system

Abstract

Provide a system. A means for inputting basic information and residential conditions of a user; means for receiving input information; A means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements; means for driving an artificial intelligence model to generate a renovation plan for the identified property; A means of collecting job information and public facility information for a designated area; means for displaying the collected information and the generated plan on a user's terminal; A system including:

Description

[Technical Field]

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

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

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

[0004] Currently, the problem of vacant houses is becoming more serious nationwide due to a declining birthrate, aging population, and depopulation. At the same time, housing prices are soaring in urban areas, making it difficult for many people to find suitable housing. Furthermore, with the spread of remote work, an increasing number of people are looking to move from urban areas to rural areas, but there is often insufficient information provided about housing and surrounding environments that meet their needs. To solve these issues, a system is needed that makes effective use of vacant houses across the country, provides housing tailored to users' needs, and provides comprehensive support for life after relocating. [Means for solving the problem]

[0005] This invention provides a system that includes a means for users to input their basic information and housing requirements, a means for receiving the input information, a means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, a means for running an artificial intelligence model to generate renovation plans for the identified properties, a means for collecting job information and public facility information for the specified area, and a means for displaying the collected information and generated plans on the user's terminal. This system allows users to easily select properties and renovate plans that meet their needs, and also provides comprehensive information about the living environment after relocating. This aims to promote the effective use of vacant houses and regional revitalization.

[0006] "User" refers to an individual who uses the system to enter their basic information and housing requirements.

[0007] "Housing conditions" refer to the specific housing requirements of the user, such as the desired layout, area, budget, etc.

[0008] "Means" refers to a device or method used to accomplish a particular function.

[0009] "Real estate database" refers to a database containing information on vacant houses across the country.

[0010] "Identifying" refers to the act of selecting the most suitable property or information based on the entered conditions.

[0011] A "renovation plan" refers to a specific plan or design proposal for renovating an existing property.

[0012] An "artificial intelligence model" refers to a system that uses techniques such as machine learning and deep learning to generate insights and predictions from data.

[0013] "Designated region" refers to a geographic area desired or selected by a user.

[0014] "Job Information" means information about employment opportunities available in a particular geographic area.

[0015] "Public facility information" refers to information about public facilities such as schools, hospitals, and parks that exist in a specific area.

[0016] "Display" refers to the act of visually showing data or information on a terminal.

[0017] "Terminal" refers to a device through which a user accesses a system for input and output. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11]FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and generates a renovation plan. It also provides job information and public facility information for the specified area. Specific embodiments are described below.

[0040] System Overview

[0041] Enter user information

[0042] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[0043] Data collection

[0044] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[0045] Renovation plan generation

[0046] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[0047] Regional information provision

[0048] The server also collects job listings and public facility information for the specified area, which is obtained by querying a local job database and a local public facility database.

[0049] Information display

[0050] Finally, the server sends all the collected information (vacant house list, renovation plans, local information) to the user's device, which displays this information in a visually easy-to-understand format.

[0051] Specific examples

[0052] Below is a concrete example of how this system works in practice.

[0053] 1. When a user enters information

[0054] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[0055] 2. When sending data to the server

[0056] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[0057] 3. When a vacant house is identified

[0058] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[0059] 4. When a renovation plan is generated

[0060] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[0061] 5. When local information is provided

[0062] The server collects local information for Tokyo, including information on local job openings and public facilities (schools, hospitals, parks, etc.).

[0063] 6. When information is displayed to the user

[0064] Ultimately, all this information is sent from the server to the user's device, which displays a list of vacant homes, details of renovation plans, local job listings, and information about public facilities in a visually easy-to-understand format.

[0065] This system allows users to easily find the housing and renovation plan that best suits their needs, and provides comprehensive support for life planning after moving in. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] A user starts the application and enters basic information and housing requirements.

[0069] The user enters detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[0070] Step 2:

[0071] The terminal temporarily stores the user's input information and sends it to the server.

