system

Abstract

We provide the system. [Solution] A means of obtaining location information of the user's place of residence, A means of collecting real estate market information based on acquired location information, A method for analyzing collected real estate market information and calculating appropriate rent, Means of providing users with analysis results and supporting evidence, A means of automatically or semi-automatically negotiating rent in response to user requests, A means of acquiring rental information in real time based on mobile location information and visually displaying appropriate rent, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, in Japanese rental contracts, rent negotiations at the time of contract renewal have not been sufficiently conducted, so it has been difficult for lessees to secure an appropriate rent based on the market price. Also, it is not easy to grasp the fluctuations in the rent market in real time, and as a result, there are many cases where lessees continue to pay an unduly high rent. This has caused a problem of disadvantaging lessees.

Means for Solving the Problems

[0005] This invention provides a system that obtains residential location information from users and collects real estate market data based on that information. The collected data is analyzed by AI to calculate an appropriate rent, and the results and evidence are recommended to the user. Furthermore, it includes means for automatically or semi-automatically negotiating rent according to the user's wishes, and supports the negotiation process through data sharing with affiliated real estate agents, thereby realizing contract renewal at an appropriate rent.

[0006] A "user" is an individual or group that uses the service and is the entity that inputs information about rental properties into the system.

[0007] "Residential location information" refers to geographical information such as the address used to identify the location of a rental property.

[0008] "Real estate market data" refers to data that shows the market conditions for rental properties, and includes information such as rent, transaction examples, and regional characteristics.

[0009] "Appropriate rent" refers to the rent for a rental property that is deemed fair and reasonable, calculated based on collected and analyzed real estate market data.

[0010] "Evidence" refers to documents and information that demonstrate the basis for the calculated fair rent, and typically includes market data and analysis results.

[0011] "Rent negotiation" refers to the process of negotiating terms regarding the rent of a rental property between the landlord and the tenant.

[0012] "Means of performing actions automatically or semi-automatically" refers to functions in which the system takes the lead in fully or partially automating the negotiation process.

[0013] A "partner real estate agent" is a professional or organization that works with the system to negotiate rents and provide contract support. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Modes for Carrying Out the Invention

[0015] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention provides a system that allows users to calculate a fair rent when renewing a lease agreement and, if necessary, receive assistance in negotiations. This system primarily operates through the collaborative efforts of a server, terminals, and users.

[0036] The user first enters the location information of their rental property into the system via a terminal. This information is used as foundational data for the server to collect relevant real estate market data.

[0037] The server retrieves the latest rental market data from external real estate market databases and APIs based on location information. This includes rental property information within the area, past rental records, current transaction status, and market trends. This collected data is analyzed by an AI algorithm to predict appropriate rents that match the current market environment.

[0038] Subsequently, the server generates a report containing the calculated appropriate rent and the supporting evidence, which is then provided to the user via their terminal. Based on this information, the user can consider more favorable terms when renewing their lease agreement.

[0039] If the user requires further assistance, they can select an option on their device to have rent negotiations handled or supported. In this case, the server provides the necessary data and recommended negotiation strategies to a partner real estate agent. The agent uses this information to efficiently negotiate with the landlord, ensuring the user can renew their lease on fair terms.

[0040] For example, suppose a user who owns a rental property in Tokyo's 23 wards uses this system. Based on the address entered by the user, the server collects data on surrounding rental properties and uses AI analysis to calculate an appropriate rent that reflects past trends and current market conditions. Based on this information, the user can find out how appropriate their property's rent is compared to the market rate and, if necessary, negotiate a rent adjustment.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user uses a terminal to enter the location information of the rental property where they live. This information is then registered as input data in the system.

[0044] Step 2:

[0045] The terminal sends the entered location information to the server. The transmitted information also includes identification information such as the user ID.

[0046] Step 3:

[0047] Based on the location information it receives, the server collects the latest market data for the relevant area from the real estate market database and related APIs.

[0048] Step 4:

[0049] The server processes collected real estate market data using an AI algorithm, analyzing local rental rates, past transaction data, and economic indicators to calculate appropriate rent.

[0050] Step 5:

[0051] The server generates a report containing the analysis results, which include the appropriate rent and the evidence supporting its calculation. This report includes graphs and statistical data.

[0052] Step 6:

[0053] The server sends the generated report to the terminal, allowing the user to check rental information and market conditions related to their property.

[0054] Step 7:

[0055] If a user wishes to negotiate the rent, they can select the negotiation assistance option on the terminal's interface.

[0056] Step 8:

[0057] The server receives requests for negotiation assistance and provides the necessary data and recommended negotiation scenarios to partner real estate agents.

[0058] Step 9:

[0059] The partner agent uses the information provided by the server to negotiate with the landlord on behalf of the user and reports the results back to the server.

[0060] Step 10:

[0061] The server sends the negotiation results to the terminal, and the user receives guidance on new rent terms and next steps.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] In traditional lease renewals, it is difficult for tenants to determine and negotiate fair market rent. Market information is volatile, and collecting and analyzing the necessary data to determine a fair price in a short time is a significant burden for the average tenant. Furthermore, formulating an appropriate negotiation strategy is difficult, which can result in the risk of renewing the contract under unfavorable terms.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for collecting real estate market information based on acquired location data, means for analyzing the collected real estate market information and predicting appropriate prices, means for presenting the analysis results and supporting documents to the user, and means for applying a generative AI model in data analysis and predicting market trends. This enables the user to quickly and easily grasp appropriate rent and negotiation strategies and renew lease agreements on favorable terms.

[0067] A "user" is an individual or organization that uses the system to obtain information regarding the renewal of a lease agreement and to make decisions regarding that information.

[0068] "Location data" refers to data that includes the address and geographical information of the property where the user resides.

[0069] "Real estate market information" refers to data related to real estate transactions in a specific area, such as prices, transaction status, and past transaction history for rental properties.

[0070] "Analysis" is the process of performing calculations and evaluations based on collected data to determine market trends and appropriate rents.

[0071] A "fair price" is the rent for a rental property that is set in a reasonable and fair manner, taking into account the current market conditions.

[0072] "Evidence" refers to data and information that supports the analysis results, and is intended to be used by users as a reference when making decisions.

[0073] A "generative AI model" is a type of artificial intelligence technology that learns market trends and price tendencies from large amounts of data and uses them for analysis and prediction.

[0074] "Market trends" refer to tendencies that indicate future market changes, such as price increases or decreases in the real estate market, and changes in the supply and demand for properties.

[0075] This system works collaboratively by servers, terminals, and users to enable users to calculate appropriate rent and secure favorable terms when renewing a lease agreement.

[0076] The server accesses an external real estate market information database based on location data entered by the user through their terminal. The specific software used here is the API of a real estate information provision platform, which retrieves local rental property information, transaction status, and past transaction history.

[0077] The server utilizes a generative AI model to analyze the acquired real estate market information. Specifically, machine learning frameworks such as TENSORFLOW® are used to predict market trends and appropriate prices. Based on these analysis results, the server generates appropriate rents and supporting documents for the user.

[0078] The terminal has a user interface (UI) that presents reports generated by the server to the user, displaying analysis results using visual graphics. Based on this information, the user can evaluate how fair the rent is compared to market rates and prepare for negotiations.

[0079] For example, if a user enters the prompt "Calculate the current fair rent for a 2LDK apartment in Shinjuku Ward, Tokyo," the server will use this address information to collect real estate market information and calculate the fair rent through analysis by a generated AI model. This allows the user to quickly find out the rent based on current market conditions, enabling them to negotiate more favorably when renewing their lease.

[0080] Furthermore, if a user wishes to negotiate the price, the terminal provides a function to assist with negotiations automatically or semi-automatically, and the server assists the negotiation process by supplying effective data and negotiation strategies to affiliated real estate professionals. This enables users to renew their lease agreements on better terms.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user uses their device to input location data for their rental property. This location data includes the address and postal code of the residence. The device packets this data and sends it to the server via a secure protocol (HTTPS) to send it to the server. As a result, the server receives the basic data necessary to continue processing.

[0084] Step 2:

[0085] The server accesses a real estate market information database based on the received location data. Using address information as a query parameter, the server retrieves rental property information, transaction history, and past transaction data within the area via an API. As output, the server stores the retrieved real estate market information in a structured format.

[0086] Step 3:

[0087] The server analyzes market trends and appropriate rents using a generated AI model based on acquired real estate market information. In this process, the AI ​​algorithm calculates market trends and average prices. The server utilizes machine learning frameworks such as TensorFlow to predict appropriate rents through data computation. A detailed report showing the analysis results is generated as output.

[0088] Step 4:

[0089] The terminal receives analysis reports sent from the server and displays them in the user interface. The terminal uses visually easy-to-understand graphs and charts to show users rent fluctuations and market overviews. Based on this information, users can make decisions regarding lease renewals.

[0090] Step 5:

[0091] If a user wishes to negotiate rent, they select a negotiation support option on the terminal interface. Based on this selection, the server provides the necessary data and recommended negotiation strategies to affiliated real estate professionals. The output includes guidelines and data to efficiently conduct negotiations, allowing the user to negotiate a more favorable contract.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] In the unstable real estate rental market, there is a problem in that users cannot determine whether the current rent is in line with market rates and have limited means to negotiate fairly. Furthermore, it is difficult to efficiently utilize real-time rental market information.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] In this invention, the server includes means for obtaining location information of the user's place of residence, means for collecting real estate market information based on the obtained location information, and means for obtaining rental information in real time based on mobile location information and visually presenting appropriate rent. This enables the user to quickly and visually confirm whether the current rent is in line with market rates and to conduct appropriate rent negotiations.

[0097] A "user" is an individual or organization that uses the system to obtain rental information for their place of residence and receives negotiation support.

[0098] "Location information of residence" refers to data that indicates the geographical location of where the user lives.

[0099] "Real estate market information" refers to a collection of data related to rental property prices, market trends, and transaction examples in a specific geographical area.

[0100] "Analysis" is the process of evaluating collected data and identifying certain patterns or trends.

[0101] "Appropriate rent" refers to a fair and appropriate rental price calculated based on collected real estate market information.

[0102] "Evidence" refers to the evidence and data used to support the results obtained through analysis.

[0103] "Automatically or semi-automatically" means that the system completes its actions with little or no user intervention, or with the system's assistance even if user intervention is present.

[0104] "Mobile location information" refers to data that shows how the location of a user or device changes over time.

[0105] "Acquiring rental information in real time" means immediately importing rental-related data into the system according to the current situation.

[0106] "Presenting visually" means showing the calculated results to the user in a visual format.

[0107] "Rent negotiation" refers to discussions between the landlord and tenant to review and adjust the terms of a lease agreement.

[0108] The system for implementing this invention provides rapid rental information for residential areas and supports users in efficiently negotiating rental rates. The following hardware and software are used to realize the system.

[0109] The server is a high-performance computer with an internet connection that receives location information from users as input data. Based on this, it accesses databases to collect real estate market information. External real estate databases and statistical APIs are used for data collection. In this process, the latest rental property information and market trends are obtained.

[0110] The collected data is analyzed on the server using an AI algorithm. The AI ​​algorithm operates using a generative AI model to calculate an appropriate rent. This calculation result is provided to the user's terminal as a report in a visually easy-to-understand format.

[0111] Users access this information through mobile devices such as smartphones and smart glasses. The devices feature an intuitive interface, allowing users to easily view results and, if necessary, select negotiation options for rent negotiations.

[0112] As a concrete example, a user residing in Shinjuku Ward, while at a cafe, can use smart glasses to obtain real-time information on nearby rental properties and check how their own rent compares to market rates. By prompting the user with a sentence like, "Please tell me if my apartment rent is appropriate based on the market rate in Shinjuku Ward," the system will immediately provide appropriate rent information.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The user enters their location information using a terminal. This entered location information is sent to the server as basic system data. Based on this data, the server prepares to collect information for use in the next processing step.

[0116] Step 2:

[0117] The server accesses external real estate market databases and APIs to collect real estate market information based on the input location data. Based on the input location data, it retrieves data on rental property prices, transaction examples, and market trends, and stores this data within the system.

