System

Abstract

An object of a system according to an embodiment is to reduce brokerage fees in real estate transactions and enable individuals to perform property transactions at low cost.SOLUTION: A system includes a property information collection part, a contract preparation part, a price negotiation part, and a transaction progress management part. The property information collection unit collects property information. The contract creation unit creates a contract on the basis of the property information collected by the property information collection unit. The price negotiation unit performs price negotiation on the basis of the contract created by the contract creation unit. The transaction progress management unit manages the progress of the transaction based on the price negotiated by the price negotiation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem that brokerage fees for real estate transactions are high, making it difficult for individuals to conduct property transactions at low cost.

[0005] The system according to the embodiment aims to reduce brokerage fees in real estate transactions and enable individuals to conduct property transactions at low cost. [Means for solving the problem]

[0006] The system according to the embodiment includes a property information collection unit, a contract creation unit, a price negotiation unit, and a transaction progress management unit. The property information collection unit collects property information. The contract creation unit creates a contract based on the property information collected by the property information collection unit. The price negotiation unit negotiates the price based on the contract created by the contract creation unit. The transaction progress management unit manages the progress of the transaction based on the price negotiated by the price negotiation unit. [Effects of the Invention]

[0007] The system according to the embodiment reduces brokerage fees in real estate transactions, allowing individuals to conduct property transactions at low cost. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The real estate brokerage system according to an embodiment of the present invention automates brokerage work in real estate sales and purchases using generative AI, significantly reducing brokerage fees. As a result, the real estate brokerage system enables individuals involved in the sale and purchase of real estate to conduct property transactions at prices significantly lower than the market price.

[0029] A real estate brokerage system according to an embodiment includes a property information collection unit, a contract creation unit, a price negotiation unit, and a transaction progress management unit. The property information collection unit collects property information. For example, it collects information such as the location, price, area, and age of the property. The property information collection unit can also organize the property information provided by a user and provide it to a buyer. For example, the property information collection unit organizes the property information based on prompts from the user and provides it to the buyer. The contract creation unit creates a contract based on the property information collected by the property information collection unit. For example, the contract creation unit automatically creates documents such as a sales contract and an important information explanation document. The contract creation unit can also create a contract based on prompts from the user and manage it as the transaction progresses. The price negotiation unit negotiates the price based on the contract created by the contract creation unit. For example, the price negotiation unit supports price negotiations between a seller and a buyer. The price negotiation unit can also negotiate the price based on prompts from the user to arrive at a price that satisfies both parties. The transaction progress management unit manages the progress of the transaction based on the price negotiated by the price negotiation unit. For example, the transaction progress management unit manages the progress of the transaction, such as the signing of a contract, confirmation of payment, and delivery of the property. The transaction progress management unit can also manage the progress of the transaction based on prompts from the user and provide notifications at appropriate times. As a result, the real estate brokerage system according to the embodiment can automate brokerage work in real estate sales and purchases and significantly reduce brokerage fees. For example, sellers and buyers can conduct property transactions at fees significantly lower than the market price, and by utilizing generation AI, brokerage fees can be earned while reducing labor costs.

[0030] The property information collection unit can organize property information based on prompts from the user and provide it to buyers. For example, the property information collection unit uses a generation AI to analyze past transaction data and implement an algorithm that dynamically sets the optimal brokerage commission rate. The generation AI collects past real estate transaction data and analyzes commission rates by transaction size and region. This develops an algorithm that dynamically sets the optimal brokerage commission rate under specific conditions. The generation AI analyzes market trends and economic indicators in real time and builds a system that dynamically adjusts commission rates. For example, it automatically updates commission rates in response to changes in economic conditions. The generation AI implements an algorithm that proposes individual commission rates based on the user's transaction history and credit information. For example, it sets a lower commission rate for users with a large transaction record. This allows property information to be organized based on the user's instructions and provided to buyers, enabling efficient property proposals.

[0031] The contract creation unit can create contracts based on prompts from the user and manage them as the transaction progresses. For example, the generation AI in the contract creation unit evaluates the credit information of both the seller and buyer in real time and makes suggestions to minimize transaction risks. The generation AI collects credit information of the seller and buyer in real time and builds a system to evaluate transaction risks. For example, it performs risk assessment based on credit scores and past transaction history. The generation AI automatically generates suggestions to minimize transaction risks. For example, if the credit risk is high, it may suggest additional guarantees or insurance. The generation AI monitors credit information in real time as the transaction progresses and develops a system that immediately notifies if a risk occurs. For example, it detects changes in the credit score and issues an alert. This enables efficient contract management by creating contracts based on user instructions and managing them as the transaction progresses.

[0032] The price negotiation unit can negotiate the price based on prompts from the user and arrive at a price that is satisfactory to both parties. The price negotiation unit, for example, uses an emotion estimation function to analyze the user's emotional state and make notifications and suggestions at the optimal timing depending on the progress of the transaction. The emotion estimation function builds a system that analyzes the user's emotional state in real time and makes notifications at the optimal timing depending on the progress of the transaction. For example, if the user is feeling stressed, it makes suggestions to help them relax. Based on the user's emotional data, it makes suggestions at the optimal timing depending on the progress of the transaction. For example, it sends notifications to encourage important decisions when the user is feeling positive. The emotion estimation function analyzes the user's emotional state and develops a system that provides counseling and support at the optimal timing depending on the progress of the transaction. For example, if the user is feeling anxious, it sends a message that gives a sense of security. This enables efficient price negotiations by negotiating the price based on the user's instructions and arriving at a price that is satisfactory to both parties.

[0033] The transaction progress management unit can manage the progress of the transaction based on prompts from the user and provide notifications at the appropriate time. For example, the transaction progress management unit can apply real estate brokerage AI to rental property brokerage and automate the rental contract procedures. Real estate brokerage AI can be applied to rental property brokerage to build a system that automates the rental contract procedures. For example, it can automate the collection of rental property information, contract creation, and tenant credit evaluation. The generation AI can develop a system that manages the progress of rental contracts in real time and automatically proceeds with the necessary procedures in rental property brokerage. For example, it can automate the signing of contracts and payment confirmation. The generation AI can build a system that evaluates tenant credit information in real time and makes suggestions to minimize risk. For example, if the credit risk is high, it can suggest additional guarantees or insurance. This allows the transaction progress to be managed based on user instructions and notifications to be provided at the appropriate time, enabling efficient transaction management.

[0034] The property information collection unit can collect future forecast data on the property's surrounding environment or the area and provide comprehensive information to buyers. In the property information collection unit, for example, a generation AI collects data on the property's surrounding environment and builds a system that provides comprehensive information to buyers. The generation AI collects data on the property's surrounding environment and builds a system that provides comprehensive information to buyers. For example, it collects information on transportation access, schools, hospitals, commercial facilities, etc. The generation AI collects future forecast data on the area and develops a system that provides comprehensive information to buyers. For example, it collects forecast data on local development plans and demographics. The generation AI builds a system that provides comprehensive information to buyers based on future forecast data on the property's surrounding environment and the area. For example, it provides data that indicates the possibility of a property's value increasing in the future. This allows the collection of future forecast data on the property's surrounding environment and the area and provides comprehensive information to buyers, enabling them to select a more appropriate property.