[0072] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[0073] Step 3:

[0074] The server receives the information from the user and searches a real estate database.

[0075] The server generates an SQL query based on the received information and extracts vacant properties from the database that match conditions such as the desired area, budget, and floor plan.

[0076] Step 4:

[0077] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[0078] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[0079] Step 5:

[0080] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[0081] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[0082] Step 6:

[0083] The server collects job information and public facility information for a specified area.

[0084] The server queries the local job and public facility databases and compiles the collected information, specifically, local job listings and public facilities such as schools, hospitals, and parks.

[0085] Step 7:

[0086] The server sends all information (vacant house list, renovation plan, local information) to the user's device.

[0087] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[0088] Step 8:

[0089] The terminal formats and displays the information it receives.

[0090] The terminal organizes the received detailed information on vacant houses, renovation plans, local job listings and information on public facilities, and displays it to the user in a visually easy-to-understand format.

[0091] ---

[0092] The above processing flow allows users to easily find vacant properties and renovation plans that suit their needs, and also to obtain comprehensive information necessary for life planning after moving in. This system contributes to the effective use of vacant properties and regional revitalization.

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] Currently, the process of users finding a new home, renovating it, and planning their life in that area requires a lot of manual work, which is extremely time-consuming and labor-intensive. There is a need for a system that can streamline this process and allow users to quickly find the home and renovation plan that is best suited to them, as well as information about the area they are moving to.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate a renovation plan for the identified property, means for using prompt text including the content of the generated renovation plan, means for collecting information on job openings and public facilities in the specified area, and means for displaying the collected information and the generated plan on the user's terminal. This allows a user to easily find a home that suits them, obtain specific and detailed renovation plans for that home, and simultaneously obtain comprehensive information on the living environment of the relocation destination.

[0098] "Basic information" refers to personal attribute information of a user, such as name, age, sex, occupation, and other information for identifying the user.

[0099] "Housing conditions" refer to conditions related to the housing desired by the user, and include specific requirements such as floor plan, area, and budget.

[0100] A "real estate database" refers to a database system that stores and allows searching of property information from across the country.

[0101] A "generative AI model" refers to a program that uses artificial intelligence technology to analyze data and generate renovation plans.

[0102] A "prompt" refers to text that contains instructions or questions given to a generative AI model.

[0103] "Job Information" means information about employment opportunities in a designated area.

[0104] "Public facility information" refers to information about public facilities such as schools, hospitals, and parks located in a designated area.

[0105] The system aims to help users plan their future life in their new home by providing information on job openings and public facilities in the area, based on the user's basic information and housing requirements.

[0106] First, when a user starts the application, a screen appears where they can enter basic information (such as name, age, gender, and occupation) and desired housing conditions (such as floor plan, area, and budget). The user enters this information, and the device sends the input information to the server in JSON format.

[0107] Based on the received information, the server generates an SQL query for the real estate database and filters the nationwide vacant house data based on the conditions. The server performs the search using a database management system (e.g., MySQL (registered trademark)). For example, it identifies vacant properties that meet the conditions "Tokyo," "under 50 million yen," and "3LDK."

[0108] Next, the information about the identified vacant property is input into a generative AI model (e.g., OpenAI (registered trademark) GPT-4 (registered trademark)) to generate a renovation plan. The prompt sent to the generative AI model is as follows:

[0109] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[0110] The generated renovation plan includes interior design images and detailed cost breakdowns, allowing users to visualize the specific renovation process.

[0111] Additionally, the server collects job listings and public accommodation information for the specified area by querying a local job database (e.g., Indeed API) and collecting public accommodation information as well. For example, it executes an API query like this:

[0112] python

[0113] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[0114] The server sends this information to the user's device, which then displays it in a visually easy-to-understand format using HTML5 and CSS3. Users can easily view a list of vacant homes, details of renovation plans, local job listings, and information on public facilities.