[0118] Step 3:

[0119] The server inputs collected real estate market information into an AI algorithm. Using a generative AI model, this data is analyzed to calculate a suitable rent. Through this data calculation, the AI ​​model evaluates multiple data points and predicts a fair rent that is appropriate for current market conditions.

[0120] Step 4:

[0121] The server generates a report containing the calculated appropriate rent and its rationale, and sends it to the terminal. This report is formatted to present the information visually and is designed to allow the user to easily review the results.

[0122] Step 5:

[0123] The terminal displays the report received by the user. Based on the information presented, the user can determine how fair their rent is compared to market rates. This information includes visual elements and is designed to be easily understood.

[0124] Step 6:

[0125] Users select options on their device to support rent negotiations as needed. The selected options are sent to the server, where data is shared with partner real estate professionals, and the negotiation process is supported. Based on the user's choices, a negotiation strategy is developed, providing a foundation for efficient negotiation.

[0126] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0127] This invention incorporates an emotion engine that recognizes the user's emotions into a system that calculates appropriate rent when renewing a lease agreement and provides negotiation support as needed. As a result, the user's emotional state is taken into consideration when presenting appropriate rent and facilitating negotiations, leading to smoother and more effective negotiations.

[0128] Users input the location information of their rental property into the system via their device. This provides the server with the basic information needed to collect real estate market data. Based on the location information, the server retrieves the latest market data from external real estate market databases and APIs and analyzes it using an AI algorithm. Based on the results of this analysis, an appropriate rent is calculated.

[0129] Furthermore, the emotion engine recognizes the user's emotional state in real time and adjusts the method of presenting appropriate rent based on that data. For example, for users who are feeling stressed, it can improve their ability to accept information by providing clear and reassuring explanations.

[0130] The data recognized by the emotion engine is also used in the negotiation process. The server suggests a negotiation style based on the user's emotional state and communicates this to the partner real estate agent. The agent uses this information to adjust communication and help the negotiation proceed more smoothly.

[0131] As a concrete example, consider a situation where a user is feeling anxious about a rent increase. This system uses the device's camera and microphone to recognize the user's emotional state through an emotion engine, and the server generates reassuring explanations and suggestions based on that information. Real estate agents receive guidance on the need for careful consideration during negotiations, allowing negotiations with landlords to proceed more flexibly and effectively. In this way, users can achieve fair contract terms while reducing their psychological burden.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] Users enter the location information of their rental property via their terminal. This information serves as the basic data for calculating the appropriate rent within the system.

[0135] Step 2:

[0136] The terminal sends the entered location information to the server. This initiates the data collection process.

[0137] Step 3:

[0138] Based on the location information received, the server collects rental market data for the relevant area through real estate market databases and external APIs. This data includes local rental rates and actual transaction examples.

[0139] Step 4:

[0140] The server analyzes collected market data using an AI algorithm to calculate appropriate rents for the relevant area. The AI ​​combines past market trends with the latest data to improve the accuracy of the calculation results.

[0141] Step 5:

[0142] The emotion engine acquires emotional data in real time from the user's device using the camera and microphone. This includes facial expression analysis and voice tone analysis.

[0143] Step 6:

[0144] The server analyzes the emotional data sent from the emotion engine to determine the user's emotional state. This information is used to determine the appropriate rent price.

[0145] Step 7:

[0146] The server calculates the appropriate rent and provides supporting evidence, then formats it into a report that is adjusted according to the user's emotional state and sends it to the terminal. For example, if the user is feeling anxious, the report will include additional information to provide reassurance.

[0147] Step 8:

[0148] Users can review the provided reports through their devices and choose to receive assistance with rent negotiations as needed.

[0149] Step 9:

[0150] The server receives requests for negotiation assistance and communicates negotiation strategies, which take into account the user's emotional state, to partner real estate agents.

[0151] Step 10:

[0152] Based on the information received from the server, partner agents negotiate with the landlord using a communication style that takes the user's feelings into consideration. The results are reported to the server and ultimately notified to the user.

[0153] (Example 2)

[0154] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0155] In traditional lease renewal procedures, rent offers and negotiations are often based on general market data without considering the feelings of the tenant. As a result, tenants may experience emotional distress, and negotiations may not proceed smoothly. Furthermore, negotiation support has not been personalized to the individual needs and circumstances of each tenant, and information sharing between real estate agents and tenants has been insufficient. There is a need to resolve these issues and provide more effective lease renewal and negotiation support.

[0156] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of a property from a user, means for collecting market information based on the acquired location information, means for analyzing the collected market information and calculating an appropriate rent, means for detecting the user's emotional state and adjusting the presented content according to that state, and means for proposing a negotiation strategy based on the emotional information and sharing the information with the partner intermediary. This makes it possible to present an appropriate rent that takes the user's emotions into consideration and to support an effective negotiation process.

[0157] A "user" is an individual or organization that enters information in order to renew a property lease agreement using the system.

[0158] "Property location information" refers to information indicating the location of a rental property, including, for example, the address and postal code.

[0159] "Market information" refers to data related to the real estate market, including rental rates, transaction status, and information on similar properties.

[0160] "Analysis" refers to the process of analyzing market information to calculate appropriate rent, and may involve machine learning or statistical methods.

[0161] "Emotional state" refers to the psychological state exhibited by the user, and is inferred from data collected through cameras and microphones.

[0162] "Provided information" refers to the rental information and negotiation information that the system provides to the user.

[0163] A "negotiation strategy" refers to the contract terms and negotiation methods proposed based on the user's circumstances and needs, and is shared with the intermediary.

[0164] An "intermediary" is an agent or broker involved in negotiating real estate transactions or lease agreements.

[0165] This invention is a system that takes into account the feelings of the user when renewing a lease agreement, calculates a fair rent, and effectively supports negotiations.

[0166] The user enters the location information of the rental property via their device. Once this input is complete, the server uses this information to access external databases and APIs to collect the latest real estate market information. This involves a general internet connection and, for example, APIs from local real estate information services. The server can use machine learning libraries such as TensorFlow or Scikit-learn to analyze this data with AI algorithms and calculate a fair rent for the user's rental property.

[0167] Furthermore, the emotion engine uses the camera and microphone built into the device to detect the user's emotional state in real time from their facial expressions and voice. This process utilizes computer vision libraries such as OpenCV and speech analysis technology. The server adjusts and presents information about rent and contract details according to the user's emotional state using a generative AI model. This generative AI model employs natural language processing technology and is programmed to provide explanations in reassuring language, for example, if the user is feeling stressed.

[0168] As a concrete example, suppose a user is expressing anxiety about an increase in rent. In this situation, the system uses the device's camera and microphone to recognize the user's emotional state, and the server generates and presents reassuring information based on that data. The real estate agent is then instructed to handle negotiations with greater consideration.

[0169] An example of a prompt for input to the generating AI model might be: "If a user is feeling stressed during real estate negotiations, please suggest how to explain a fair rent in a way that will reassure them." This process will reduce the user's psychological burden and enable them to renew their lease agreement more effectively.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] The user enters the location information of the rental property on the terminal. This input transmits the information to the system. As output, location data for use by the server is generated.

[0173] Step 2:

[0174] The server uses location information received from the user to access external real estate databases and APIs to collect market information. The input is location information, and the output is market information data related to that property. This process involves data acquisition via the internet.

[0175] Step 3:

[0176] The server inputs collected market information into an AI algorithm to calculate a fair rent. The input is market information data, and the output is the calculated fair rent. In this step, data analysis is performed using libraries such as TensorFlow and Scikit-learn.

[0177] Step 4:

[0178] The device uses a camera and microphone to collect the user's facial expressions and voice, and sends them to an emotion engine. The input is the user's real-time facial expressions and voice, and the output is the recognized emotional state. In this process, emotion analysis is performed using libraries such as OpenCV.

[0179] Step 5:

[0180] The server adjusts the rent presentation method using a generative AI model based on the emotional state obtained from the emotion engine. The input is emotional state data, and the output is adjusted rent information. The server uses natural language processing to generate information that matches the user's state.

[0181] Step 6:

[0182] The server proposes negotiation strategies along with adjusted rent information and shares this information with partner real estate agents. The input is adjusted rent information and negotiation strategies, and the output is instructional information for agents. This allows agents to conduct appropriate negotiations tailored to the client's emotional state.

[0183] (Application Example 2)

[0184] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0185] In today's market, when renewing housing contracts or purchasing interior goods, insufficient fair pricing and negotiation often leave consumers feeling anxious and uncertain. In particular, information provision and negotiations that do not consider the customer's feelings can be burdensome. In such situations, there is a need for appropriate pricing calculations and negotiation support that take the customer's feelings into consideration.

[0186] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0187] In this invention, the server includes means for obtaining location information of a living space from a user, means for collecting building market data based on the obtained location information, means for analyzing the collected building market data and calculating appropriate fees, means for recognizing the user's emotional state and providing information in accordance with those emotions, and means for sensing the customer's emotions in a store and supporting individually tailored product suggestions and price negotiations. This enables smooth price negotiations and suggestions that take the user's emotions into consideration.

[0188] A "user" refers to an individual or legal entity that receives services in a living space or store through the system.

[0189] "Residential space" is a term that refers to a building or a part of a building that is primarily used for the purpose of human habitation.

[0190] "Location information" refers to data that indicates the geographical location of a specific residential space or store.

[0191] "Building market data" refers to information that includes market information and price data related to buildings in a specific region or area.

[0192] "Fair pricing" refers to pricing that is deemed fair and appropriate based on market data.

[0193] "Emotional state" refers to the psychological and emotional responses that a user exhibits to a particular situation or piece of information.

[0194] "Information presentation" refers to the act of providing users with specific data and proposals.

[0195] A "store" refers to a commercial facility where goods or services are provided.

[0196] "Product recommendation" refers to recommending suitable products or services based on consumers' interests and needs.

[0197] "Price negotiation" refers to discussions about fees that take place in order to determine the terms of a transaction.

[0198] The system for implementing this invention utilizes various hardware and software to calculate appropriate fees and provide users with emotionally relevant information. Primarily, a server and a terminal work together to acquire location information about the user's living space and collect and analyze building market data based on that information. The server uses an AI algorithm to analyze the collected data and calculate appropriate fees. This calculation may utilize, for example, an analytical tool developed in Python.

[0199] The devices are smartphones and tablets, and they are equipped with emotion recognition software called an emotion engine to recognize the user's emotional state. The emotion engine detects changes in the user's facial expressions and voice and analyzes those emotions in real time. This analysis uses input data obtained from a camera module and microphone.

[0200] When a user visits an interior design store, the system can automatically make personalized product suggestions and negotiate prices based on their emotional state. For example, if the emotion engine determines that a user is looking at a particular piece of high-end furniture with interest, the terminal will present special offers and detailed product information in a friendly manner.

[0201] For example, if a user smiles while browsing products, the system will detect this and activate a generative AI model that displays a customized message such as, "This is the item you've been waiting for! Available now at a special price." An example of a prompt would be, "Generate a description tailored to the product the user is interested in and present a special offer adjusted based on the user's emotional state."

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The server obtains location information of the user's living space. The input is detailed address data entered by the user on their device. Based on this information, the server prepares to collect building market data. The server accesses the database using APIs as needed.

[0205] Step 2:

[0206] The server collects building market data based on acquired location information. The input here is location information, and the output is the latest market data. The server accesses external databases to collect the necessary market information. At this stage, data is obtained from multiple sources via the internet.

[0207] Step 3:

[0208] The server analyzes collected building market data and calculates appropriate pricing. The input data is collected market information, and the output is the amount of appropriate pricing. The server uses an AI algorithm to analyze the data and calculate appropriate pricing considering current market trends and historical data.

[0209] Step 4:

[0210] The device uses a camera and microphone to recognize the user's emotional state in real time. The input is data of the user's facial expressions and voice, and the output is the analyzed emotional state. An emotion engine is activated, processing the data to determine the user's emotions.

[0211] Step 5:

[0212] The server provides optimal information based on the user's emotional state. The input is emotional data analyzed by the emotion engine, and the output is customized information for the user. A generative AI model is used to generate suitable suggestions and special offers based on the prompt text.

[0213] Step 6:

[0214] The terminal presents the user with generated information and special offers. The input is customized information from the server, and the output is what is displayed on the user's screen. The terminal adjusts the display so that the presented information is visually clear and easy to understand.

