efficiently presenting property information has become a crucial challenge.

[0314] 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.

[0315] In this invention, the server includes means for acquiring and analyzing storage information and customer information; means for providing information that matches the customer's wishes based on the analysis results; means for calculating a fair price based on information acquired from a database; means for visually presenting information using virtual reality technology; means for automatically processing customer inquiries; means for suggesting personalized information using artificial intelligence; and means for enabling viewing of information in a virtual space using a mobile information terminal or device. As a result, customers can efficiently acquire property information that matches their wishes and visually confirm properties through virtual reality.

[0316] "Storage information" refers to data collected to understand the user's wishes and needs, and is an important factor when selecting a property.

[0317] "Customer information" refers to information necessary to respond to individual requests, such as user profiles and behavioral history.

[0318] "Analysis" is the process of processing collected information using AI algorithms to select properties that match the user's preferences.

[0319] "Fair price" refers to a reasonable property price calculated by AI based on market trends and past transactions.

[0320] "Virtual reality technology" is a technology that uses 3D technology to visualize the interior of a property, making users feel as if they are actually viewing it.

[0321] "Automated inquiry processing" is a function in which AI understands user questions and requests through natural language processing and responds quickly.

[0322] "Artificial intelligence" is an advanced processing technology that analyzes customer information and provides property information tailored to individual needs.

[0323] "Personal information terminals" refer to smartphones and head-mounted displays used by users to access virtual stores and information.

[0324] A "virtual space" is a computer-generated area where users can view and manipulate property information within a digital environment.

[0325] This system is designed to allow users to efficiently acquire real estate information and provide a realistic experience through virtual reality. The server uses artificial intelligence to analyze customer and storage information and generate personalized property information. Machine learning frameworks such as Python's TensorFlow and PyTorch are used for this analysis.

[0326] The acquired property information is visualized in a virtual reality environment using Unity. Users can experience these virtual properties via smartphones or head-mounted displays such as Oculus Quest. When users view properties in the virtual space, the server calculates and displays a fair price in real time based on market trend data and past transaction information. A database management system assists in this price calculation.

[0327] On the device, natural language processing technology powered by Google's Dialogflow is implemented, allowing users to input questions and uncertainties about properties via a chat interface. An AI chatbot then responds quickly, supporting the user's decision-making. Furthermore, a template engine is used for the automatic generation of contract documents, enabling simple and accurate document creation.

[0328] For example, if a user enters criteria such as "I'm looking for a 3LDK apartment in Tokyo where pets are allowed," the system will list the properties that best match those criteria. The user can then virtually tour multiple properties and experience the process of selecting the one they like best.

[0329] An example of a prompt to input into the generating AI model is as follows: "Visualize the most suitable property information based on the user's desired conditions for a virtual viewing. Utilize VR technology to present detailed property information as well."

[0330] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0331] Step 1:

[0332] The server collects user preferences and profile information. The entered data is formatted as preprocessing for analysis by an AI algorithm. This prepares the system to gain a detailed understanding of the user's individual needs.

[0333] Step 2:

[0334] The server analyzes the collected user data using Python's TensorFlow. Based on the analysis, property information that best matches the user's preferences is selected. This output is a property list based on the user's desired conditions.

[0335] Step 3:

[0336] The server uses Unity to visualize selected property information within a 3D virtual reality environment. Based on the input data, the structure and interior of the property are realistically rendered in the virtual space, which the user views using a head-mounted display.

[0337] Step 4:

[0338] Users tour properties in a virtual space using a smartphone or head-mounted display. Depending on the user's selection, the server switches scenes or loads information on other properties as needed.

[0339] Step 5:

[0340] The server retrieves market trends and historical transaction information from the database and calculates a fair price in real time using Python. The calculation results are presented to users during virtual viewings and serve as useful price information.

[0341] Step 6:

[0342] User inquiries are sent via a text chat interface. The device uses Google's Dialogflow to analyze the natural language input, and an AI chatbot generates an appropriate response.

[0343] Step 7:

[0344] The server uses a template engine to automatically generate contract documents for the property selected by the user. This process automatically populates the template document with the necessary information, ensuring accurate and rapid document creation.

[0345] 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.

[0346] This invention implements a system that provides more personalized information by combining a conventional property information provision system with an emotion engine that recognizes the user's emotions. The server uses not only the desired conditions and behavioral history received from the user, but also emotion data acquired from the user's terminal for analysis. The emotion engine detects emotions from the user's voice, text, facial expressions, etc., and quantifies their state.

[0347] The server uses this sentiment data to optimize the user experience by making adjustments when suggesting properties and providing information. For example, if a user is experiencing stress, the number of suggested properties will be reduced to lessen the visual burden. Furthermore, properties deemed to be of high interest will receive priority in displaying detailed information and additional content.

[0348] By incorporating user emotions obtained through an emotion engine into price predictions, more appropriate price information is presented to users. This allows for pricing that is psychologically acceptable to users.

[0349] Furthermore, when a user asks a question through the chat interface, the server uses an emotion engine to understand the user's emotional state and generate an appropriate response based on that. For example, if the user is feeling anxious, the server will respond using clearer and more polite language.

[0350] This emotional data is also used in the contract document generation process to adjust the process so that users can proceed with the contract in a calm state. This enables the real estate brokerage service to be flexible and effective, tailored to the user's psychological state.

[0351] This system allows users to have an experience that goes beyond mere information provision, enabling them to make more suitable choices based on their individual needs and emotions.

[0352] The following describes the processing flow.

[0353] Step 1:

[0354] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server. The device also captures the user's facial expressions and tone of voice as emotional data through voice and camera.

[0355] Step 2:

[0356] The server comprehensively analyzes the user's desired conditions, past search history, and emotional data analyzed by the emotion engine. In this process, the AI ​​algorithm selects properties by taking into account information corresponding to the user's emotional state.

[0357] Step 3:

[0358] Based on the analysis results, the server selects the most suitable properties for the user and generates a list of selected properties. The number and display format of these properties are adjusted according to the user's emotional state.

[0359] Step 4:

[0360] The terminal displays a generated list of properties to the user. The user can view property details through an emotion-optimized interface. Furthermore, for properties of interest, a virtual tour using virtual reality technology is available.

[0361] Step 5:

[0362] The server analyzes market data related to the selected property and calculates a fair price using an AI model. This price information is then adjusted based on sentiment data to make it psychologically more acceptable to the user.

[0363] Step 6:

[0364] The device notifies the user of detailed information, including the calculated fair price. This allows the user to fully understand the property's price and details, enabling them to confidently choose a property.

[0365] Step 7:

[0366] When a user enters an inquiry via the chat interface from their device, the server uses an emotion engine to analyze the user's emotional state.

[0367] Step 8:

[0368] Based on the results of sentiment analysis, the server generates a response to the user in an appropriate tone and content. For example, if the user is feeling stressed, the response will be organized clearly and reassuringly.

[0369] Step 9:

[0370] When a user decides to purchase a property, the server uses a template-based automatic contract generation function to create a contract and automatically inputs the necessary information.

[0371] Step 10:

[0372] The terminal presents the generated contract to the user and provides a confirmation and approval process, including notes regarding the user's psychological state. This allows the user to proceed with the contract process in a calm and composed manner.

[0373] (Example 2)

[0374] 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".

[0375] Conventional information systems provide uniform information and pricing data without adequately considering the emotional state of individual users, making it difficult to provide information optimized to users' needs and psychological conditions. As a result, particularly in real estate transactions, users sometimes experienced stress and dissatisfaction due to information overload and a lack of appropriate pricing.

[0376] 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.

[0377] In this invention, the server includes means for recognizing and acquiring the user's emotional state, means for adjusting the content of information provided using the results of the emotional analysis, and means for considering emotional data in the process of generating contract documents. This enables flexible and personalized information provision and optimization of the contract process in accordance with the user's emotional state.

[0378] "Storage information" refers to information about the content and conditions related to specific services or products that users are seeking.

[0379] "User information" refers to information including the attributes, preferences, and past behavioral history of an individual using the service.

[0380] "Analyzing" means extracting meaning from acquired data and processing it to provide useful information.

[0381] A "data set" is a collection of information in which multiple data points or records are aggregated.

[0382] "Virtual environment technology" is a technology that uses computer technology to provide users with a visual experience that differs from the real world.

[0383] "Emotional state" refers to the psychological and sensory state that a user is experiencing at a particular moment.

[0384] "Emotional analysis" is a technology that quantifies or classifies a user's psychological state based on data such as voice and facial expressions provided by the user.

