system

Abstract

We provide the system. [Solution] A means for selecting relevant information using an information selection unit based on the generated information, A means for performing registration control using the reservation management unit based on the said information, A means of using an output unit that presents selected relevant information and sets according to the conditions, A means of using mobile devices to obtain information and streamline property search and reservation, A means of providing property information to customers using a terminal device, 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 chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the real estate industry, the procedures for property management and interior viewing are complicated, which leads to problems such as delays in customer response. In a busy business environment, manual management of property information and adjustment of interior viewing schedules are required, significantly reducing efficiency. As a result, prompt customer response is hindered, which may lead to a decrease in customer satisfaction. To solve such problems, it is necessary to automate the management of property information and the procedures for interior viewing to improve business efficiency.

Means for Solving the Problems

[0005] This invention provides a means for selecting relevant information using an information selection unit based on generated information. It also includes a means for performing registration control using a reservation management unit based on that information. Furthermore, it provides a means for using an output unit that presents the selected relevant information and sets according to conditions. This realizes a support system for the real estate industry that improves operational efficiency and enables rapid customer response. In addition, it includes an evaluation unit that evaluates the proposed information based on the generated information to further improve the accuracy of the system. Furthermore, by using an automatically controlled communication means to send notifications based on specified conditions, it facilitates communication with customers and optimizes operational efficiency.

[0006] "Generated information" refers to data and information that is automatically generated from computer programs or databases.

[0007] An "information selection unit" is a component that has the function of selecting appropriate information from a large amount of input information based on specific conditions or criteria.

[0008] "Related information" refers to information that is necessary or useful in relation to a specific issue.

[0009] The "Reservation Management Department" is a component that manages reservation-related information and has functions for registering reservations and adjusting schedules.

[0010] "Registration control" refers to the procedures for managing and operating systems to ensure that new information and data are correctly recorded.

[0011] The "output unit" is a component that has the function of presenting selected information or results to the user.

[0012] The "evaluation unit" is a component that has the function of judging and evaluating the value and accuracy of the proposed information and options.

[0013] An "automatically controlled communication method" is a means that has the function of automatically transmitting information to users or other systems based on conditions set within the system.

[0014] A "notification unit" is a component that has the function of conveying important information or alerts to the user or system based on specified conditions. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

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

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

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

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

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

[0023] [First Embodiment]

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

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

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

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

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

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

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

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0036] The system based on this invention consists of a series of components including a server, terminals, and users. Its purpose is to improve the efficiency of real estate operations and expedite customer service.

[0037] The server automatically collects daily property information from real estate agents' databases and processes the generated information. This information is normalized through an AI algorithm and stored in the database as detailed information for each property. Once the property information update is complete, the information selection unit filters the conditions and extracts relevant information. The server also uses a reservation management unit to control registration for viewing appointments and scheduling adjustments.

[0038] The terminal provides an interface for users to input their desired conditions. Users can input conditions according to their preferences (e.g., region, price range, floor plan, etc.). The terminal sends these conditions to the server and receives the processing results. At this time, the output unit is used to present the selected relevant information to the user.

[0039] Users can view a list of suggested properties on their device and schedule viewings for properties that interest them. After a viewing is scheduled, the system uses the reservation management unit to adjust the available dates and times and notifies the user. This process involves notifications generated by the server's automated communication system being delivered to the user via their device.

[0040] Furthermore, the evaluation unit plays a role in optimizing the system by evaluating the accuracy of the generated information and the information suggested through user feedback. This function contributes to improving the quality of information and thus enhances the user experience. The notification unit also supports users in receiving necessary information in a timely manner by sending important updates and alerts.

[0041] In this way, the system of the present invention provides a comprehensive solution for real estate agents to efficiently manage properties and conduct viewings, and to enable smooth communication with customers.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The server accesses a database of real estate agents at a designated time each day to collect the latest property information. This information is formatted by an AI algorithm and stored on the server as detailed data.

[0045] Step 2:

[0046] The user enters their desired property criteria through the terminal's interface. These criteria include price, location, and number of rooms. The terminal then sends the entered information to the server.

[0047] Step 3:

[0048] The server uses an information selection unit to extract relevant properties based on the customer's requested criteria. The selected property information is then organized into a proposal list.

[0049] Step 4:

[0050] The terminal receives a list of suggestions sent from the server and presents the property information to the user in an easy-to-understand manner. The user can then view the list and select properties that interest them.

[0051] Step 5:

[0052] The user selects a property they are interested in and makes a viewing appointment. The user selects available dates using a calendar format and enters their desired viewing date and time into the device.

[0053] Step 6:

[0054] The server uses the reservation management unit to check the reservation for the selected date and time, and after adjusting it with the property's availability, confirms the reservation.

[0055] Step 7:

[0056] The terminal notifies the user of reservation confirmation information from the server. The notification unit delivers details and confirmation information about the viewing reservation to the user.

[0057] Step 8:

[0058] The server uses the evaluation department to collect feedback on each property as a follow-up after viewings. User evaluations are used to improve the system and further enhance the accuracy of information recommendations.

[0059] (Example 1)

[0060] 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."

[0061] In current real estate operations, data collection from diverse sources and subsequent information processing are typically done manually, hindering operational efficiency. Furthermore, it is difficult for users to quickly obtain accurate property information, potentially leading to decreased customer satisfaction. Additionally, managing reservations and improving information based on user feedback is time-consuming, hindering the overall optimization of operations.

[0062] 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.

[0063] This invention includes means for a server to automatically acquire information from an information storage device, normalize it using a processing unit, and store it in a structured data format as detailed information; means for a processing unit to filter information based on conditional information entered using an input device and select highly relevant information; and means for displaying the selected information through an output device and enabling operations according to the set conditions. This enables efficient automation of the collection, processing, and presentation of real estate information, allowing users to quickly acquire valuable information.

[0064] An "information storage device" is a computer or data storage device that has the function of temporarily or permanently storing various types of information.

[0065] A "processing unit" is a computer device used to analyze and process collected information, and it has the function of normalizing information and selecting data according to the requirements.

[0066] An "input device" is a device used by a user to transmit conditional information to a system, and usually refers to a keyboard or touch panel.

[0067] An "output device" is a device used to display processed information to the user, and includes displays, printers, and other similar devices.

[0068] A "control device" is a computer system or its components that have the function of automatically performing specific business processes, such as managing and adjusting reservations.

[0069] An "evaluation device" is a component of a system that has the function of evaluating the accuracy and usefulness of information based on user feedback.

[0070] A "communication device" is a device that automatically sends and receives data inside and outside a system, and examples include network interface cards and modems.

[0071] A "generative AI model" refers to an artificial intelligence model that has the ability to learn from large amounts of data and generate information related to a specific task.

[0072] This invention is implemented using a system that includes an information storage device, a processing unit, an input device, an output device, a control device, an evaluation device, and a communication device.

[0073] Information storage devices store various types of information related to real estate operations, and servers automatically retrieve data from these devices. Specifically, database servers, for example, are used.

[0074] The processing unit is used to normalize the acquired information. The server uses this unit to process the information and store it in a standardized data format. Software incorporating AI algorithms is used here.

[0075] An input device provides an interface used when a user enters their desired conditions into a terminal. This typically includes a keyboard or touch panel.

[0076] The output device is used to present information to the user. The terminal displays the selected information on the screen in a list format.

[0077] The control unit is a device used by the server for reservation management and scheduling. This process is carried out by a specific software module.

[0078] The evaluation device is used to assess the accuracy of the proposed information based on user feedback. This helps to improve the quality of the system.

[0079] Communication devices are used when the server automatically sends notifications to users. These notifications are sent via email or push notifications through network devices.

[0080] As a concrete example, consider a case where a user inputs the conditions "a 3LDK apartment in Tokyo, priced under 50 million yen." This information is sent to the server via an input device, which uses a processing unit to filter and extract highly relevant property information. The results are then displayed in list format by an output device. When the user selects a property and makes a viewing appointment, the control device adjusts the appointment time and notifies the user via a communication device.

[0081] An example of a prompt message could be, "Please provide me with information on 3LDK apartments in Tokyo priced under 50 million yen." This allows the user to quickly obtain information that matches their criteria.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The server automatically retrieves real estate property information from its data storage device every morning. This input data includes details such as property location, price, floor plan, and year of construction. The retrieved information is normalized using an AI algorithm and converted into a standard format. The normalized data is then stored in a database in a structured data format.

[0085] Step 2:

[0086] The terminal provides an interface for users to input the desired property criteria. These criteria include location, price range, and floor plan. The terminal sends the entered criteria to the server. The server uses a processing unit to search its database for properties that match the criteria and generates a filtered property list.

[0087] Step 3:

[0088] The server sends filtered property information to the terminal. The terminal outputs the received list for the user to view. By reviewing this list, the user can quickly find properties that meet their criteria. Specifically, the property information is displayed on the user's screen in list format.

[0089] Step 4:

[0090] The user selects a property of interest from the displayed property list and makes a viewing reservation. This action sends a reservation request to the server. The server uses a control device to check the available dates and times for the property and automatically adjusts the schedule. The adjusted date and time are sent to the terminal via a communication device to notify the user.

[0091] Step 5:

[0092] The server records the user's reservation status and notifies them when the reservation is complete. Users can check the notification on their terminal and confirm the reservation date. They can also provide feedback. This feedback is collected using an evaluation device and used to improve the accuracy of the system's information.

[0093] (Application Example 1)

[0094] 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."

[0095] The process of searching for property information and scheduling viewings in real estate is cumbersome, making it difficult for customers to quickly find properties that match their desired criteria, thus reducing operational efficiency. Furthermore, there are insufficient means of providing timely information to visitors, highlighting the need to improve the customer experience.

[0096] 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.

[0097] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for performing registration control using a reservation management unit based on said information, means for using an output unit to present the selected relevant information and set according to conditions, means for acquiring information using a mobile terminal to streamline property information search and reservation, and means for providing property information to visitors using a terminal device. This enables the rapid provision of property information and the streamlining of viewing reservations.

[0098] "Generated information" refers to detailed property information automatically collected from real estate agents' databases and normalized by an AI algorithm.

[0099] The "information selection unit" is a function that selects relevant information that matches the user's desired conditions based on the generated information.

[0100] The "Reservation Management Department" is a function that implements registration and control for making viewing reservations and scheduling adjustments.

[0101] The "output section" is a function that presents selected relevant information to the user and allows them to make settings according to the conditions.

[0102] A "mobile terminal" is a portable electronic device that allows users to search for property information and make viewing appointments.

[0103] A "terminal device" is a device used in a physical store that allows for the input and presentation of property information to customers.

[0104] To implement this invention, a system is constructed using a server, a mobile terminal, and terminal devices. The server automatically collects property information from a real estate agent's database, normalizes the information through an AI algorithm using a programming language such as Python or Node.js, and stores it in an SQL database. Next, an information selection unit selects relevant information based on the user's desired conditions, and a reservation management unit controls the registration of viewing reservations and schedules.

[0105] On mobile devices, an application developed using React Native allows users to input their desired criteria and retrieve relevant property information. Users can search for properties and schedule viewings through a simple interface. The terminals are installed in physical stores, allowing visitors to check property information and schedule viewings for their desired properties. Firebase Cloud Messaging is used to send push notifications to users during this process.

[0106] Specifically, for example, when a user enters conditions such as "Tokyo, Shibuya, 3LDK, under 30 million yen" into the app, the server displays filtered property information on the mobile device or terminal, allowing the user to make viewing reservations for properties they are interested in. This information provision and reservation function facilitates smooth real estate transactions at the store.