[0215] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0216] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0217] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0221] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0222] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0223] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0224] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0225] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0226] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0227] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0228] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0229] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0230] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0231] This invention provides a system that allows users to calculate a fair rent when renewing a lease agreement and, if necessary, receive assistance in negotiations. This system primarily operates through the collaborative efforts of a server, terminals, and users.

[0232] The user first enters the location information of their rental property into the system via a terminal. This information is used as foundational data for the server to collect relevant real estate market data.

[0233] The server retrieves the latest rental market data from external real estate market databases and APIs based on location information. This includes rental property information within the area, past rental records, current transaction status, and market trends. This collected data is analyzed by an AI algorithm to predict appropriate rents that match the current market environment.

[0234] Subsequently, the server generates a report containing the calculated appropriate rent and the supporting evidence, which is then provided to the user via their terminal. Based on this information, the user can consider more favorable terms when renewing their lease agreement.

[0235] If the user requires further assistance, they can select an option on their device to have rent negotiations handled or supported. In this case, the server provides the necessary data and recommended negotiation strategies to a partner real estate agent. The agent uses this information to efficiently negotiate with the landlord, ensuring the user can renew their lease on fair terms.

[0236] For example, suppose a user who owns a rental property in Tokyo's 23 wards uses this system. Based on the address entered by the user, the server collects data on surrounding rental properties and uses AI analysis to calculate an appropriate rent that reflects past trends and current market conditions. Based on this information, the user can find out how appropriate their property's rent is compared to the market rate and, if necessary, negotiate a rent adjustment.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] The user uses a terminal to enter the location information of the rental property where they live. This information is then registered as input data in the system.

[0240] Step 2:

[0241] The terminal sends the entered location information to the server. The transmitted information also includes identification information such as the user ID.

[0242] Step 3:

[0243] Based on the location information it receives, the server collects the latest market data for the relevant area from the real estate market database and related APIs.

[0244] Step 4:

[0245] The server processes collected real estate market data using an AI algorithm, analyzing local rental rates, past transaction data, and economic indicators to calculate appropriate rent.

[0246] Step 5:

[0247] The server generates a report containing the analysis results, which include the appropriate rent and the evidence supporting its calculation. This report includes graphs and statistical data.

[0248] Step 6:

[0249] The server sends the generated report to the terminal, allowing the user to check rental information and market conditions related to their property.

[0250] Step 7:

[0251] If a user wishes to negotiate the rent, they can select the negotiation assistance option on the terminal's interface.

[0252] Step 8:

[0253] The server receives requests for negotiation assistance and provides the necessary data and recommended negotiation scenarios to partner real estate agents.

[0254] Step 9:

[0255] The partner agent uses the information provided by the server to negotiate with the landlord on behalf of the user and reports the results back to the server.

[0256] Step 10:

[0257] The server sends the negotiation results to the terminal, and the user receives guidance on new rent terms and next steps.

[0258] (Example 1)

[0259] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0260] In traditional lease renewals, it is difficult for tenants to determine and negotiate fair market rent. Market information is volatile, and collecting and analyzing the necessary data to determine a fair price in a short time is a significant burden for the average tenant. Furthermore, formulating an appropriate negotiation strategy is difficult, which can result in the risk of renewing the contract under unfavorable terms.

[0261] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0262] In this invention, the server includes means for collecting real estate market information based on acquired location data, means for analyzing the collected real estate market information and predicting appropriate prices, means for presenting the analysis results and supporting documents to the user, and means for applying a generative AI model in data analysis and predicting market trends. This enables the user to quickly and easily grasp appropriate rent and negotiation strategies and renew lease agreements on favorable terms.

[0263] A "user" is an individual or organization that uses the system to obtain information regarding the renewal of a lease agreement and to make decisions regarding that information.

[0264] "Location data" refers to data that includes the address and geographical information of the property where the user resides.

[0265] "Real estate market information" refers to data related to real estate transactions in a specific area, such as prices, transaction status, and past transaction history for rental properties.

[0266] "Analysis" is the process of performing calculations and evaluations based on collected data to determine market trends and appropriate rents.

[0267] A "fair price" is the rent for a rental property that is set in a reasonable and fair manner, taking into account the current market conditions.

[0268] "Evidence" refers to data and information that supports the analysis results, and is intended to be used by users as a reference when making decisions.

[0269] A "generative AI model" is a type of artificial intelligence technology that learns market trends and price tendencies from large amounts of data and uses them for analysis and prediction.

[0270] "Market trends" refer to tendencies that indicate future market changes, such as price increases or decreases in the real estate market, and changes in the supply and demand for properties.

[0271] This system works collaboratively by servers, terminals, and users to enable users to calculate appropriate rent and secure favorable terms when renewing a lease agreement.

[0272] The server accesses an external real estate market information database based on location data entered by the user through their terminal. The specific software used here is the API of a real estate information provision platform, which retrieves local rental property information, transaction status, and past transaction history.

[0273] The server utilizes a generative AI model to analyze the acquired real estate market information. Specifically, machine learning frameworks such as TensorFlow are used to predict market trends and fair prices. Based on these analysis results, the server generates a fair rent for the user and supporting documentation to justify it.

[0274] The terminal has a user interface (UI) that presents reports generated by the server to the user, displaying analysis results using visual graphics. Based on this information, the user can evaluate how fair the rent is compared to market rates and prepare for negotiations.

[0275] For example, if a user enters the prompt "Calculate the current fair rent for a 2LDK apartment in Shinjuku Ward, Tokyo," the server will use this address information to collect real estate market information and calculate the fair rent through analysis by a generated AI model. This allows the user to quickly find out the rent based on current market conditions, enabling them to negotiate more favorably when renewing their lease.

[0276] Furthermore, if a user wishes to negotiate the price, the terminal provides a function to assist with negotiations automatically or semi-automatically, and the server assists the negotiation process by supplying effective data and negotiation strategies to affiliated real estate professionals. This enables users to renew their lease agreements on better terms.

[0277] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0278] Step 1:

[0279] The user uses their device to input location data for their rental property. This location data includes the address and postal code of the residence. The device packets this data and sends it to the server via a secure protocol (HTTPS) to send it to the server. As a result, the server receives the basic data necessary to continue processing.

[0280] Step 2:

[0281] Based on the received location data, the server accesses the real estate market information database. The server uses the address information as a query parameter and obtains rental property information, transaction history, past transaction data, etc. within the region through the API. As output, the server holds the obtained real estate market information in a structured format.

[0282] Step 3:

[0283] Based on the obtained real estate market information, the server uses a generative AI model to analyze market trends and appropriate rental fees. In this process, the AI algorithm calculates market trends and average prices. The server utilizes a machine learning framework such as TensorFlow to predict appropriate rental fees through data operations. As output, a detailed report showing the analysis results is generated.

[0284] Step 4:

[0285] The terminal receives the analysis report sent from the server and displays it on the user interface. The terminal uses visually easy-to-understand graphs and charts to show the user the fluctuations in rental fees and an overview of the market. Based on this information, the user can make decisions for use when renewing the rental contract.

[0286] Step 5:

[0287] When the user wishes to negotiate the rental fee, they select negotiation support options on the interface of the terminal. Based on this selection, the server provides the necessary data and recommended negotiation strategies to the partnering real estate experts. The output includes guidelines and data for efficiently advancing the negotiation, allowing the user to negotiate a more favorable contract.

[0288] (Application Example 1)

[0289] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0290] In the unstable real estate rental market, there is a problem in that users cannot determine whether the current rent is in line with market rates and have limited means to negotiate fairly. Furthermore, it is difficult to efficiently utilize real-time rental market information.

[0291] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0292] In this invention, the server includes means for obtaining location information of the user's place of residence, means for collecting real estate market information based on the obtained location information, and means for obtaining rental information in real time based on mobile location information and visually presenting appropriate rent. This enables the user to quickly and visually confirm whether the current rent is in line with market rates and to conduct appropriate rent negotiations.

[0293] A "user" is an individual or organization that uses the system to obtain rental information for their place of residence and receives negotiation support.

[0294] "Location information of residence" refers to data that indicates the geographical location of where the user lives.

[0295] "Real estate market information" refers to a collection of data related to rental property prices, market trends, and transaction examples in a specific geographical area.

[0296] "Analysis" is the process of evaluating collected data and identifying certain patterns or trends.

[0297] "Appropriate rent" refers to a fair and appropriate rental price calculated based on collected real estate market information.

[0298] "Evidence" refers to the evidence and data used to support the results obtained through analysis.

[0299] "Automatically or semi-automatically" means that the system completes its actions with little or no user intervention, or with the system's assistance even if user intervention is present.

[0300] "Mobile location information" refers to data that shows how the location of a user or device changes over time.

[0301] "Acquiring rental information in real time" means immediately importing rental-related data into the system according to the current situation.

[0302] "Presenting visually" means showing the calculated results to the user in a visual format.

[0303] "Rent negotiation" refers to discussions between the landlord and tenant to review and adjust the terms of a lease agreement.

[0304] The system for implementing this invention provides rapid rental information for residential areas and supports users in efficiently negotiating rental rates. The following hardware and software are used to realize the system.

[0305] The server is a high-performance computer with an internet connection that receives location information from users as input data. Based on this, it accesses databases to collect real estate market information. External real estate databases and statistical APIs are used for data collection. In this process, the latest rental property information and market trends are obtained.

[0306] The collected data is analyzed on the server using an AI algorithm. The AI ​​algorithm operates using a generative AI model to calculate an appropriate rent. This calculation result is provided to the user's terminal as a report in a visually easy-to-understand format.

[0307] The user accesses this information through mobile devices such as smartphones and smart glasses. The terminal is equipped with an intuitive interface, enabling the user to easily check the results and select negotiation options for rent negotiation if necessary.

[0308] As a specific example, when a user living in Shinjuku Ward is at a certain café, they can use smart glasses to obtain real-time information on rental properties in the vicinity and check how their rent compares to the market price. By inputting a prompt sentence such as "Please tell me if the rent for my apartment is appropriate based on the rental market in Shinjuku Ward", the system immediately presents appropriate rental information.

[0309] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0310] Step 1:

[0311] The user inputs the location information of their place of residence using the terminal. The input location information is sent to the server as the basic data of the system. Based on this data, the server prepares to collect the information to be used in the next processing step.

[0312] Step 2:

[0313] The server accesses external real estate market databases and APIs to collect real estate market information based on the input location information. Based on the location information as input, data on the prices of rental properties, transaction cases, and market trends are obtained and accumulated within the system.

[0314] Step 3:

[0315] The server inputs the collected real estate market information into the AI algorithm. Using the generated AI model, this data is analyzed to calculate the corresponding rent. Through the data calculations performed here, the AI model evaluates multiple data points and predicts the appropriate rent suitable for the current market conditions.

[0316] Step 4:

[0317] The server generates a report containing the calculated appropriate rent and its rationale, and sends it to the terminal. This report is formatted to present the information visually and is designed to allow the user to easily review the results.

[0318] Step 5:

[0319] The terminal displays the report received by the user. Based on the information presented, the user can determine how fair their rent is compared to market rates. This information includes visual elements and is designed to be easily understood.

[0320] Step 6:

[0321] Users select options on their device to support rent negotiations as needed. The selected options are sent to the server, where data is shared with partner real estate professionals, and the negotiation process is supported. Based on the user's choices, a negotiation strategy is developed, providing a foundation for efficient negotiation.

[0322] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0323] This invention incorporates an emotion engine that recognizes the user's emotions into a system that calculates appropriate rent when renewing a lease agreement and provides negotiation support as needed. As a result, the user's emotional state is taken into consideration when presenting appropriate rent and facilitating negotiations, leading to smoother and more effective negotiations.

[0324] Users input the location information of their rental property into the system via their device. This provides the server with the basic information needed to collect real estate market data. Based on the location information, the server retrieves the latest market data from external real estate market databases and APIs and analyzes it using an AI algorithm. Based on the results of this analysis, an appropriate rent is calculated.

[0325] Furthermore, the emotion engine recognizes the user's emotional state in real time and adjusts the method of presenting appropriate rent based on that data. For example, for users who are feeling stressed, it can improve their ability to accept information by providing clear and reassuring explanations.