[0035] The property information collection unit collects data on the energy efficiency or environmental impact of properties and can propose eco-friendly properties. In the property information collection unit, for example, a generation AI collects energy efficiency data on properties and builds a system that proposes eco-friendly properties. The generation AI collects energy efficiency data on properties and builds a system that proposes eco-friendly properties. For example, it evaluates the energy consumption and insulation performance of properties. The generation AI collects environmental impact data on properties and develops a system that proposes eco-friendly properties. For example, it evaluates the CO2 emissions and renewable energy usage of properties. The generation AI builds a system that proposes eco-friendly properties based on data on the energy efficiency and environmental impact of properties. For example, it prioritizes the proposal of properties with high energy efficiency and low environmental impact. In this way, by collecting data on the energy efficiency and environmental impact of properties and proposing eco-friendly properties, it becomes possible to select environmentally conscious properties.

[0036] The property information collection unit can automatically generate a 3D model or virtual tour of a property to provide visual information to buyers. The property information collection unit, for example, builds a system in which a generation AI automatically generates a 3D model of a property to provide visual information to buyers. The generation AI automatically generates a 3D model of a property to build a system that provides visual information to buyers. For example, the internal structure and layout of a property are displayed in a 3D model. The generation AI develops a system that automatically generates a virtual tour of a property to provide visual information to buyers. For example, it allows buyers to tour the interior of a property in a virtual tour. The generation AI builds a system that provides visual information to buyers based on the 3D model or virtual tour of the property. For example, detailed information about the property is displayed in a 3D model or virtual tour. This allows the automatic generation of a 3D model or virtual tour of a property to provide visual information to buyers, thereby providing more detailed property information.

[0037] The contract creation unit can automatically generate contracts that comply with the laws and regulations of each country and support international real estate transactions. For example, the contract creation unit uses generation AI to build a system in which it collects the laws and regulations of each country and automatically generates contracts based on them. The generation AI builds a system in which it collects the laws and regulations of each country and automatically generates contracts based on them. For example, it generates contracts that meet the legal requirements of each country. The generation AI develops a system that automatically generates contracts in multiple languages ​​to support international real estate transactions. For example, it generates contracts that support multiple languages ​​such as English and Chinese. The generation AI builds a system that automatically generates contracts that comply with the laws and regulations of each country and supports international real estate transactions. For example, it automatically generates documents required for international transactions. This allows it to automatically generate contracts that comply with the laws and regulations of each country and support international real estate transactions, thereby minimizing legal risks.

[0038] The contract creation unit can automatically audit the contents of a contract and propose modifications to minimize legal risks. The contract creation unit, for example, builds a system in which a generation AI automatically audits the contents of a contract and proposes modifications to minimize legal risks. The generation AI builds a system in which it automatically audits the contents of a contract and proposes modifications to minimize legal risks. For example, it checks the clauses of a contract and modifies any parts that pose risks. The generation AI develops a system that analyzes the contents of a contract and automatically generates modification proposals to minimize legal risks. For example, it presents modification proposals to meet legal requirements. The generation AI builds a system in which it automatically audits the contents of a contract and proposes modifications to minimize legal risks. For example, it modifies the clauses of a contract to make them legally correct. This makes it possible to reduce legal risks by automatically auditing the contents of a contract and proposing modifications to minimize legal risks.

[0039] The transaction progress management unit monitors the progress of the transaction in real time and can respond immediately if a problem occurs. For example, the transaction progress management unit builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it automatically concludes contracts and confirms payments. The generation AI analyzes the progress of the transaction and develops a system that responds immediately if a problem occurs. For example, it automatically carries out the necessary procedures as the transaction progresses. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it displays the progress of the transaction on a dashboard and detects and notifies of any abnormalities. This allows the transaction to proceed smoothly by monitoring the progress of the transaction in real time and responding immediately if a problem occurs.

[0040] The transaction progress management unit can evaluate risks at each step of a transaction and make proposals to minimize the risks. The transaction progress management unit, for example, builds a system in which a generation AI evaluates risks at each step of a transaction and makes proposals to minimize the risks. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. The generation AI develops a system that analyzes transaction risks and makes proposals to minimize the risks. For example, it monitors the progress of a transaction and responds immediately if a risk occurs. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. In this way, by evaluating risks at each step of a transaction and making proposals to minimize the risks, the safety of transactions is improved.

[0041] The transaction progress management unit can visualize the transaction progress and provide a dashboard that the user can intuitively understand. For example, the transaction progress management unit constructs a system in which a generation AI visualizes the transaction progress and provides a dashboard that the user can intuitively understand. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, each step of the transaction is displayed graphically. The generation AI analyzes the transaction progress and develops a system that provides a dashboard that the user can intuitively understand. For example, the transaction progress is updated in real time. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, the transaction progress is displayed in graphs and charts. This visualizes the transaction progress and provides a dashboard that the user can intuitively understand, making it easier to grasp the transaction progress.

[0042] The transaction progress management unit can automatically generate necessary documents and procedures as the transaction progresses and provide them to the user. The transaction progress management unit, for example, builds a system in which a generation AI automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. The generation AI builds a system in which it automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it automatically generates contracts and payment confirmations. The generation AI develops a system that analyzes the progress of the transaction and automatically generates necessary documents and procedures and provides them to the user. For example, it automatically generates documents as the transaction progresses. The generation AI builds a system that automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it monitors the progress of the transaction and automatically generates necessary documents. This makes it possible to streamline transaction procedures by automatically generating necessary documents and procedures as the transaction progresses and providing them to the user.

[0043] The price negotiation department can introduce an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy. For example, the price negotiation department introduces an algorithm in which a generation AI analyzes past negotiation data and proposes the optimal negotiation strategy. The generation AI collects past price negotiation data and develops an algorithm that proposes the optimal negotiation strategy. For example, it analyzes successful negotiation patterns and reflects them in proposals. The generation AI analyzes market trends and economic indicators in real time and builds a system that proposes the optimal negotiation strategy. For example, it automatically updates the negotiation strategy in response to changes in the economic situation. The generation AI introduces an algorithm that proposes an individual negotiation strategy based on the user's negotiation history and credit information. For example, it proposes a specific strategy to users with a strong track record in negotiations. In this way, by introducing an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy, the success rate of negotiations is improved.

[0044] The price negotiation unit can analyze the price bid history of sellers and buyers in real time and make the optimal price proposal according to the progress of negotiations. In the price negotiation unit, for example, the generation AI collects the price bid history of sellers and buyers in real time and makes the optimal price proposal according to the progress of negotiations. The generation AI collects the price bid history of sellers and buyers in real time and builds a system that makes the optimal price proposal according to the progress of negotiations. For example, it proposes the optimal price based on past price bid data. The generation AI develops a system that analyzes the progress of negotiations in real time and makes the optimal price proposal. For example, it dynamically adjusts the price according to the progress of negotiations. The generation AI builds a system that makes the optimal price proposal according to the progress of negotiations based on the price bid history of sellers and buyers. For example, it analyzes the price negotiation history and proposes the optimal price. This improves the efficiency of negotiations by analyzing the price bid history of sellers and buyers in real time and making the optimal price proposal according to the progress of negotiations.