[0115] As a specific example, suppose a user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen). Based on this information, the server searches a real estate database using the criteria "Tokyo," "under 50 million yen," and "3LDK," and inputs the information on identified vacant properties into a generative AI model to generate a renovation plan. The generated plan includes a design for an open kitchen with an expanded living room and a detailed cost breakdown. The server then collects job information and public facility information for the specified area and sends all of this information to the device. The device displays this information in an easy-to-understand format, allowing the user to obtain all the information they need.

[0116] This system allows users to efficiently find the most suitable housing and renovation plan, and provides comprehensive support for life planning after relocating. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[0117] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0118] Step 1: Enter your user information

[0119] When a user launches the application, a screen appears where they can enter their basic information and housing requirements. Specifically, the user enters information such as their name, age, gender, occupation, desired layout, area, and budget. The input data is converted to JSON format and is ready to be sent to the server in the next step.

[0120] Input: Name, age, gender, occupation, floor plan, area, budget

[0121] Output: User information in JSON format

[0122] Step 2: Sending data to the server

[0123] The terminal receives the information entered by the user and sends it to the server in the form of an HTTP POST request, which the server receives and begins preparing a database search.

[0124] Input: User information in JSON format

[0125] Output: HTTP POST request to the server

[0126] Specific behavior:

[0127] When the user presses the "Submit" button, the device sends an HTTP POST request to the server that looks like this:

[0128] http

[0129] POST / submit-user-info HTTP / 1.1

[0130] Host: example.com

[0131] Content-Type: application / json

[0132] {

[0133] "name": "Yamada Taro",

[0134] "age": 35,

[0135] "gender": "male",

[0136] "occupation": "teacher",

[0137] "layout": "3LDK",

[0138] "region": "Tokyo",

[0139] "budget": 5000

[0140] }

[0141] Step 3: Search for vacant properties

[0142] The server executes an SQL query against the real estate database based on the received user information. The query is generated based on the user's criteria and identifies properties that match the criteria from nationwide vacant home data. This generates a list of properties that match the criteria.

[0143] Input: User information in JSON format

[0144] Output: List of properties that match the criteria (SQL query results)

[0145] Specific behavior:

[0146] The server generates an SQL query like this and runs it against the real estate database:

[0147] sql

[0148] SELECT FROM properties WHERE region='Tokyo' AND price <= 50000000 AND layout='3LDK';

[0149] The results obtained from the database are organized in a list format and passed to the next step.

[0150] Step 4: Generate a renovation plan

[0151] Based on the information on the identified vacant property, the server inputs a prompt statement into the generative AI model to generate a renovation plan. This prompt statement contains specific renovation requests, and the AI ​​model automatically generates a plan based on that.

[0152] Input: List of properties that match the criteria, prompt text

[0153] Output: Generated renovation plan

[0154] Specific behavior:

[0155] The server sends the following prompt to the generative AI model:

[0156] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[0157] The AI ​​model generates a renovation plan and returns the results to the server, including interior design images and cost breakdowns.

[0158] Step 5: Gather local information

[0159] The server collects job information and public facility information for the specified area by issuing API queries to the local job database and public facility database to obtain the required information.

[0160] Input: User's desired region information

[0161] Output: Local job information, public facility information

[0162] Specific behavior:

[0163] The server sends the following request to the local jobs API:

[0164] python

[0165] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[0166] Similarly, API queries are issued to collect public facility information and retrieve data.

[0167] Step 6: Sending information to the device and displaying it

[0168] The server then sends all the collected information (vacant house lists, renovation plans, and local information) to the user's device, which receives it and displays it in a visually easy-to-understand format.

[0169] Input: Vacant house list, renovation plan, local information

[0170] Output: Final display data to the terminal

[0171] Specific behavior:

[0172] The server sends the following HTTP response to the device:

[0173] http

[0174] HTTP / 1.1 200 OK

[0175] Content-Type: application / json

[0176] {

[0177] "properties": [...],

[0178] "renovation_plan": {...},

[0179] "jobs": [...],

[0180] "public_facilities": {...}

[0181] }

[0182] The device visually displays the received data using HTML5 and CSS3, making it easy for users to view.