[0385] The "contract document generation process" refers to the process of creating the documents necessary for a legal agreement or transaction to be concluded.

[0386] "Template information" refers to template information that defines the standard format for documents and data.

[0387] This invention is a system that utilizes emotion recognition technology to provide information and real estate brokerage services optimized for the user. The main components of the system are a server, a terminal, and a user.

[0388] First, the device is equipped with a camera and microphone to acquire data such as the user's voice, facial expressions, and entered preferences. This data is sent to a server that performs emotion analysis. The server uses general emotion analysis software to quantify the emotional state from this data. Specifically, it is possible to use emotion analysis tools from cloud services such as Microsoft Azure.

[0389] The server analyzes real estate property information retrieved from the database based on emotional data and provides information tailored to each user's emotional state. For example, if the analysis indicates that a user is feeling stressed, the server reduces the number of suggested properties to lessen the visual burden. On the other hand, for properties that the user has shown interest in, detailed information and additional content are displayed preferentially.

[0390] In addition, emotional data is input into AI models and used in price prediction and contract document creation processes. At the contract stage, the system checks the user's relaxed state and adjusts the content and wording of the contract documents to reduce psychological burden.

[0391] As a concrete example of the system, suppose a user is looking for a new place to live. If the stress or anxiety the user feels while reviewing the properties is detected through emotion analysis, the server will simplify the information about the suggested properties and adjust it so that the user can make a selection in a relaxed state. An example of a prompt message generated by the AI ​​model would be, "If the user is feeling anxious, how should the suggested property information be simplified?"

[0392] In this way, by implementing this invention, users can receive personalized real estate brokerage services that respond to their emotions.

[0393] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0394] Step 1:

[0395] The device acquires voice and facial expression data from the user and also accepts text input such as region and budget as desired conditions. This data is sent to the server as input data for sentiment analysis. Specifically, the device captures voice and video in real time using a microphone and camera and prepares a text input form.

[0396] Step 2:

[0397] The server receives voice, facial expression, and text data transmitted from the terminal and inputs it into the emotion analysis engine. The input data is processed by the emotion analysis engine and output as numerical data representing the user's emotional state. Specifically, it analyzes changes in voice tone and facial expression to quantify emotions such as joy, stress, and anxiety.

[0398] Step 3:

[0399] The server analyzes real estate property information based on quantified emotional data. It filters property information retrieved from the database according to each user's emotional state and desired conditions, and creates tailored suggestions. Specifically, when a user is feeling stressed, it extracts only the most important properties from the database and reduces the suggestion list.

[0400] Step 4:

[0401] The server uses a generative AI model to predict the price information to be provided to the user. Using sentiment data and historical transaction data as input, it runs the price prediction model and outputs a price range that the user finds acceptable. Specifically, if the sentiment state is positive, it broadens the user's options by suggesting a wider range of price points.

[0402] Step 5:

[0403] The terminal presents the user with adjusted property information, price predictions, and additional information generated by the server. The information is displayed in a visually intuitive interface, making it easy for the user to understand and make selections. Specifically, it dynamically adjusts colors and font sizes according to the user's emotions.

[0404] Step 6:

[0405] If the user wishes to enter into a contract, the server starts the contract document generation process. Based on sentiment data, it adjusts the elements and wording of the contract to help the user enter into the contract calmly, and then outputs the final contract. Specifically, it simplifies or elaborates on template selections and item descriptions according to the user's sentiment.

[0406] This trend will allow users to receive real estate brokerage services that are tailored to their own needs and preferences.

[0407] (Application Example 2)

[0408] 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."

[0409] Current information provision systems struggle to provide appropriate information that takes into account the user's emotional state, and especially in electronic payments, there is a lack of means to reduce user stress and anxiety. As a result, the user experience is not satisfactory, and there are challenges in maintaining service use and improving customer satisfaction.

[0410] 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.

[0411] In this invention, the server includes means for analyzing user emotional data in addition to acquired storage information and customer information; means for providing information that matches the customer's wishes and emotional state based on the analysis results; and means for visually presenting the information through an interface dynamically adjusted based on the emotional data. This enables the provision of information and optimization of the payment experience in accordance with the user's emotional state.

[0412] "Storage information" is a general term for data related to customers and numerical information collected in transactions.

[0413] "Customer information" refers to specific data about customers, such as personal information and past transaction history.

[0414] "User emotional data" refers to information that quantifies the emotional state of users, collected through voice, text, facial expressions, etc.

[0415] "Means of analysis" refers to devices and software that perform calculations and processing to derive useful information from collected data.

[0416] "Means of provision" refers to mechanisms and methods for appropriately and effectively conveying information to users based on the analysis results.

[0417] A "dynamically responsive interface" is a flexible interface that changes its screen layout and operation methods according to the user's emotions and how they use it.

[0418] "Means of visual presentation" refers to technologies and devices that visually present information to users using images, diagrams, and other visual means.

[0419] This invention is a system that optimizes the electronic payment experience by utilizing user emotional data. The server first receives emotional data acquired from the user's smartphone or smart glasses. This emotional data is analyzed by an emotion engine based on voice, facial expressions, and text data. This analysis uses a machine learning model such as Firebase ML Kit to quantify emotions in real time.

[0420] The server evaluates the user's psychological state based on acquired emotional data and dynamically provides optimal information. For example, if the user is feeling stressed, the UI design and operation methods are simplified. Flutter is used to build a visually superior interface. As a result, users are not overwhelmed with information on the payment screen and can complete transactions smoothly.

[0421] Furthermore, the server optimizes its pricing based on user sentiment, presenting prices that are appropriate for the user. The pricing is calculated using an algorithm that combines historical transaction data with real-time sentiment data.

[0422] As a concrete example, consider a payment scenario in a shopping mall. If the app detects stress due to congestion while the user is selecting items and heading to the checkout, it automatically opens a shortcut menu and presents an option to quickly complete the payment using a registered payment method. This significantly improves the user experience.

[0423] An example of a prompt would be: "The emotion engine is currently detecting how frustrated the user is with the waiting time at the checkout. Based on this data, what customer support measures do you think would be effective?" This prompt can be input into a generating AI model to obtain more specific action suggestions.

[0424] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0425] Step 1:

[0426] The device collects the user's voice, facial expressions, and text data in real time. This raw data is acquired as input and converted into a digital format using speech recognition software and a camera application. The device then transmits this input data to an emotion engine.

[0427] Step 2:

[0428] The server uses an emotion engine to analyze the acquired voice, facial expressions, and text data to quantify the user's emotional state. This process employs machine learning models such as Firebase ML Kit to output a score for a specific emotion based on the input data.

[0429] Step 3:

[0430] The server evaluates the user's psychological state based on quantified emotion data and dynamically adjusts the interface. Specifically, it uses Flutter to modify UI elements and simplifies information if it indicates stress. This results in an optimized user interface.

[0431] Step 4:

[0432] Users conduct transactions through a customized UI. During this process, user selections and inputs are sent back to the server and processed as new input data.

[0433] Step 5:

[0434] The server combines user sentiment data with past transaction information to calculate and present the most suitable price. As a result, optimized price information is output and visually presented to the user.

[0435] Step 6:

[0436] When the server interacts with the user, it generates appropriate responses based on emotional data. Using a generative AI model, it processes prompts and generates suggestions such as, "Based on this data, what customer support measures do you think would be effective?" and outputs them.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] [Third Embodiment]

[0441] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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).

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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".

[0453] In this invention, to implement an AI-powered real estate brokerage system, the server receives data such as customer preferences, past behavioral history, and profile information. This data, along with real estate information in the database, is analyzed by an AI algorithm.

[0454] Based on this analysis, the server selects real estate information that matches the customer's desired conditions and generates a list of the most suitable properties. The terminal then presents the generated property list in an interface that the user can easily view and operate. Based on the presented information, the customer can select a property, obtain detailed information, or conduct a virtual viewing using virtual reality technology.

[0455] The server also uses AI to automatically calculate the fair market price of a property based on transaction history and market trends collected from the database. This allows users to obtain pricing information that reflects the latest market data.

[0456] Furthermore, the server is equipped with an automated response system that uses natural language processing technology to analyze user inquiries and respond quickly and accurately 24 hours a day. Users can ask questions and make inquiries about properties through a chat interface, and an AI chatbot will respond to them.

[0457] This system also streamlines contract-related tasks. The server automatically generates contract documents using template information and automatically inputs the necessary information, providing users with quick and accurate documents. This simplifies procedures and reduces errors.