[0045] The property information collection unit collects past repair history or maintenance information of a property, and can provide highly transparent information to buyers. For example, the property information collection unit uses a generation AI to collect past repair history of a property and build a system that provides highly transparent information to buyers. The generation AI collects past repair history of a property and builds a system that provides highly transparent information to buyers. For example, it provides details of repairs and renovations that have been carried out in the past. The generation AI collects maintenance information of a property and develops a system that provides highly transparent information to buyers. For example, it provides a history of regular maintenance and future maintenance schedules. The generation AI builds a system that provides highly transparent information to buyers based on the property's past repair history and maintenance information. For example, it provides information that allows for a detailed understanding of the property's condition. This allows the collection of past repair history and maintenance information of a property and provides highly transparent information to buyers, enabling them to select a reliable property.

[0046] The contract creation department can improve the reliability and security of contracts by using electronic signatures and blockchain technology. For example, the contract creation department builds a system in which a generation AI uses electronic signature technology to improve the reliability of contracts. The generation AI builds a system that improves the reliability of contracts by using electronic signature technology. For example, it adds an electronic signature to a contract to prevent tampering. The generation AI develops a system that improves the security of contracts by using blockchain technology. For example, it records the contract history on a blockchain to ensure transparency. The generation AI builds a system that improves the reliability and security of contracts by using electronic signatures and blockchain technology. For example, it realizes contract tampering detection and history management. In this way, by improving the reliability and security of contracts by using electronic signatures and blockchain technology, it is possible to prevent tampering and ensure transparency of contracts.

[0047] The contract creation unit can monitor the contract fulfillment status in real time and immediately notify if a problem occurs. For example, the contract creation unit builds a system in which the generation AI monitors the contract fulfillment status in real time and immediately notifies if a problem occurs. The generation AI builds a system that monitors the contract fulfillment status in real time and immediately notifies if a problem occurs. For example, it detects and notifies payment delays and contract violations. The generation AI develops a system that analyzes the contract fulfillment status and immediately notifies if a problem occurs. For example, it monitors the progress of the contract, detects abnormalities, and issues an alert. The generation AI builds a system that monitors the contract fulfillment status in real time and immediately notifies if a problem occurs. For example, it displays the contract fulfillment status on a dashboard and detects and notifies if an abnormality occurs. This ensures contract fulfillment by monitoring the contract fulfillment status in real time and immediately notifying if a problem occurs.

[0048] The price negotiation unit collects price data from different markets and regions and can support price negotiations from a global perspective. For example, the generation AI collects price data from different markets and regions and supports price negotiations from a global perspective. The generation AI collects price data from different markets and regions and builds a system that supports price negotiations from a global perspective. For example, it proposes the optimal price based on the market price in each region. The generation AI analyzes global price data and develops a system that supports price negotiations in different markets and regions. For example, it supports price negotiations in international transactions. The generation AI builds a system that supports price negotiations from a global perspective based on price data from different markets and regions. For example, it proposes prices that take into account the economic conditions of each region. This enables more appropriate price negotiations by collecting price data from different markets and regions and supporting price negotiations from a global perspective.

[0049] The price negotiation unit can simulate the results of price negotiations and predict the optimal negotiation result. In the price negotiation unit, for example, a generation AI simulates the results of price negotiations and predicts the optimal negotiation result. The generation AI builds a system that simulates the results of price negotiations and predicts the optimal negotiation result. For example, it runs a simulation based on past negotiation data and predicts the optimal result. The generation AI simulates price negotiations and develops a system that predicts the optimal negotiation result. For example, it tries different negotiation strategies and predicts the result with the highest success rate. The generation AI builds a system that simulates the results of price negotiations and predicts the optimal negotiation result. For example, it adjusts the progress of negotiations based on the simulation results. In this way, the success rate of negotiations is improved by simulating the results of price negotiations and predicting the optimal negotiation result.

[0050] The transaction progress management unit monitors the progress of the transaction in real time and can respond immediately if a problem occurs. For example, the transaction progress management unit builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it automatically concludes contracts and confirms payments. The generation AI analyzes the progress of the transaction and develops a system that responds immediately if a problem occurs. For example, it automatically carries out the necessary procedures as the transaction progresses. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it displays the progress of the transaction on a dashboard and detects and notifies of any abnormalities. This allows the transaction to proceed smoothly by monitoring the progress of the transaction in real time and responding immediately if a problem occurs.

[0051] The transaction progress management unit can evaluate risks at each step of a transaction and make proposals to minimize the risks. The transaction progress management unit, for example, builds a system in which a generation AI evaluates risks at each step of a transaction and makes proposals to minimize the risks. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. The generation AI develops a system that analyzes transaction risks and makes proposals to minimize the risks. For example, it monitors the progress of a transaction and responds immediately if a risk occurs. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. In this way, by evaluating risks at each step of a transaction and making proposals to minimize the risks, the safety of transactions is improved.

[0052] The transaction progress management unit can visualize the transaction progress and provide a dashboard that the user can intuitively understand. For example, the transaction progress management unit constructs a system in which a generation AI visualizes the transaction progress and provides a dashboard that the user can intuitively understand. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, each step of the transaction is displayed graphically. The generation AI analyzes the transaction progress and develops a system that provides a dashboard that the user can intuitively understand. For example, the transaction progress is updated in real time. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, the transaction progress is displayed in graphs and charts. This visualizes the transaction progress and provides a dashboard that the user can intuitively understand, making it easier to grasp the transaction progress.

[0053] The transaction progress management unit can automatically generate necessary documents and procedures as the transaction progresses and provide them to the user. The transaction progress management unit, for example, builds a system in which a generation AI automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. The generation AI builds a system in which it automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it automatically generates contracts and payment confirmations. The generation AI develops a system that analyzes the progress of the transaction and automatically generates necessary documents and procedures and provides them to the user. For example, it automatically generates documents as the transaction progresses. The generation AI builds a system that automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it monitors the progress of the transaction and automatically generates necessary documents. This makes it possible to streamline transaction procedures by automatically generating necessary documents and procedures as the transaction progresses and providing them to the user.

[0054] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0055] The property information collection unit can collect data on the surrounding environment of a property and provide comprehensive information to buyers. For example, it collects information on schools, hospitals, commercial facilities, transportation access, etc. in the vicinity of the property and provides it to buyers. The property information collection unit can also collect future forecast data for the area and provide buyers with information predicting future value fluctuations. For example, it collects forecast data on local development plans and demographics and provides it to buyers. This allows buyers to make more appropriate property selections by providing comprehensive information on the surrounding environment of the property and future value fluctuations.

[0056] The contract creation unit can automatically generate contracts that comply with the laws and regulations of each country, supporting international real estate transactions. For example, a system can be built in which the generation AI collects the laws and regulations of each country and automatically generates contracts based on them. The generation AI generates contracts that meet the legal requirements of each country and can also create contracts in multiple languages. For example, it can generate contracts in multiple languages ​​such as English and Chinese. This minimizes legal risks and ensures smooth transactions, even in international real estate transactions.

[0057] The transaction progress management department monitors the progress of transactions in real time and can respond immediately if any problems arise. For example, we will build a system in which the generation AI monitors the progress of transactions in real time and automatically concludes contracts and confirms payments. The generation AI will develop a system that analyzes the progress of transactions and responds immediately if any problems arise. For example, it will automatically carry out the necessary procedures as the transaction progresses. This will enable the smooth progress of transactions by monitoring the progress of transactions in real time and responding immediately if any problems arise.