[0107] The generated AI model optimizes the system by utilizing user feedback and uses prompts to more effectively provide property information and schedule viewings. For example, using a prompt such as "I'm looking for a property in the Shibuya area of ​​Tokyo that meets the criteria of 3LDK and under 30 million yen. Please let me know the available dates and times for viewings," allows for the provision of accurate information to the user, improving the user experience.

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] The server automatically collects property information from real estate agents' databases. The input consists of property information stored in each real estate agent's database, which is retrieved via API using Python or Node.js. The retrieved information is stored on the server as raw data.

[0111] Step 2:

[0112] The server normalizes the collected property information using an AI algorithm. The input is the raw data collected in step 1, and by applying the AI ​​algorithm, the data format is corrected and duplicates and errors are removed. This process yields standardized property information, which is then stored in an SQL database.

[0113] Step 3:

[0114] The user opens the application on their mobile device and enters their desired criteria. These criteria (e.g., location, price range, floor plan) are then sent to the server. The application is developed using React Native, resulting in an intuitive and smooth user experience.

[0115] Step 4:

[0116] The server selects relevant information from the SQL database based on the user's desired conditions. The input is the user's conditions received in step 3, and property information that matches the conditions is extracted through a filtering process. This result is then sent to the mobile terminal as relevant information.

[0117] Step 5:

[0118] The user views property information displayed on their mobile device and selects properties of interest. The selected properties become eligible for viewing reservations, and the user specifies their preferred date and time in the app. This action sends the reservation conditions to the server.

[0119] Step 6:

[0120] The server uses the reservation management unit to adjust the available viewing dates and times based on the user's reservation conditions. The input is the desired reservation conditions in step 5, and the algorithm calculates the available slots and determines the reservation date and time.

[0121] Step 7:

[0122] The server notifies the user of the scheduled viewing appointment date and time, and also sends a push notification to their mobile device. Firebase Cloud Messaging is used to allow the user to confirm the appointment date and time. This ensures that the user receives confirmation that the appointment is complete.

[0123] Step 8:

[0124] The generative AI model collects user feedback and uses it to optimize the system. The input is user feedback, and the output is improved prompts and increased accuracy in providing property information, thereby enhancing the user experience.

[0125] 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.

[0126] The system in this invention aims to provide a more personalized user experience by centering on the interaction between a server, a terminal, and a user, and combining this with an emotion engine. In addition to the basic functions of the system, it has the ability to recognize and analyze the user's emotions and adjust output and notifications according to the situation.

[0127] In addition to collecting and processing regular property information, the server analyzes emotional data obtained from users through an emotion engine. The emotion engine includes an algorithm that automatically estimates emotions from inputs provided by the user to the terminal (e.g., tone of voice, text input content, facial recognition, etc.). This emotional data is reflected in the processing results of the information selection unit and is used to adjust the suggested properties and information.

[0128] The device functions as an interface for users to provide emotional input. For example, users input text or audio containing questions or excitement they felt during the property selection process. The device sends this to the emotion engine, which then supports analysis on the server. Based on the analysis results, the user is shown more relevant information and notifications.

[0129] Users receive a personalized experience based on their unique emotions. For example, if a user shows a positive reaction to a particular property listing, the server evaluates this emotion and recommends more properties with similar characteristics. Furthermore, by incorporating emotion data into the notification system, the server can generate follow-up notifications best suited to the user's situation. This makes the property selection and viewing process more intuitive and effective.

[0130] The implementation of this system will enable highly personalized customer interactions and improve the user experience. This is expected to play a key role in the digital transformation of the real estate industry.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] Users can express their preferences and feelings by entering text messages or voice messages via their devices when selecting properties.

[0134] Step 2:

[0135] The terminal sends the entered user information to the server and also passes it to an emotion engine for emotional data analysis. This analysis is based on factors such as the user's voice tone and word choices.

[0136] Step 3:

[0137] The server receives the analysis results from the emotion engine and sends that information to the information selection unit. This allows the server to prioritize selecting properties that are likely to interest the user.

[0138] Step 4:

[0139] The terminal displays a list of properties sent from the server to the user. Because the suggested properties are adjusted based on the user's preferences, more accurate recommendations are provided.

[0140] Step 5:

[0141] Users select properties they are interested in and schedule viewings. Their selections are sent from their device to the server.

[0142] Step 6:

[0143] The server uses the reservation management department to make adjustments, taking into account sentiment data and past selection history, to determine the optimal reservation date and time.

[0144] Step 7:

[0145] The device notifies the user of reservation confirmation information from the server. This notification is customized based on the user's sentiment data.

[0146] Step 8:

[0147] User feedback and further sentiment data are sent to the server through the evaluation department. This information is used to improve the system and make more accurate property recommendations.

[0148] (Example 2)

[0149] 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".

[0150] In modern society, there is a growing demand for systems that provide appropriate information based on users' emotions and preferences. However, currently, it is difficult to provide information that adequately meets the individual needs of users. Furthermore, information selection and notification optimization based on emotions are insufficient, and there is room to improve the user experience. Therefore, there is a need for a new system that accurately analyzes users' emotions and provides information based on them quickly and accurately.

[0151] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0152] In this invention, the server includes means for selecting relevant data using a data selection unit based on generated data, means for analyzing the user's emotions using an emotion analysis engine, and means for evaluating similarity and making recommendations using a generative AI model. This enables the provision of highly personalized information based on the user's emotions.

[0153] "Generated data" refers to information created in a specific format or method for use within a system.

[0154] The "data selection unit" refers to the functions and components used to select relevant information from the generated data.

[0155] A "reservation control unit" refers to the functions and components within a system that manage registration and scheduling.

[0156] An "output device" is hardware or software that presents selected data and provides information to the user.

[0157] An "emotion analysis engine" is an algorithm or technology that analyzes a user's emotions and utilizes the results in the system.

[0158] A "generative AI model" is an artificial intelligence model designed to generate specific results based on input data.

[0159] A "notification device" is a function or component that sends information or messages to a user.

[0160] This invention is achieved through a system based on the interaction between a server, a terminal, and a user. At the core of the system is the analysis of user emotions based on generated data, the selection of relevant data based on that analysis, and similarity evaluation and recommendations using a generative AI model.

[0161] The server uses a database to collect property and related information, and then uses an emotion analysis engine to analyze the user's emotional state based on the generated data. This utilizes a database and machine learning engine running on a typical cloud computing service. A natural language processing library is used for the analysis, and the user's input is numerically represented as an emotion score.

[0162] The terminal functions as an interface for users to provide emotional input. Users can input via voice or text through common devices such as smartphones or personal computers. This input is processed by voice recognition software installed in the terminal and sent to the server. For example, if a user voice-inputs "I like this garden," the terminal converts this to text and immediately sends it to the server.

[0163] Users can view recommended information and provide feedback. The feedback provided is analyzed again on the server and fed back into the recommendation model, enabling the provision of even more accurate information. An example of a prompt message is, "I want to find a property located in the countryside with a large garden."

[0164] Thus, by using this system, users can obtain personalized information and suggestions based on their emotions and preferences, making the real estate selection process smoother.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] Users use their devices to express their emotions and preferences through voice or text input. This input is done via smartphones or computers and is temporarily recorded by the device. The purpose of the input is to clearly communicate specific requests or emotions.

[0168] Step 2:

[0169] The device converts collected voice input into text data using speech recognition software. This text data helps improve the accuracy of sentiment analysis. By processing the input data (voice) and obtaining text data as output, it prepares for the next analysis step. Specifically, voice input is converted into text such as "I like properties with large gardens."

[0170] Step 3:

[0171] The server receives text data sent from the terminal and analyzes the data using an emotion analysis engine. This analysis process calculates an emotion score using natural language processing techniques. The input is text data, and the output is an emotion score or tagged emotion expression. For example, positive emotions are assigned a high score.

[0172] Step 4:

[0173] The server uses a generative AI model based on the sentiment analysis results to select the most suitable information for recommendations. It analyzes the received text data, performs similarity evaluations, and selects highly relevant property information. The input is the sentiment score and the user's desired conditions, and the output is a list of recommended properties.

[0174] Step 5:

[0175] The server transmits selected property information to the terminal and outputs it to the user. This output is visually presented on the user's display and is designed for more intuitive confirmation. The input is recommended property data processed on the server side, and the output is a display on the user interface. Based on this, users can provide further feedback.

[0176] This process allows users to receive more accurate real estate information based on their emotions and preferences.

[0177] (Application Example 2)

[0178] 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".

[0179] In modern society, general information and services provided by common technological systems often fail to adequately address the individual needs and emotions of users. Therefore, there is a growing demand for more personalized experiences that take users' emotions into account, thereby improving their quality of life. In particular, when providing support within the home through consumer robots, flexible services based on the user's emotional state are essential.

[0180] 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.

[0181] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for using a control device that performs reservation management based on said information, means for using an output device that presents the selected relevant information and sets according to conditions, and means for using an emotion analysis engine that recognizes the user's emotion data and adjusts the suggested content and notifications according to the situation. This enables personalized information selection and notifications that correspond to the individual user's emotions, and in particular, the suggestions and actions of consumer robots in the home become more in line with the user's psychological state.

[0182] An "information selection unit" is a device that selects and provides information relevant to the user from the generated information.

[0183] A "control device" is a device that automatically manages things like reservations and registrations based on selected information.

[0184] An "output device" is a device that presents selected information and settings to the user.

[0185] An "emotion analysis engine" is an algorithm or device that analyzes emotional data obtained from users to estimate the user's psychological state.

[0186] A "communication device" is a device that automatically sends notifications to the user based on specified conditions or sentiment analysis results.

[0187] In the system realizing this invention, the server first uses an information selection unit to select relevant information based on the generated information. The selected information is managed by a control device, and the information necessary for the user is prepared. The output device presents the selected relevant information to the user and allows them to make settings according to the situation. Furthermore, by using an emotion analysis engine, the system can recognize and analyze emotional data from the user's facial expressions and tone of voice to understand the user's psychological state.

[0188] The hardware used in this application example includes cameras and microphones for facial recognition and voice tone analysis. Specifically, Intel RealSense and Kinect cameras are used. In terms of software, an emotion analysis algorithm is built using Python in a ROS (Robot Operating System) environment, and user emotions are modeled using TENSORFLOW®. Based on the emotion data analyzed on the server side, prompt messages are sent to a generative AI model, such as OpenAI®'s GPT-4®, which then generates appropriate suggestions and notifications.

[0189] As a concrete example, a server and a robot work together to read the facial expressions of a user relaxing in the living room and suggest, "You look tired, shall we play some relaxing music?" If the user is smiling, it might say, "You seem to be in a good mood, why don't we enjoy today's beautiful weather together?" Examples of prompts for the generative AI model include, "The user has been identified as stressed. What action would you recommend?" and "If the user is showing signs of happiness, what activity would you suggest?"

[0190] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0191] Step 1:

[0192] The device captures the user's voice and facial expressions using its camera and microphone. Specifically, the camera takes a real-time photo of the user's face, and the microphone records their voice. This data is then sent as input to an emotion analysis engine.

[0193] Step 2:

[0194] The server uses an emotion analysis engine to analyze voice and facial expression data sent from the terminal. Based on the input data, a TensorFlow model running on a Python script estimates the user's emotion. The output is the user's emotion label (e.g., stress, happiness).

[0195] Step 3:

[0196] The server uses an information selection unit to select relevant information and suggestions based on the analysis results. Taking emotion labels as input, the selection algorithm determines an appropriate suggestion (e.g., playing relaxing music) and generates suggestion information as output.

[0197] Step 4:

[0198] The server sends prompt messages to the generating AI model, which then generates further actions tailored to the user's situation. Specifically, it sends the previously recorded emotion label and suggested content as prompt messages to the generating AI model, and obtains the optimal action plan as output from the model.