[0183] Through a step-by-step process, the system can provide users with the best available vacant properties and renovation plans, as well as comprehensive information on living in the designated area.

[0184] (Application example 1)

[0185] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0186] Conventional real estate search systems were limited to identifying properties based on user-specified criteria, and lacked the ability to generate renovation plans or provide local information. Furthermore, there was no way to provide users with property search results, renovation plans, and local information in a visually easy-to-understand format. Furthermore, when properties were being shown in physical stores, it was difficult for users to immediately grasp detailed information and renovation plans. These issues made it difficult for users to select the appropriate property and determine the appropriate renovation plan.

[0187] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0188] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate renovation plans for the identified properties, means for collecting job information and public facility information for a specified area, means for displaying the collected information and the generated plans on the user's terminal, and means for displaying the collected information and the generated plans in augmented reality through smart glasses. This allows users to visually check specific property information, renovation plans, and local information using augmented reality even in physical stores.

[0189] "User basic information" refers to personal data provided by the user, including information such as age, gender, occupation, and contact details.

[0190] "Housing conditions" refer to the specifications and characteristics of the property desired by the user, such as floor plan, budget, location, and facilities.

[0191] A "real estate database" is a database system that registers property information from all over the country, and includes data such as property addresses, prices, floor plans, and photos.

[0192] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to generate new information or plans from data.

[0193] "Job Information" means information about employment opportunities and job postings in a specified area, including data such as job type, salary, and location.

[0194] "Public facility information" refers to information about public infrastructure and service facilities within a specific area, such as schools, hospitals, parks, and libraries.

[0195] "Smart glasses" are wearable devices equipped with augmented reality technology, and are glasses-type terminals with built-in displays.

[0196] "Augmented reality" is a technology that overlays digital information onto the real environment, displaying virtual information alongside real objects in the user's field of vision.

[0197] A "renovation plan" is a plan for renovating and remodeling an existing building, and includes blueprints, interior design drawings, and cost details.

[0198] "Means for displaying information in a visually easy-to-understand manner" refers to methods and tools for providing information graphically so that users can easily understand the information, and is a display means that includes diagrams and image illustrations.

[0199] The present invention provides a system that allows users to visually check property information and renovation plans in a physical store using smart glasses. Specific embodiments are described in detail below.

[0200] System Program and Processing Overview

[0201] The server uses voice and gesture recognition technology to input the user's basic information and living conditions. The user puts on the smart glasses and inputs their conditions through voice commands or gestures. This information is then sent from the smart glasses to the server.

[0202] The server uses the received information to search a nationwide real estate database and identify properties that meet the user's criteria. The search results include the property's address, price, floor plan, photos, and more.

[0203] The server runs a generative AI model to generate a renovation plan for the identified property. The generative AI model automatically generates a renovation plan based on the input property information, providing interior image drawings and detailed cost breakdowns.

[0204] The server then queries a relevant database to gather job and public facility information for the specified area, providing detailed information about employment opportunities and public infrastructure in the area.

[0205] The collected information and generated plans are displayed on the user's device (smart glasses), which uses augmented reality technology to visually display property details, renovation plans, and local information.

[0206] This allows users to use augmented reality to check detailed property information, renovation plans, and local information even in physical stores, and even make specific decisions on the spot.

[0207] Hardware and software used

[0208] Hardware: Smart glasses (e.g., Microsoft® HoloLens®)

[0209] Software: AR libraries (e.g., ARCore, ARKit), cloud databases (e.g., Firebase, AWS), generative AI models (e.g., GPT-4)

[0210] Natural language explanation of the process

[0211] The server uses a voice recognition engine (e.g., Google® Speech-to-Text) and gesture recognition (e.g., OpenCV) to collect data from users entering their basic information and housing requirements. This information is sent to the cloud and searched through a nationwide real estate database. The search results include basic information such as the property's address, floor plan, price, and photos.