[0326] The data recognized by the emotion engine is also used in the negotiation process. The server suggests a negotiation style based on the user's emotional state and communicates this to the partner real estate agent. The agent uses this information to adjust communication and help the negotiation proceed more smoothly.

[0327] As a concrete example, consider a situation where a user is feeling anxious about a rent increase. This system uses the device's camera and microphone to recognize the user's emotional state through an emotion engine, and the server generates reassuring explanations and suggestions based on that information. Real estate agents receive guidance on the need for careful consideration during negotiations, allowing negotiations with landlords to proceed more flexibly and effectively. In this way, users can achieve fair contract terms while reducing their psychological burden.

[0328] The following describes the processing flow.

[0329] Step 1:

[0330] Users enter the location information of their rental property via their terminal. This information serves as the basic data for calculating the appropriate rent within the system.

[0331] Step 2:

[0332] The terminal sends the entered location information to the server. This initiates the data collection process.

[0333] Step 3:

[0334] Based on the location information received, the server collects rental market data for the relevant area through real estate market databases and external APIs. This data includes local rental rates and actual transaction examples.

[0335] Step 4:

[0336] The server analyzes collected market data using an AI algorithm to calculate appropriate rents for the relevant area. The AI ​​combines past market trends with the latest data to improve the accuracy of the calculation results.

[0337] Step 5:

[0338] The emotion engine acquires emotional data in real time from the user's device using the camera and microphone. This includes facial expression analysis and voice tone analysis.

[0339] Step 6:

[0340] The server analyzes the emotional data sent from the emotion engine to determine the user's emotional state. This information is used to determine the appropriate rent price.

[0341] Step 7:

[0342] The server calculates the appropriate rent and provides supporting evidence, then formats it into a report that is adjusted according to the user's emotional state and sends it to the terminal. For example, if the user is feeling anxious, the report will include additional information to provide reassurance.

[0343] Step 8:

[0344] Users can review the provided reports through their devices and choose to receive assistance with rent negotiations as needed.

[0345] Step 9:

[0346] The server receives requests for negotiation assistance and communicates negotiation strategies, which take into account the user's emotional state, to partner real estate agents.

[0347] Step 10:

[0348] Based on the information received from the server, partner agents negotiate with the landlord using a communication style that takes the user's feelings into consideration. The results are reported to the server and ultimately notified to the user.

[0349] (Example 2)

[0350] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0351] In traditional lease renewal procedures, rent offers and negotiations are often based on general market data without considering the feelings of the tenant. As a result, tenants may experience emotional distress, and negotiations may not proceed smoothly. Furthermore, negotiation support has not been personalized to the individual needs and circumstances of each tenant, and information sharing between real estate agents and tenants has been insufficient. There is a need to resolve these issues and provide more effective lease renewal and negotiation support.

[0352] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of a property from a user, means for collecting market information based on the acquired location information, means for analyzing the collected market information and calculating an appropriate rent, means for detecting the user's emotional state and adjusting the presented content according to that state, and means for proposing a negotiation strategy based on the emotional information and sharing the information with the partner intermediary. This makes it possible to present an appropriate rent that takes the user's emotions into consideration and to support an effective negotiation process.

[0353] A "user" is an individual or organization that enters information in order to renew a property lease agreement using the system.

[0354] "Property location information" refers to information indicating the location of a rental property, including, for example, the address and postal code.

[0355] "Market information" refers to data related to the real estate market, including rental rates, transaction status, and information on similar properties.

[0356] "Analysis" refers to the process of analyzing market information to calculate appropriate rent, and may involve machine learning or statistical methods.

[0357] "Emotional state" refers to the psychological state exhibited by the user, and is inferred from data collected through cameras and microphones.

[0358] "Provided information" refers to the rental information and negotiation information that the system provides to the user.

[0359] A "negotiation strategy" refers to the contract terms and negotiation methods proposed based on the user's circumstances and needs, and is shared with the intermediary.

[0360] An "intermediary" is an agent or broker involved in negotiating real estate transactions or lease agreements.

[0361] This invention is a system that takes into account the feelings of the user when renewing a lease agreement, calculates a fair rent, and effectively supports negotiations.

[0362] The user enters the location information of the rental property via their device. Once this input is complete, the server uses this information to access external databases and APIs to collect the latest real estate market information. This involves a general internet connection and, for example, APIs from local real estate information services. The server can use machine learning libraries such as TensorFlow or Scikit-learn to analyze this data with AI algorithms and calculate a fair rent for the user's rental property.

[0363] Furthermore, the emotion engine uses the camera and microphone built into the device to detect the user's emotional state in real time from their facial expressions and voice. This process utilizes computer vision libraries such as OpenCV and speech analysis technology. The server adjusts and presents information about rent and contract details according to the user's emotional state using a generative AI model. This generative AI model employs natural language processing technology and is programmed to provide explanations in reassuring language, for example, if the user is feeling stressed.

[0364] As a concrete example, suppose a user is expressing anxiety about an increase in rent. In this situation, the system uses the device's camera and microphone to recognize the user's emotional state, and the server generates and presents reassuring information based on that data. The real estate agent is then instructed to handle negotiations with greater consideration.

[0365] An example of a prompt for input to the generating AI model might be: "If a user is feeling stressed during real estate negotiations, please suggest how to explain a fair rent in a way that will reassure them." This process will reduce the user's psychological burden and enable them to renew their lease agreement more effectively.

[0366] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0367] Step 1:

[0368] The user enters the location information of the rental property on the terminal. This input transmits the information to the system. As output, location data for use by the server is generated.

[0369] Step 2:

[0370] The server uses location information received from the user to access external real estate databases and APIs to collect market information. The input is location information, and the output is market information data related to that property. This process involves data acquisition via the internet.

[0371] Step 3:

[0372] The server inputs collected market information into an AI algorithm to calculate a fair rent. The input is market information data, and the output is the calculated fair rent. In this step, data analysis is performed using libraries such as TensorFlow and Scikit-learn.

[0373] Step 4:

[0374] The device uses a camera and microphone to collect the user's facial expressions and voice, and sends them to an emotion engine. The input is the user's real-time facial expressions and voice, and the output is the recognized emotional state. In this process, emotion analysis is performed using libraries such as OpenCV.

[0375] Step 5:

[0376] The server adjusts the rent presentation method using a generative AI model based on the emotional state obtained from the emotion engine. The input is emotional state data, and the output is adjusted rent information. The server uses natural language processing to generate information that matches the user's state.

[0377] Step 6:

[0378] The server proposes negotiation strategies along with adjusted rent information and shares this information with partner real estate agents. The input is adjusted rent information and negotiation strategies, and the output is instructional information for agents. This allows agents to conduct appropriate negotiations tailored to the client's emotional state.

[0379] (Application Example 2)

[0380] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0381] In today's market, when renewing housing contracts or purchasing interior goods, insufficient fair pricing and negotiation often leave consumers feeling anxious and uncertain. In particular, information provision and negotiations that do not consider the customer's feelings can be burdensome. In such situations, there is a need for appropriate pricing calculations and negotiation support that take the customer's feelings into consideration.

[0382] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0383] In this invention, the server includes means for obtaining location information of a living space from a user, means for collecting building market data based on the obtained location information, means for analyzing the collected building market data and calculating appropriate fees, means for recognizing the user's emotional state and providing information in accordance with those emotions, and means for sensing the customer's emotions in a store and supporting individually tailored product suggestions and price negotiations. This enables smooth price negotiations and suggestions that take the user's emotions into consideration.

[0384] A "user" refers to an individual or legal entity that receives services in a living space or store through the system.

[0385] "Residential space" is a term that refers to a building or a part of a building that is primarily used for the purpose of human habitation.

[0386] "Location information" refers to data that indicates the geographical location of a specific residential space or store.

[0387] "Building market data" refers to information that includes market information and price data related to buildings in a specific region or area.

[0388] "Fair pricing" refers to pricing that is deemed fair and appropriate based on market data.

[0389] "Emotional state" refers to the psychological and emotional responses that a user exhibits to a particular situation or piece of information.

[0390] "Information presentation" refers to the act of providing users with specific data and proposals.

[0391] A "store" refers to a commercial facility where goods or services are provided.

[0392] "Product recommendation" refers to recommending suitable products or services based on consumers' interests and needs.

[0393] "Price negotiation" refers to discussions about fees that take place in order to determine the terms of a transaction.

[0394] The system for implementing this invention utilizes various hardware and software to calculate appropriate fees and provide users with emotionally relevant information. Primarily, a server and a terminal work together to acquire location information about the user's living space and collect and analyze building market data based on that information. The server uses an AI algorithm to analyze the collected data and calculate appropriate fees. This calculation may utilize, for example, an analytical tool developed in Python.

[0395] The devices are smartphones and tablets, and they are equipped with emotion recognition software called an emotion engine to recognize the user's emotional state. The emotion engine detects changes in the user's facial expressions and voice and analyzes those emotions in real time. This analysis uses input data obtained from a camera module and microphone.

[0396] When a user visits an interior design store, the system can automatically make personalized product suggestions and negotiate prices based on their emotional state. For example, if the emotion engine determines that a user is looking at a particular piece of high-end furniture with interest, the terminal will present special offers and detailed product information in a friendly manner.

[0397] For example, if a user smiles while browsing products, the system will detect this and activate a generative AI model that displays a customized message such as, "This is the item you've been waiting for! Available now at a special price." An example of a prompt would be, "Generate a description tailored to the product the user is interested in and present a special offer adjusted based on the user's emotional state."

[0398] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0399] Step 1:

[0400] The server obtains location information of the user's living space. The input is detailed address data entered by the user on their device. Based on this information, the server prepares to collect building market data. The server accesses the database using APIs as needed.

[0401] Step 2:

[0402] The server collects building market data based on acquired location information. The input here is location information, and the output is the latest market data. The server accesses external databases to collect the necessary market information. At this stage, data is obtained from multiple sources via the internet.

[0403] Step 3:

[0404] The server analyzes collected building market data and calculates appropriate pricing. The input data is collected market information, and the output is the amount of appropriate pricing. The server uses an AI algorithm to analyze the data and calculate appropriate pricing considering current market trends and historical data.

[0405] Step 4:

[0406] The device uses a camera and microphone to recognize the user's emotional state in real time. The input is data of the user's facial expressions and voice, and the output is the analyzed emotional state. An emotion engine is activated, processing the data to determine the user's emotions.

[0407] Step 5:

[0408] The server provides optimal information based on the user's emotional state. The input is emotional data analyzed by the emotion engine, and the output is customized information for the user. A generative AI model is used to generate suitable suggestions and special offers based on the prompt text.

[0409] Step 6:

[0410] The terminal presents the user with generated information and special offers. The input is customized information from the server, and the output is what is displayed on the user's screen. The terminal adjusts the display so that the presented information is visually clear and easy to understand.

[0411] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0412] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0413] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0414] [Third Embodiment]

[0415] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0416] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0417] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0418] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0419] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0420] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0421] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0422] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0423] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0424] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0425] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0426] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0427] This invention provides a system that allows users to calculate a fair rent when renewing a lease agreement and, if necessary, receive assistance in negotiations. This system primarily operates through the collaborative efforts of a server, terminals, and users.

[0428] The user first enters the location information of their rental property into the system via a terminal. This information is used as foundational data for the server to collect relevant real estate market data.

[0429] The server retrieves the latest rental market data from external real estate market databases and APIs based on location information. This includes rental property information within the area, past rental records, current transaction status, and market trends. This collected data is analyzed by an AI algorithm to predict appropriate rents that match the current market environment.

[0430] Subsequently, the server generates a report containing the calculated appropriate rent and the supporting evidence, which is then provided to the user via their terminal. Based on this information, the user can consider more favorable terms when renewing their lease agreement.

[0431] If the user requires further assistance, they can select an option on their device to have rent negotiations handled or supported. In this case, the server provides the necessary data and recommended negotiation strategies to a partner real estate agent. The agent uses this information to efficiently negotiate with the landlord, ensuring the user can renew their lease on fair terms.