[0058] The property information collection unit can collect data on the energy efficiency or environmental impact of properties and suggest eco-friendly properties. For example, a system can be built in which the generation AI collects energy efficiency data on properties and suggests eco-friendly properties. The generation AI evaluates the energy consumption and insulation performance of properties and suggests eco-friendly properties. It can also collect environmental impact data on properties and evaluate CO2 emissions and renewable energy usage. This makes it possible to select environmentally friendly properties by collecting data on the energy efficiency and environmental impact of properties and suggesting eco-friendly properties.

[0059] The transaction progress management department can evaluate the risks at each step of the transaction and make proposals to minimize the risks. For example, we will build a system in which the generation AI evaluates the risks at each step of the transaction, evaluates the risks as the transaction progresses, and proposes necessary measures. The generation AI will develop a system that analyzes the risks of the transaction and makes proposals to minimize the risks. For example, it will monitor the progress of the transaction and respond immediately if a risk occurs. This will enable us to evaluate the risks at each step of the transaction and make proposals to minimize the risks, thereby improving the safety of the transaction.

[0060] The price negotiation department can introduce an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy. For example, a generation AI collects past negotiation data, analyzes successful negotiation patterns, and develops an algorithm that proposes the optimal negotiation strategy. The generation AI analyzes market trends and economic indicators in real time and builds a system that proposes the optimal negotiation strategy. For example, it automatically updates the negotiation strategy in response to changes in the economic situation. This makes it possible to improve the success rate of negotiations by introducing an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy.

[0061] The property information collection unit can automatically generate 3D models or virtual tours of properties to provide buyers with visual information. For example, a system will be built in which the generation AI automatically generates 3D models of properties and displays the internal structure and layout of the properties in 3D. The generation AI will develop a system that automatically generates virtual tours of properties, allowing buyers to view the interior of the properties on a virtual tour. This will enable more detailed property information to be provided by automatically generating 3D models and virtual tours of properties and providing visual information to buyers.

[0062] The processing flow of the first embodiment will be briefly explained below.

[0063] Step 1: The property information collection unit collects property information. For example, it collects information such as the location, price, area, and age of the property. The property information collection unit can also organize the property information provided by the user and provide it to the buyer. For example, the property information collection unit organizes the property information based on prompts from the user and provides it to the buyer. Step 2: The contract creation unit creates a contract based on the property information collected by the property information collection unit. For example, the contract creation unit automatically creates documents such as a sales contract and an explanation of important matters. The contract creation unit can also create a contract based on prompts from the user and manage it as the transaction progresses. Step 3: The price negotiation unit negotiates the price based on the contract created by the contract creation unit. For example, the price negotiation unit supports price negotiations between the seller and the buyer. The price negotiation unit can also negotiate the price based on prompts from the user to arrive at a price that satisfies both parties. Step 4: The transaction progress management unit manages the progress of the transaction based on the price negotiated by the price negotiation unit. For example, the transaction progress management unit manages the progress of the transaction, such as the signing of a contract, confirmation of payment, and delivery of the property. The transaction progress management unit can also manage the progress of the transaction based on prompts from the user and notify them at the appropriate time.

[0064] (Example 2) The real estate brokerage system according to an embodiment of the present invention automates brokerage work in real estate sales and purchases using generative AI, significantly reducing brokerage fees. As a result, the real estate brokerage system enables individuals involved in the sale and purchase of real estate to conduct property transactions at prices significantly lower than the market price.

[0065] A real estate brokerage system according to an embodiment includes a property information collection unit, a contract creation unit, a price negotiation unit, and a transaction progress management unit. The property information collection unit collects property information. For example, it collects information such as the location, price, area, and age of the property. The property information collection unit can also organize the property information provided by a user and provide it to a buyer. For example, the property information collection unit organizes the property information based on prompts from the user and provides it to the buyer. The contract creation unit creates a contract based on the property information collected by the property information collection unit. For example, the contract creation unit automatically creates documents such as a sales contract and an important information explanation document. The contract creation unit can also create a contract based on prompts from the user and manage it as the transaction progresses. The price negotiation unit negotiates the price based on the contract created by the contract creation unit. For example, the price negotiation unit supports price negotiations between a seller and a buyer. The price negotiation unit can also negotiate the price based on prompts from the user to arrive at a price that satisfies both parties. The transaction progress management unit manages the progress of the transaction based on the price negotiated by the price negotiation unit. For example, the transaction progress management unit manages the progress of the transaction, such as the signing of a contract, confirmation of payment, and delivery of the property. The transaction progress management unit can also manage the progress of the transaction based on prompts from the user and provide notifications at appropriate times. As a result, the real estate brokerage system according to the embodiment can automate brokerage work in real estate sales and purchases and significantly reduce brokerage fees. For example, sellers and buyers can conduct property transactions at fees significantly lower than the market price, and by utilizing generation AI, brokerage fees can be earned while reducing labor costs.

[0066] The property information collection unit can organize property information based on prompts from the user and provide it to buyers. For example, the property information collection unit uses a generation AI to analyze past transaction data and implement an algorithm that dynamically sets the optimal brokerage commission rate. The generation AI collects past real estate transaction data and analyzes commission rates by transaction size and region. This develops an algorithm that dynamically sets the optimal brokerage commission rate under specific conditions. The generation AI analyzes market trends and economic indicators in real time and builds a system that dynamically adjusts commission rates. For example, it automatically updates commission rates in response to changes in economic conditions. The generation AI implements an algorithm that proposes individual commission rates based on the user's transaction history and credit information. For example, it sets a lower commission rate for users with a large transaction record. This allows property information to be organized based on the user's instructions and provided to buyers, enabling efficient property proposals.

[0067] The contract creation unit can create contracts based on prompts from the user and manage them as the transaction progresses. For example, the generation AI in the contract creation unit evaluates the credit information of both the seller and buyer in real time and makes suggestions to minimize transaction risks. The generation AI collects credit information of the seller and buyer in real time and builds a system to evaluate transaction risks. For example, it performs risk assessment based on credit scores and past transaction history. The generation AI automatically generates suggestions to minimize transaction risks. For example, if the credit risk is high, it may suggest additional guarantees or insurance. The generation AI monitors credit information in real time as the transaction progresses and develops a system that immediately notifies if a risk occurs. For example, it detects changes in the credit score and issues an alert. This enables efficient contract management by creating contracts based on user instructions and managing them as the transaction progresses.

[0068] The price negotiation unit can negotiate the price based on prompts from the user and arrive at a price that is satisfactory to both parties. The price negotiation unit, for example, uses an emotion estimation function to analyze the user's emotional state and make notifications and suggestions at the optimal timing depending on the progress of the transaction. The emotion estimation function builds a system that analyzes the user's emotional state in real time and makes notifications at the optimal timing depending on the progress of the transaction. For example, if the user is feeling stressed, it makes suggestions to help them relax. Based on the user's emotional data, it makes suggestions at the optimal timing depending on the progress of the transaction. For example, it sends notifications to encourage important decisions when the user is feeling positive. The emotion estimation function analyzes the user's emotional state and develops a system that provides counseling and support at the optimal timing depending on the progress of the transaction. For example, if the user is feeling anxious, it sends a message that gives a sense of security. This enables efficient price negotiations by negotiating the price based on the user's instructions and arriving at a price that is satisfactory to both parties.