[0212] The server inputs the acquired property information into a generative AI model to generate a renovation plan. Using a generative AI model (e.g., GPT-4), a renovation plan is automatically generated based on the user's criteria, and interior design drawings and detailed cost estimates are provided.

[0213] Additionally, the server retrieves job and public facility information for the specified area from a relational database, allowing the user to view information about job opportunities and public services in the area.

[0214] This information is sent to the smart glasses and displayed visually using the AR library, allowing users to intuitively understand detailed property information and renovation plans even in a physical store.

[0215] Examples of concrete examples and prompts

[0216] Example: A user can wear smart glasses in a physical store and input voice commands such as "Tell me about 3LDK properties," "Show me renovation plans for open kitchens," and "Show me information about nearby hospitals," and appropriate property information, renovation plans, and local information will be displayed using AR.

[0217] Prompt Sentence Examples

[0218] "Tell me about a 3LDK property."

[0219] "I'd like to see your open kitchen renovation plan."

[0220] "Show me information about nearby hospitals"

[0221] These features improve the user experience and make property selection and renovation planning more efficient.

[0222] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0223] Step 1:

[0224] The user puts on the smart glasses and inputs basic information and housing requirements using voice commands and gestures. The glasses' built-in voice recognition engine (e.g., Google Speech-to-Text) and gesture recognition software (e.g., OpenCV) are used to capture voice and movement data. This provides input data such as age, gender, occupation, desired floor plan, desired area, and budget. This data is then sent from the device to a server.

[0225] Step 2:

[0226] The server performs a real estate database search based on the received user information. It generates an SQL query to filter the database and retrieve property listings that match the specified criteria. Input data includes the user's desired layout, area, and budget, and output data includes relevant property information (e.g., address, price, layout, and photos).

[0227] Step 3:

[0228] The server uses the acquired property information as input data for a generative AI model (e.g., GPT-4) to generate a renovation plan. The generative AI model analyzes the property's floor plan and photos, and automatically generates a renovation plan that meets the user's needs. The input data is the property information and the user's desired conditions, and the output data is the renovation plan (e.g., interior design drawings and detailed cost breakdowns).

[0229] Step 4:

[0230] The server queries a relational database to gather job and public facility information for a given area, using the user-specified area as input and providing information about job opportunities and public facilities (schools, hospitals, parks, etc.) in that area as output.

[0231] Step 5:

[0232] The server sends the collected information and generated renovation plans to the user's smart glasses. Specifically, it uses an AR library (e.g., ARCore, ARKit) to process the data to display the information in a visually understandable way. The input data is property information, renovation plans, and local information, and the output data is the AR content displayed on the smart glasses.

[0233] Step 6:

[0234] The device receives the transmitted data and displays it in augmented reality on the smart glasses' display. Property details, renovation plans, and local information are superimposed on the user's field of vision, allowing the user to see the property's image and renovation possibilities in real time.

[0235] This series of processes allows users to intuitively check detailed property information, renovation plans, and local information even in physical stores using augmented reality technology.

[0236] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0237] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments are described below.

[0238] System Overview

[0239] Enter user information

[0240] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[0241] Data collection

[0242] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[0243] Renovation plan generation

[0244] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[0245] Emotion recognition by emotion engine

[0246] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to evaluate their satisfaction and stress level.

[0247] Emotion-Based Optimization

[0248] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[0249] Regional information provision

[0250] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[0251] Information display

[0252] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[0253] Specific examples

[0254] Below is a concrete example of how this system works in practice.