[0458] In this way, AI-powered systems make it possible to provide efficient and customer-oriented real estate brokerage services. Specific benefits include users quickly obtaining property information that matches their preferences, receiving virtual reality-based viewings and price quotes based on accurate market information, and significantly simplifying contract procedures.

[0459] The following describes the processing flow.

[0460] Step 1:

[0461] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server.

[0462] Step 2:

[0463] The server retrieves user preferences and past browsing history from its database. Based on this data, it uses an AI algorithm to analyze suitable real estate information.

[0464] Step 3:

[0465] The server uses AI analysis results to select the properties best suited to the customer's preferences and generates a property list. This list is then sent to the user's device.

[0466] Step 4:

[0467] The terminal displays the received property list in a user-friendly interface and organizes it into a format that allows users to view detailed information and images of each property.

[0468] Step 5:

[0469] Users can select properties of interest via their devices and view detailed information. In some cases, they can also choose a virtual tour using virtual reality technology.

[0470] Step 6:

[0471] The server analyzes market data based on the detailed information of the selected property and uses AI to calculate a fair price.

[0472] Step 7:

[0473] The device notifies the user of detailed information, including the calculated fair price, and the user can verify the price.

[0474] Step 8:

[0475] The user enters their question using the chat interface on their device.

[0476] Step 9:

[0477] The server analyzes the received question using natural language processing technology, and the AI ​​chatbot generates an appropriate answer.

[0478] Step 10:

[0479] The server generates a response, which is then sent to the user's device, allowing the user to immediately see the response.

[0480] Step 11:

[0481] When a user decides to purchase a property, the server runs a template-based automated contract creation program to generate a contract with the necessary information automatically entered.

[0482] Step 12:

[0483] The terminal presents the generated contract to the user, enabling online confirmation and approval.

[0484] (Example 1)

[0485] 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."

[0486] Conventional information systems struggled to provide detailed information that responded immediately to individual user requests, resulting in significant time and effort spent on manual information gathering and inquiry handling. Furthermore, there were challenges in accuracy and efficiency in properly valuing goods and creating contract documents, highlighting the need for new technological solutions to improve the user experience.

[0487] 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.

[0488] In this invention, the server includes means for receiving and analyzing input data acquired from a communication terminal, means for extracting and providing information suitable for a specific request based on the analysis results, and means for calculating a price using information acquired from a data storage unit. This enables accurate and prompt responses to diverse user requests, as well as efficient price evaluation and contract document creation.

[0489] A "communication terminal" is a device used to send and receive information, and is used by users to input or view data.

[0490] "Input data" refers to the information provided by users when specifying particular requests or conditions, and it forms the basis for the system's analysis.

[0491] "Means of analysis" refers to a function that performs a process of calculating or evaluating information that matches the user's requests and conditions using the received data.

[0492] The "data storage unit" is a component for accumulating related information such as product information and market data, and is a data storage that is referenced during analysis and information provision.

[0493] "Virtual reality technology" refers to technologies that use virtual reality to provide users with visual information, and is a technique for digitally recreating real-life experiences.

[0494] "Natural language processing technology" is a computer technology that understands inquiries entered in human language and responds appropriately, and it is a method of processing human language using AI.

[0495] "Means for automatically generating document information" refers to a function that efficiently and accurately creates necessary documents based on pre-configured templates and provided data.

[0496] A description of embodiments for carrying out this invention will be given.

[0497] This real estate brokerage system consists of a communication terminal, a server, a data storage unit, and an analysis engine utilizing AI technology. The server receives data such as desired conditions and profile information entered by the user via the communication terminal. This data is analyzed by a generative AI model using machine learning frameworks such as TensorFlow. The AI ​​model matches real estate information stored in a large database with user information to identify property information that suits the user's preferences.

[0498] The server uses data analysis libraries such as scikit-learn to analyze information obtained from historical market data and transaction history in order to calculate the fair price of an asset. This allows it to provide users with information based on objective and up-to-date market analysis.

[0499] The device is built using front-end technologies such as React and Vue.js, providing users with an intuitive interface. Through this interface, users can virtually tour properties using virtual reality technology. Using a VR headset, users can examine the property in detail from a 360-degree perspective.

[0500] Furthermore, the server utilizes natural language processing technology to interpret user inquiries and has an automated response function for quick responses. By using an AI chatbot, the server can handle inquiries 24 hours a day. For example, if a user enters the question "Can I keep pets in this property?" into the chat interface, the server will check its database and provide the relevant information immediately.

[0501] Regarding the automated generation of contract documents, the server utilizes template information and integrates with electronic contract services such as DocuSign to establish a process for accurately and quickly creating the necessary documents. This allows users to complete contract procedures smoothly online.

[0502] As a concrete example of a prompt, you can use a command such as, "Please find a 3LDK property that is within a 10-minute walk from the station and allows pets." Based on this command, the AI ​​will filter relevant real estate information and present suitable properties to the user.

[0503] This system configuration allows for a more efficient real estate brokerage process and significantly improves the user experience.

[0504] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0505] Step 1:

[0506] The server receives user preferences, behavioral history, and profile information via a communication terminal. This data is stored in a database as input. The data is used as foundational information to identify user needs.

[0507] Step 2:

[0508] The server analyzes the received data using generative AI models such as TensorFlow. This step uses machine learning algorithms to generate prompts and identify real estate information that matches them. The output is a list of properties that best match the user's preferences. This list is then ranked by scoring.

[0509] Step 3:

[0510] The server formats the generated property list into an intuitive user interface using React or Vue.js. The terminal displays the property list to the user through this interface. The input is the property list, and the output is a screen formatted for easy viewing by the user.

[0511] Step 4:

[0512] Users view property details and conduct virtual tours through their devices. This step utilizes virtual space technology to allow users to experience the property's interior from a 360-degree perspective. The input is the property information selected by the user, and the output is a real-time generated virtual tour video.

[0513] Step 5:

[0514] The server calculates the fair market value of a property using data analysis techniques such as scikit-learn, based on past transaction history and market trends. The input is market transaction data, and the output is the calculated price information. This allows users to verify prices based on market value.

[0515] Step 6:

[0516] Questions and inquiries from users are sent to the server via a chat interface. The server analyzes these inquiries using natural language processing, and an AI chatbot provides an appropriate answer. The input is the user's inquiry, and the output is the analyzed answer information.

[0517] Step 7:

[0518] In contract procedures, the server automatically generates contract documents using template information. Necessary information is retrieved from a database, and the document is accurately created in conjunction with electronic contract services such as DocuSign. Input consists of the necessary contract template and user information, while output is the automatically generated contract.

[0519] (Application Example 1)

[0520] 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."

[0521] In today's real estate market, it is difficult for customers to quickly and accurately obtain property information that matches their preferences. Furthermore, there is a growing demand for fair pricing based on market trends and streamlined contract procedures. At the same time, customers increasingly desire to view properties virtually without visiting in person. Against this backdrop, providing customers with personalized experiences while efficiently presenting property information has become a crucial challenge.

[0522] 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.

[0523] In this invention, the server includes means for acquiring and analyzing storage information and customer information; means for providing information that matches the customer's wishes based on the analysis results; means for calculating a fair price based on information acquired from a database; means for visually presenting information using virtual reality technology; means for automatically processing customer inquiries; means for suggesting personalized information using artificial intelligence; and means for enabling viewing of information in a virtual space using a mobile information terminal or device. As a result, customers can efficiently acquire property information that matches their wishes and visually confirm properties through virtual reality.

[0524] "Storage information" refers to data collected to understand the user's wishes and needs, and is an important factor when selecting a property.

[0525] "Customer information" refers to information necessary to respond to individual requests, such as user profiles and behavioral history.

[0526] "Analysis" is the process of processing collected information using AI algorithms to select properties that match the user's preferences.

[0527] "Fair price" refers to a reasonable property price calculated by AI based on market trends and past transactions.

[0528] "Virtual reality technology" is a technology that uses 3D technology to visualize the interior of a property, making users feel as if they are actually viewing it.

[0529] "Automated inquiry processing" is a function in which AI understands user questions and requests through natural language processing and responds quickly.

[0530] "Artificial intelligence" is an advanced processing technology that analyzes customer information and provides property information tailored to individual needs.

[0531] "Personal information terminals" refer to smartphones and head-mounted displays used by users to access virtual stores and information.

[0532] A "virtual space" is a computer-generated area where users can view and manipulate property information within a digital environment.

[0533] This system is designed to allow users to efficiently acquire real estate information and provide a realistic experience through virtual reality. The server uses artificial intelligence to analyze customer and storage information and generate personalized property information. Machine learning frameworks such as Python's TensorFlow and PyTorch are used for this analysis.