[0069] The transaction progress management unit can manage the progress of the transaction based on prompts from the user and provide notifications at the appropriate time. For example, the transaction progress management unit can apply real estate brokerage AI to rental property brokerage and automate the rental contract procedures. Real estate brokerage AI can be applied to rental property brokerage to build a system that automates the rental contract procedures. For example, it can automate the collection of rental property information, contract creation, and tenant credit evaluation. The generation AI can develop a system that manages the progress of rental contracts in real time and automatically proceeds with the necessary procedures in rental property brokerage. For example, it can automate the signing of contracts and payment confirmation. The generation AI can build a system that evaluates tenant credit information in real time and makes suggestions to minimize risk. For example, if the credit risk is high, it can suggest additional guarantees or insurance. This allows the transaction progress to be managed based on user instructions and notifications to be provided at the appropriate time, enabling efficient transaction management.

[0070] The property information collection unit can collect future forecast data on the property's surrounding environment or the area and provide comprehensive information to buyers. In the property information collection unit, for example, a generation AI collects data on the property's surrounding environment and builds a system that provides comprehensive information to buyers. The generation AI collects data on the property's surrounding environment and builds a system that provides comprehensive information to buyers. For example, it collects information on transportation access, schools, hospitals, commercial facilities, etc. The generation AI collects future forecast data on the area and develops a system that provides comprehensive information to buyers. For example, it collects forecast data on local development plans and demographics. The generation AI builds a system that provides comprehensive information to buyers based on future forecast data on the property's surrounding environment and the area. For example, it provides data that indicates the possibility of a property's value increasing in the future. This allows the collection of future forecast data on the property's surrounding environment and the area and provides comprehensive information to buyers, enabling them to select a more appropriate property.

[0071] The property information collection unit collects data on the energy efficiency or environmental impact of properties and can propose eco-friendly properties. In the property information collection unit, for example, a generation AI collects energy efficiency data on properties and builds a system that proposes eco-friendly properties. The generation AI collects energy efficiency data on properties and builds a system that proposes eco-friendly properties. For example, it evaluates the energy consumption and insulation performance of properties. The generation AI collects environmental impact data on properties and develops a system that proposes eco-friendly properties. For example, it evaluates the CO2 emissions and renewable energy usage of properties. The generation AI builds a system that proposes eco-friendly properties based on data on the energy efficiency and environmental impact of properties. For example, it prioritizes the proposal of properties with high energy efficiency and low environmental impact. In this way, by collecting data on the energy efficiency and environmental impact of properties and proposing eco-friendly properties, it becomes possible to select environmentally conscious properties.

[0072] The property information collection unit can automatically generate a 3D model or virtual tour of a property to provide visual information to buyers. The property information collection unit, for example, builds a system in which a generation AI automatically generates a 3D model of a property to provide visual information to buyers. The generation AI automatically generates a 3D model of a property to build a system that provides visual information to buyers. For example, the internal structure and layout of a property are displayed in a 3D model. The generation AI develops a system that automatically generates a virtual tour of a property to provide visual information to buyers. For example, it allows buyers to tour the interior of a property in a virtual tour. The generation AI builds a system that provides visual information to buyers based on the 3D model or virtual tour of the property. For example, detailed information about the property is displayed in a 3D model or virtual tour. This allows the automatic generation of a 3D model or virtual tour of a property to provide visual information to buyers, thereby providing more detailed property information.

[0073] The contract creation unit can automatically generate contracts that comply with the laws and regulations of each country and support international real estate transactions. For example, the contract creation unit uses generation AI to build a system in which it collects the laws and regulations of each country and automatically generates contracts based on them. The generation AI builds a system in which it collects the laws and regulations of each country and automatically generates contracts based on them. For example, it generates contracts that meet the legal requirements of each country. The generation AI develops a system that automatically generates contracts in multiple languages ​​to support international real estate transactions. For example, it generates contracts that support multiple languages ​​such as English and Chinese. The generation AI builds a system that automatically generates contracts that comply with the laws and regulations of each country and supports international real estate transactions. For example, it automatically generates documents required for international transactions. This allows it to automatically generate contracts that comply with the laws and regulations of each country and support international real estate transactions, thereby minimizing legal risks.

[0074] The contract creation unit can automatically audit the contents of a contract and propose modifications to minimize legal risks. The contract creation unit, for example, builds a system in which a generation AI automatically audits the contents of a contract and proposes modifications to minimize legal risks. The generation AI builds a system in which it automatically audits the contents of a contract and proposes modifications to minimize legal risks. For example, it checks the clauses of a contract and modifies any parts that pose risks. The generation AI develops a system that analyzes the contents of a contract and automatically generates modification proposals to minimize legal risks. For example, it presents modification proposals to meet legal requirements. The generation AI builds a system in which it automatically audits the contents of a contract and proposes modifications to minimize legal risks. For example, it modifies the clauses of a contract to make them legally correct. This makes it possible to reduce legal risks by automatically auditing the contents of a contract and proposing modifications to minimize legal risks.

[0075] The transaction progress management unit monitors the progress of the transaction in real time and can respond immediately if a problem occurs. For example, the transaction progress management unit builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it automatically concludes contracts and confirms payments. The generation AI analyzes the progress of the transaction and develops a system that responds immediately if a problem occurs. For example, it automatically carries out the necessary procedures as the transaction progresses. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it displays the progress of the transaction on a dashboard and detects and notifies of any abnormalities. This allows the transaction to proceed smoothly by monitoring the progress of the transaction in real time and responding immediately if a problem occurs.

[0076] The transaction progress management unit can evaluate risks at each step of a transaction and make proposals to minimize the risks. The transaction progress management unit, for example, builds a system in which a generation AI evaluates risks at each step of a transaction and makes proposals to minimize the risks. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. The generation AI develops a system that analyzes transaction risks and makes proposals to minimize the risks. For example, it monitors the progress of a transaction and responds immediately if a risk occurs. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. In this way, by evaluating risks at each step of a transaction and making proposals to minimize the risks, the safety of transactions is improved.

[0077] The transaction progress management unit can visualize the transaction progress and provide a dashboard that the user can intuitively understand. For example, the transaction progress management unit constructs a system in which a generation AI visualizes the transaction progress and provides a dashboard that the user can intuitively understand. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, each step of the transaction is displayed graphically. The generation AI analyzes the transaction progress and develops a system that provides a dashboard that the user can intuitively understand. For example, the transaction progress is updated in real time. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, the transaction progress is displayed in graphs and charts. This visualizes the transaction progress and provides a dashboard that the user can intuitively understand, making it easier to grasp the transaction progress.

[0078] The transaction progress management unit can automatically generate necessary documents and procedures as the transaction progresses and provide them to the user. The transaction progress management unit, for example, builds a system in which a generation AI automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. The generation AI builds a system in which it automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it automatically generates contracts and payment confirmations. The generation AI develops a system that analyzes the progress of the transaction and automatically generates necessary documents and procedures and provides them to the user. For example, it automatically generates documents as the transaction progresses. The generation AI builds a system that automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it monitors the progress of the transaction and automatically generates necessary documents. This makes it possible to streamline transaction procedures by automatically generating necessary documents and procedures as the transaction progresses and providing them to the user.