[0199] Step 5:

[0200] The device presents the user with suggested information received from the server and performs the corresponding action. For example, if the user is feeling stressed, it will send a voice notification saying, "We will play music to help you relax," and then play the appropriate music.

[0201] 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.

[0202] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0203] 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.

[0204] [Second Embodiment]

[0205] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0206] 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.

[0207] 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).

[0208] 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.

[0209] 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.

[0210] 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).

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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".

[0217] The system based on this invention consists of a series of components including a server, terminals, and users. Its purpose is to improve the efficiency of real estate operations and expedite customer service.

[0218] The server automatically collects daily property information from real estate agents' databases and processes the generated information. This information is normalized through an AI algorithm and stored in the database as detailed information for each property. Once the property information update is complete, the information selection unit filters the conditions and extracts relevant information. The server also uses a reservation management unit to control registration for viewing appointments and scheduling adjustments.

[0219] The terminal provides an interface for users to input their desired conditions. Users can input conditions according to their preferences (e.g., region, price range, floor plan, etc.). The terminal sends these conditions to the server and receives the processing results. At this time, the output unit is used to present the selected relevant information to the user.

[0220] Users can view a list of suggested properties on their device and schedule viewings for properties that interest them. After a viewing is scheduled, the system uses the reservation management unit to adjust the available dates and times and notifies the user. This process involves notifications generated by the server's automated communication system being delivered to the user via their device.

[0221] Furthermore, the evaluation unit plays a role in optimizing the system by evaluating the accuracy of the generated information and the information suggested through user feedback. This function contributes to improving the quality of information and thus enhances the user experience. The notification unit also supports users in receiving necessary information in a timely manner by sending important updates and alerts.

[0222] In this way, the system of the present invention provides a comprehensive solution for real estate agents to efficiently manage properties and conduct viewings, and to enable smooth communication with customers.

[0223] The following describes the processing flow.

[0224] Step 1:

[0225] The server accesses a database of real estate agents at a designated time each day to collect the latest property information. This information is formatted by an AI algorithm and stored on the server as detailed data.

[0226] Step 2:

[0227] The user enters their desired property criteria through the terminal's interface. These criteria include price, location, and number of rooms. The terminal then sends the entered information to the server.

[0228] Step 3:

[0229] The server uses an information selection unit to extract relevant properties based on the customer's requested criteria. The selected property information is then organized into a proposal list.

[0230] Step 4:

[0231] The terminal receives a list of suggestions sent from the server and presents the property information to the user in an easy-to-understand manner. The user can then view the list and select properties that interest them.

[0232] Step 5:

[0233] The user selects a property they are interested in and makes a viewing appointment. The user selects available dates using a calendar format and enters their desired viewing date and time into the device.

[0234] Step 6:

[0235] The server uses the reservation management unit to check the reservation for the selected date and time, and after adjusting it with the property's availability, confirms the reservation.

[0236] Step 7:

[0237] The terminal notifies the user of reservation confirmation information from the server. The notification unit delivers details and confirmation information about the viewing reservation to the user.

[0238] Step 8:

[0239] The server uses the evaluation department to collect feedback on each property as a follow-up after viewings. User evaluations are used to improve the system and further enhance the accuracy of information recommendations.

[0240] (Example 1)

[0241] 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."

[0242] In current real estate operations, data collection from diverse sources and subsequent information processing are typically done manually, hindering operational efficiency. Furthermore, it is difficult for users to quickly obtain accurate property information, potentially leading to decreased customer satisfaction. Additionally, managing reservations and improving information based on user feedback is time-consuming, hindering the overall optimization of operations.

[0243] 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.

[0244] This invention includes means for a server to automatically acquire information from an information storage device, normalize it using a processing unit, and store it in a structured data format as detailed information; means for a processing unit to filter information based on conditional information entered using an input device and select highly relevant information; and means for displaying the selected information through an output device and enabling operations according to the set conditions. This enables efficient automation of the collection, processing, and presentation of real estate information, allowing users to quickly acquire valuable information.

[0245] An "information storage device" is a computer or data storage device that has the function of temporarily or permanently storing various types of information.

[0246] A "processing unit" is a computer device used to analyze and process collected information, and it has the function of normalizing information and selecting data according to the requirements.

[0247] An "input device" is a device used by a user to transmit conditional information to a system, and usually refers to a keyboard or touch panel.

[0248] An "output device" is a device used to display processed information to the user, and includes displays, printers, and other similar devices.

[0249] A "control device" is a computer system or its components that have the function of automatically performing specific business processes, such as managing and adjusting reservations.

[0250] An "evaluation device" is a component of a system that has the function of evaluating the accuracy and usefulness of information based on user feedback.

[0251] A "communication device" is a device that automatically sends and receives data inside and outside a system, and examples include network interface cards and modems.

[0252] A "generative AI model" refers to an artificial intelligence model that has the ability to learn from large amounts of data and generate information related to a specific task.

[0253] This invention is implemented using a system that includes an information storage device, a processing unit, an input device, an output device, a control device, an evaluation device, and a communication device.

[0254] Information storage devices store various types of information related to real estate operations, and servers automatically retrieve data from these devices. Specifically, database servers, for example, are used.

[0255] The processing unit is used to normalize the acquired information. The server uses this unit to process the information and store it in a standardized data format. Software incorporating AI algorithms is used here.

[0256] An input device provides an interface used when a user enters their desired conditions into a terminal. This typically includes a keyboard or touch panel.

[0257] The output device is used to present information to the user. The terminal displays the selected information on the screen in a list format.

[0258] The control unit is a device used by the server for reservation management and scheduling. This process is carried out by a specific software module.

[0259] The evaluation device is used to assess the accuracy of the proposed information based on user feedback. This helps to improve the quality of the system.

[0260] Communication devices are used when the server automatically sends notifications to users. These notifications are sent via email or push notifications through network devices.

[0261] As a concrete example, consider a case where a user inputs the conditions "a 3LDK apartment in Tokyo, priced under 50 million yen." This information is sent to the server via an input device, which uses a processing unit to filter and extract highly relevant property information. The results are then displayed in list format by an output device. When the user selects a property and makes a viewing appointment, the control device adjusts the appointment time and notifies the user via a communication device.

[0262] An example of a prompt message could be, "Please provide me with information on 3LDK apartments in Tokyo priced under 50 million yen." This allows the user to quickly obtain information that matches their criteria.

[0263] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0264] Step 1:

[0265] The server automatically retrieves real estate property information from its data storage device every morning. This input data includes details such as property location, price, floor plan, and year of construction. The retrieved information is normalized using an AI algorithm and converted into a standard format. The normalized data is then stored in a database in a structured data format.

[0266] Step 2:

[0267] The terminal provides an interface for users to input the desired property criteria. These criteria include location, price range, and floor plan. The terminal sends the entered criteria to the server. The server uses a processing unit to search its database for properties that match the criteria and generates a filtered property list.

[0268] Step 3:

[0269] The server sends filtered property information to the terminal. The terminal outputs the received list for the user to view. By reviewing this list, the user can quickly find properties that meet their criteria. Specifically, the property information is displayed on the user's screen in list format.

[0270] Step 4:

[0271] The user selects a property of interest from the displayed property list and makes a viewing reservation. This action sends a reservation request to the server. The server uses a control device to check the available dates and times for the property and automatically adjusts the schedule. The adjusted date and time are sent to the terminal via a communication device to notify the user.

[0272] Step 5:

[0273] The server records the user's reservation status and notifies them when the reservation is complete. Users can check the notification on their terminal and confirm the reservation date. They can also provide feedback. This feedback is collected using an evaluation device and used to improve the accuracy of the system's information.

[0274] (Application Example 1)

[0275] 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."

[0276] The process of searching for property information and scheduling viewings in real estate is cumbersome, making it difficult for customers to quickly find properties that match their desired criteria, thus reducing operational efficiency. Furthermore, there are insufficient means of providing timely information to visitors, highlighting the need to improve the customer experience.

[0277] 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.

[0278] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for performing registration control using a reservation management unit based on said information, means for using an output unit to present the selected relevant information and set according to conditions, means for acquiring information using a mobile terminal to streamline property information search and reservation, and means for providing property information to visitors using a terminal device. This enables the rapid provision of property information and the streamlining of viewing reservations.

[0279] "Generated information" refers to detailed property information automatically collected from real estate agents' databases and normalized by an AI algorithm.

[0280] The "information selection unit" is a function that selects relevant information that matches the user's desired conditions based on the generated information.

[0281] The "Reservation Management Department" is a function that implements registration control for performing interior inspection reservations and schedule adjustments.

[0282] The "Output Department" is a function that presents selected related information to the user and makes settings according to conditions.

[0283] The "Mobile Terminal" is a portable electronic device that enables users to search for property information and make interior inspection reservations.

[0284] The "Terminal Device" is a device that can input and present property information to visitors in a physical store.

[0285] To implement this invention, a system using a server, a mobile terminal, and a terminal device is constructed. The server automatically collects property information from the real estate agent's database, normalizes the information through an AI algorithm using programming languages such as Python and Node.js, and stores it in a SQL database. Next, the information selection department selects related information based on the user's desired conditions, and the reservation management department performs registration control for interior inspection reservations and schedules.

[0286] On the mobile terminal, through an application developed using React Native, users can input their desired conditions and obtain related property information. Users can search for property information through a simple interface and make interior inspection reservations. The terminal device is installed in a physical store, allowing visitors to view property information and adjust the schedule for the desired property. At this time, Firebase Cloud Messaging is used to send push notifications to users.

[0287] Specifically, for example, when a user enters conditions such as "Tokyo, Shibuya, 3LDK, under 30 million yen" into the app, the server displays filtered property information on the mobile device or terminal, allowing the user to make viewing reservations for properties they are interested in. This information provision and reservation function facilitates smooth real estate transactions at the store.

[0288] The generated AI model optimizes the system by utilizing user feedback and uses prompts to more effectively provide property information and schedule viewings. For example, using a prompt such as "I'm looking for a property in the Shibuya area of ​​Tokyo that meets the criteria of 3LDK and under 30 million yen. Please let me know the available dates and times for viewings," allows for the provision of accurate information to the user, improving the user experience.

[0289] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0290] Step 1:

[0291] The server automatically collects property information from real estate agents' databases. The input consists of property information stored in each real estate agent's database, which is retrieved via API using Python or Node.js. The retrieved information is stored on the server as raw data.

[0292] Step 2:

[0293] The server normalizes the collected property information using an AI algorithm. The input is the raw data collected in step 1, and by applying the AI ​​algorithm, the data format is corrected and duplicates and errors are removed. This process yields standardized property information, which is then stored in an SQL database.

[0294] Step 3:

[0295] The user opens the application on their mobile device and enters their desired criteria. These criteria (e.g., location, price range, floor plan) are then sent to the server. The application is developed using React Native, resulting in an intuitive and smooth user experience.

[0296] Step 4:

[0297] The server selects relevant information from the SQL database based on the user's desired conditions. The input is the user's conditions received in step 3, and property information that matches the conditions is extracted through a filtering process. This result is then sent to the mobile terminal as relevant information.

[0298] Step 5:

[0299] The user views property information displayed on their mobile device and selects properties of interest. The selected properties become eligible for viewing reservations, and the user specifies their preferred date and time in the app. This action sends the reservation conditions to the server.

[0300] Step 6:

[0301] The server uses the reservation management unit to adjust the available viewing dates and times based on the user's reservation conditions. The input is the desired reservation conditions in step 5, and the algorithm calculates the available slots and determines the reservation date and time.

[0302] Step 7:

[0303] The server notifies the user of the scheduled viewing appointment date and time, and also sends a push notification to their mobile device. Firebase Cloud Messaging is used to allow the user to confirm the appointment date and time. This ensures that the user receives confirmation that the appointment is complete.