[0534] The acquired property information is visualized in a virtual reality environment using Unity. Users can experience these virtual properties via smartphones or head-mounted displays such as Oculus Quest. When users view properties in the virtual space, the server calculates and displays a fair price in real time based on market trend data and past transaction information. A database management system assists in this price calculation.

[0535] On the device, natural language processing technology powered by Google's Dialogflow is implemented, allowing users to input questions and uncertainties about properties via a chat interface. An AI chatbot then responds quickly, supporting the user's decision-making. Furthermore, a template engine is used for the automatic generation of contract documents, enabling simple and accurate document creation.

[0536] For example, if a user enters criteria such as "I'm looking for a 3LDK apartment in Tokyo where pets are allowed," the system will list the properties that best match those criteria. The user can then virtually tour multiple properties and experience the process of selecting the one they like best.

[0537] An example of a prompt to input into the generating AI model is as follows: "Visualize the most suitable property information based on the user's desired conditions for a virtual viewing. Utilize VR technology to present detailed property information as well."

[0538] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0539] Step 1:

[0540] The server collects user preferences and profile information. The entered data is formatted as preprocessing for analysis by an AI algorithm. This prepares the system to gain a detailed understanding of the user's individual needs.

[0541] Step 2:

[0542] The server analyzes the collected user data using Python's TensorFlow. Based on the analysis, property information that best matches the user's preferences is selected. This output is a property list based on the user's desired conditions.

[0543] Step 3:

[0544] The server uses Unity to visualize selected property information within a 3D virtual reality environment. Based on the input data, the structure and interior of the property are realistically rendered in the virtual space, which the user views using a head-mounted display.

[0545] Step 4:

[0546] Users tour properties in a virtual space using a smartphone or head-mounted display. Depending on the user's selection, the server switches scenes or loads information on other properties as needed.

[0547] Step 5:

[0548] The server retrieves market trends and historical transaction information from the database and calculates a fair price in real time using Python. The calculation results are presented to users during virtual viewings and serve as useful price information.

[0549] Step 6:

[0550] User inquiries are sent via a text chat interface. The device uses Google's Dialogflow to analyze the natural language input, and an AI chatbot generates an appropriate response.

[0551] Step 7:

[0552] The server uses a template engine to automatically generate contract documents for the property selected by the user. This process automatically populates the template document with the necessary information, ensuring accurate and rapid document creation.

[0553] 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.

[0554] This invention implements a system that provides more personalized information by combining a conventional property information provision system with an emotion engine that recognizes the user's emotions. The server uses not only the desired conditions and behavioral history received from the user, but also emotion data acquired from the user's terminal for analysis. The emotion engine detects emotions from the user's voice, text, facial expressions, etc., and quantifies their state.

[0555] The server uses this sentiment data to optimize the user experience by making adjustments when suggesting properties and providing information. For example, if a user is experiencing stress, the number of suggested properties will be reduced to lessen the visual burden. Furthermore, properties deemed to be of high interest will receive priority in displaying detailed information and additional content.

[0556] By incorporating user emotions obtained through an emotion engine into price predictions, more appropriate price information is presented to users. This allows for pricing that is psychologically acceptable to users.

[0557] Furthermore, when a user asks a question through the chat interface, the server uses an emotion engine to understand the user's emotional state and generate an appropriate response based on that. For example, if the user is feeling anxious, the server will respond using clearer and more polite language.

[0558] This emotional data is also used in the contract document generation process to adjust the process so that users can proceed with the contract in a calm state. This enables the real estate brokerage service to be flexible and effective, tailored to the user's psychological state.

[0559] This system allows users to have an experience that goes beyond mere information provision, enabling them to make more suitable choices based on their individual needs and emotions.

[0560] The following describes the processing flow.

[0561] Step 1:

[0562] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server. The device also captures the user's facial expressions and tone of voice as emotional data through voice and camera.

[0563] Step 2:

[0564] The server comprehensively analyzes the user's desired conditions, past search history, and emotional data analyzed by the emotion engine. In this process, the AI ​​algorithm selects properties by taking into account information corresponding to the user's emotional state.

[0565] Step 3:

[0566] Based on the analysis results, the server selects the most suitable properties for the user and generates a list of selected properties. The number and display format of these properties are adjusted according to the user's emotional state.

[0567] Step 4:

[0568] The terminal displays a generated list of properties to the user. The user can view property details through an emotion-optimized interface. Furthermore, for properties of interest, a virtual tour using virtual reality technology is available.

[0569] Step 5:

[0570] The server analyzes market data related to the selected property and calculates a fair price using an AI model. This price information is then adjusted based on sentiment data to make it psychologically more acceptable to the user.

[0571] Step 6:

[0572] The device notifies the user of detailed information, including the calculated fair price. This allows the user to fully understand the property's price and details, enabling them to confidently choose a property.

[0573] Step 7:

[0574] When a user enters an inquiry via the chat interface from their device, the server uses an emotion engine to analyze the user's emotional state.

[0575] Step 8:

[0576] Based on the results of sentiment analysis, the server generates a response to the user in an appropriate tone and content. For example, if the user is feeling stressed, the response will be organized clearly and reassuringly.

[0577] Step 9:

[0578] When a user decides to purchase a property, the server uses a template-based automatic contract generation function to create a contract and automatically inputs the necessary information.

[0579] Step 10:

[0580] The terminal presents the generated contract to the user and provides a confirmation and approval process, including notes regarding the user's psychological state. This allows the user to proceed with the contract process in a calm and composed manner.

[0581] (Example 2)

[0582] 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."

[0583] Conventional information systems provide uniform information and pricing data without adequately considering the emotional state of individual users, making it difficult to provide information optimized to users' needs and psychological conditions. As a result, particularly in real estate transactions, users sometimes experienced stress and dissatisfaction due to information overload and a lack of appropriate pricing.

[0584] 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.

[0585] In this invention, the server includes means for recognizing and acquiring the user's emotional state, means for adjusting the content of information provided using the results of the emotional analysis, and means for considering emotional data in the process of generating contract documents. This enables flexible and personalized information provision and optimization of the contract process in accordance with the user's emotional state.

[0586] "Storage information" refers to information about the content and conditions related to specific services or products that users are seeking.

[0587] "User information" refers to information including the attributes, preferences, and past behavioral history of an individual using the service.

[0588] "Analyzing" means extracting meaning from acquired data and processing it to provide useful information.

[0589] A "data set" is a collection of information in which multiple data points or records are aggregated.

[0590] "Virtual environment technology" is a technology that uses computer technology to provide users with a visual experience that differs from the real world.

[0591] "Emotional state" refers to the psychological and sensory state that a user is experiencing at a particular moment.

[0592] "Emotional analysis" is a technology that quantifies or classifies a user's psychological state based on data such as voice and facial expressions provided by the user.

[0593] The "contract document generation process" refers to the process of creating the documents necessary for a legal agreement or transaction to be concluded.

[0594] "Template information" refers to template information that defines the standard format for documents and data.

[0595] This invention is a system that utilizes emotion recognition technology to provide information and real estate brokerage services optimized for the user. The main components of the system are a server, a terminal, and a user.

[0596] First, the device is equipped with a camera and microphone to acquire data such as the user's voice, facial expressions, and entered preferences. This data is sent to a server that performs emotion analysis. The server uses general emotion analysis software to quantify the emotional state from this data. Specifically, it is possible to use emotion analysis tools from cloud services such as Microsoft Azure.

[0597] The server analyzes real estate property information retrieved from the database based on emotional data and provides information tailored to each user's emotional state. For example, if the analysis indicates that a user is feeling stressed, the server reduces the number of suggested properties to lessen the visual burden. On the other hand, for properties that the user has shown interest in, detailed information and additional content are displayed preferentially.

[0598] In addition, emotional data is input into AI models and used in price prediction and contract document creation processes. At the contract stage, the system checks the user's relaxed state and adjusts the content and wording of the contract documents to reduce psychological burden.

[0599] As a concrete example of the system, suppose a user is looking for a new place to live. If the stress or anxiety the user feels while reviewing the properties is detected through emotion analysis, the server will simplify the information about the suggested properties and adjust it so that the user can make a selection in a relaxed state. An example of a prompt message generated by the AI ​​model would be, "If the user is feeling anxious, how should the suggested property information be simplified?"

[0600] In this way, by implementing this invention, users can receive personalized real estate brokerage services that respond to their emotions.