[0079] The transaction progress management unit can use the emotion estimation function to analyze the user's emotional state as the transaction progresses and make suggestions to reduce stress. The transaction progress management unit, for example, uses the emotion estimation function to monitor the user's emotional response to the transaction progress in real time and make suggestions to elicit positive emotions. The emotion estimation function builds a system that monitors the user's emotional response to the transaction progress in real time and makes suggestions to elicit positive emotions. For example, it provides an environment in which the user can relax. A system is developed that monitors the user's emotional response to the transaction progress based on the user's emotion data and makes suggestions to elicit positive emotions. For example, it makes suggestions that make the user feel at ease. The emotion estimation function builds a system that monitors the user's emotional response to the transaction progress in real time and makes suggestions to elicit positive emotions. For example, it progresses the transaction so that the user does not feel stressed. This improves the user's trading experience by analyzing the user's emotional state as the transaction progresses and making suggestions to reduce stress.

[0080] The price negotiation department can introduce an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy. For example, the price negotiation department introduces an algorithm in which a generation AI analyzes past negotiation data and proposes the optimal negotiation strategy. The generation AI collects past price negotiation data and develops an algorithm that proposes the optimal negotiation strategy. For example, it analyzes successful negotiation patterns and reflects them in proposals. The generation AI analyzes market trends and economic indicators in real time and builds a system that proposes the optimal negotiation strategy. For example, it automatically updates the negotiation strategy in response to changes in the economic situation. The generation AI introduces an algorithm that proposes an individual negotiation strategy based on the user's negotiation history and credit information. For example, it proposes a specific strategy to users with a strong track record in negotiations. In this way, by introducing an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy, the success rate of negotiations is improved.

[0081] The price negotiation unit can analyze the price bid history of sellers and buyers in real time and make the optimal price proposal according to the progress of negotiations. In the price negotiation unit, for example, the generation AI collects the price bid history of sellers and buyers in real time and makes the optimal price proposal according to the progress of negotiations. The generation AI collects the price bid history of sellers and buyers in real time and builds a system that makes the optimal price proposal according to the progress of negotiations. For example, it proposes the optimal price based on past price bid data. The generation AI develops a system that analyzes the progress of negotiations in real time and makes the optimal price proposal. For example, it dynamically adjusts the price according to the progress of negotiations. The generation AI builds a system that makes the optimal price proposal according to the progress of negotiations based on the price bid history of sellers and buyers. For example, it analyzes the price negotiation history and proposes the optimal price. This improves the efficiency of negotiations by analyzing the price bid history of sellers and buyers in real time and making the optimal price proposal according to the progress of negotiations.

[0082] The price negotiation unit can use the emotion estimation function to analyze the emotional state of the user during negotiations and make suggestions to reduce stress. The price negotiation unit, for example, uses the emotion estimation function to build a system that analyzes the emotional state of the user during negotiations in real time and makes suggestions to reduce stress. The emotion estimation function builds a system that analyzes the emotional state of the user during negotiations in real time and makes suggestions to reduce stress. For example, if the user is feeling stressed, it makes suggestions to relax. A system is developed that analyzes the emotional state during negotiations based on the user's emotion data and makes suggestions to reduce stress. For example, it makes suggestions that make the user feel at ease. The emotion estimation function builds a system that analyzes the emotional state of the user during negotiations and makes suggestions to reduce stress. For example, it provides an environment where the user can relax. This improves the user's negotiation experience by analyzing the emotional state of the user during negotiations and making suggestions to reduce stress.

[0083] The property information collection unit collects past repair history or maintenance information of a property, and can provide highly transparent information to buyers. For example, the property information collection unit uses a generation AI to collect past repair history of a property and build a system that provides highly transparent information to buyers. The generation AI collects past repair history of a property and builds a system that provides highly transparent information to buyers. For example, it provides details of repairs and renovations that have been carried out in the past. The generation AI collects maintenance information of a property and develops a system that provides highly transparent information to buyers. For example, it provides a history of regular maintenance and future maintenance schedules. The generation AI builds a system that provides highly transparent information to buyers based on the property's past repair history and maintenance information. For example, it provides information that allows for a detailed understanding of the property's condition. This allows the collection of past repair history and maintenance information of a property and provides highly transparent information to buyers, enabling them to select a reliable property.

[0084] The property information collection unit can use the emotion estimation function to make property suggestions based on the buyer's preferences and lifestyle. The property information collection unit, for example, uses the emotion estimation function to analyze the buyer's preferences and lifestyle in real time and build a system that suggests the most suitable property. The emotion estimation function analyzes the buyer's preferences and lifestyle in real time and builds a system that suggests the most suitable property. For example, it prioritizes suggesting properties that the buyer has positive emotions about. A system is developed that suggests properties that suit the buyer's preferences and lifestyle based on the buyer's emotion data. For example, it suggests properties that provide a relaxing environment for the buyer. The emotion estimation function builds a system that makes property suggestions based on the buyer's preferences and lifestyle. For example, it prioritizes suggesting properties that the buyer does not feel stressed about. This makes it possible to make property suggestions based on the buyer's preferences and lifestyle, enabling a more appropriate property selection.

[0085] The contract creation unit can use the emotion estimation function to evaluate the user's level of understanding and satisfaction with the contents of the contract and provide supplemental explanations as necessary. The contract creation unit, for example, uses the emotion estimation function to build a system that evaluates the user's level of understanding and satisfaction with the contents of the contract in real time and provides supplemental explanations as necessary. The emotion estimation function builds a system that evaluates the user's level of understanding and satisfaction with the contents of the contract in real time and provides supplemental explanations as necessary. For example, it provides additional explanations for parts about which the user has doubts. A system is developed that evaluates the user's level of understanding and satisfaction with the contents of the contract based on the user's emotion data and provides supplemental explanations as necessary. For example, it provides detailed explanations for parts about which the user has concerns. The emotion estimation function builds a system that evaluates the user's level of understanding and satisfaction with the contents of the contract and provides supplemental explanations as necessary. For example, it provides additional information for parts about which the user does not understand. In this way, the user's understanding can be deepened by evaluating the user's level of understanding and satisfaction with the contents of the contract and providing supplemental explanations as necessary.

[0086] The contract creation department can improve the reliability and security of contracts by using electronic signatures and blockchain technology. For example, the contract creation department builds a system in which a generation AI uses electronic signature technology to improve the reliability of contracts. The generation AI builds a system that improves the reliability of contracts by using electronic signature technology. For example, it adds an electronic signature to a contract to prevent tampering. The generation AI develops a system that improves the security of contracts by using blockchain technology. For example, it records the contract history on a blockchain to ensure transparency. The generation AI builds a system that improves the reliability and security of contracts by using electronic signatures and blockchain technology. For example, it realizes contract tampering detection and history management. In this way, by improving the reliability and security of contracts by using electronic signatures and blockchain technology, it is possible to prevent tampering and ensure transparency of contracts.

[0087] The contract creation unit can monitor the contract fulfillment status in real time and immediately notify if a problem occurs. For example, the contract creation unit builds a system in which the generation AI monitors the contract fulfillment status in real time and immediately notifies if a problem occurs. The generation AI builds a system that monitors the contract fulfillment status in real time and immediately notifies if a problem occurs. For example, it detects and notifies payment delays and contract violations. The generation AI develops a system that analyzes the contract fulfillment status and immediately notifies if a problem occurs. For example, it monitors the progress of the contract, detects abnormalities, and issues an alert. The generation AI builds a system that monitors the contract fulfillment status in real time and immediately notifies if a problem occurs. For example, it displays the contract fulfillment status on a dashboard and detects and notifies if an abnormality occurs. This ensures contract fulfillment by monitoring the contract fulfillment status in real time and immediately notifying if a problem occurs.