[0432] For example, suppose a user who owns a rental property in Tokyo's 23 wards uses this system. Based on the address entered by the user, the server collects data on surrounding rental properties and uses AI analysis to calculate an appropriate rent that reflects past trends and current market conditions. Based on this information, the user can find out how appropriate their property's rent is compared to the market rate and, if necessary, negotiate a rent adjustment.

[0433] The following describes the processing flow.

[0434] Step 1:

[0435] The user uses a terminal to enter the location information of the rental property where they live. This information is then registered as input data in the system.

[0436] Step 2:

[0437] The terminal sends the entered location information to the server. The transmitted information also includes identification information such as the user ID.

[0438] Step 3:

[0439] Based on the location information it receives, the server collects the latest market data for the relevant area from the real estate market database and related APIs.

[0440] Step 4:

[0441] The server processes collected real estate market data using an AI algorithm, analyzing local rental rates, past transaction data, and economic indicators to calculate appropriate rent.

[0442] Step 5:

[0443] The server generates a report containing the analysis results, which include the appropriate rent and the evidence supporting its calculation. This report includes graphs and statistical data.

[0444] Step 6:

[0445] The server sends the generated report to the terminal, allowing the user to check rental information and market conditions related to their property.

[0446] Step 7:

[0447] If a user wishes to negotiate the rent, they can select the negotiation assistance option on the terminal's interface.

[0448] Step 8:

[0449] The server receives requests for negotiation assistance and provides the necessary data and recommended negotiation scenarios to partner real estate agents.

[0450] Step 9:

[0451] The partner agent uses the information provided by the server to negotiate with the landlord on behalf of the user and reports the results back to the server.

[0452] Step 10:

[0453] The server sends the negotiation results to the terminal, and the user receives guidance on new rent terms and next steps.

[0454] (Example 1)

[0455] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0456] In traditional lease renewals, it is difficult for tenants to determine and negotiate fair market rent. Market information is volatile, and collecting and analyzing the necessary data to determine a fair price in a short time is a significant burden for the average tenant. Furthermore, formulating an appropriate negotiation strategy is difficult, which can result in the risk of renewing the contract under unfavorable terms.

[0457] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0458] In this invention, the server includes means for collecting real estate market information based on acquired location data, means for analyzing the collected real estate market information and predicting appropriate prices, means for presenting the analysis results and supporting documents to the user, and means for applying a generative AI model in data analysis and predicting market trends. This enables the user to quickly and easily grasp appropriate rent and negotiation strategies and renew lease agreements on favorable terms.

[0459] A "user" is an individual or organization that uses the system to obtain information regarding the renewal of a lease agreement and to make decisions regarding that information.

[0460] "Location data" refers to data that includes the address and geographical information of the property where the user resides.

[0461] "Real estate market information" refers to data related to real estate transactions in a specific area, such as prices, transaction status, and past transaction history for rental properties.

[0462] "Analysis" is the process of performing calculations and evaluations based on collected data to determine market trends and appropriate rents.

[0463] A "fair price" is the rent for a rental property that is set in a reasonable and fair manner, taking into account the current market conditions.

[0464] "Evidence" refers to data and information that supports the analysis results, and is intended to be used by users as a reference when making decisions.

[0465] A "generative AI model" is a type of artificial intelligence technology that learns market trends and price tendencies from large amounts of data and uses them for analysis and prediction.

[0466] "Market trends" refer to tendencies that indicate future market changes, such as price increases or decreases in the real estate market, and changes in the supply and demand for properties.

[0467] This system works collaboratively by servers, terminals, and users to enable users to calculate appropriate rent and secure favorable terms when renewing a lease agreement.

[0468] The server accesses an external real estate market information database based on location data entered by the user through their terminal. The specific software used here is the API of a real estate information provision platform, which retrieves local rental property information, transaction status, and past transaction history.

[0469] The server utilizes a generative AI model to analyze the acquired real estate market information. Specifically, machine learning frameworks such as TensorFlow are used to predict market trends and fair prices. Based on these analysis results, the server generates a fair rent for the user and supporting documentation to justify it.

[0470] The terminal has a user interface (UI) that presents reports generated by the server to the user, displaying analysis results using visual graphics. Based on this information, the user can evaluate how fair the rent is compared to market rates and prepare for negotiations.

[0471] For example, if a user enters the prompt "Calculate the current fair rent for a 2LDK apartment in Shinjuku Ward, Tokyo," the server will use this address information to collect real estate market information and calculate the fair rent through analysis by a generated AI model. This allows the user to quickly find out the rent based on current market conditions, enabling them to negotiate more favorably when renewing their lease.

[0472] Furthermore, if a user wishes to negotiate the price, the terminal provides a function to assist with negotiations automatically or semi-automatically, and the server assists the negotiation process by supplying effective data and negotiation strategies to affiliated real estate professionals. This enables users to renew their lease agreements on better terms.

[0473] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0474] Step 1:

[0475] The user uses their device to input location data for their rental property. This location data includes the address and postal code of the residence. The device packets this data and sends it to the server via a secure protocol (HTTPS) to send it to the server. As a result, the server receives the basic data necessary to continue processing.

[0476] Step 2:

[0477] The server accesses a real estate market information database based on the received location data. Using address information as a query parameter, the server retrieves rental property information, transaction history, and past transaction data within the area via an API. As output, the server stores the retrieved real estate market information in a structured format.

[0478] Step 3:

[0479] The server analyzes market trends and appropriate rents using a generated AI model based on acquired real estate market information. In this process, the AI ​​algorithm calculates market trends and average prices. The server utilizes machine learning frameworks such as TensorFlow to predict appropriate rents through data computation. A detailed report showing the analysis results is generated as output.

[0480] Step 4:

[0481] The terminal receives analysis reports sent from the server and displays them in the user interface. The terminal uses visually easy-to-understand graphs and charts to show users rent fluctuations and market overviews. Based on this information, users can make decisions regarding lease renewals.

[0482] Step 5:

[0483] If a user wishes to negotiate rent, they select a negotiation support option on the terminal interface. Based on this selection, the server provides the necessary data and recommended negotiation strategies to affiliated real estate professionals. The output includes guidelines and data to efficiently conduct negotiations, allowing the user to negotiate a more favorable contract.

[0484] (Application Example 1)

[0485] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0486] In the unstable real estate rental market, there is a problem in that users cannot determine whether the current rent is in line with market rates and have limited means to negotiate fairly. Furthermore, it is difficult to efficiently utilize real-time rental market information.

[0487] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0488] In this invention, the server includes means for obtaining location information of the user's place of residence, means for collecting real estate market information based on the obtained location information, and means for obtaining rental information in real time based on mobile location information and visually presenting appropriate rent. This enables the user to quickly and visually confirm whether the current rent is in line with market rates and to conduct appropriate rent negotiations.

[0489] A "user" is an individual or organization that uses the system to obtain rental information for their place of residence and receives negotiation support.

[0490] "Location information of residence" refers to data that indicates the geographical location of where the user lives.

[0491] "Real estate market information" refers to a collection of data related to rental property prices, market trends, and transaction examples in a specific geographical area.

[0492] "Analysis" is the process of evaluating collected data and identifying certain patterns or trends.

[0493] "Appropriate rent" refers to a fair and appropriate rental price calculated based on collected real estate market information.

[0494] "Evidence" refers to the evidence and data used to support the results obtained through analysis.

[0495] "Automatically or semi-automatically" means that the system completes its actions with little or no user intervention, or with the system's assistance even if user intervention is present.

[0496] "Mobile location information" refers to data that shows how the location of a user or device changes over time.

[0497] "Acquiring rental information in real time" means immediately importing rental-related data into the system according to the current situation.

[0498] "Presenting visually" means showing the calculated results to the user in a visual format.

[0499] "Rent negotiation" refers to discussions between the landlord and tenant to review and adjust the terms of a lease agreement.

[0500] The system for implementing this invention provides rapid rental information for residential areas and supports users in efficiently negotiating rental rates. The following hardware and software are used to realize the system.

[0501] The server is a high-performance computer with an internet connection that receives location information from users as input data. Based on this, it accesses databases to collect real estate market information. External real estate databases and statistical APIs are used for data collection. In this process, the latest rental property information and market trends are obtained.

[0502] The collected data is analyzed on the server using an AI algorithm. The AI ​​algorithm operates using a generative AI model to calculate an appropriate rent. This calculation result is provided to the user's terminal as a report in a visually easy-to-understand format.

[0503] Users access this information through mobile devices such as smartphones and smart glasses. The devices feature an intuitive interface, allowing users to easily view results and, if necessary, select negotiation options for rent negotiations.

[0504] As a concrete example, a user residing in Shinjuku Ward, while at a cafe, can use smart glasses to obtain real-time information on nearby rental properties and check how their own rent compares to market rates. By prompting the user with a sentence like, "Please tell me if my apartment rent is appropriate based on the market rate in Shinjuku Ward," the system will immediately provide appropriate rent information.

[0505] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0506] Step 1:

[0507] The user enters their location information using a terminal. This entered location information is sent to the server as basic system data. Based on this data, the server prepares to collect information for use in the next processing step.

[0508] Step 2:

[0509] The server accesses external real estate market databases and APIs to collect real estate market information based on the input location data. Based on the input location data, it retrieves data on rental property prices, transaction examples, and market trends, and stores this data within the system.

[0510] Step 3:

[0511] The server inputs collected real estate market information into an AI algorithm. Using a generative AI model, this data is analyzed to calculate a suitable rent. Through this data calculation, the AI ​​model evaluates multiple data points and predicts a fair rent that is appropriate for current market conditions.

[0512] Step 4:

[0513] The server generates a report containing the calculated appropriate rent and its rationale, and sends it to the terminal. This report is formatted to present the information visually and is designed to allow the user to easily review the results.

[0514] Step 5:

[0515] The terminal displays the report received by the user. Based on the information presented, the user can determine how fair their rent is compared to market rates. This information includes visual elements and is designed to be easily understood.

[0516] Step 6:

[0517] Users select options on their device to support rent negotiations as needed. The selected options are sent to the server, where data is shared with partner real estate professionals, and the negotiation process is supported. Based on the user's choices, a negotiation strategy is developed, providing a foundation for efficient negotiation.

[0518] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0519] This invention incorporates an emotion engine that recognizes the user's emotions into a system that calculates appropriate rent when renewing a lease agreement and provides negotiation support as needed. As a result, the user's emotional state is taken into consideration when presenting appropriate rent and facilitating negotiations, leading to smoother and more effective negotiations.

[0520] Users input the location information of their rental property into the system via their device. This provides the server with the basic information needed to collect real estate market data. Based on the location information, the server retrieves the latest market data from external real estate market databases and APIs and analyzes it using an AI algorithm. Based on the results of this analysis, an appropriate rent is calculated.

[0521] Furthermore, the emotion engine recognizes the user's emotional state in real time and adjusts the method of presenting appropriate rent based on that data. For example, for users who are feeling stressed, it can improve their ability to accept information by providing clear and reassuring explanations.

[0522] The data recognized by the emotion engine is also used in the negotiation process. The server suggests a negotiation style based on the user's emotional state and communicates this to the partner real estate agent. The agent uses this information to adjust communication and help the negotiation proceed more smoothly.

[0523] As a concrete example, consider a situation where a user is feeling anxious about a rent increase. This system uses the device's camera and microphone to recognize the user's emotional state through an emotion engine, and the server generates reassuring explanations and suggestions based on that information. Real estate agents receive guidance on the need for careful consideration during negotiations, allowing negotiations with landlords to proceed more flexibly and effectively. In this way, users can achieve fair contract terms while reducing their psychological burden.

[0524] The following describes the processing flow.

[0525] Step 1:

[0526] Users enter the location information of their rental property via their terminal. This information serves as the basic data for calculating the appropriate rent within the system.

[0527] Step 2:

[0528] The terminal sends the entered location information to the server. This initiates the data collection process.

[0529] Step 3:

[0530] Based on the location information received, the server collects rental market data for the relevant area through real estate market databases and external APIs. This data includes local rental rates and actual transaction examples.

[0531] Step 4:

[0532] The server analyzes collected market data using an AI algorithm to calculate appropriate rents for the relevant area. The AI ​​combines past market trends with the latest data to improve the accuracy of the calculation results.