[0601] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0602] Step 1:

[0603] The device acquires voice and facial expression data from the user and also accepts text input such as region and budget as desired conditions. This data is sent to the server as input data for sentiment analysis. Specifically, the device captures voice and video in real time using a microphone and camera and prepares a text input form.

[0604] Step 2:

[0605] The server receives voice, facial expression, and text data transmitted from the terminal and inputs it into the emotion analysis engine. The input data is processed by the emotion analysis engine and output as numerical data representing the user's emotional state. Specifically, it analyzes changes in voice tone and facial expression to quantify emotions such as joy, stress, and anxiety.

[0606] Step 3:

[0607] The server analyzes real estate property information based on quantified emotional data. It filters property information retrieved from the database according to each user's emotional state and desired conditions, and creates tailored suggestions. Specifically, when a user is feeling stressed, it extracts only the most important properties from the database and reduces the suggestion list.

[0608] Step 4:

[0609] The server uses a generative AI model to predict the price information to be provided to the user. Using sentiment data and historical transaction data as input, it runs the price prediction model and outputs a price range that the user finds acceptable. Specifically, if the sentiment state is positive, it broadens the user's options by suggesting a wider range of price points.

[0610] Step 5:

[0611] The terminal presents the user with adjusted property information, price predictions, and additional information generated by the server. The information is displayed in a visually intuitive interface, making it easy for the user to understand and make selections. Specifically, it dynamically adjusts colors and font sizes according to the user's emotions.

[0612] Step 6:

[0613] If the user wishes to enter into a contract, the server starts the contract document generation process. Based on sentiment data, it adjusts the elements and wording of the contract to help the user enter into the contract calmly, and then outputs the final contract. Specifically, it simplifies or elaborates on template selections and item descriptions according to the user's sentiment.

[0614] This trend will allow users to receive real estate brokerage services that are tailored to their own needs and preferences.

[0615] (Application Example 2)

[0616] 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."

[0617] Current information provision systems struggle to provide appropriate information that takes into account the user's emotional state, and especially in electronic payments, there is a lack of means to reduce user stress and anxiety. As a result, the user experience is not satisfactory, and there are challenges in maintaining service use and improving customer satisfaction.

[0618] 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.

[0619] In this invention, the server includes means for analyzing user emotional data in addition to acquired storage information and customer information; means for providing information that matches the customer's wishes and emotional state based on the analysis results; and means for visually presenting the information through an interface dynamically adjusted based on the emotional data. This enables the provision of information and optimization of the payment experience in accordance with the user's emotional state.

[0620] "Storage information" is a general term for data related to customers and numerical information collected in transactions.

[0621] "Customer information" refers to specific data about customers, such as personal information and past transaction history.

[0622] "User emotional data" refers to information that quantifies the emotional state of users, collected through voice, text, facial expressions, etc.

[0623] "Means of analysis" refers to devices and software that perform calculations and processing to derive useful information from collected data.

[0624] "Means of provision" refers to mechanisms and methods for appropriately and effectively conveying information to users based on the analysis results.

[0625] A "dynamically responsive interface" is a flexible interface that changes its screen layout and operation methods according to the user's emotions and how they use it.

[0626] "Means of visual presentation" refers to technologies and devices that visually present information to users using images, diagrams, and other visual means.

[0627] This invention is a system that optimizes the electronic payment experience by utilizing user emotional data. The server first receives emotional data acquired from the user's smartphone or smart glasses. This emotional data is analyzed by an emotion engine based on voice, facial expressions, and text data. This analysis uses a machine learning model such as Firebase ML Kit to quantify emotions in real time.

[0628] The server evaluates the user's psychological state based on acquired emotional data and dynamically provides optimal information. For example, if the user is feeling stressed, the UI design and operation methods are simplified. Flutter is used to build a visually superior interface. As a result, users are not overwhelmed with information on the payment screen and can complete transactions smoothly.

[0629] Furthermore, the server optimizes its pricing based on user sentiment, presenting prices that are appropriate for the user. The pricing is calculated using an algorithm that combines historical transaction data with real-time sentiment data.

[0630] As a concrete example, consider a payment scenario in a shopping mall. If the app detects stress due to congestion while the user is selecting items and heading to the checkout, it automatically opens a shortcut menu and presents an option to quickly complete the payment using a registered payment method. This significantly improves the user experience.

[0631] An example of a prompt would be: "The emotion engine is currently detecting how frustrated the user is with the waiting time at the checkout. Based on this data, what customer support measures do you think would be effective?" This prompt can be input into a generating AI model to obtain more specific action suggestions.

[0632] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0633] Step 1:

[0634] The device collects the user's voice, facial expressions, and text data in real time. This raw data is acquired as input and converted into a digital format using speech recognition software and a camera application. The device then transmits this input data to an emotion engine.

[0635] Step 2:

[0636] The server uses an emotion engine to analyze the acquired voice, facial expressions, and text data to quantify the user's emotional state. This process employs machine learning models such as Firebase ML Kit to output a score for a specific emotion based on the input data.

[0637] Step 3:

[0638] The server evaluates the user's psychological state based on quantified emotion data and dynamically adjusts the interface. Specifically, it uses Flutter to modify UI elements and simplifies information if it indicates stress. This results in an optimized user interface.

[0639] Step 4:

[0640] Users conduct transactions through a customized UI. During this process, user selections and inputs are sent back to the server and processed as new input data.

[0641] Step 5:

[0642] The server combines user sentiment data with past transaction information to calculate and present the most suitable price. As a result, optimized price information is output and visually presented to the user.

[0643] Step 6:

[0644] When the server interacts with the user, it generates appropriate responses based on emotional data. Using a generative AI model, it processes prompts and generates suggestions such as, "Based on this data, what customer support measures do you think would be effective?" and outputs them.

[0645] 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.

[0646] 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.

[0647] 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.

[0648] [Fourth Embodiment]

[0649] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0650] 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.

[0651] 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).

[0652] 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.

[0653] 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.

[0654] 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).

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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".

[0662] In this invention, to implement an AI-powered real estate brokerage system, the server receives data such as customer preferences, past behavioral history, and profile information. This data, along with real estate information in the database, is analyzed by an AI algorithm.

[0663] Based on this analysis, the server selects real estate information that matches the customer's desired conditions and generates a list of the most suitable properties. The terminal then presents the generated property list in an interface that the user can easily view and operate. Based on the presented information, the customer can select a property, obtain detailed information, or conduct a virtual viewing using virtual reality technology.

[0664] The server also uses AI to automatically calculate the fair market price of a property based on transaction history and market trends collected from the database. This allows users to obtain pricing information that reflects the latest market data.

[0665] Furthermore, the server is equipped with an automated response system that uses natural language processing technology to analyze user inquiries and respond quickly and accurately 24 hours a day. Users can ask questions and make inquiries about properties through a chat interface, and an AI chatbot will respond to them.

[0666] This system also streamlines contract-related tasks. The server automatically generates contract documents using template information and automatically inputs the necessary information, providing users with quick and accurate documents. This simplifies procedures and reduces errors.

[0667] In this way, AI-powered systems make it possible to provide efficient and customer-oriented real estate brokerage services. Specific benefits include users quickly obtaining property information that matches their preferences, receiving virtual reality-based viewings and price quotes based on accurate market information, and significantly simplifying contract procedures.

[0668] The following describes the processing flow.

[0669] Step 1:

[0670] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server.

[0671] Step 2:

[0672] The server retrieves user preferences and past browsing history from its database. Based on this data, it uses an AI algorithm to analyze suitable real estate information.

[0673] Step 3:

[0674] The server uses AI analysis results to select the properties best suited to the customer's preferences and generates a property list. This list is then sent to the user's device.

[0675] Step 4:

[0676] The terminal displays the received property list in a user-friendly interface and organizes it into a format that allows users to view detailed information and images of each property.

[0677] Step 5:

[0678] Users can select properties of interest via their devices and view detailed information. In some cases, they can also choose a virtual tour using virtual reality technology.

[0679] Step 6:

[0680] The server analyzes market data based on the detailed information of the selected property and uses AI to calculate a fair price.

[0681] Step 7:

[0682] The device notifies the user of detailed information, including the calculated fair price, and the user can verify the price.

[0683] Step 8:

[0684] The user enters their question using the chat interface on their device.

[0685] Step 9:

[0686] The server analyzes the received question using natural language processing technology, and the AI ​​chatbot generates an appropriate answer.

[0687] Step 10:

[0688] The server generates a response, which is then sent to the user's device, allowing the user to immediately see the response.