[0304] Step 8:

[0305] The generated AI model collects user feedback and optimizes the system using prompt sentences. The input is the user feedback, and the output is the improved prompt sentence and the enhanced accuracy of property information provision, thereby enabling an improved user experience.

[0306] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0307] The system in the present invention aims to provide a more personalized user experience by centering on the interaction among the server, the terminal, and the user and combining an emotion engine with this. In addition to the basic functions of the system, it has the ability to recognize and analyze the user's emotions and adjust the output and notifications according to the situation.

[0308] In addition to collecting and processing ordinary property information, the server analyzes the emotion data obtained from the user through the emotion engine. The emotion engine includes an algorithm that automatically estimates emotions from the input provided by the user to the terminal (e.g., tone of voice, content of text input, facial expression recognition, etc.). This emotion data is reflected in the processing results of the information selection unit and is used to adjust the proposed properties and information.

[0309] The terminal functions as an interface for the user to provide emotion input. As a specific example, the user inputs text or voice including doubts or excitement felt during the process of selecting a property. The terminal sends this to the emotion engine to support analysis on the server. Based on the analysis results, more appropriate information and notifications are displayed to the user.

[0310] Users receive a personalized experience based on their unique emotions. For example, if a user shows a positive reaction to a particular property listing, the server evaluates this emotion and recommends more properties with similar characteristics. Furthermore, by incorporating emotion data into the notification system, the server can generate follow-up notifications best suited to the user's situation. This makes the property selection and viewing process more intuitive and effective.

[0311] The implementation of this system will enable highly personalized customer interactions and improve the user experience. This is expected to play a key role in the digital transformation of the real estate industry.

[0312] The following describes the processing flow.

[0313] Step 1:

[0314] Users can express their preferences and feelings by entering text messages or voice messages via their devices when selecting properties.

[0315] Step 2:

[0316] The terminal sends the entered user information to the server and also passes it to an emotion engine for emotional data analysis. This analysis is based on factors such as the user's voice tone and word choices.

[0317] Step 3:

[0318] The server receives the analysis results from the emotion engine and sends that information to the information selection unit. This allows the server to prioritize selecting properties that are likely to interest the user.

[0319] Step 4:

[0320] The terminal displays a list of properties sent from the server to the user. Because the suggested properties are adjusted based on the user's preferences, more accurate recommendations are provided.

[0321] Step 5:

[0322] Users select properties they are interested in and schedule viewings. Their selections are sent from their device to the server.

[0323] Step 6:

[0324] The server uses the reservation management department to make adjustments, taking into account sentiment data and past selection history, to determine the optimal reservation date and time.

[0325] Step 7:

[0326] The device notifies the user of reservation confirmation information from the server. This notification is customized based on the user's sentiment data.

[0327] Step 8:

[0328] User feedback and further sentiment data are sent to the server through the evaluation department. This information is used to improve the system and make more accurate property recommendations.

[0329] (Example 2)

[0330] 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".

[0331] In modern society, there is a growing demand for systems that provide appropriate information based on users' emotions and preferences. However, currently, it is difficult to provide information that adequately meets the individual needs of users. Furthermore, information selection and notification optimization based on emotions are insufficient, and there is room to improve the user experience. Therefore, there is a need for a new system that accurately analyzes users' emotions and provides information based on them quickly and accurately.

[0332] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0333] In this invention, the server includes means for selecting relevant data using a data selection unit based on generated data, means for analyzing the user's emotions using an emotion analysis engine, and means for evaluating similarity and making recommendations using a generative AI model. This enables the provision of highly personalized information based on the user's emotions.

[0334] "Generated data" refers to information created in a specific format or method for use within a system.

[0335] The "data selection unit" refers to the functions and components used to select relevant information from the generated data.

[0336] A "reservation control unit" refers to the functions and components within a system that manage registration and scheduling.

[0337] An "output device" is hardware or software that presents selected data and provides information to the user.

[0338] An "emotion analysis engine" is an algorithm or technology that analyzes a user's emotions and utilizes the results in the system.

[0339] A "generative AI model" is an artificial intelligence model designed to generate specific results based on input data.

[0340] A "notification device" is a function or component that sends information or messages to a user.

[0341] This invention is achieved through a system based on the interaction between a server, a terminal, and a user. At the core of the system is the analysis of user emotions based on generated data, the selection of relevant data based on that analysis, and similarity evaluation and recommendations using a generative AI model.

[0342] The server uses a database to collect property and related information, and then uses an emotion analysis engine to analyze the user's emotional state based on the generated data. This utilizes a database and machine learning engine running on a typical cloud computing service. A natural language processing library is used for the analysis, and the user's input is numerically represented as an emotion score.

[0343] The terminal functions as an interface for users to provide emotional input. Users can input via voice or text through common devices such as smartphones or personal computers. This input is processed by voice recognition software installed in the terminal and sent to the server. For example, if a user voice-inputs "I like this garden," the terminal converts this to text and immediately sends it to the server.

[0344] Users can view recommended information and provide feedback. The feedback provided is analyzed again on the server and fed back into the recommendation model, enabling the provision of even more accurate information. An example of a prompt message is, "I want to find a property located in the countryside with a large garden."

[0345] Thus, by using this system, users can obtain personalized information and suggestions based on their emotions and preferences, making the real estate selection process smoother.

[0346] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0347] Step 1:

[0348] Users use their devices to express their emotions and preferences through voice or text input. This input is done via smartphones or computers and is temporarily recorded by the device. The purpose of the input is to clearly communicate specific requests or emotions.

[0349] Step 2:

[0350] The device converts collected voice input into text data using speech recognition software. This text data helps improve the accuracy of sentiment analysis. By processing the input data (voice) and obtaining text data as output, it prepares for the next analysis step. Specifically, voice input is converted into text such as "I like properties with large gardens."

[0351] Step 3:

[0352] The server receives text data sent from the terminal and analyzes the data using an emotion analysis engine. This analysis process calculates an emotion score using natural language processing techniques. The input is text data, and the output is an emotion score or tagged emotion expression. For example, positive emotions are assigned a high score.

[0353] Step 4:

[0354] The server uses a generative AI model based on the sentiment analysis results to select the most suitable information for recommendations. It analyzes the received text data, performs similarity evaluations, and selects highly relevant property information. The input is the sentiment score and the user's desired conditions, and the output is a list of recommended properties.

[0355] Step 5:

[0356] The server transmits selected property information to the terminal and outputs it to the user. This output is visually presented on the user's display and is designed for more intuitive confirmation. The input is recommended property data processed on the server side, and the output is a display on the user interface. Based on this, users can provide further feedback.

[0357] This process allows users to receive more accurate real estate information based on their emotions and preferences.

[0358] (Application Example 2)

[0359] 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 as the "terminal".

[0360] In modern society, general information and services provided by common technological systems often fail to adequately address the individual needs and emotions of users. Therefore, there is a growing demand for more personalized experiences that take users' emotions into account, thereby improving their quality of life. In particular, when providing support within the home through consumer robots, flexible services based on the user's emotional state are essential.

[0361] 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.

[0362] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for using a control device that performs reservation management based on said information, means for using an output device that presents the selected relevant information and sets according to conditions, and means for using an emotion analysis engine that recognizes the user's emotion data and adjusts the suggested content and notifications according to the situation. This enables personalized information selection and notifications that correspond to the individual user's emotions, and in particular, the suggestions and actions of consumer robots in the home become more in line with the user's psychological state.

[0363] An "information selection unit" is a device that selects and provides information relevant to the user from the generated information.

[0364] A "control device" is a device that automatically manages things like reservations and registrations based on selected information.

[0365] An "output device" is a device that presents selected information and settings to the user.

[0366] An "emotion analysis engine" is an algorithm or device that analyzes emotional data obtained from users to estimate the user's psychological state.

[0367] A "communication device" is a device that automatically sends notifications to the user based on specified conditions or sentiment analysis results.

[0368] In the system realizing this invention, the server first uses an information selection unit to select relevant information based on the generated information. The selected information is managed by a control device, and the information necessary for the user is prepared. The output device presents the selected relevant information to the user and allows them to make settings according to the situation. Furthermore, by using an emotion analysis engine, the system can recognize and analyze emotional data from the user's facial expressions and tone of voice to understand the user's psychological state.

[0369] The hardware used in this application example includes cameras and microphones for facial recognition and voice tone analysis. Specifically, Intel RealSense and Kinect cameras are used. In terms of software, an emotion analysis algorithm is built using Python in a ROS (Robot Operating System) environment, and TensorFlow is used to model the user's emotions. Based on the emotion data analyzed on the server side, prompt messages are sent to a generative AI model, such as OpenAI's GPT-4, which then generates appropriate suggestions and notifications.

[0370] As a concrete example, a server and a robot work together to read the facial expressions of a user relaxing in the living room and suggest, "You look tired, shall we play some relaxing music?" If the user is smiling, it might say, "You seem to be in a good mood, why don't we enjoy today's beautiful weather together?" Examples of prompts for the generative AI model include, "The user has been identified as stressed. What action would you recommend?" and "If the user is showing signs of happiness, what activity would you suggest?"

[0371] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0372] Step 1:

[0373] The device captures the user's voice and facial expressions using its camera and microphone. Specifically, the camera takes a real-time photo of the user's face, and the microphone records their voice. This data is then sent as input to an emotion analysis engine.

[0374] Step 2:

[0375] The server uses an emotion analysis engine to analyze voice and facial expression data sent from the terminal. Based on the input data, a TensorFlow model running on a Python script estimates the user's emotion. The output is the user's emotion label (e.g., stress, happiness).

[0376] Step 3:

[0377] The server uses an information selection unit to select relevant information and suggestions based on the analysis results. Taking emotion labels as input, the selection algorithm determines an appropriate suggestion (e.g., playing relaxing music) and generates suggestion information as output.

[0378] Step 4:

[0379] The server sends prompt messages to the generating AI model, which then generates further actions tailored to the user's situation. Specifically, it sends the previously recorded emotion label and suggested content as prompt messages to the generating AI model, and obtains the optimal action plan as output from the model.

[0380] Step 5:

[0381] The device presents the user with suggested information received from the server and performs the corresponding action. For example, if the user is feeling stressed, it will send a voice notification saying, "We will play music to help you relax," and then play the appropriate music.

[0382] 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.

[0383] 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.

[0384] 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.

[0385] [Third Embodiment]

[0386] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0387] 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.

[0388] 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).

[0389] 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.

[0390] 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.

[0391] 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).

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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.

[0396] 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.

[0397] 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".

[0398] The system based on this invention consists of a series of components including a server, terminals, and users. Its purpose is to improve the efficiency of real estate operations and expedite customer service.

[0399] The server automatically collects daily property information from real estate agents' databases and processes the generated information. This information is normalized through an AI algorithm and stored in the database as detailed information for each property. Once the property information update is complete, the information selection unit filters the conditions and extracts relevant information. The server also uses a reservation management unit to control registration for viewing appointments and scheduling adjustments.

[0400] The terminal provides an interface for users to input their desired conditions. Users can input conditions according to their preferences (e.g., region, price range, floor plan, etc.). The terminal sends these conditions to the server and receives the processing results. At this time, the output unit is used to present the selected relevant information to the user.

[0401] Users can view a list of suggested properties on their device and schedule viewings for properties that interest them. After a viewing is scheduled, the system uses the reservation management unit to adjust the available dates and times and notifies the user. This process involves notifications generated by the server's automated communication system being delivered to the user via their device.