[0533] Step 5:

[0534] The emotion engine acquires emotional data in real time from the user's device using the camera and microphone. This includes facial expression analysis and voice tone analysis.

[0535] Step 6:

[0536] The server analyzes the emotional data sent from the emotion engine to determine the user's emotional state. This information is used to determine the appropriate rent price.

[0537] Step 7:

[0538] The server calculates the appropriate rent and provides supporting evidence, then formats it into a report that is adjusted according to the user's emotional state and sends it to the terminal. For example, if the user is feeling anxious, the report will include additional information to provide reassurance.

[0539] Step 8:

[0540] Users can review the provided reports through their devices and choose to receive assistance with rent negotiations as needed.

[0541] Step 9:

[0542] The server receives requests for negotiation assistance and communicates negotiation strategies, which take into account the user's emotional state, to partner real estate agents.

[0543] Step 10:

[0544] Based on the information received from the server, partner agents negotiate with the landlord using a communication style that takes the user's feelings into consideration. The results are reported to the server and ultimately notified to the user.

[0545] (Example 2)

[0546] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0547] In traditional lease renewal procedures, rent offers and negotiations are often based on general market data without considering the feelings of the tenant. As a result, tenants may experience emotional distress, and negotiations may not proceed smoothly. Furthermore, negotiation support has not been personalized to the individual needs and circumstances of each tenant, and information sharing between real estate agents and tenants has been insufficient. There is a need to resolve these issues and provide more effective lease renewal and negotiation support.

[0548] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of a property from a user, means for collecting market information based on the acquired location information, means for analyzing the collected market information and calculating an appropriate rent, means for detecting the user's emotional state and adjusting the presented content according to that state, and means for proposing a negotiation strategy based on the emotional information and sharing the information with the partner intermediary. This makes it possible to present an appropriate rent that takes the user's emotions into consideration and to support an effective negotiation process.

[0549] A "user" is an individual or organization that enters information in order to renew a property lease agreement using the system.

[0550] "Property location information" refers to information indicating the location of a rental property, including, for example, the address and postal code.

[0551] "Market information" refers to data related to the real estate market, including rental rates, transaction status, and information on similar properties.

[0552] "Analysis" refers to the process of analyzing market information to calculate appropriate rent, and may involve machine learning or statistical methods.

[0553] "Emotional state" refers to the psychological state exhibited by the user, and is inferred from data collected through cameras and microphones.

[0554] "Provided information" refers to the rental information and negotiation information that the system provides to the user.

[0555] A "negotiation strategy" refers to the contract terms and negotiation methods proposed based on the user's circumstances and needs, and is shared with the intermediary.

[0556] An "intermediary" is an agent or broker involved in negotiating real estate transactions or lease agreements.

[0557] This invention is a system that takes into account the feelings of the user when renewing a lease agreement, calculates a fair rent, and effectively supports negotiations.

[0558] The user enters the location information of the rental property via their device. Once this input is complete, the server uses this information to access external databases and APIs to collect the latest real estate market information. This involves a general internet connection and, for example, APIs from local real estate information services. The server can use machine learning libraries such as TensorFlow or Scikit-learn to analyze this data with AI algorithms and calculate a fair rent for the user's rental property.

[0559] Furthermore, the emotion engine uses the camera and microphone built into the device to detect the user's emotional state in real time from their facial expressions and voice. This process utilizes computer vision libraries such as OpenCV and speech analysis technology. The server adjusts and presents information about rent and contract details according to the user's emotional state using a generative AI model. This generative AI model employs natural language processing technology and is programmed to provide explanations in reassuring language, for example, if the user is feeling stressed.

[0560] As a concrete example, suppose a user is expressing anxiety about an increase in rent. In this situation, the system uses the device's camera and microphone to recognize the user's emotional state, and the server generates and presents reassuring information based on that data. The real estate agent is then instructed to handle negotiations with greater consideration.

[0561] An example of a prompt for input to the generating AI model might be: "If a user is feeling stressed during real estate negotiations, please suggest how to explain a fair rent in a way that will reassure them." This process will reduce the user's psychological burden and enable them to renew their lease agreement more effectively.

[0562] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0563] Step 1:

[0564] The user enters the location information of the rental property on the terminal. This input transmits the information to the system. As output, location data for use by the server is generated.

[0565] Step 2:

[0566] The server uses location information received from the user to access external real estate databases and APIs to collect market information. The input is location information, and the output is market information data related to that property. This process involves data acquisition via the internet.

[0567] Step 3:

[0568] The server inputs collected market information into an AI algorithm to calculate a fair rent. The input is market information data, and the output is the calculated fair rent. In this step, data analysis is performed using libraries such as TensorFlow and Scikit-learn.

[0569] Step 4:

[0570] The device uses a camera and microphone to collect the user's facial expressions and voice, and sends them to an emotion engine. The input is the user's real-time facial expressions and voice, and the output is the recognized emotional state. In this process, emotion analysis is performed using libraries such as OpenCV.

[0571] Step 5:

[0572] The server adjusts the rent presentation method using a generative AI model based on the emotional state obtained from the emotion engine. The input is emotional state data, and the output is adjusted rent information. The server uses natural language processing to generate information that matches the user's state.

[0573] Step 6:

[0574] The server proposes negotiation strategies along with adjusted rent information and shares this information with partner real estate agents. The input is adjusted rent information and negotiation strategies, and the output is instructional information for agents. This allows agents to conduct appropriate negotiations tailored to the client's emotional state.

[0575] (Application Example 2)

[0576] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0577] In today's market, when renewing housing contracts or purchasing interior goods, insufficient fair pricing and negotiation often leave consumers feeling anxious and uncertain. In particular, information provision and negotiations that do not consider the customer's feelings can be burdensome. In such situations, there is a need for appropriate pricing calculations and negotiation support that take the customer's feelings into consideration.

[0578] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0579] In this invention, the server includes means for obtaining location information of a living space from a user, means for collecting building market data based on the obtained location information, means for analyzing the collected building market data and calculating appropriate fees, means for recognizing the user's emotional state and providing information in accordance with those emotions, and means for sensing the customer's emotions in a store and supporting individually tailored product suggestions and price negotiations. This enables smooth price negotiations and suggestions that take the user's emotions into consideration.

[0580] A "user" refers to an individual or legal entity that receives services in a living space or store through the system.

[0581] "Residential space" is a term that refers to a building or a part of a building that is primarily used for the purpose of human habitation.

[0582] "Location information" refers to data that indicates the geographical location of a specific residential space or store.

[0583] "Building market data" refers to information that includes market information and price data related to buildings in a specific region or area.

[0584] "Fair pricing" refers to pricing that is deemed fair and appropriate based on market data.

[0585] "Emotional state" refers to the psychological and emotional responses that a user exhibits to a particular situation or piece of information.

[0586] "Information presentation" refers to the act of providing users with specific data and proposals.

[0587] A "store" refers to a commercial facility where goods or services are provided.

[0588] "Product recommendation" refers to recommending suitable products or services based on consumers' interests and needs.

[0589] "Price negotiation" refers to discussions about fees that take place in order to determine the terms of a transaction.

[0590] The system for implementing this invention utilizes various hardware and software to calculate appropriate fees and provide users with emotionally relevant information. Primarily, a server and a terminal work together to acquire location information about the user's living space and collect and analyze building market data based on that information. The server uses an AI algorithm to analyze the collected data and calculate appropriate fees. This calculation may utilize, for example, an analytical tool developed in Python.

[0591] The devices are smartphones and tablets, and they are equipped with emotion recognition software called an emotion engine to recognize the user's emotional state. The emotion engine detects changes in the user's facial expressions and voice and analyzes those emotions in real time. This analysis uses input data obtained from a camera module and microphone.

[0592] When a user visits an interior design store, the system can automatically make personalized product suggestions and negotiate prices based on their emotional state. For example, if the emotion engine determines that a user is looking at a particular piece of high-end furniture with interest, the terminal will present special offers and detailed product information in a friendly manner.

[0593] For example, if a user smiles while browsing products, the system will detect this and activate a generative AI model that displays a customized message such as, "This is the item you've been waiting for! Available now at a special price." An example of a prompt would be, "Generate a description tailored to the product the user is interested in and present a special offer adjusted based on the user's emotional state."

[0594] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0595] Step 1:

[0596] The server obtains location information of the user's living space. The input is detailed address data entered by the user on their device. Based on this information, the server prepares to collect building market data. The server accesses the database using APIs as needed.

[0597] Step 2:

[0598] The server collects building market data based on acquired location information. The input here is location information, and the output is the latest market data. The server accesses external databases to collect the necessary market information. At this stage, data is obtained from multiple sources via the internet.

[0599] Step 3:

[0600] The server analyzes collected building market data and calculates appropriate pricing. The input data is collected market information, and the output is the amount of appropriate pricing. The server uses an AI algorithm to analyze the data and calculate appropriate pricing considering current market trends and historical data.

[0601] Step 4:

[0602] The device uses a camera and microphone to recognize the user's emotional state in real time. The input is data of the user's facial expressions and voice, and the output is the analyzed emotional state. An emotion engine is activated, processing the data to determine the user's emotions.

[0603] Step 5:

[0604] The server provides optimal information based on the user's emotional state. The input is emotional data analyzed by the emotion engine, and the output is customized information for the user. A generative AI model is used to generate suitable suggestions and special offers based on the prompt text.

[0605] Step 6:

[0606] The terminal presents the user with generated information and special offers. The input is customized information from the server, and the output is what is displayed on the user's screen. The terminal adjusts the display so that the presented information is visually clear and easy to understand.

[0607] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0608] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0609] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0610] [Fourth Embodiment]

[0611] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0612] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0613] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0614] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0615] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0616] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0617] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0618] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0619] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0620] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0621] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0622] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0623] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0624] This invention provides a system that allows users to calculate a fair rent when renewing a lease agreement and, if necessary, receive assistance in negotiations. This system primarily operates through the collaborative efforts of a server, terminals, and users.

[0625] The user first enters the location information of their rental property into the system via a terminal. This information is used as foundational data for the server to collect relevant real estate market data.

[0626] The server retrieves the latest rental market data from external real estate market databases and APIs based on location information. This includes rental property information within the area, past rental records, current transaction status, and market trends. This collected data is analyzed by an AI algorithm to predict appropriate rents that match the current market environment.

[0627] Subsequently, the server generates a report containing the calculated appropriate rent and the supporting evidence, which is then provided to the user via their terminal. Based on this information, the user can consider more favorable terms when renewing their lease agreement.

[0628] If the user requires further assistance, they can select an option on their device to have rent negotiations handled or supported. In this case, the server provides the necessary data and recommended negotiation strategies to a partner real estate agent. The agent uses this information to efficiently negotiate with the landlord, ensuring the user can renew their lease on fair terms.

[0629] For example, suppose a user who owns a rental property in Tokyo's 23 wards uses this system. Based on the address entered by the user, the server collects data on surrounding rental properties and uses AI analysis to calculate an appropriate rent that reflects past trends and current market conditions. Based on this information, the user can find out how appropriate their property's rent is compared to the market rate and, if necessary, negotiate a rent adjustment.

[0630] The following describes the processing flow.

[0631] Step 1:

[0632] The user uses a terminal to enter the location information of the rental property where they live. This information is then registered as input data in the system.

[0633] Step 2:

[0634] The terminal sends the entered location information to the server. The transmitted information also includes identification information such as the user ID.

[0635] Step 3:

[0636] Based on the location information it receives, the server collects the latest market data for the relevant area from the real estate market database and related APIs.

[0637] Step 4:

[0638] The server processes collected real estate market data using an AI algorithm, analyzing local rental rates, past transaction data, and economic indicators to calculate appropriate rent.

[0639] Step 5:

[0640] The server generates a report containing the analysis results, which include the appropriate rent and the evidence supporting its calculation. This report includes graphs and statistical data.

[0641] Step 6:

[0642] The server sends the generated report to the terminal, allowing the user to check rental information and market conditions related to their property.

[0643] Step 7:

[0644] If a user wishes to negotiate the rent, they can select the negotiation assistance option on the terminal's interface.

[0645] Step 8:

[0646] The server receives requests for negotiation assistance and provides the necessary data and recommended negotiation scenarios to partner real estate agents.