[0689] Step 11:

[0690] When a user decides to purchase a property, the server runs a template-based automated contract creation program to generate a contract with the necessary information automatically entered.

[0691] Step 12:

[0692] The terminal presents the generated contract to the user, enabling online confirmation and approval.

[0693] (Example 1)

[0694] 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".

[0695] Conventional information systems struggled to provide detailed information that responded immediately to individual user requests, resulting in significant time and effort spent on manual information gathering and inquiry handling. Furthermore, there were challenges in accuracy and efficiency in properly valuing goods and creating contract documents, highlighting the need for new technological solutions to improve the user experience.

[0696] 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.

[0697] In this invention, the server includes means for receiving and analyzing input data acquired from a communication terminal, means for extracting and providing information suitable for a specific request based on the analysis results, and means for calculating a price using information acquired from a data storage unit. This enables accurate and prompt responses to diverse user requests, as well as efficient price evaluation and contract document creation.

[0698] A "communication terminal" is a device used to send and receive information, and is used by users to input or view data.

[0699] "Input data" refers to the information provided by users when specifying particular requests or conditions, and it forms the basis for the system's analysis.

[0700] "Means of analysis" refers to a function that performs a process of calculating or evaluating information that matches the user's requests and conditions using the received data.

[0701] The "data storage unit" is a component for accumulating related information such as product information and market data, and is a data storage that is referenced during analysis and information provision.

[0702] "Virtual reality technology" refers to technologies that use virtual reality to provide users with visual information, and is a technique for digitally recreating real-life experiences.

[0703] "Natural language processing technology" is a computer technology that understands inquiries entered in human language and responds appropriately, and it is a method of processing human language using AI.

[0704] "Means for automatically generating document information" refers to a function that efficiently and accurately creates necessary documents based on pre-configured templates and provided data.

[0705] A description of embodiments for carrying out this invention will be given.

[0706] This real estate brokerage system consists of a communication terminal, a server, a data storage unit, and an analysis engine utilizing AI technology. The server receives data such as desired conditions and profile information entered by the user via the communication terminal. This data is analyzed by a generative AI model using machine learning frameworks such as TensorFlow. The AI ​​model matches real estate information stored in a large database with user information to identify property information that suits the user's preferences.

[0707] The server uses data analysis libraries such as scikit-learn to analyze information obtained from historical market data and transaction history in order to calculate the fair price of an asset. This allows it to provide users with information based on objective and up-to-date market analysis.

[0708] The device is built using front-end technologies such as React and Vue.js, providing users with an intuitive interface. Through this interface, users can virtually tour properties using virtual reality technology. Using a VR headset, users can examine the property in detail from a 360-degree perspective.

[0709] Furthermore, the server utilizes natural language processing technology to interpret user inquiries and has an automated response function for quick responses. By using an AI chatbot, the server can handle inquiries 24 hours a day. For example, if a user enters the question "Can I keep pets in this property?" into the chat interface, the server will check its database and provide the relevant information immediately.

[0710] Regarding the automated generation of contract documents, the server utilizes template information and integrates with electronic contract services such as DocuSign to establish a process for accurately and quickly creating the necessary documents. This allows users to complete contract procedures smoothly online.

[0711] As a concrete example of a prompt, you can use a command such as, "Please find a 3LDK property that is within a 10-minute walk from the station and allows pets." Based on this command, the AI ​​will filter relevant real estate information and present suitable properties to the user.

[0712] This system configuration allows for a more efficient real estate brokerage process and significantly improves the user experience.

[0713] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0714] Step 1:

[0715] The server receives user preferences, behavioral history, and profile information via a communication terminal. This data is stored in a database as input. The data is used as foundational information to identify user needs.

[0716] Step 2:

[0717] The server analyzes the received data using generative AI models such as TensorFlow. This step uses machine learning algorithms to generate prompts and identify real estate information that matches them. The output is a list of properties that best match the user's preferences. This list is then ranked by scoring.

[0718] Step 3:

[0719] The server formats the generated property list into an intuitive user interface using React or Vue.js. The terminal displays the property list to the user through this interface. The input is the property list, and the output is a screen formatted for easy viewing by the user.

[0720] Step 4:

[0721] Users view property details and conduct virtual tours through their devices. This step utilizes virtual space technology to allow users to experience the property's interior from a 360-degree perspective. The input is the property information selected by the user, and the output is a real-time generated virtual tour video.

[0722] Step 5:

[0723] The server calculates the fair market value of a property using data analysis techniques such as scikit-learn, based on past transaction history and market trends. The input is market transaction data, and the output is the calculated price information. This allows users to verify prices based on market value.

[0724] Step 6:

[0725] Questions and inquiries from users are sent to the server via a chat interface. The server analyzes these inquiries using natural language processing, and an AI chatbot provides an appropriate answer. The input is the user's inquiry, and the output is the analyzed answer information.

[0726] Step 7:

[0727] In contract procedures, the server automatically generates contract documents using template information. Necessary information is retrieved from a database, and the document is accurately created in conjunction with electronic contract services such as DocuSign. Input consists of the necessary contract template and user information, while output is the automatically generated contract.

[0728] (Application Example 1)

[0729] 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".

[0730] In today's real estate market, it is difficult for customers to quickly and accurately obtain property information that matches their preferences. Furthermore, there is a growing demand for fair pricing based on market trends and streamlined contract procedures. At the same time, customers increasingly desire to view properties virtually without visiting in person. Against this backdrop, providing customers with personalized experiences while efficiently presenting property information has become a crucial challenge.

[0731] 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.

[0732] In this invention, the server includes means for acquiring and analyzing storage information and customer information; means for providing information that matches the customer's wishes based on the analysis results; means for calculating a fair price based on information acquired from a database; means for visually presenting information using virtual reality technology; means for automatically processing customer inquiries; means for suggesting personalized information using artificial intelligence; and means for enabling viewing of information in a virtual space using a mobile information terminal or device. As a result, customers can efficiently acquire property information that matches their wishes and visually confirm properties through virtual reality.

[0733] "Storage information" refers to data collected to understand the user's wishes and needs, and is an important factor when selecting a property.

[0734] "Customer information" refers to information necessary to respond to individual requests, such as user profiles and behavioral history.

[0735] "Analysis" is the process of processing collected information using AI algorithms to select properties that match the user's preferences.

[0736] "Fair price" refers to a reasonable property price calculated by AI based on market trends and past transactions.

[0737] "Virtual reality technology" is a technology that uses 3D technology to visualize the interior of a property, making users feel as if they are actually viewing it.

[0738] "Automated inquiry processing" is a function in which AI understands user questions and requests through natural language processing and responds quickly.

[0739] "Artificial intelligence" is an advanced processing technology that analyzes customer information and provides property information tailored to individual needs.

[0740] "Personal information terminals" refer to smartphones and head-mounted displays used by users to access virtual stores and information.

[0741] A "virtual space" is a computer-generated area where users can view and manipulate property information within a digital environment.

[0742] This system is designed to allow users to efficiently acquire real estate information and provide a realistic experience through virtual reality. The server uses artificial intelligence to analyze customer and storage information and generate personalized property information. Machine learning frameworks such as Python's TensorFlow and PyTorch are used for this analysis.

[0743] The acquired property information is visualized in a virtual reality environment using Unity. Users can experience these virtual properties via smartphones or head-mounted displays such as Oculus Quest. When users view properties in the virtual space, the server calculates and displays a fair price in real time based on market trend data and past transaction information. A database management system assists in this price calculation.

[0744] On the device, natural language processing technology powered by Google's Dialogflow is implemented, allowing users to input questions and uncertainties about properties via a chat interface. An AI chatbot then responds quickly, supporting the user's decision-making. Furthermore, a template engine is used for the automatic generation of contract documents, enabling simple and accurate document creation.

[0745] For example, if a user enters criteria such as "I'm looking for a 3LDK apartment in Tokyo where pets are allowed," the system will list the properties that best match those criteria. The user can then virtually tour multiple properties and experience the process of selecting the one they like best.

[0746] An example of a prompt to input into the generating AI model is as follows: "Visualize the most suitable property information based on the user's desired conditions for a virtual viewing. Utilize VR technology to present detailed property information as well."

[0747] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0748] Step 1:

[0749] The server collects user preferences and profile information. The entered data is formatted as preprocessing for analysis by an AI algorithm. This prepares the system to gain a detailed understanding of the user's individual needs.

[0750] Step 2:

[0751] The server analyzes the collected user data using Python's TensorFlow. Based on the analysis, property information that best matches the user's preferences is selected. This output is a property list based on the user's desired conditions.