[0402] Furthermore, the evaluation unit plays a role in optimizing the system by evaluating the accuracy of the generated information and the information suggested through user feedback. This function contributes to improving the quality of information and thus enhances the user experience. The notification unit also supports users in receiving necessary information in a timely manner by sending important updates and alerts.

[0403] In this way, the system of the present invention provides a comprehensive solution for real estate agents to efficiently manage properties and conduct viewings, and to enable smooth communication with customers.

[0404] The following describes the processing flow.

[0405] Step 1:

[0406] The server accesses a database of real estate agents at a designated time each day to collect the latest property information. This information is formatted by an AI algorithm and stored on the server as detailed data.

[0407] Step 2:

[0408] The user enters their desired property criteria through the terminal's interface. These criteria include price, location, and number of rooms. The terminal then sends the entered information to the server.

[0409] Step 3:

[0410] The server uses an information selection unit to extract relevant properties based on the customer's requested criteria. The selected property information is then organized into a proposal list.

[0411] Step 4:

[0412] The terminal receives a list of suggestions sent from the server and presents the property information to the user in an easy-to-understand manner. The user can then view the list and select properties that interest them.

[0413] Step 5:

[0414] The user selects a property they are interested in and makes a viewing appointment. The user selects available dates using a calendar format and enters their desired viewing date and time into the device.

[0415] Step 6:

[0416] The server uses the reservation management unit to check the reservation for the selected date and time, and after adjusting it with the property's availability, confirms the reservation.

[0417] Step 7:

[0418] The terminal notifies the user of reservation confirmation information from the server. The notification unit delivers details and confirmation information about the viewing reservation to the user.

[0419] Step 8:

[0420] The server uses the evaluation department to collect feedback on each property as a follow-up after viewings. User evaluations are used to improve the system and further enhance the accuracy of information recommendations.

[0421] (Example 1)

[0422] 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."

[0423] In current real estate operations, data collection from diverse sources and subsequent information processing are typically done manually, hindering operational efficiency. Furthermore, it is difficult for users to quickly obtain accurate property information, potentially leading to decreased customer satisfaction. Additionally, managing reservations and improving information based on user feedback is time-consuming, hindering the overall optimization of operations.

[0424] 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.

[0425] This invention includes means for a server to automatically acquire information from an information storage device, normalize it using a processing unit, and store it in a structured data format as detailed information; means for a processing unit to filter information based on conditional information entered using an input device and select highly relevant information; and means for displaying the selected information through an output device and enabling operations according to the set conditions. This enables efficient automation of the collection, processing, and presentation of real estate information, allowing users to quickly acquire valuable information.

[0426] An "information storage device" is a computer or data storage device that has the function of temporarily or permanently storing various types of information.

[0427] A "processing unit" is a computer device used to analyze and process collected information, and it has the function of normalizing information and selecting data according to the requirements.

[0428] An "input device" is a device used by a user to transmit conditional information to a system, and usually refers to a keyboard or touch panel.

[0429] An "output device" is a device used to display processed information to the user, and includes displays, printers, and other similar devices.

[0430] A "control device" is a computer system or its components that have the function of automatically performing specific business processes, such as managing and adjusting reservations.

[0431] An "evaluation device" is a component of a system that has the function of evaluating the accuracy and usefulness of information based on user feedback.

[0432] A "communication device" is a device that automatically sends and receives data inside and outside a system, and examples include network interface cards and modems.

[0433] A "generative AI model" refers to an artificial intelligence model that has the ability to learn from large amounts of data and generate information related to a specific task.

[0434] This invention is implemented using a system that includes an information storage device, a processing unit, an input device, an output device, a control device, an evaluation device, and a communication device.

[0435] Information storage devices store various types of information related to real estate operations, and servers automatically retrieve data from these devices. Specifically, database servers, for example, are used.

[0436] The processing unit is used to normalize the acquired information. The server uses this unit to process the information and store it in a standardized data format. Software incorporating AI algorithms is used here.

[0437] An input device provides an interface used when a user enters their desired conditions into a terminal. This typically includes a keyboard or touch panel.

[0438] The output device is used to present information to the user. The terminal displays the selected information on the screen in a list format.

[0439] The control unit is a device used by the server for reservation management and scheduling. This process is carried out by a specific software module.

[0440] The evaluation device is used to assess the accuracy of the proposed information based on user feedback. This helps to improve the quality of the system.

[0441] Communication devices are used when the server automatically sends notifications to users. These notifications are sent via email or push notifications through network devices.

[0442] As a concrete example, consider a case where a user inputs the conditions "a 3LDK apartment in Tokyo, priced under 50 million yen." This information is sent to the server via an input device, which uses a processing unit to filter and extract highly relevant property information. The results are then displayed in list format by an output device. When the user selects a property and makes a viewing appointment, the control device adjusts the appointment time and notifies the user via a communication device.

[0443] An example of a prompt message could be, "Please provide me with information on 3LDK apartments in Tokyo priced under 50 million yen." This allows the user to quickly obtain information that matches their criteria.

[0444] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0445] Step 1:

[0446] The server automatically retrieves real estate property information from its data storage device every morning. This input data includes details such as property location, price, floor plan, and year of construction. The retrieved information is normalized using an AI algorithm and converted into a standard format. The normalized data is then stored in a database in a structured data format.

[0447] Step 2:

[0448] The terminal provides an interface for users to input the desired property criteria. These criteria include location, price range, and floor plan. The terminal sends the entered criteria to the server. The server uses a processing unit to search its database for properties that match the criteria and generates a filtered property list.

[0449] Step 3:

[0450] The server sends filtered property information to the terminal. The terminal outputs the received list for the user to view. By reviewing this list, the user can quickly find properties that meet their criteria. Specifically, the property information is displayed on the user's screen in list format.

[0451] Step 4:

[0452] The user selects a property of interest from the displayed property list and makes a viewing reservation. This action sends a reservation request to the server. The server uses a control device to check the available dates and times for the property and automatically adjusts the schedule. The adjusted date and time are sent to the terminal via a communication device to notify the user.

[0453] Step 5:

[0454] The server records the user's reservation status and notifies them when the reservation is complete. Users can check the notification on their terminal and confirm the reservation date. They can also provide feedback. This feedback is collected using an evaluation device and used to improve the accuracy of the system's information.

[0455] (Application Example 1)

[0456] 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."

[0457] The process of searching for property information and scheduling viewings in real estate is cumbersome, making it difficult for customers to quickly find properties that match their desired criteria, thus reducing operational efficiency. Furthermore, there are insufficient means of providing timely information to visitors, highlighting the need to improve the customer experience.

[0458] 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.

[0459] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for performing registration control using a reservation management unit based on said information, means for using an output unit to present the selected relevant information and set according to conditions, means for acquiring information using a mobile terminal to streamline property information search and reservation, and means for providing property information to visitors using a terminal device. This enables the rapid provision of property information and the streamlining of viewing reservations.

[0460] "Generated information" refers to detailed property information automatically collected from real estate agents' databases and normalized by an AI algorithm.

[0461] The "information selection unit" is a function that selects relevant information that matches the user's desired conditions based on the generated information.

[0462] The "Reservation Management Department" is a function that implements registration and control for making viewing reservations and scheduling adjustments.

[0463] The "output section" is a function that presents selected relevant information to the user and allows them to make settings according to the conditions.

[0464] A "mobile terminal" is a portable electronic device that allows users to search for property information and make viewing appointments.

[0465] A "terminal device" is a device used in a physical store that allows for the input and presentation of property information to customers.

[0466] To implement this invention, a system is constructed using a server, a mobile terminal, and terminal devices. The server automatically collects property information from a real estate agent's database, normalizes the information through an AI algorithm using a programming language such as Python or Node.js, and stores it in an SQL database. Next, an information selection unit selects relevant information based on the user's desired conditions, and a reservation management unit controls the registration of viewing reservations and schedules.

[0467] On mobile devices, an application developed using React Native allows users to input their desired criteria and retrieve relevant property information. Users can search for properties and schedule viewings through a simple interface. The terminals are installed in physical stores, allowing visitors to check property information and schedule viewings for their desired properties. Firebase Cloud Messaging is used to send push notifications to users during this process.

[0468] Specifically, for example, when a user enters conditions such as "Tokyo, Shibuya, 3LDK, under 30 million yen" into the app, the server displays filtered property information on the mobile device or terminal, allowing the user to make viewing reservations for properties they are interested in. This information provision and reservation function facilitates smooth real estate transactions at the store.

[0469] The generated AI model optimizes the system by utilizing user feedback and uses prompts to more effectively provide property information and schedule viewings. For example, using a prompt such as "I'm looking for a property in the Shibuya area of ​​Tokyo that meets the criteria of 3LDK and under 30 million yen. Please let me know the available dates and times for viewings," allows for the provision of accurate information to the user, improving the user experience.

[0470] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0471] Step 1:

[0472] The server automatically collects property information from real estate agents' databases. The input consists of property information stored in each real estate agent's database, which is retrieved via API using Python or Node.js. The retrieved information is stored on the server as raw data.

[0473] Step 2:

[0474] The server normalizes the collected property information using an AI algorithm. The input is the raw data collected in step 1, and by applying the AI ​​algorithm, the data format is corrected and duplicates and errors are removed. This process yields standardized property information, which is then stored in an SQL database.

[0475] Step 3:

[0476] The user opens the application on their mobile device and enters their desired criteria. These criteria (e.g., location, price range, floor plan) are then sent to the server. The application is developed using React Native, resulting in an intuitive and smooth user experience.

[0477] Step 4:

[0478] The server selects relevant information from the SQL database based on the user's desired conditions. The input is the user's conditions received in step 3, and property information that matches the conditions is extracted through a filtering process. This result is then sent to the mobile terminal as relevant information.

[0479] Step 5:

[0480] The user views property information displayed on their mobile device and selects properties of interest. The selected properties become eligible for viewing reservations, and the user specifies their preferred date and time in the app. This action sends the reservation conditions to the server.

[0481] Step 6:

[0482] The server uses the reservation management unit to adjust the available viewing dates and times based on the user's reservation conditions. The input is the desired reservation conditions in step 5, and the algorithm calculates the available slots and determines the reservation date and time.

[0483] Step 7:

[0484] The server notifies the user of the scheduled viewing appointment date and time, and also sends a push notification to their mobile device. Firebase Cloud Messaging is used to allow the user to confirm the appointment date and time. This ensures that the user receives confirmation that the appointment is complete.

[0485] Step 8:

[0486] The generative AI model collects user feedback and uses it to optimize the system. The input is user feedback, and the output is improved prompts and increased accuracy in providing property information, thereby enhancing the user experience.

[0487] 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.

[0488] The system in this invention aims to provide a more personalized user experience by centering on the interaction between a server, a terminal, and a user, and combining this with an emotion engine. In addition to the basic functions of the system, it has the ability to recognize and analyze the user's emotions and adjust output and notifications according to the situation.

[0489] In addition to collecting and processing regular property information, the server analyzes emotional data obtained from users through an emotion engine. The emotion engine includes an algorithm that automatically estimates emotions from inputs provided by the user to the terminal (e.g., tone of voice, text input content, facial recognition, etc.). This emotional data is reflected in the processing results of the information selection unit and is used to adjust the suggested properties and information.

[0490] The device functions as an interface for users to provide emotional input. For example, users input text or audio containing questions or excitement they felt during the property selection process. The device sends this to the emotion engine, which then supports analysis on the server. Based on the analysis results, the user is shown more relevant information and notifications.

[0491] Users receive a personalized experience based on their unique emotions. For example, if a user shows a positive reaction to a particular property listing, the server evaluates this emotion and recommends more properties with similar characteristics. Furthermore, by incorporating emotion data into the notification system, the server can generate follow-up notifications best suited to the user's situation. This makes the property selection and viewing process more intuitive and effective.