[0088] The contract creation unit can use the emotion estimation function to analyze the user's emotional response to the contents of the contract and make suggested revisions to evoke positive emotions. The contract creation unit, for example, uses the emotion estimation function to build a system that analyzes the user's emotional response to the contents of the contract in real time and makes suggested revisions to evoke positive emotions. The emotion estimation function builds a system that analyzes the user's emotional response to the contents of the contract in real time and makes suggested revisions to evoke positive emotions. For example, it corrects parts that make the user feel uneasy. A system is developed that analyzes the user's emotional response to the contents of the contract based on the user's emotion data and makes suggested revisions to evoke positive emotions. For example, it changes the expression to make it easier for the user to accept. The emotion estimation function builds a system that analyzes the user's emotional response to the contents of the contract and makes suggested revisions to evoke positive emotions. For example, it revises the contract so that the user feels at ease. In this way, the user's emotional response to the contents of the contract is analyzed and suggested revisions to evoke positive emotions are made, thereby improving the user's level of acceptance.

[0089] The price negotiation unit collects price data from different markets and regions and can support price negotiations from a global perspective. For example, the generation AI collects price data from different markets and regions and supports price negotiations from a global perspective. The generation AI collects price data from different markets and regions and builds a system that supports price negotiations from a global perspective. For example, it proposes the optimal price based on the market price in each region. The generation AI analyzes global price data and develops a system that supports price negotiations in different markets and regions. For example, it supports price negotiations in international transactions. The generation AI builds a system that supports price negotiations from a global perspective based on price data from different markets and regions. For example, it proposes prices that take into account the economic conditions of each region. This enables more appropriate price negotiations by collecting price data from different markets and regions and supporting price negotiations from a global perspective.

[0090] The price negotiation unit can simulate the results of price negotiations and predict the optimal negotiation result. In the price negotiation unit, for example, a generation AI simulates the results of price negotiations and predicts the optimal negotiation result. The generation AI builds a system that simulates the results of price negotiations and predicts the optimal negotiation result. For example, it runs a simulation based on past negotiation data and predicts the optimal result. The generation AI simulates price negotiations and develops a system that predicts the optimal negotiation result. For example, it tries different negotiation strategies and predicts the result with the highest success rate. The generation AI builds a system that simulates the results of price negotiations and predicts the optimal negotiation result. For example, it adjusts the progress of negotiations based on the simulation results. In this way, the success rate of negotiations is improved by simulating the results of price negotiations and predicting the optimal negotiation result.

[0091] The price negotiation unit can use the emotion estimation function to monitor the emotional reactions of the user during negotiations in real time and make suggestions to elicit positive emotions. The price negotiation unit, for example, uses the emotion estimation function to monitor the emotional reactions of the user during negotiations in real time and make suggestions to elicit positive emotions. The emotion estimation function builds a system that monitors the emotional reactions of the user during negotiations in real time and makes suggestions to elicit positive emotions. For example, it provides an environment in which the user can relax. A system is developed that monitors the emotional reactions of the user during negotiations based on the user's emotion data and makes suggestions to elicit positive emotions. For example, it makes suggestions that make the user feel at ease. The emotion estimation function builds a system that monitors the emotional reactions of the user during negotiations in real time and makes suggestions to elicit positive emotions. For example, it advances negotiations so that the user does not feel stressed. In this way, the emotional reactions of the user during negotiations can be monitored in real time and suggestions to elicit positive emotions can be made, thereby improving the success rate of negotiations.

[0092] The transaction progress management unit monitors the progress of the transaction in real time and can respond immediately if a problem occurs. For example, the transaction progress management unit builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it automatically concludes contracts and confirms payments. The generation AI analyzes the progress of the transaction and develops a system that responds immediately if a problem occurs. For example, it automatically carries out the necessary procedures as the transaction progresses. The generation AI builds a system in which the generation AI monitors the progress of the transaction in real time and responds immediately if a problem occurs. For example, it displays the progress of the transaction on a dashboard and detects and notifies of any abnormalities. This allows the transaction to proceed smoothly by monitoring the progress of the transaction in real time and responding immediately if a problem occurs.

[0093] The transaction progress management unit can evaluate risks at each step of a transaction and make proposals to minimize the risks. The transaction progress management unit, for example, builds a system in which a generation AI evaluates risks at each step of a transaction and makes proposals to minimize the risks. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. The generation AI develops a system that analyzes transaction risks and makes proposals to minimize the risks. For example, it monitors the progress of a transaction and responds immediately if a risk occurs. The generation AI builds a system in which it evaluates risks at each step of a transaction and makes proposals to minimize the risks. For example, it performs risk assessment as the transaction progresses and proposes necessary measures. In this way, by evaluating risks at each step of a transaction and making proposals to minimize the risks, the safety of transactions is improved.

[0094] The transaction progress management unit can visualize the transaction progress and provide a dashboard that the user can intuitively understand. For example, the transaction progress management unit constructs a system in which a generation AI visualizes the transaction progress and provides a dashboard that the user can intuitively understand. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, each step of the transaction is displayed graphically. The generation AI analyzes the transaction progress and develops a system that provides a dashboard that the user can intuitively understand. For example, the transaction progress is updated in real time. The generation AI constructs a system in which the transaction progress is visualized and provides a dashboard that the user can intuitively understand. For example, the transaction progress is displayed in graphs and charts. This visualizes the transaction progress and provides a dashboard that the user can intuitively understand, making it easier to grasp the transaction progress.

[0095] The transaction progress management unit can automatically generate necessary documents and procedures as the transaction progresses and provide them to the user. The transaction progress management unit, for example, builds a system in which a generation AI automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. The generation AI builds a system in which it automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it automatically generates contracts and payment confirmations. The generation AI develops a system that analyzes the progress of the transaction and automatically generates necessary documents and procedures and provides them to the user. For example, it automatically generates documents as the transaction progresses. The generation AI builds a system that automatically generates necessary documents and procedures as the transaction progresses and provides them to the user. For example, it monitors the progress of the transaction and automatically generates necessary documents. This makes it possible to streamline transaction procedures by automatically generating necessary documents and procedures as the transaction progresses and providing them to the user.

[0096] The transaction progress management unit can use the emotion estimation function to analyze the user's emotional state as the transaction progresses and make suggestions to reduce stress. The transaction progress management unit, for example, uses the emotion estimation function to monitor the user's emotional response to the transaction progress in real time and make suggestions to elicit positive emotions. The emotion estimation function builds a system that monitors the user's emotional response to the transaction progress in real time and makes suggestions to elicit positive emotions. For example, it provides an environment in which the user can relax. A system is developed that monitors the user's emotional response to the transaction progress based on the user's emotion data and makes suggestions to elicit positive emotions. For example, it makes suggestions that make the user feel at ease. The emotion estimation function builds a system that monitors the user's emotional response to the transaction progress in real time and makes suggestions to elicit positive emotions. For example, it progresses the transaction so that the user does not feel stressed. This improves the user's trading experience by analyzing the user's emotional state as the transaction progresses and making suggestions to reduce stress.

[0097] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0098] The property information collection unit can collect data on the surrounding environment of a property and provide comprehensive information to buyers. For example, it collects information on schools, hospitals, commercial facilities, transportation access, etc. in the vicinity of the property and provides it to buyers. The property information collection unit can also collect future forecast data for the area and provide buyers with information predicting future value fluctuations. For example, it collects forecast data on local development plans and demographics and provides it to buyers. This allows buyers to make more appropriate property selections by providing comprehensive information on the surrounding environment of the property and future value fluctuations.