[0255] 1. When a user enters information

[0256] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[0257] 2. When sending data to the server

[0258] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[0259] 3. When a vacant house is identified

[0260] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[0261] 4. When a renovation plan is generated

[0262] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[0263] 5. When the emotion engine recognizes the user's emotions

[0264] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[0265] 6. Optimizing your renovation plan based on emotions

[0266] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[0267] 7. When local information is provided

[0268] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[0269] 8. When information is displayed to the user

[0270] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[0271] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[0272] The processing flow will be explained below.

[0273] Step 1:

[0274] A user starts the application and enters basic information and housing requirements.

[0275] Users enter detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[0276] Step 2:

[0277] The terminal temporarily stores the user's input information and sends it to the server.

[0278] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[0279] Step 3:

[0280] The server receives the information from the user and searches a real estate database.

[0281] The server generates an SQL query based on the received information and extracts vacant properties from the database that match the desired area, budget, and floor plan.

[0282] Step 4:

[0283] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[0284] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[0285] Step 5:

[0286] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[0287] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[0288] Step 6:

[0289] The emotion engine recognizes the user's emotions.

[0290] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice in real time to assess their happiness or dissatisfaction.

[0291] Step 7:

[0292] Optimize renovation plans based on an emotion engine.

[0293] Based on the emotions recognized, the system evaluates the user's preferences and stress level and suggests modifications to the renovation plan accordingly. For example, if the user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design.

[0294] Step 8:

[0295] The server collects job information and public facility information for a specified area.

[0296] The server queries the job and public facility databases for the area and compiles the collected information. Specifically, it retrieves information on local jobs and public facilities such as schools, hospitals, and parks. The emotion engine takes into account the user's preferences and stress level and provides the most appropriate local information based on the results.

[0297] Step 9:

[0298] The server sends all information (vacant house list, renovation plan, emotion-based optimization plan, local information) to the user's device.

[0299] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[0300] Step 10:

[0301] The terminal formats and displays the information it receives.

[0302] The device organizes the received information about vacant houses, renovation plans, suggested revisions to the plans based on emotions, local job information, and information about public facilities, and displays it to the user in a visually easy-to-understand format.

[0303] ---

[0304] This detailed processing flowchart allows users to easily find the best vacant property and renovation plan, and furthermore, by utilizing the emotion engine, they can select a home that will give them the highest level of satisfaction. Furthermore, they can obtain comprehensive information necessary for planning their life after moving. This system will greatly contribute to the effective use of vacant properties and regional revitalization.

[0305] Example 2

[0306] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0307] Conventional housing selection and renovation plan generation systems lack the ability to recognize the user's emotional state and optimize the plan based on that, making it difficult to maximize user satisfaction. Furthermore, they lacked a means to provide comprehensive local information, resulting in insufficient information for selecting a relocation destination. This made it difficult for users to select the optimal housing that best suited their needs and emotions.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0309] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving an artificial intelligence model to generate a renovation plan for the identified property, means for analyzing the user's facial expressions and voice to recognize their emotional state, means for optimizing the renovation plan based on the recognized emotional state, means for collecting job information and public facility information in a specified area, and means for displaying the collected information and the generated plan on the user's terminal. This makes it possible to provide an optimal renovation plan based on the user's emotional state and comprehensive local information.

[0310] "User information" is data including the user's basic information and desired housing conditions.

[0311] "Housing conditions" include the layout, area, budget, and other conditions of the property desired by the user.

[0312] A "terminal" is a device through which a user inputs information and receives information from a server.

[0313] A "server" is a computer system that receives user information, searches the database, and generates renovation plans.

[0314] The "real estate database" is a database that stores information on vacant houses and properties across the country.

[0315] An "SQL query" is a Structured Query Language command issued to a database to perform a search.

[0316] A "generative AI model" is an artificial intelligence model that generates renovation plans based on input data.

[0317] A "renovation plan" is a detailed plan including proposed interior design drawings and cost breakdowns for a specified property.

[0318] An "emotion engine" is a software engine that has the function of analyzing a user's facial expressions and voice and recognizing their emotional state.