[0647] Step 9:

[0648] The partner agent uses the information provided by the server to negotiate with the landlord on behalf of the user and reports the results back to the server.

[0649] Step 10:

[0650] The server sends the negotiation results to the terminal, and the user receives guidance on new rent terms and next steps.

[0651] (Example 1)

[0652] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0653] In traditional lease renewals, it is difficult for tenants to determine and negotiate fair market rent. Market information is volatile, and collecting and analyzing the necessary data to determine a fair price in a short time is a significant burden for the average tenant. Furthermore, formulating an appropriate negotiation strategy is difficult, which can result in the risk of renewing the contract under unfavorable terms.

[0654] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0655] In this invention, the server includes means for collecting real estate market information based on acquired location data, means for analyzing the collected real estate market information and predicting appropriate prices, means for presenting the analysis results and supporting documents to the user, and means for applying a generative AI model in data analysis and predicting market trends. This enables the user to quickly and easily grasp appropriate rent and negotiation strategies and renew lease agreements on favorable terms.

[0656] A "user" is an individual or organization that uses the system to obtain information regarding the renewal of a lease agreement and to make decisions regarding that information.

[0657] "Location data" refers to data that includes the address and geographical information of the property where the user resides.

[0658] "Real estate market information" refers to data related to real estate transactions in a specific area, such as prices, transaction status, and past transaction history for rental properties.

[0659] "Analysis" is the process of performing calculations and evaluations based on collected data to determine market trends and appropriate rents.

[0660] A "fair price" is the rent for a rental property that is set in a reasonable and fair manner, taking into account the current market conditions.

[0661] "Evidence" refers to data and information that supports the analysis results, and is intended to be used by users as a reference when making decisions.

[0662] A "generative AI model" is a type of artificial intelligence technology that learns market trends and price tendencies from large amounts of data and uses them for analysis and prediction.

[0663] "Market trends" refer to tendencies that indicate future market changes, such as price increases or decreases in the real estate market, and changes in the supply and demand for properties.

[0664] This system works collaboratively by servers, terminals, and users to enable users to calculate appropriate rent and secure favorable terms when renewing a lease agreement.

[0665] The server accesses an external real estate market information database based on location data entered by the user through their terminal. The specific software used here is the API of a real estate information provision platform, which retrieves local rental property information, transaction status, and past transaction history.

[0666] The server utilizes a generative AI model to analyze the acquired real estate market information. Specifically, machine learning frameworks such as TensorFlow are used to predict market trends and fair prices. Based on these analysis results, the server generates a fair rent for the user and supporting documentation to justify it.

[0667] The terminal has a user interface (UI) that presents reports generated by the server to the user, displaying analysis results using visual graphics. Based on this information, the user can evaluate how fair the rent is compared to market rates and prepare for negotiations.

[0668] For example, if a user enters the prompt "Calculate the current fair rent for a 2LDK apartment in Shinjuku Ward, Tokyo," the server will use this address information to collect real estate market information and calculate the fair rent through analysis by a generated AI model. This allows the user to quickly find out the rent based on current market conditions, enabling them to negotiate more favorably when renewing their lease.

[0669] Furthermore, if a user wishes to negotiate the price, the terminal provides a function to assist with negotiations automatically or semi-automatically, and the server assists the negotiation process by supplying effective data and negotiation strategies to affiliated real estate professionals. This enables users to renew their lease agreements on better terms.

[0670] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0671] Step 1:

[0672] The user uses their device to input location data for their rental property. This location data includes the address and postal code of the residence. The device packets this data and sends it to the server via a secure protocol (HTTPS) to send it to the server. As a result, the server receives the basic data necessary to continue processing.

[0673] Step 2:

[0674] The server accesses a real estate market information database based on the received location data. Using address information as a query parameter, the server retrieves rental property information, transaction history, and past transaction data within the area via an API. As output, the server stores the retrieved real estate market information in a structured format.

[0675] Step 3:

[0676] The server analyzes market trends and appropriate rents using a generated AI model based on acquired real estate market information. In this process, the AI ​​algorithm calculates market trends and average prices. The server utilizes machine learning frameworks such as TensorFlow to predict appropriate rents through data computation. A detailed report showing the analysis results is generated as output.

[0677] Step 4:

[0678] The terminal receives analysis reports sent from the server and displays them in the user interface. The terminal uses visually easy-to-understand graphs and charts to show users rent fluctuations and market overviews. Based on this information, users can make decisions regarding lease renewals.

[0679] Step 5:

[0680] If a user wishes to negotiate rent, they select a negotiation support option on the terminal interface. Based on this selection, the server provides the necessary data and recommended negotiation strategies to affiliated real estate professionals. The output includes guidelines and data to efficiently conduct negotiations, allowing the user to negotiate a more favorable contract.

[0681] (Application Example 1)

[0682] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0683] In the unstable real estate rental market, there is a problem in that users cannot determine whether the current rent is in line with market rates and have limited means to negotiate fairly. Furthermore, it is difficult to efficiently utilize real-time rental market information.

[0684] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0685] In this invention, the server includes means for obtaining location information of the user's place of residence, means for collecting real estate market information based on the obtained location information, and means for obtaining rental information in real time based on mobile location information and visually presenting appropriate rent. This enables the user to quickly and visually confirm whether the current rent is in line with market rates and to conduct appropriate rent negotiations.

[0686] A "user" is an individual or organization that uses the system to obtain rental information for their place of residence and receives negotiation support.

[0687] "Location information of residence" refers to data that indicates the geographical location of where the user lives.

[0688] "Real estate market information" refers to a collection of data related to rental property prices, market trends, and transaction examples in a specific geographical area.

[0689] "Analysis" is the process of evaluating collected data and identifying certain patterns or trends.

[0690] "Appropriate rent" refers to a fair and appropriate rental price calculated based on collected real estate market information.

[0691] "Evidence" refers to the evidence and data used to support the results obtained through analysis.

[0692] "Automatically or semi-automatically" means that the system completes its actions with little or no user intervention, or with the system's assistance even if user intervention is present.

[0693] "Mobile location information" refers to data that shows how the location of a user or device changes over time.

[0694] "Acquiring rental information in real time" means immediately importing rental-related data into the system according to the current situation.

[0695] "Presenting visually" means showing the calculated results to the user in a visual format.

[0696] "Rent negotiation" refers to discussions between the landlord and tenant to review and adjust the terms of a lease agreement.

[0697] The system for implementing this invention provides rapid rental information for residential areas and supports users in efficiently negotiating rental rates. The following hardware and software are used to realize the system.

[0698] The server is a high-performance computer with an internet connection that receives location information from users as input data. Based on this, it accesses databases to collect real estate market information. External real estate databases and statistical APIs are used for data collection. In this process, the latest rental property information and market trends are obtained.

[0699] The collected data is analyzed on the server using an AI algorithm. The AI ​​algorithm operates using a generative AI model to calculate an appropriate rent. This calculation result is provided to the user's terminal as a report in a visually easy-to-understand format.

[0700] Users access this information through mobile devices such as smartphones and smart glasses. The devices feature an intuitive interface, allowing users to easily view results and, if necessary, select negotiation options for rent negotiations.

[0701] As a concrete example, a user residing in Shinjuku Ward, while at a cafe, can use smart glasses to obtain real-time information on nearby rental properties and check how their own rent compares to market rates. By prompting the user with a sentence like, "Please tell me if my apartment rent is appropriate based on the market rate in Shinjuku Ward," the system will immediately provide appropriate rent information.

[0702] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0703] Step 1:

[0704] The user enters their location information using a terminal. This entered location information is sent to the server as basic system data. Based on this data, the server prepares to collect information for use in the next processing step.

[0705] Step 2:

[0706] The server accesses external real estate market databases and APIs to collect real estate market information based on the input location data. Based on the input location data, it retrieves data on rental property prices, transaction examples, and market trends, and stores this data within the system.

[0707] Step 3:

[0708] The server inputs collected real estate market information into an AI algorithm. Using a generative AI model, this data is analyzed to calculate a suitable rent. Through this data calculation, the AI ​​model evaluates multiple data points and predicts a fair rent that is appropriate for current market conditions.

[0709] Step 4:

[0710] The server generates a report containing the calculated appropriate rent and its rationale, and sends it to the terminal. This report is formatted to present the information visually and is designed to allow the user to easily review the results.

[0711] Step 5:

[0712] The terminal displays the report received by the user. Based on the information presented, the user can determine how fair their rent is compared to market rates. This information includes visual elements and is designed to be easily understood.

[0713] Step 6:

[0714] Users select options on their device to support rent negotiations as needed. The selected options are sent to the server, where data is shared with partner real estate professionals, and the negotiation process is supported. Based on the user's choices, a negotiation strategy is developed, providing a foundation for efficient negotiation.

[0715] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0716] This invention incorporates an emotion engine that recognizes the user's emotions into a system that calculates appropriate rent when renewing a lease agreement and provides negotiation support as needed. As a result, the user's emotional state is taken into consideration when presenting appropriate rent and facilitating negotiations, leading to smoother and more effective negotiations.

[0717] Users input the location information of their rental property into the system via their device. This provides the server with the basic information needed to collect real estate market data. Based on the location information, the server retrieves the latest market data from external real estate market databases and APIs and analyzes it using an AI algorithm. Based on the results of this analysis, an appropriate rent is calculated.

[0718] Furthermore, the emotion engine recognizes the user's emotional state in real time and adjusts the method of presenting appropriate rent based on that data. For example, for users who are feeling stressed, it can improve their ability to accept information by providing clear and reassuring explanations.

[0719] The data recognized by the emotion engine is also used in the negotiation process. The server suggests a negotiation style based on the user's emotional state and communicates this to the partner real estate agent. The agent uses this information to adjust communication and help the negotiation proceed more smoothly.

[0720] As a concrete example, consider a situation where a user is feeling anxious about a rent increase. This system uses the device's camera and microphone to recognize the user's emotional state through an emotion engine, and the server generates reassuring explanations and suggestions based on that information. Real estate agents receive guidance on the need for careful consideration during negotiations, allowing negotiations with landlords to proceed more flexibly and effectively. In this way, users can achieve fair contract terms while reducing their psychological burden.

[0721] The following describes the processing flow.

[0722] Step 1:

[0723] Users enter the location information of their rental property via their terminal. This information serves as the basic data for calculating the appropriate rent within the system.

[0724] Step 2:

[0725] The terminal sends the entered location information to the server. This initiates the data collection process.

[0726] Step 3:

[0727] Based on the location information received, the server collects rental market data for the relevant area through real estate market databases and external APIs. This data includes local rental rates and actual transaction examples.

[0728] Step 4:

[0729] The server analyzes collected market data using an AI algorithm to calculate appropriate rents for the relevant area. The AI ​​combines past market trends with the latest data to improve the accuracy of the calculation results.

[0730] Step 5:

[0731] The emotion engine acquires emotional data in real time from the user's device using the camera and microphone. This includes facial expression analysis and voice tone analysis.

[0732] Step 6:

[0733] The server analyzes the emotional data sent from the emotion engine to determine the user's emotional state. This information is used to determine the appropriate rent price.

[0734] Step 7:

[0735] The server calculates the appropriate rent and provides supporting evidence, then formats it into a report that is adjusted according to the user's emotional state and sends it to the terminal. For example, if the user is feeling anxious, the report will include additional information to provide reassurance.

[0736] Step 8:

[0737] Users can review the provided reports through their devices and choose to receive assistance with rent negotiations as needed.

[0738] Step 9:

[0739] The server receives requests for negotiation assistance and communicates negotiation strategies, which take into account the user's emotional state, to partner real estate agents.

[0740] Step 10:

[0741] Based on the information received from the server, partner agents negotiate with the landlord using a communication style that takes the user's feelings into consideration. The results are reported to the server and ultimately notified to the user.

[0742] (Example 2)

[0743] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0744] In traditional lease renewal procedures, rent offers and negotiations are often based on general market data without considering the feelings of the tenant. As a result, tenants may experience emotional distress, and negotiations may not proceed smoothly. Furthermore, negotiation support has not been personalized to the individual needs and circumstances of each tenant, and information sharing between real estate agents and tenants has been insufficient. There is a need to resolve these issues and provide more effective lease renewal and negotiation support.