[0752] Step 3:

[0753] The server uses Unity to visualize selected property information within a 3D virtual reality environment. Based on the input data, the structure and interior of the property are realistically rendered in the virtual space, which the user views using a head-mounted display.

[0754] Step 4:

[0755] Users tour properties in a virtual space using a smartphone or head-mounted display. Depending on the user's selection, the server switches scenes or loads information on other properties as needed.

[0756] Step 5:

[0757] The server retrieves market trends and historical transaction information from the database and calculates a fair price in real time using Python. The calculation results are presented to users during virtual viewings and serve as useful price information.

[0758] Step 6:

[0759] User inquiries are sent via a text chat interface. The device uses Google's Dialogflow to analyze the natural language input, and an AI chatbot generates an appropriate response.

[0760] Step 7:

[0761] The server uses a template engine to automatically generate contract documents for the property selected by the user. This process automatically populates the template document with the necessary information, ensuring accurate and rapid document creation.

[0762] 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.

[0763] This invention implements a system that provides more personalized information by combining a conventional property information provision system with an emotion engine that recognizes the user's emotions. The server uses not only the desired conditions and behavioral history received from the user, but also emotion data acquired from the user's terminal for analysis. The emotion engine detects emotions from the user's voice, text, facial expressions, etc., and quantifies their state.

[0764] The server uses this sentiment data to optimize the user experience by making adjustments when suggesting properties and providing information. For example, if a user is experiencing stress, the number of suggested properties will be reduced to lessen the visual burden. Furthermore, properties deemed to be of high interest will receive priority in displaying detailed information and additional content.

[0765] By incorporating user emotions obtained through an emotion engine into price predictions, more appropriate price information is presented to users. This allows for pricing that is psychologically acceptable to users.

[0766] Furthermore, when a user asks a question through the chat interface, the server uses an emotion engine to understand the user's emotional state and generate an appropriate response based on that. For example, if the user is feeling anxious, the server will respond using clearer and more polite language.

[0767] This emotional data is also used in the contract document generation process to adjust the process so that users can proceed with the contract in a calm state. This enables the real estate brokerage service to be flexible and effective, tailored to the user's psychological state.

[0768] This system allows users to have an experience that goes beyond mere information provision, enabling them to make more suitable choices based on their individual needs and emotions.

[0769] The following describes the processing flow.

[0770] Step 1:

[0771] The user enters their desired criteria (e.g., area, floor plan, budget, etc.) using their device and sends a property search request to the server. The device also captures the user's facial expressions and tone of voice as emotional data through voice and camera.

[0772] Step 2:

[0773] The server comprehensively analyzes the user's desired conditions, past search history, and emotional data analyzed by the emotion engine. In this process, the AI ​​algorithm selects properties by taking into account information corresponding to the user's emotional state.

[0774] Step 3:

[0775] Based on the analysis results, the server selects the most suitable properties for the user and generates a list of selected properties. The number and display format of these properties are adjusted according to the user's emotional state.

[0776] Step 4:

[0777] The terminal displays a generated list of properties to the user. The user can view property details through an emotion-optimized interface. Furthermore, for properties of interest, a virtual tour using virtual reality technology is available.

[0778] Step 5:

[0779] The server analyzes market data related to the selected property and calculates a fair price using an AI model. This price information is then adjusted based on sentiment data to make it psychologically more acceptable to the user.

[0780] Step 6:

[0781] The device notifies the user of detailed information, including the calculated fair price. This allows the user to fully understand the property's price and details, enabling them to confidently choose a property.

[0782] Step 7:

[0783] When a user enters an inquiry via the chat interface from their device, the server uses an emotion engine to analyze the user's emotional state.

[0784] Step 8:

[0785] Based on the results of sentiment analysis, the server generates a response to the user in an appropriate tone and content. For example, if the user is feeling stressed, the response will be organized clearly and reassuringly.

[0786] Step 9:

[0787] When a user decides to purchase a property, the server uses a template-based automatic contract generation function to create a contract and automatically inputs the necessary information.

[0788] Step 10:

[0789] The terminal presents the generated contract to the user and provides a confirmation and approval process, including notes regarding the user's psychological state. This allows the user to proceed with the contract process in a calm and composed manner.

[0790] (Example 2)

[0791] 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".

[0792] Conventional information systems provide uniform information and pricing data without adequately considering the emotional state of individual users, making it difficult to provide information optimized to users' needs and psychological conditions. As a result, particularly in real estate transactions, users sometimes experienced stress and dissatisfaction due to information overload and a lack of appropriate pricing.

[0793] 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.

[0794] In this invention, the server includes means for recognizing and acquiring the user's emotional state, means for adjusting the content of information provided using the results of the emotional analysis, and means for considering emotional data in the process of generating contract documents. This enables flexible and personalized information provision and optimization of the contract process in accordance with the user's emotional state.

[0795] "Storage information" refers to information about the content and conditions related to specific services or products that users are seeking.

[0796] "User information" refers to information including the attributes, preferences, and past behavioral history of an individual using the service.

[0797] "Analyzing" means extracting meaning from acquired data and processing it to provide useful information.

[0798] A "data set" is a collection of information in which multiple data points or records are aggregated.

[0799] "Virtual environment technology" is a technology that uses computer technology to provide users with a visual experience that differs from the real world.

[0800] "Emotional state" refers to the psychological and sensory state that a user is experiencing at a particular moment.

[0801] "Emotional analysis" is a technology that quantifies or classifies a user's psychological state based on data such as voice and facial expressions provided by the user.

[0802] The "contract document generation process" refers to the process of creating the documents necessary for a legal agreement or transaction to be concluded.

[0803] "Template information" refers to template information that defines the standard format for documents and data.

[0804] This invention is a system that utilizes emotion recognition technology to provide information and real estate brokerage services optimized for the user. The main components of the system are a server, a terminal, and a user.

[0805] First, the device is equipped with a camera and microphone to acquire data such as the user's voice, facial expressions, and entered preferences. This data is sent to a server that performs emotion analysis. The server uses general emotion analysis software to quantify the emotional state from this data. Specifically, it is possible to use emotion analysis tools from cloud services such as Microsoft Azure.

[0806] The server analyzes real estate property information retrieved from the database based on emotional data and provides information tailored to each user's emotional state. For example, if the analysis indicates that a user is feeling stressed, the server reduces the number of suggested properties to lessen the visual burden. On the other hand, for properties that the user has shown interest in, detailed information and additional content are displayed preferentially.

[0807] In addition, emotional data is input into AI models and used in price prediction and contract document creation processes. At the contract stage, the system checks the user's relaxed state and adjusts the content and wording of the contract documents to reduce psychological burden.

[0808] As a concrete example of the system, suppose a user is looking for a new place to live. If the stress or anxiety the user feels while reviewing the properties is detected through emotion analysis, the server will simplify the information about the suggested properties and adjust it so that the user can make a selection in a relaxed state. An example of a prompt message generated by the AI ​​model would be, "If the user is feeling anxious, how should the suggested property information be simplified?"

[0809] In this way, by implementing this invention, users can receive personalized real estate brokerage services that respond to their emotions.

[0810] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0811] Step 1:

[0812] The device acquires voice and facial expression data from the user and also accepts text input such as region and budget as desired conditions. This data is sent to the server as input data for sentiment analysis. Specifically, the device captures voice and video in real time using a microphone and camera and prepares a text input form.

[0813] Step 2:

[0814] The server receives voice, facial expression, and text data transmitted from the terminal and inputs it into the emotion analysis engine. The input data is processed by the emotion analysis engine and output as numerical data representing the user's emotional state. Specifically, it analyzes changes in voice tone and facial expression to quantify emotions such as joy, stress, and anxiety.

[0815] Step 3:

[0816] The server analyzes real estate property information based on quantified emotional data. It filters property information retrieved from the database according to each user's emotional state and desired conditions, and creates tailored suggestions. Specifically, when a user is feeling stressed, it extracts only the most important properties from the database and reduces the suggestion list.

[0817] Step 4:

[0818] The server uses a generative AI model to predict the price information to be provided to the user. Using sentiment data and historical transaction data as input, it runs the price prediction model and outputs a price range that the user finds acceptable. Specifically, if the sentiment state is positive, it broadens the user's options by suggesting a wider range of price points.

[0819] Step 5:

[0820] The terminal presents the user with adjusted property information, price predictions, and additional information generated by the server. The information is displayed in a visually intuitive interface, making it easy for the user to understand and make selections. Specifically, it dynamically adjusts colors and font sizes according to the user's emotions.