[0492] The implementation of this system will enable highly personalized customer interactions and improve the user experience. This is expected to play a key role in the digital transformation of the real estate industry.

[0493] The following describes the processing flow.

[0494] Step 1:

[0495] Users can express their preferences and feelings by entering text messages or voice messages via their devices when selecting properties.

[0496] Step 2:

[0497] The terminal sends the entered user information to the server and also passes it to an emotion engine for emotional data analysis. This analysis is based on factors such as the user's voice tone and word choices.

[0498] Step 3:

[0499] The server receives the analysis results from the emotion engine and sends that information to the information selection unit. This allows the server to prioritize selecting properties that are likely to interest the user.

[0500] Step 4:

[0501] The terminal displays a list of properties sent from the server to the user. Because the suggested properties are adjusted based on the user's preferences, more accurate recommendations are provided.

[0502] Step 5:

[0503] Users select properties they are interested in and schedule viewings. Their selections are sent from their device to the server.

[0504] Step 6:

[0505] The server uses the reservation management department to make adjustments, taking into account sentiment data and past selection history, to determine the optimal reservation date and time.

[0506] Step 7:

[0507] The device notifies the user of reservation confirmation information from the server. This notification is customized based on the user's sentiment data.

[0508] Step 8:

[0509] User feedback and further sentiment data are sent to the server through the evaluation department. This information is used to improve the system and make more accurate property recommendations.

[0510] (Example 2)

[0511] 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."

[0512] In modern society, there is a growing demand for systems that provide appropriate information based on users' emotions and preferences. However, currently, it is difficult to provide information that adequately meets the individual needs of users. Furthermore, information selection and notification optimization based on emotions are insufficient, and there is room to improve the user experience. Therefore, there is a need for a new system that accurately analyzes users' emotions and provides information based on them quickly and accurately.

[0513] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0514] In this invention, the server includes means for selecting relevant data using a data selection unit based on generated data, means for analyzing the user's emotions using an emotion analysis engine, and means for evaluating similarity and making recommendations using a generative AI model. This enables the provision of highly personalized information based on the user's emotions.

[0515] "Generated data" refers to information created in a specific format or method for use within a system.

[0516] The "data selection unit" refers to the functions and components used to select relevant information from the generated data.

[0517] A "reservation control unit" refers to the functions and components within a system that manage registration and scheduling.

[0518] An "output device" is hardware or software that presents selected data and provides information to the user.

[0519] An "emotion analysis engine" is an algorithm or technology that analyzes a user's emotions and utilizes the results in the system.

[0520] A "generative AI model" is an artificial intelligence model designed to generate specific results based on input data.

[0521] A "notification device" is a function or component that sends information or messages to a user.

[0522] This invention is achieved through a system based on the interaction between a server, a terminal, and a user. At the core of the system is the analysis of user emotions based on generated data, the selection of relevant data based on that analysis, and similarity evaluation and recommendations using a generative AI model.

[0523] The server uses a database to collect property and related information, and then uses an emotion analysis engine to analyze the user's emotional state based on the generated data. This utilizes a database and machine learning engine running on a typical cloud computing service. A natural language processing library is used for the analysis, and the user's input is numerically represented as an emotion score.

[0524] The terminal functions as an interface for users to provide emotional input. Users can input via voice or text through common devices such as smartphones or personal computers. This input is processed by voice recognition software installed in the terminal and sent to the server. For example, if a user voice-inputs "I like this garden," the terminal converts this to text and immediately sends it to the server.

[0525] Users can view recommended information and provide feedback. The feedback provided is analyzed again on the server and fed back into the recommendation model, enabling the provision of even more accurate information. An example of a prompt message is, "I want to find a property located in the countryside with a large garden."

[0526] Thus, by using this system, users can obtain personalized information and suggestions based on their emotions and preferences, making the real estate selection process smoother.

[0527] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0528] Step 1:

[0529] Users use their devices to express their emotions and preferences through voice or text input. This input is done via smartphones or computers and is temporarily recorded by the device. The purpose of the input is to clearly communicate specific requests or emotions.

[0530] Step 2:

[0531] The device converts collected voice input into text data using speech recognition software. This text data helps improve the accuracy of sentiment analysis. By processing the input data (voice) and obtaining text data as output, it prepares for the next analysis step. Specifically, voice input is converted into text such as "I like properties with large gardens."

[0532] Step 3:

[0533] The server receives text data sent from the terminal and analyzes the data using an emotion analysis engine. This analysis process calculates an emotion score using natural language processing techniques. The input is text data, and the output is an emotion score or tagged emotion expression. For example, positive emotions are assigned a high score.

[0534] Step 4:

[0535] The server uses a generative AI model based on the sentiment analysis results to select the most suitable information for recommendations. It analyzes the received text data, performs similarity evaluations, and selects highly relevant property information. The input is the sentiment score and the user's desired conditions, and the output is a list of recommended properties.

[0536] Step 5:

[0537] The server transmits selected property information to the terminal and outputs it to the user. This output is visually presented on the user's display and is designed for more intuitive confirmation. The input is recommended property data processed on the server side, and the output is a display on the user interface. Based on this, users can provide further feedback.

[0538] This process allows users to receive more accurate real estate information based on their emotions and preferences.

[0539] (Application Example 2)

[0540] 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."

[0541] In modern society, general information and services provided by common technological systems often fail to adequately address the individual needs and emotions of users. Therefore, there is a growing demand for more personalized experiences that take users' emotions into account, thereby improving their quality of life. In particular, when providing support within the home through consumer robots, flexible services based on the user's emotional state are essential.

[0542] 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.

[0543] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for using a control device that performs reservation management based on said information, means for using an output device that presents the selected relevant information and sets according to conditions, and means for using an emotion analysis engine that recognizes the user's emotion data and adjusts the suggested content and notifications according to the situation. This enables personalized information selection and notifications that correspond to the individual user's emotions, and in particular, the suggestions and actions of consumer robots in the home become more in line with the user's psychological state.

[0544] An "information selection unit" is a device that selects and provides information relevant to the user from the generated information.

[0545] A "control device" is a device that automatically manages things like reservations and registrations based on selected information.

[0546] An "output device" is a device that presents selected information and settings to the user.

[0547] An "emotion analysis engine" is an algorithm or device that analyzes emotional data obtained from users to estimate the user's psychological state.

[0548] A "communication device" is a device that automatically sends notifications to the user based on specified conditions or sentiment analysis results.

[0549] In the system realizing this invention, the server first uses an information selection unit to select relevant information based on the generated information. The selected information is managed by a control device, and the information necessary for the user is prepared. The output device presents the selected relevant information to the user and allows them to make settings according to the situation. Furthermore, by using an emotion analysis engine, the system can recognize and analyze emotional data from the user's facial expressions and tone of voice to understand the user's psychological state.

[0550] The hardware used in this application example includes cameras and microphones for facial recognition and voice tone analysis. Specifically, Intel RealSense and Kinect cameras are used. In terms of software, an emotion analysis algorithm is built using Python in a ROS (Robot Operating System) environment, and TensorFlow is used to model the user's emotions. Based on the emotion data analyzed on the server side, prompt messages are sent to a generative AI model, such as OpenAI's GPT-4, which then generates appropriate suggestions and notifications.

[0551] As a concrete example, a server and a robot work together to read the facial expressions of a user relaxing in the living room and suggest, "You look tired, shall we play some relaxing music?" If the user is smiling, it might say, "You seem to be in a good mood, why don't we enjoy today's beautiful weather together?" Examples of prompts for the generative AI model include, "The user has been identified as stressed. What action would you recommend?" and "If the user is showing signs of happiness, what activity would you suggest?"

[0552] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0553] Step 1:

[0554] The device captures the user's voice and facial expressions using its camera and microphone. Specifically, the camera takes a real-time photo of the user's face, and the microphone records their voice. This data is then sent as input to an emotion analysis engine.

[0555] Step 2:

[0556] The server uses an emotion analysis engine to analyze voice and facial expression data sent from the terminal. Based on the input data, a TensorFlow model running on a Python script estimates the user's emotion. The output is the user's emotion label (e.g., stress, happiness).

[0557] Step 3:

[0558] The server uses an information selection unit to select relevant information and suggestions based on the analysis results. Taking emotion labels as input, the selection algorithm determines an appropriate suggestion (e.g., playing relaxing music) and generates suggestion information as output.

[0559] Step 4:

[0560] The server sends prompt messages to the generating AI model, which then generates further actions tailored to the user's situation. Specifically, it sends the previously recorded emotion label and suggested content as prompt messages to the generating AI model, and obtains the optimal action plan as output from the model.

[0561] Step 5:

[0562] The device presents the user with suggested information received from the server and performs the corresponding action. For example, if the user is feeling stressed, it will send a voice notification saying, "We will play music to help you relax," and then play the appropriate music.

[0563] 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.

[0564] 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.

[0565] 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.

[0566] [Fourth Embodiment]

[0567] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0568] 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.

[0569] 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).

[0570] 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.

[0571] 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.

[0572] 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).

[0573] 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.

[0574] 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.

[0575] 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.

[0576] 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.

[0577] 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.

[0578] 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.

[0579] 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".

[0580] The system based on this invention consists of a series of components including a server, terminals, and users. Its purpose is to improve the efficiency of real estate operations and expedite customer service.

[0581] The server automatically collects daily property information from real estate agents' databases and processes the generated information. This information is normalized through an AI algorithm and stored in the database as detailed information for each property. Once the property information update is complete, the information selection unit filters the conditions and extracts relevant information. The server also uses a reservation management unit to control registration for viewing appointments and scheduling adjustments.

[0582] The terminal provides an interface for users to input their desired conditions. Users can input conditions according to their preferences (e.g., region, price range, floor plan, etc.). The terminal sends these conditions to the server and receives the processing results. At this time, the output unit is used to present the selected relevant information to the user.

[0583] Users can view a list of suggested properties on their device and schedule viewings for properties that interest them. After a viewing is scheduled, the system uses the reservation management unit to adjust the available dates and times and notifies the user. This process involves notifications generated by the server's automated communication system being delivered to the user via their device.

[0584] Furthermore, the evaluation unit plays a role in optimizing the system by evaluating the accuracy of the generated information and the information suggested through user feedback. This function contributes to improving the quality of information and thus enhances the user experience. The notification unit also supports users in receiving necessary information in a timely manner by sending important updates and alerts.

[0585] In this way, the system of the present invention provides a comprehensive solution for real estate agents to efficiently manage properties and conduct viewings, and to enable smooth communication with customers.

[0586] The following describes the processing flow.

[0587] Step 1:

[0588] The server accesses a database of real estate agents at a designated time each day to collect the latest property information. This information is formatted by an AI algorithm and stored on the server as detailed data.

[0589] Step 2:

[0590] The user enters their desired property criteria through the terminal's interface. These criteria include price, location, and number of rooms. The terminal then sends the entered information to the server.

[0591] Step 3:

[0592] The server uses an information selection unit to extract relevant properties based on the customer's requested criteria. The selected property information is then organized into a proposal list.

[0593] Step 4:

[0594] The terminal receives a list of suggestions sent from the server and presents the property information to the user in an easy-to-understand manner. The user can then view the list and select properties that interest them.

[0595] Step 5:

[0596] The user selects a property they are interested in and makes a viewing appointment. The user selects available dates using a calendar format and enters their desired viewing date and time into the device.

[0597] Step 6:

[0598] The server uses the reservation management unit to check the reservation for the selected date and time, and after adjusting it with the property's availability, confirms the reservation.

[0599] Step 7:

[0600] The terminal notifies the user of reservation confirmation information from the server. The notification unit delivers details and confirmation information about the viewing reservation to the user.