[0319] "Emotional state" refers to a user's psychological state, such as their satisfaction level or stress level.

[0320] A "job database" is a database that stores job information for a specified area.

[0321] The "public facility database" is a database that stores information on public facilities such as schools, hospitals, and parks in a specified area.

[0322] "Regional information" is data including job information and public facility information related to a specified region.

[0323] "Means for displaying information in a visually easy-to-understand manner" is a function for displaying information in a format that is easily understandable to the user.

[0324] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments of the present invention are described below.

[0325] System Overview

[0326] Enter user information

[0327] When a user starts the application, a screen appears on the device where the user can enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[0328] Data collection

[0329] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[0330] Renovation plan generation

[0331] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[0332] Emotion recognition by emotion engine

[0333] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to assess their satisfaction and stress level.

[0334] Emotion-Based Optimization

[0335] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[0336] Regional information provision

[0337] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[0338] Information display

[0339] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[0340] Specific examples

[0341] Below is a concrete example of how this system works in practice.

[0342] 1. When a user enters information

[0343] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[0344] 2. When sending data to the server

[0345] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[0346] 3. When a vacant house is identified

[0347] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[0348] 4. When a renovation plan is generated

[0349] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[0350] 5. When the emotion engine recognizes the user's emotions

[0351] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[0352] 6. Optimizing your renovation plan based on emotions

[0353] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[0354] 7. When local information is provided

[0355] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[0356] 8. When information is displayed to the user

[0357] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[0358] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[0359] Examples of prompt statements

[0360] "Please suggest the best renovation plan and local information for a user who is a woman in her 30s looking for a 3LDK property in Tokyo with a budget of 50 million yen or less."

[0361] The above is a specific embodiment of the present invention.

[0362] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0363] Step 1:

[0364] The user starts the application.

[0365] Input: Nothing in particular.

[0366] Action: A user taps an application on their device to launch it.

[0367] Output: The application's welcome screen is displayed.

[0368] Step 2:

[0369] The terminal displays a screen for the user to input basic information and desired housing conditions.

[0370] Input: None (based on application default settings).

[0371] How it works: The device displays a form for entering basic information and housing requirements.

[0372] Output: The user input form (name, age, gender, floor plan, area, budget, etc.) is displayed on the screen.

[0373] Step 3:

[0374] The user enters basic information and desired housing conditions.

[0375] Input: Name, age, gender, desired layout (e.g. 3LDK), desired area (e.g. Tokyo), budget (e.g. 50 million yen).

[0376] What happens: A user enters information into a form and taps the "Submit" button.

[0377] Output: The entered information is saved on the device.

[0378] Step 4:

[0379] The terminal transmits the input information to the server.

[0380] Input: Basic information and housing requirements entered by the user.

[0381] Operation: The device converts the input information into JSON format and sends it to the server.

[0382] Output: The server stores the received user information in a database.

[0383] Step 5:

[0384] Based on the user information received by the server, an SQL query is generated to search the real estate database.

[0385] Input: User's basic information and living conditions.

[0386] What it does: The server generates an SQL query of the form "SELECT FROM real estate database WHERE...".

[0387] Output: The generated SQL query.

[0388] Step 6:

[0389] The server runs SQL queries against a real estate database to identify vacant properties that meet the criteria.

[0390] Input: The generated SQL query.

[0391] How it works: The server queries the database to retrieve a list of available properties that fit the criteria.

[0392] Output: A list of identified vacant properties.

[0393] Step 7:

[0394] The server inputs the identified vacant house information into the generative AI model.

[0395] Input: Information about the identified vacant house.

[0396] How it works: The server inputs vacant house information into the generative AI model along with the prompt, "Please propose a renovation plan based on the user's requests."

[0397] Output: The prompt sentence and vacant house information input to the generative AI model.

[0398] Step 8:

[0399] The generative AI model generates a renovation plan (interior image and detailed cost breakdown).