[0821] Step 6:

[0822] If the user wishes to enter into a contract, the server starts the contract document generation process. Based on sentiment data, it adjusts the elements and wording of the contract to help the user enter into the contract calmly, and then outputs the final contract. Specifically, it simplifies or elaborates on template selections and item descriptions according to the user's sentiment.

[0823] This trend will allow users to receive real estate brokerage services that are tailored to their own needs and preferences.

[0824] (Application Example 2)

[0825] 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".

[0826] Current information provision systems struggle to provide appropriate information that takes into account the user's emotional state, and especially in electronic payments, there is a lack of means to reduce user stress and anxiety. As a result, the user experience is not satisfactory, and there are challenges in maintaining service use and improving customer satisfaction.

[0827] 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.

[0828] In this invention, the server includes means for analyzing user emotional data in addition to acquired storage information and customer information; means for providing information that matches the customer's wishes and emotional state based on the analysis results; and means for visually presenting the information through an interface dynamically adjusted based on the emotional data. This enables the provision of information and optimization of the payment experience in accordance with the user's emotional state.

[0829] "Storage information" is a general term for data related to customers and numerical information collected in transactions.

[0830] "Customer information" refers to specific data about customers, such as personal information and past transaction history.

[0831] "User emotional data" refers to information that quantifies the emotional state of users, collected through voice, text, facial expressions, etc.

[0832] "Means of analysis" refers to devices and software that perform calculations and processing to derive useful information from collected data.

[0833] "Means of provision" refers to mechanisms and methods for appropriately and effectively conveying information to users based on the analysis results.

[0834] A "dynamically responsive interface" is a flexible interface that changes its screen layout and operation methods according to the user's emotions and how they use it.

[0835] "Means of visual presentation" refers to technologies and devices that visually present information to users using images, diagrams, and other visual means.

[0836] This invention is a system that optimizes the electronic payment experience by utilizing user emotional data. The server first receives emotional data acquired from the user's smartphone or smart glasses. This emotional data is analyzed by an emotion engine based on voice, facial expressions, and text data. This analysis uses a machine learning model such as Firebase ML Kit to quantify emotions in real time.

[0837] The server evaluates the user's psychological state based on acquired emotional data and dynamically provides optimal information. For example, if the user is feeling stressed, the UI design and operation methods are simplified. Flutter is used to build a visually superior interface. As a result, users are not overwhelmed with information on the payment screen and can complete transactions smoothly.

[0838] Furthermore, the server optimizes its pricing based on user sentiment, presenting prices that are appropriate for the user. The pricing is calculated using an algorithm that combines historical transaction data with real-time sentiment data.

[0839] As a concrete example, consider a payment scenario in a shopping mall. If the app detects stress due to congestion while the user is selecting items and heading to the checkout, it automatically opens a shortcut menu and presents an option to quickly complete the payment using a registered payment method. This significantly improves the user experience.

[0840] An example of a prompt would be: "The emotion engine is currently detecting how frustrated the user is with the waiting time at the checkout. Based on this data, what customer support measures do you think would be effective?" This prompt can be input into a generating AI model to obtain more specific action suggestions.

[0841] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0842] Step 1:

[0843] The device collects the user's voice, facial expressions, and text data in real time. This raw data is acquired as input and converted into a digital format using speech recognition software and a camera application. The device then transmits this input data to an emotion engine.

[0844] Step 2:

[0845] The server uses an emotion engine to analyze the acquired voice, facial expressions, and text data to quantify the user's emotional state. This process employs machine learning models such as Firebase ML Kit to output a score for a specific emotion based on the input data.

[0846] Step 3:

[0847] The server evaluates the user's psychological state based on quantified emotion data and dynamically adjusts the interface. Specifically, it uses Flutter to modify UI elements and simplifies information if it indicates stress. This results in an optimized user interface.

[0848] Step 4:

[0849] Users conduct transactions through a customized UI. During this process, user selections and inputs are sent back to the server and processed as new input data.

[0850] Step 5:

[0851] The server combines user sentiment data with past transaction information to calculate and present the most suitable price. As a result, optimized price information is output and visually presented to the user.

[0852] Step 6:

[0853] When the server interacts with the user, it generates appropriate responses based on emotional data. Using a generative AI model, it processes prompts and generates suggestions such as, "Based on this data, what customer support measures do you think would be effective?" and outputs them.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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."

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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 to be incorporated by reference.

[0875] The following is further disclosed regarding the embodiments described above.

[0876] (Claim 1)

[0877] A means of acquiring and analyzing storage information and customer information,

[0878] A means of providing information that matches the customer's wishes based on the analysis results,

[0879] A method for calculating a fair price using information obtained from a database,

[0880] A means of visually presenting information using virtual reality technology,

[0881] A method for automatically processing customer inquiries,

[0882] A system that includes this.

[0883] (Claim 2)

[0884] The system according to claim 1, comprising means for predicting a price based on past transaction information.

[0885] (Claim 3)

[0886] The system according to claim 1, comprising means for automatically generating contract information using template information.

[0887] "Example 1"

[0888] (Claim 1)

[0889] A means for receiving input data acquired from a communication terminal and analyzing it,

[0890] A means for extracting and providing information suitable for a specific request based on the analysis results,

[0891] A means for calculating the price using information obtained from the data storage unit,

[0892] A means of visually presenting information using virtual space technology,

[0893] A means of automatically processing queries using natural language processing technology,

[0894] A means of automatically generating document information and inputting necessary information,

[0895] A system that includes this.

[0896] (Claim 2)

[0897] The system according to claim 1, comprising means for predicting the value of an article based on analyzed market information.

[0898] (Claim 3)

[0899] The system according to claim 1, comprising means for automatically creating a contract document from a template and entered information.

[0900] "Application Example 1"

[0901] (Claim 1)

[0902] A means of acquiring and analyzing storage information and customer information,

[0903] A means of providing information that matches the customer's wishes based on the analysis results,

[0904] A method for calculating a fair price using information obtained from a database,

[0905] A means of visually presenting information using virtual reality technology,

[0906] A method for automatically processing customer inquiries,

[0907] A means of proposing personalized information using artificial intelligence,

[0908] Means that enable viewing of information in a virtual space using a mobile information terminal or device,

[0909] A system that includes this.

[0910] (Claim 2)

[0911] The system according to claim 1, comprising means for predicting a price based on past transaction information.

[0912] (Claim 3)

[0913] The system according to claim 1, comprising means for automatically generating contract information using template information and natural language processing technology for providing personalized dialogue.

[0914] "Example 2 of combining an emotion engine"

[0915] (Claim 1)

[0916] A means for acquiring and analyzing storage information and user information,

[0917] A means of providing information that matches the user's wishes based on the analysis results,

[0918] A method for calculating a fair price based on information obtained from a data set,

[0919] A means of visually presenting information using virtual environment technology,

[0920] Means for recognizing and acquiring the emotional state of users,

[0921] A means of adjusting the content of information provided using the results of sentiment analysis,

[0922] In the process of generating contract documents, means of considering emotional data,

[0923] A means of automatically processing inquiries from users,

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, comprising means for predicting a price based on past transaction information and user sentiment data.

[0927] (Claim 3)

[0928] The system according to claim 1, comprising means for automatically generating contract information using template information and sentiment data.

[0929] "Application example 2 when combining with an emotional engine"

[0930] (Claim 1)

[0931] In addition to the acquired storage information and customer information, a means to analyze user sentiment data,

[0932] A means of providing information that matches the customer's wishes and emotional state based on the analysis results,

[0933] A means of visually presenting information through an interface dynamically adjusted based on emotional data,

[0934] A method for presenting the optimal price using user sentiment data,

[0935] A means of automatically generating appropriate responses to inquiries based on emotions,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, comprising means for predicting a price based on past transaction information and user sentiment data.

[0939] (Claim 3)

[0940] The system according to claim 1, comprising means for automatically generating contract information using template information optimized for the user's emotional state. [Explanation of Symbols]

[0941] 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 of acquiring and analyzing storage information and customer information, A means of providing information that matches the customer's wishes based on the analysis results, A method for calculating a fair price using information obtained from a database, A means of visually presenting information using virtual reality technology, A method for automatically processing customer inquiries, A means of proposing personalized information using artificial intelligence, Means that enable viewing of information in a virtual space using a mobile information terminal or device, A system that includes this.

2. The system according to claim 1, comprising means for predicting a price based on past transaction information.

3. The system according to claim 1, comprising means for automatically generating contract information using template information and natural language processing technology for providing personalized dialogue.

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