[0601] Step 8:

[0602] The server uses the evaluation department to collect feedback on each property as a follow-up after viewings. User evaluations are used to improve the system and further enhance the accuracy of information recommendations.

[0603] (Example 1)

[0604] 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".

[0605] In current real estate operations, data collection from diverse sources and subsequent information processing are typically done manually, hindering operational efficiency. Furthermore, it is difficult for users to quickly obtain accurate property information, potentially leading to decreased customer satisfaction. Additionally, managing reservations and improving information based on user feedback is time-consuming, hindering the overall optimization of operations.

[0606] 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.

[0607] This invention includes means for a server to automatically acquire information from an information storage device, normalize it using a processing unit, and store it in a structured data format as detailed information; means for a processing unit to filter information based on conditional information entered using an input device and select highly relevant information; and means for displaying the selected information through an output device and enabling operations according to the set conditions. This enables efficient automation of the collection, processing, and presentation of real estate information, allowing users to quickly acquire valuable information.

[0608] An "information storage device" is a computer or data storage device that has the function of temporarily or permanently storing various types of information.

[0609] A "processing unit" is a computer device used to analyze and process collected information, and it has the function of normalizing information and selecting data according to the requirements.

[0610] An "input device" is a device used by a user to transmit conditional information to a system, and usually refers to a keyboard or touch panel.

[0611] An "output device" is a device used to display processed information to the user, and includes displays, printers, and other similar devices.

[0612] A "control device" is a computer system or its components that have the function of automatically performing specific business processes, such as managing and adjusting reservations.

[0613] An "evaluation device" is a component of a system that has the function of evaluating the accuracy and usefulness of information based on user feedback.

[0614] A "communication device" is a device that automatically sends and receives data inside and outside a system, and examples include network interface cards and modems.

[0615] A "generative AI model" refers to an artificial intelligence model that has the ability to learn from large amounts of data and generate information related to a specific task.

[0616] This invention is implemented using a system that includes an information storage device, a processing unit, an input device, an output device, a control device, an evaluation device, and a communication device.

[0617] Information storage devices store various types of information related to real estate operations, and servers automatically retrieve data from these devices. Specifically, database servers, for example, are used.

[0618] The processing unit is used to normalize the acquired information. The server uses this unit to process the information and store it in a standardized data format. Software incorporating AI algorithms is used here.

[0619] An input device provides an interface used when a user enters their desired conditions into a terminal. This typically includes a keyboard or touch panel.

[0620] The output device is used to present information to the user. The terminal displays the selected information on the screen in a list format.

[0621] The control unit is a device used by the server for reservation management and scheduling. This process is carried out by a specific software module.

[0622] The evaluation device is used to assess the accuracy of the proposed information based on user feedback. This helps to improve the quality of the system.

[0623] Communication devices are used when the server automatically sends notifications to users. These notifications are sent via email or push notifications through network devices.

[0624] As a concrete example, consider a case where a user inputs the conditions "a 3LDK apartment in Tokyo, priced under 50 million yen." This information is sent to the server via an input device, which uses a processing unit to filter and extract highly relevant property information. The results are then displayed in list format by an output device. When the user selects a property and makes a viewing appointment, the control device adjusts the appointment time and notifies the user via a communication device.

[0625] An example of a prompt message could be, "Please provide me with information on 3LDK apartments in Tokyo priced under 50 million yen." This allows the user to quickly obtain information that matches their criteria.

[0626] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0627] Step 1:

[0628] The server automatically retrieves real estate property information from its data storage device every morning. This input data includes details such as property location, price, floor plan, and year of construction. The retrieved information is normalized using an AI algorithm and converted into a standard format. The normalized data is then stored in a database in a structured data format.

[0629] Step 2:

[0630] The terminal provides an interface for users to input the desired property criteria. These criteria include location, price range, and floor plan. The terminal sends the entered criteria to the server. The server uses a processing unit to search its database for properties that match the criteria and generates a filtered property list.

[0631] Step 3:

[0632] The server sends filtered property information to the terminal. The terminal outputs the received list for the user to view. By reviewing this list, the user can quickly find properties that meet their criteria. Specifically, the property information is displayed on the user's screen in list format.

[0633] Step 4:

[0634] The user selects a property of interest from the displayed property list and makes a viewing reservation. This action sends a reservation request to the server. The server uses a control device to check the available dates and times for the property and automatically adjusts the schedule. The adjusted date and time are sent to the terminal via a communication device to notify the user.

[0635] Step 5:

[0636] The server records the user's reservation status and notifies them when the reservation is complete. Users can check the notification on their terminal and confirm the reservation date. They can also provide feedback. This feedback is collected using an evaluation device and used to improve the accuracy of the system's information.

[0637] (Application Example 1)

[0638] 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".

[0639] The process of searching for property information and scheduling viewings in real estate is cumbersome, making it difficult for customers to quickly find properties that match their desired criteria, thus reducing operational efficiency. Furthermore, there are insufficient means of providing timely information to visitors, highlighting the need to improve the customer experience.

[0640] 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.

[0641] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for performing registration control using a reservation management unit based on said information, means for using an output unit to present the selected relevant information and set according to conditions, means for acquiring information using a mobile terminal to streamline property information search and reservation, and means for providing property information to visitors using a terminal device. This enables the rapid provision of property information and the streamlining of viewing reservations.

[0642] "Generated information" refers to detailed property information automatically collected from real estate agents' databases and normalized by an AI algorithm.

[0643] The "information selection unit" is a function that selects relevant information that matches the user's desired conditions based on the generated information.

[0644] The "Reservation Management Department" is a function that implements registration and control for making viewing reservations and scheduling adjustments.

[0645] The "output section" is a function that presents selected relevant information to the user and allows them to make settings according to the conditions.

[0646] A "mobile terminal" is a portable electronic device that allows users to search for property information and make viewing appointments.

[0647] A "terminal device" is a device used in a physical store that allows for the input and presentation of property information to customers.

[0648] To implement this invention, a system is constructed using a server, a mobile terminal, and terminal devices. The server automatically collects property information from a real estate agent's database, normalizes the information through an AI algorithm using a programming language such as Python or Node.js, and stores it in an SQL database. Next, an information selection unit selects relevant information based on the user's desired conditions, and a reservation management unit controls the registration of viewing reservations and schedules.

[0649] On mobile devices, an application developed using React Native allows users to input their desired criteria and retrieve relevant property information. Users can search for properties and schedule viewings through a simple interface. The terminals are installed in physical stores, allowing visitors to check property information and schedule viewings for their desired properties. Firebase Cloud Messaging is used to send push notifications to users during this process.

[0650] Specifically, for example, when a user enters conditions such as "Tokyo, Shibuya, 3LDK, under 30 million yen" into the app, the server displays filtered property information on the mobile device or terminal, allowing the user to make viewing reservations for properties they are interested in. This information provision and reservation function facilitates smooth real estate transactions at the store.

[0651] The generated AI model optimizes the system by utilizing user feedback and uses prompts to more effectively provide property information and schedule viewings. For example, using a prompt such as "I'm looking for a property in the Shibuya area of ​​Tokyo that meets the criteria of 3LDK and under 30 million yen. Please let me know the available dates and times for viewings," allows for the provision of accurate information to the user, improving the user experience.

[0652] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0653] Step 1:

[0654] The server automatically collects property information from real estate agents' databases. The input consists of property information stored in each real estate agent's database, which is retrieved via API using Python or Node.js. The retrieved information is stored on the server as raw data.

[0655] Step 2:

[0656] The server normalizes the collected property information using an AI algorithm. The input is the raw data collected in step 1, and by applying the AI ​​algorithm, the data format is corrected and duplicates and errors are removed. This process yields standardized property information, which is then stored in an SQL database.

[0657] Step 3:

[0658] The user opens the application on their mobile device and enters their desired criteria. These criteria (e.g., location, price range, floor plan) are then sent to the server. The application is developed using React Native, resulting in an intuitive and smooth user experience.

[0659] Step 4:

[0660] The server selects relevant information from the SQL database based on the user's desired conditions. The input is the user's conditions received in step 3, and property information that matches the conditions is extracted through a filtering process. This result is then sent to the mobile terminal as relevant information.

[0661] Step 5:

[0662] The user views property information displayed on their mobile device and selects properties of interest. The selected properties become eligible for viewing reservations, and the user specifies their preferred date and time in the app. This action sends the reservation conditions to the server.

[0663] Step 6:

[0664] The server uses the reservation management unit to adjust the available viewing dates and times based on the user's reservation conditions. The input is the desired reservation conditions in step 5, and the algorithm calculates the available slots and determines the reservation date and time.

[0665] Step 7:

[0666] The server notifies the user of the scheduled viewing appointment date and time, and also sends a push notification to their mobile device. Firebase Cloud Messaging is used to allow the user to confirm the appointment date and time. This ensures that the user receives confirmation that the appointment is complete.

[0667] Step 8:

[0668] The generative AI model collects user feedback and uses it to optimize the system. The input is user feedback, and the output is improved prompts and increased accuracy in providing property information, thereby enhancing the user experience.

[0669] 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.

[0670] The system in this invention aims to provide a more personalized user experience by centering on the interaction between a server, a terminal, and a user, and combining this with an emotion engine. In addition to the basic functions of the system, it has the ability to recognize and analyze the user's emotions and adjust output and notifications according to the situation.

[0671] In addition to collecting and processing regular property information, the server analyzes emotional data obtained from users through an emotion engine. The emotion engine includes an algorithm that automatically estimates emotions from inputs provided by the user to the terminal (e.g., tone of voice, text input content, facial recognition, etc.). This emotional data is reflected in the processing results of the information selection unit and is used to adjust the suggested properties and information.

[0672] The device functions as an interface for users to provide emotional input. For example, users input text or audio containing questions or excitement they felt during the property selection process. The device sends this to the emotion engine, which then supports analysis on the server. Based on the analysis results, the user is shown more relevant information and notifications.

[0673] Users receive a personalized experience based on their unique emotions. For example, if a user shows a positive reaction to a particular property listing, the server evaluates this emotion and recommends more properties with similar characteristics. Furthermore, by incorporating emotion data into the notification system, the server can generate follow-up notifications best suited to the user's situation. This makes the property selection and viewing process more intuitive and effective.

[0674] The implementation of this system will enable highly personalized customer interactions and improve the user experience. This is expected to play a key role in the digital transformation of the real estate industry.

[0675] The following describes the processing flow.

[0676] Step 1:

[0677] Users can express their preferences and feelings by entering text messages or voice messages via their devices when selecting properties.

[0678] Step 2:

[0679] The terminal sends the entered user information to the server and also passes it to an emotion engine for emotional data analysis. This analysis is based on factors such as the user's voice tone and word choices.

[0680] Step 3:

[0681] The server receives the analysis results from the emotion engine and sends that information to the information selection unit. This allows the server to prioritize selecting properties that are likely to interest the user.

[0682] Step 4:

[0683] The terminal displays a list of properties sent from the server to the user. Because the suggested properties are adjusted based on the user's preferences, more accurate recommendations are provided.

[0684] Step 5:

[0685] Users select properties they are interested in and schedule viewings. Their selections are sent from their device to the server.

[0686] Step 6:

[0687] The server uses the reservation management department to make adjustments, taking into account sentiment data and past selection history, to determine the optimal reservation date and time.

[0688] Step 7:

[0689] The device notifies the user of reservation confirmation information from the server. This notification is customized based on the user's sentiment data.

[0690] Step 8:

[0691] User feedback and further sentiment data are sent to the server through the evaluation department. This information is used to improve the system and make more accurate property recommendations.

[0692] (Example 2)

[0693] 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".