[0099] The contract creation unit can automatically generate contracts that comply with the laws and regulations of each country, supporting international real estate transactions. For example, a system can be built in which the generation AI collects the laws and regulations of each country and automatically generates contracts based on them. The generation AI generates contracts that meet the legal requirements of each country and can also create contracts in multiple languages. For example, it can generate contracts in multiple languages ​​such as English and Chinese. This minimizes legal risks and ensures smooth transactions, even in international real estate transactions.

[0100] The price negotiation unit can use the emotion estimation function to analyze the emotional state of the user during negotiation and make suggestions to reduce stress. For example, the emotion estimation function analyzes the emotional state of the user during negotiation in real time and makes suggestions to help the user relax if the user is feeling stressed. Based on the user's emotion data, the emotional state during negotiation can also be analyzed and suggestions made to help the user feel at ease. In this way, the user's negotiation experience can be improved by analyzing the user's emotional state during negotiation and making suggestions to reduce stress.

[0101] The transaction progress management department monitors the progress of transactions in real time and can respond immediately if any problems arise. For example, we will build a system in which the generation AI monitors the progress of transactions in real time and automatically concludes contracts and confirms payments. The generation AI will develop a system that analyzes the progress of transactions and responds immediately if any problems arise. For example, it will automatically carry out the necessary procedures as the transaction progresses. This will enable the smooth progress of transactions by monitoring the progress of transactions in real time and responding immediately if any problems arise.

[0102] The property information collection unit can collect data on the energy efficiency or environmental impact of properties and suggest eco-friendly properties. For example, a system can be built in which the generation AI collects energy efficiency data on properties and suggests eco-friendly properties. The generation AI evaluates the energy consumption and insulation performance of properties and suggests eco-friendly properties. It can also collect environmental impact data on properties and evaluate CO2 emissions and renewable energy usage. This makes it possible to select environmentally friendly properties by collecting data on the energy efficiency and environmental impact of properties and suggesting eco-friendly properties.

[0103] The contract creation unit can use the emotion estimation function to evaluate the user's level of understanding and satisfaction with the contents of the contract and provide supplemental explanations as needed. For example, the emotion estimation function can evaluate the user's level of understanding and satisfaction with the contents of the contract in real time and provide additional explanations for any parts of the contract that the user has questions about. It can also evaluate the user's level of understanding and satisfaction with the contents of the contract based on the user's emotion data and provide detailed explanations as needed. This makes it possible to deepen the user's understanding by evaluating the user's level of understanding and satisfaction with the contents of the contract and providing supplemental explanations as needed.

[0104] The transaction progress management department can evaluate the risks at each step of the transaction and make proposals to minimize the risks. For example, we will build a system in which the generation AI evaluates the risks at each step of the transaction, evaluates the risks as the transaction progresses, and proposes necessary measures. The generation AI will develop a system that analyzes the risks of the transaction and makes proposals to minimize the risks. For example, it will monitor the progress of the transaction and respond immediately if a risk occurs. This will enable us to evaluate the risks at each step of the transaction and make proposals to minimize the risks, thereby improving the safety of the transaction.

[0105] The price negotiation department can introduce an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy. For example, a generation AI collects past negotiation data, analyzes successful negotiation patterns, and develops an algorithm that proposes the optimal negotiation strategy. The generation AI analyzes market trends and economic indicators in real time and builds a system that proposes the optimal negotiation strategy. For example, it automatically updates the negotiation strategy in response to changes in the economic situation. This makes it possible to improve the success rate of negotiations by introducing an algorithm that analyzes past negotiation data and proposes the optimal negotiation strategy.

[0106] The property information collection unit can automatically generate 3D models or virtual tours of properties to provide buyers with visual information. For example, a system will be built in which the generation AI automatically generates 3D models of properties and displays the internal structure and layout of the properties in 3D. The generation AI will develop a system that automatically generates virtual tours of properties, allowing buyers to view the interior of the properties on a virtual tour. This will enable more detailed property information to be provided by automatically generating 3D models and virtual tours of properties and providing visual information to buyers.

[0107] The transaction progress management unit can use the emotion estimation function to analyze the user's emotional state regarding the progress of the transaction and make suggestions to reduce stress. For example, the emotion estimation function can monitor the user's emotional response to the progress of the transaction in real time and provide an environment in which the user can relax. Based on the user's emotion data, it can also monitor the user's emotional response to the progress of the transaction and make suggestions to elicit positive emotions. This can improve the user's trading experience by analyzing the user's emotional state regarding the progress of the transaction and making suggestions to reduce stress.

[0108] The processing flow of the second embodiment will be briefly explained below.

[0109] Step 1: The property information collection unit collects property information. For example, it collects information such as the location, price, area, and age of the property. The property information collection unit can also organize the property information provided by the user and provide it to the buyer. For example, the property information collection unit organizes the property information based on prompts from the user and provides it to the buyer. Step 2: The contract creation unit creates a contract based on the property information collected by the property information collection unit. For example, the contract creation unit automatically creates documents such as a sales contract and an explanation of important matters. The contract creation unit can also create a contract based on prompts from the user and manage it as the transaction progresses. Step 3: The price negotiation unit negotiates the price based on the contract created by the contract creation unit. For example, the price negotiation unit supports price negotiations between the seller and the buyer. The price negotiation unit can also negotiate the price based on prompts from the user to arrive at a price that satisfies both parties. Step 4: The transaction progress management unit manages the progress of the transaction based on the price negotiated by the price negotiation unit. For example, the transaction progress management unit manages the progress of the transaction, such as the signing of a contract, confirmation of payment, and delivery of the property. The transaction progress management unit can also manage the progress of the transaction based on prompts from the user and notify them at the appropriate time.

[0110] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0111] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0112] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0113] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0114] 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.

[0115] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0116] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0117] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0119] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0120] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0121] 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.

[0122] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0123] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0124] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0125] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0126] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0127] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0128] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0129] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0130] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0131] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0132] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0133] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0134] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0135] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0136] 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.

[0137] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0138] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0139] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0140] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0141] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0142] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0143] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0144] 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.

[0145] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0146] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0147] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0148] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0149] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0150] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0151] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0152] 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.

[0153] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0154] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0155] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0156] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0157] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0158] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0159] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0160] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0161] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0162] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0163] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0164] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0165] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0166] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0167] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0168] 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.

[0169] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0170] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0171] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific process may be a single processor.

[0172] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0173] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0174] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0175] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0176] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0177] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a property information collection unit that collects property information; a contract creation unit that creates a contract based on the property information collected by the property information collection unit; a price negotiation unit that negotiates prices based on the contract created by the contract creation unit; a transaction progress management unit that manages the progress of the transaction based on the price negotiated by the price negotiation unit. A system characterized by:

2. The property information collection unit Organizing the property information based on prompts from the user and providing it to the buyer 2. The system of claim 1.

3. The contract creation unit Creating the contract based on prompts from the user and managing the transaction as it progresses 2. The system of claim 1.

4. The price negotiation unit Negotiating the price based on prompts from the user to arrive at a price that is acceptable to both parties 2. The system of claim 1.

5. The transaction progress management unit Manage the progress of the transaction based on prompts from the user and provide timely notifications 2. The system of claim 1.

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