[0745] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of a property from a user, means for collecting market information based on the acquired location information, means for analyzing the collected market information and calculating an appropriate rent, means for detecting the user's emotional state and adjusting the presented content according to that state, and means for proposing a negotiation strategy based on the emotional information and sharing the information with the partner intermediary. This makes it possible to present an appropriate rent that takes the user's emotions into consideration and to support an effective negotiation process.

[0746] A "user" is an individual or organization that enters information in order to renew a property lease agreement using the system.

[0747] "Property location information" refers to information indicating the location of a rental property, including, for example, the address and postal code.

[0748] "Market information" refers to data related to the real estate market, including rental rates, transaction status, and information on similar properties.

[0749] "Analysis" refers to the process of analyzing market information to calculate appropriate rent, and may involve machine learning or statistical methods.

[0750] "Emotional state" refers to the psychological state exhibited by the user, and is inferred from data collected through cameras and microphones.

[0751] "Provided information" refers to the rental information and negotiation information that the system provides to the user.

[0752] A "negotiation strategy" refers to the contract terms and negotiation methods proposed based on the user's circumstances and needs, and is shared with the intermediary.

[0753] An "intermediary" is an agent or broker involved in negotiating real estate transactions or lease agreements.

[0754] This invention is a system that takes into account the feelings of the user when renewing a lease agreement, calculates a fair rent, and effectively supports negotiations.

[0755] The user enters the location information of the rental property via their device. Once this input is complete, the server uses this information to access external databases and APIs to collect the latest real estate market information. This involves a general internet connection and, for example, APIs from local real estate information services. The server can use machine learning libraries such as TensorFlow or Scikit-learn to analyze this data with AI algorithms and calculate a fair rent for the user's rental property.

[0756] Furthermore, the emotion engine uses the camera and microphone built into the device to detect the user's emotional state in real time from their facial expressions and voice. This process utilizes computer vision libraries such as OpenCV and speech analysis technology. The server adjusts and presents information about rent and contract details according to the user's emotional state using a generative AI model. This generative AI model employs natural language processing technology and is programmed to provide explanations in reassuring language, for example, if the user is feeling stressed.

[0757] As a concrete example, suppose a user is expressing anxiety about an increase in rent. In this situation, the system uses the device's camera and microphone to recognize the user's emotional state, and the server generates and presents reassuring information based on that data. The real estate agent is then instructed to handle negotiations with greater consideration.

[0758] An example of a prompt for input to the generating AI model might be: "If a user is feeling stressed during real estate negotiations, please suggest how to explain a fair rent in a way that will reassure them." This process will reduce the user's psychological burden and enable them to renew their lease agreement more effectively.

[0759] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0760] Step 1:

[0761] The user enters the location information of the rental property on the terminal. This input transmits the information to the system. As output, location data for use by the server is generated.

[0762] Step 2:

[0763] The server uses location information received from the user to access external real estate databases and APIs to collect market information. The input is location information, and the output is market information data related to that property. This process involves data acquisition via the internet.

[0764] Step 3:

[0765] The server inputs collected market information into an AI algorithm to calculate a fair rent. The input is market information data, and the output is the calculated fair rent. In this step, data analysis is performed using libraries such as TensorFlow and Scikit-learn.

[0766] Step 4:

[0767] The device uses a camera and microphone to collect the user's facial expressions and voice, and sends them to an emotion engine. The input is the user's real-time facial expressions and voice, and the output is the recognized emotional state. In this process, emotion analysis is performed using libraries such as OpenCV.

[0768] Step 5:

[0769] The server adjusts the rent presentation method using a generative AI model based on the emotional state obtained from the emotion engine. The input is emotional state data, and the output is adjusted rent information. The server uses natural language processing to generate information that matches the user's state.

[0770] Step 6:

[0771] The server proposes negotiation strategies along with adjusted rent information and shares this information with partner real estate agents. The input is adjusted rent information and negotiation strategies, and the output is instructional information for agents. This allows agents to conduct appropriate negotiations tailored to the client's emotional state.

[0772] (Application Example 2)

[0773] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0774] In today's market, when renewing housing contracts or purchasing interior goods, insufficient fair pricing and negotiation often leave consumers feeling anxious and uncertain. In particular, information provision and negotiations that do not consider the customer's feelings can be burdensome. In such situations, there is a need for appropriate pricing calculations and negotiation support that take the customer's feelings into consideration.

[0775] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0776] In this invention, the server includes means for obtaining location information of a living space from a user, means for collecting building market data based on the obtained location information, means for analyzing the collected building market data and calculating appropriate fees, means for recognizing the user's emotional state and providing information in accordance with those emotions, and means for sensing the customer's emotions in a store and supporting individually tailored product suggestions and price negotiations. This enables smooth price negotiations and suggestions that take the user's emotions into consideration.

[0777] A "user" refers to an individual or legal entity that receives services in a living space or store through the system.

[0778] "Residential space" is a term that refers to a building or a part of a building that is primarily used for the purpose of human habitation.

[0779] "Location information" refers to data that indicates the geographical location of a specific residential space or store.

[0780] "Building market data" refers to information that includes market information and price data related to buildings in a specific region or area.

[0781] "Fair pricing" refers to pricing that is deemed fair and appropriate based on market data.

[0782] "Emotional state" refers to the psychological and emotional responses that a user exhibits to a particular situation or piece of information.

[0783] "Information presentation" refers to the act of providing users with specific data and proposals.

[0784] A "store" refers to a commercial facility where goods or services are provided.

[0785] "Product recommendation" refers to recommending suitable products or services based on consumers' interests and needs.

[0786] "Price negotiation" refers to discussions about fees that take place in order to determine the terms of a transaction.

[0787] The system for implementing this invention utilizes various hardware and software to calculate appropriate fees and provide users with emotionally relevant information. Primarily, a server and a terminal work together to acquire location information about the user's living space and collect and analyze building market data based on that information. The server uses an AI algorithm to analyze the collected data and calculate appropriate fees. This calculation may utilize, for example, an analytical tool developed in Python.

[0788] The devices are smartphones and tablets, and they are equipped with emotion recognition software called an emotion engine to recognize the user's emotional state. The emotion engine detects changes in the user's facial expressions and voice and analyzes those emotions in real time. This analysis uses input data obtained from a camera module and microphone.

[0789] When a user visits an interior design store, the system can automatically make personalized product suggestions and negotiate prices based on their emotional state. For example, if the emotion engine determines that a user is looking at a particular piece of high-end furniture with interest, the terminal will present special offers and detailed product information in a friendly manner.

[0790] For example, if a user smiles while browsing products, the system will detect this and activate a generative AI model that displays a customized message such as, "This is the item you've been waiting for! Available now at a special price." An example of a prompt would be, "Generate a description tailored to the product the user is interested in and present a special offer adjusted based on the user's emotional state."

[0791] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0792] Step 1:

[0793] The server obtains location information of the user's living space. The input is detailed address data entered by the user on their device. Based on this information, the server prepares to collect building market data. The server accesses the database using APIs as needed.

[0794] Step 2:

[0795] The server collects building market data based on acquired location information. The input here is location information, and the output is the latest market data. The server accesses external databases to collect the necessary market information. At this stage, data is obtained from multiple sources via the internet.

[0796] Step 3:

[0797] The server analyzes collected building market data and calculates appropriate pricing. The input data is collected market information, and the output is the amount of appropriate pricing. The server uses an AI algorithm to analyze the data and calculate appropriate pricing considering current market trends and historical data.

[0798] Step 4:

[0799] The device uses a camera and microphone to recognize the user's emotional state in real time. The input is data of the user's facial expressions and voice, and the output is the analyzed emotional state. An emotion engine is activated, processing the data to determine the user's emotions.

[0800] Step 5:

[0801] The server provides optimal information based on the user's emotional state. The input is emotional data analyzed by the emotion engine, and the output is customized information for the user. A generative AI model is used to generate suitable suggestions and special offers based on the prompt text.

[0802] Step 6:

[0803] The terminal presents the user with generated information and special offers. The input is customized information from the server, and the output is what is displayed on the user's screen. The terminal adjusts the display so that the presented information is visually clear and easy to understand.

[0804] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0805] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0806] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0807] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0808] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0809] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0810] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0811] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0812] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0813] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0814] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0815] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0816] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0817] 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.

[0818] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0819] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0820] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0821] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0822] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0823] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0824] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0825] The following is further disclosed regarding the embodiments described above.

[0826] (Claim 1)

[0827] A means of obtaining residential location information from users,

[0828] A means of collecting real estate market data based on acquired location information,

[0829] A method for analyzing collected real estate market data and calculating appropriate rent,

[0830] Means of providing users with analysis results and evidence,

[0831] A means of automatically or semi-automatically negotiating rent in response to user requests,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, which updates real estate market data in real time and optimizes the analysis model.

[0835] (Claim 3)

[0836] The system according to claim 1, which shares data with partner real estate agents and supports the negotiation process.

[0837] "Example 1"

[0838] (Claim 1)

[0839] A means of obtaining location data of residences from users,

[0840] A means of collecting real estate market information based on acquired location data,

[0841] A method for analyzing collected real estate market information and predicting appropriate prices,

[0842] A means of presenting analysis results and supporting documents to users,

[0843] A means of automatically or semi-automatically negotiating prices according to the user's needs,

[0844] A means of predicting market trends by applying generative AI models in data analysis,

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, which updates real estate market information in real time and optimizes the analysis algorithm.

[0848] (Claim 3)

[0849] The system according to claim 1, which shares information with collaborating real estate professionals and supports negotiation procedures.

[0850] "Application Example 1"

[0851] (Claim 1)

[0852] A means of obtaining location information of the user's place of residence,

[0853] A means of collecting real estate market information based on acquired location information,

[0854] A method for analyzing collected real estate market information and calculating appropriate rent,

[0855] Means of providing users with analysis results and supporting evidence,

[0856] A means of automatically or semi-automatically negotiating rent in response to user requests,

[0857] A means of acquiring rental information in real time based on mobile location information and visually displaying appropriate rent,

[0858] A system that includes this.

[0859] (Claim 2)

[0860] The system according to claim 1, which updates real estate market information in real time and optimizes the analysis model.

[0861] (Claim 3)

[0862] The system according to claim 1, which shares information with partner real estate professionals and supports the negotiation process.

[0863] "Example 2 of combining an emotion engine"

[0864] (Claim 1)

[0865] A means of obtaining property location information from users,

[0866] A means of collecting market information based on acquired location information,

[0867] A means of analyzing collected market information and calculating appropriate rent,

[0868] Means for providing users with analysis results and related information,

[0869] A means for detecting the user's emotional state and adjusting the presented content according to that state,

[0870] A means of proposing negotiation strategies based on emotional information and sharing information with partner intermediaries,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, which updates market information in real time and improves the analysis method.

[0874] (Claim 3)

[0875] The system according to claim 1, which shares information with partner intermediaries and supports the progress of negotiations.

[0876] "Application example 2 when combining with an emotional engine"

[0877] (Claim 1)

[0878] A means of obtaining location information of the living space from the user,

[0879] A means of collecting building market data based on acquired location information,

[0880] A method for analyzing collected building market data and calculating appropriate fees,

[0881] Means of providing users with analysis results and evidence,

[0882] A means of recognizing the emotional state of the user and presenting information in accordance with that emotion,

[0883] A means of sensing customer emotions in a store and supporting personalized product suggestions and price negotiations,

[0884] A means of automatically or semi-automatically negotiating prices in response to user requests,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, which updates building market data in real time and optimizes the analysis model.

[0888] (Claim 3)

[0889] The system according to claim 1, which shares data with partner building agents and supports the negotiation process. [Explanation of Symbols]

[0890] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining location information of the user's place of residence, A means of collecting real estate market information based on acquired location information, A method for analyzing collected real estate market information and calculating appropriate rent, Means of providing users with analysis results and supporting evidence, A means of automatically or semi-automatically negotiating rent in response to user requests, A means of acquiring rental information in real time based on mobile location information and visually displaying appropriate rent, A system that includes this.

2. The system according to claim 1, which updates real estate market information in real time and optimizes the analysis model.

3. The system according to claim 1, which shares information with partner real estate professionals and supports the negotiation process.

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