[0694] In modern society, there is a growing demand for systems that provide appropriate information based on users' emotions and preferences. However, currently, it is difficult to provide information that adequately meets the individual needs of users. Furthermore, information selection and notification optimization based on emotions are insufficient, and there is room to improve the user experience. Therefore, there is a need for a new system that accurately analyzes users' emotions and provides information based on them quickly and accurately.

[0695] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0696] In this invention, the server includes means for selecting relevant data using a data selection unit based on generated data, means for analyzing the user's emotions using an emotion analysis engine, and means for evaluating similarity and making recommendations using a generative AI model. This enables the provision of highly personalized information based on the user's emotions.

[0697] "Generated data" refers to information created in a specific format or method for use within a system.

[0698] The "data selection unit" refers to the functions and components used to select relevant information from the generated data.

[0699] A "reservation control unit" refers to the functions and components within a system that manage registration and scheduling.

[0700] An "output device" is hardware or software that presents selected data and provides information to the user.

[0701] An "emotion analysis engine" is an algorithm or technology that analyzes a user's emotions and utilizes the results in the system.

[0702] A "generative AI model" is an artificial intelligence model designed to generate specific results based on input data.

[0703] A "notification device" is a function or component that sends information or messages to a user.

[0704] This invention is achieved through a system based on the interaction between a server, a terminal, and a user. At the core of the system is the analysis of user emotions based on generated data, the selection of relevant data based on that analysis, and similarity evaluation and recommendations using a generative AI model.

[0705] The server uses a database to collect property and related information, and then uses an emotion analysis engine to analyze the user's emotional state based on the generated data. This utilizes a database and machine learning engine running on a typical cloud computing service. A natural language processing library is used for the analysis, and the user's input is numerically represented as an emotion score.

[0706] The terminal functions as an interface for users to provide emotional input. Users can input via voice or text through common devices such as smartphones or personal computers. This input is processed by voice recognition software installed in the terminal and sent to the server. For example, if a user voice-inputs "I like this garden," the terminal converts this to text and immediately sends it to the server.

[0707] Users can view recommended information and provide feedback. The feedback provided is analyzed again on the server and fed back into the recommendation model, enabling the provision of even more accurate information. An example of a prompt message is, "I want to find a property located in the countryside with a large garden."

[0708] Thus, by using this system, users can obtain personalized information and suggestions based on their emotions and preferences, making the real estate selection process smoother.

[0709] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0710] Step 1:

[0711] Users use their devices to express their emotions and preferences through voice or text input. This input is done via smartphones or computers and is temporarily recorded by the device. The purpose of the input is to clearly communicate specific requests or emotions.

[0712] Step 2:

[0713] The device converts collected voice input into text data using speech recognition software. This text data helps improve the accuracy of sentiment analysis. By processing the input data (voice) and obtaining text data as output, it prepares for the next analysis step. Specifically, voice input is converted into text such as "I like properties with large gardens."

[0714] Step 3:

[0715] The server receives text data sent from the terminal and analyzes the data using an emotion analysis engine. This analysis process calculates an emotion score using natural language processing techniques. The input is text data, and the output is an emotion score or tagged emotion expression. For example, positive emotions are assigned a high score.

[0716] Step 4:

[0717] The server uses a generative AI model based on the sentiment analysis results to select the most suitable information for recommendations. It analyzes the received text data, performs similarity evaluations, and selects highly relevant property information. The input is the sentiment score and the user's desired conditions, and the output is a list of recommended properties.

[0718] Step 5:

[0719] The server transmits selected property information to the terminal and outputs it to the user. This output is visually presented on the user's display and is designed for more intuitive confirmation. The input is recommended property data processed on the server side, and the output is a display on the user interface. Based on this, users can provide further feedback.

[0720] This process allows users to receive more accurate real estate information based on their emotions and preferences.

[0721] (Application Example 2)

[0722] 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".

[0723] In modern society, general information and services provided by common technological systems often fail to adequately address the individual needs and emotions of users. Therefore, there is a growing demand for more personalized experiences that take users' emotions into account, thereby improving their quality of life. In particular, when providing support within the home through consumer robots, flexible services based on the user's emotional state are essential.

[0724] 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.

[0725] In this invention, the server includes means for selecting relevant information using an information selection unit based on generated information, means for using a control device that performs reservation management based on said information, means for using an output device that presents the selected relevant information and sets according to conditions, and means for using an emotion analysis engine that recognizes the user's emotion data and adjusts the suggested content and notifications according to the situation. This enables personalized information selection and notifications that correspond to the individual user's emotions, and in particular, the suggestions and actions of consumer robots in the home become more in line with the user's psychological state.

[0726] An "information selection unit" is a device that selects and provides information relevant to the user from the generated information.

[0727] A "control device" is a device that automatically manages things like reservations and registrations based on selected information.

[0728] An "output device" is a device that presents selected information and settings to the user.

[0729] An "emotion analysis engine" is an algorithm or device that analyzes emotional data obtained from users to estimate the user's psychological state.

[0730] A "communication device" is a device that automatically sends notifications to the user based on specified conditions or sentiment analysis results.

[0731] In the system realizing this invention, the server first uses an information selection unit to select relevant information based on the generated information. The selected information is managed by a control device, and the information necessary for the user is prepared. The output device presents the selected relevant information to the user and allows them to make settings according to the situation. Furthermore, by using an emotion analysis engine, the system can recognize and analyze emotional data from the user's facial expressions and tone of voice to understand the user's psychological state.

[0732] The hardware used in this application example includes cameras and microphones for facial recognition and voice tone analysis. Specifically, Intel RealSense and Kinect cameras are used. In terms of software, an emotion analysis algorithm is built using Python in a ROS (Robot Operating System) environment, and TensorFlow is used to model the user's emotions. Based on the emotion data analyzed on the server side, prompt messages are sent to a generative AI model, such as OpenAI's GPT-4, which then generates appropriate suggestions and notifications.

[0733] As a concrete example, a server and a robot work together to read the facial expressions of a user relaxing in the living room and suggest, "You look tired, shall we play some relaxing music?" If the user is smiling, it might say, "You seem to be in a good mood, why don't we enjoy today's beautiful weather together?" Examples of prompts for the generative AI model include, "The user has been identified as stressed. What action would you recommend?" and "If the user is showing signs of happiness, what activity would you suggest?"

[0734] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0735] Step 1:

[0736] The device captures the user's voice and facial expressions using its camera and microphone. Specifically, the camera takes a real-time photo of the user's face, and the microphone records their voice. This data is then sent as input to an emotion analysis engine.

[0737] Step 2:

[0738] The server uses an emotion analysis engine to analyze voice and facial expression data sent from the terminal. Based on the input data, a TensorFlow model running on a Python script estimates the user's emotion. The output is the user's emotion label (e.g., stress, happiness).

[0739] Step 3:

[0740] The server uses an information selection unit to select relevant information and suggestions based on the analysis results. Taking emotion labels as input, the selection algorithm determines an appropriate suggestion (e.g., playing relaxing music) and generates suggestion information as output.

[0741] Step 4:

[0742] The server sends prompt messages to the generating AI model, which then generates further actions tailored to the user's situation. Specifically, it sends the previously recorded emotion label and suggested content as prompt messages to the generating AI model, and obtains the optimal action plan as output from the model.

[0743] Step 5:

[0744] The device presents the user with suggested information received from the server and performs the corresponding action. For example, if the user is feeling stressed, it will send a voice notification saying, "We will play music to help you relax," and then play the appropriate music.

[0745] 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.

[0746] 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.

[0747] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0748] 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.

[0749] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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."

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] The following is further disclosed regarding the embodiments described above.

[0767] (Claim 1)

[0768] A means for selecting relevant information using an information selection unit based on the generated information,

[0769] A means for performing registration control using the reservation management unit based on the said information,

[0770] A means of using an output unit that presents selected relevant information and sets according to the conditions,

[0771] A system that includes this.

[0772] (Claim 2)

[0773] The system according to claim 1, further comprising an evaluation unit that evaluates proposed information based on the generated information.

[0774] (Claim 3)

[0775] The system according to claim 1, comprising a notification unit that provides notifications based on specified conditions using automatically controlled communication means.

[0776] "Example 1"

[0777] (Claim 1)

[0778] A means for automatically acquiring information from an information storage device, normalizing it using a processing unit, and saving it as detailed information in a structured data format,

[0779] A means for a processing unit to filter information and select highly relevant information based on conditional information input using an input device,

[0780] A means for displaying selected information through an output device and enabling operation according to the set conditions,

[0781] A means for managing reservations using a control device, adjusting the time, and presenting the results through an output device,

[0782] A means of evaluating the accuracy of proposed information based on user feedback using an evaluation device,

[0783] A means of automatically transmitting information via a communication device and notifying important information according to the time,

[0784] A system that includes this.

[0785] (Claim 2)

[0786] The system according to claim 1, which uses an evaluation device to generate prompt statements based on user conditions and presents corresponding results.

[0787] (Claim 3)

[0788] The system according to claim 1, which uses a generative AI model to perform data analysis and processes that contribute to improving the quality of information.

[0789] "Application Example 1"

[0790] (Claim 1)

[0791] A means for selecting relevant information using an information selection unit based on the generated information,

[0792] A means for performing registration control using the reservation management unit based on the said information,

[0793] A means of using an output unit that presents selected relevant information and sets according to the conditions,

[0794] A means of using mobile devices to obtain information and streamline property search and reservation,

[0795] A means of providing property information to customers using a terminal device,

[0796] A system that includes this.

[0797] (Claim 2)

[0798] The system according to claim 1, further comprising an evaluation unit that evaluates proposed information based on the generated information.

[0799] (Claim 3)

[0800] The system according to claim 1, comprising a notification unit that provides notifications based on specified conditions using automatically controlled communication means.

[0801] "Example 2 of combining an emotion engine"

[0802] (Claim 1)

[0803] A means for selecting relevant data using a data selection unit based on the generated data,

[0804] Means for performing registration control using a reservation control unit based on the said data,

[0805] A means of using an output device that presents selected relevant data and sets according to the conditions,

[0806] A means of analyzing a user's emotions using an emotion analysis engine,

[0807] A method for evaluating similarity and making recommendations using a generative AI model,

[0808] A system that includes this.

[0809] (Claim 2)

[0810] The system according to claim 1, further comprising an evaluation unit that evaluates proposed data based on the generated data.

[0811] (Claim 3)

[0812] The system according to claim 1, comprising a notification device that provides notifications based on specified conditions using automatically controlled communication means.

[0813] "Application example 2 when combining with an emotional engine"

[0814] (Claim 1)

[0815] A means for selecting relevant information using an information selection unit based on the generated information,

[0816] A means of using a control device that performs reservation management based on the said information,

[0817] A means of using an output device that presents selected relevant information and makes settings according to the conditions,

[0818] A means of using an emotion analysis engine that recognizes user emotion data and adjusts suggestions and notifications according to the situation,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, comprising an evaluation device that evaluates proposed information based on generated information, and further combining it with a device that determines personalized actions based on the user's emotions.

[0822] (Claim 3)

[0823] The system according to claim 1, comprising a communication device that provides notifications based on specified conditions and user sentiment analysis results using automatically controlled communication means. [Explanation of Symbols]

[0824] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for selecting relevant information using an information selection unit based on the generated information, A means for performing registration control using the reservation management unit based on the said information, A means of using an output unit that presents selected relevant information and sets according to the conditions, A means of using mobile devices to obtain information and streamline property search and reservation, A means of providing property information to customers using a terminal device, A system that includes this.

2. The system according to claim 1, further comprising an evaluation unit that evaluates proposed information based on the generated information.

3. The system according to claim 1, comprising a notification unit that provides notifications based on specified conditions using automatically controlled communication means.

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