[0400] Input: Prompt statement and vacant house information.

[0401] How it works: A generative AI model builds renovation plans, producing interior design images and a breakdown of the costs involved.

[0402] Output: The generated renovation plan.

[0403] Step 9:

[0404] The server temporarily saves the generated renovation plan.

[0405] Input: Generated renovation plan.

[0406] How it works: The server stores the generated plan in a temporary database.

[0407] Output: Renovation plans saved in a temporary database.

[0408] Step 10:

[0409] The user views the proposed renovation plan.

[0410] Input: Generated renovation plan.

[0411] Operation: The device displays the plan information received from the server.

[0412] Output: Renovation plan displayed on the device.

[0413] Step 11:

[0414] The emotion engine analyzes the user's facial expressions and voice to recognize their emotional state (satisfaction, stress level).

[0415] Input: User's facial expression video and audio data.

[0416] How it works: The emotion engine uses real-time facial recognition and voice analysis to assess emotional state.

[0417] Output: Emotional state (e.g., satisfaction level, dissatisfaction level).

[0418] Step 12:

[0419] The emotion engine sends the emotional state to the server.

[0420] Input: Evaluated emotional state.

[0421] How it works: The emotion engine sends the emotional state in JSON format to the server.

[0422] Output: Emotional state sent to the server.

[0423] Step 13:

[0424] Based on the emotional state received by the server, correction conditions are input into the generative AI model to generate a new renovation plan.

[0425] Input: Emotional state data, vacant house information.

[0426] How it works: The server inputs the prompt statement "The user is dissatisfied, so please propose a different renovation plan" and the correction conditions into the generative AI model.

[0427] Output: The modified conditions and prompt sentences fed into the generative AI model.

[0428] Step 14:

[0429] The generative AI model generates a revised renovation plan.

[0430] Input: Prompt statement and correction condition.

[0431] How it works: A generative AI model builds new renovation plans, generating new interior renderings and revised cost breakdowns.

[0432] Output: The newly generated renovation plan.

[0433] Step 15:

[0434] The server transmits the revised renovation plan to the user's terminal.

[0435] Input: Revised renovation plan.

[0436] How it works: The server sends a remediation plan in JSON format to the user's device.

[0437] Output: The revised renovation plan sent to the device.

[0438] Step 16:

[0439] The server generates an SQL query to search the local job database and public facility database based on the user's desired area.

[0440] Input: User's preferred region data.

[0441] What it does: The server generates SQL queries of the form "SELECT FROM job database WHERE region=..." and "SELECT FROM utility database WHERE region=...".

[0442] Output: The generated SQL query.

[0443] Step 17:

[0444] The server runs SQL queries to retrieve job listings and public facility information.

[0445] Input: The generated SQL query.

[0446] How it works: The server runs SQL queries against the database to retrieve a list of jobs and public accommodations.

[0447] Output: A list of the job and public facility information retrieved.

[0448] Step 18:

[0449] The server temporarily saves the acquired regional information.

[0450] Input: Retrieved job information and public facility information.

[0451] How it works: The server stores the location information in a temporary database.

[0452] Output: Region information stored in a temporary database.

[0453] Step 19:

[0454] The emotion engine takes into account the user's stress level and selects the most appropriate local information.

[0455] Input: Retrieved local information, user's stress level.

[0456] How it works: The emotion engine selects local information based on stress levels and creates a candidate list.

[0457] Output: A list of selected locality candidates.

[0458] Step 20:

[0459] The server finally sends all the information (vacant house list, renovation plan, emotion-based optimization plan, and local information) to the user's device.

[0460] Input: vacant home listings, renovation plans, sentiment-based plans, local information.

[0461] How it works: The server aggregates the information and sends it to the user's device in JSON format.

[0462] Output: Comprehensive information sent to the terminal.

[0463] Step 21:

[0464] The device displays this information in a visually easy-to-understand format.

[0465] Input: General information sent from the server.

[0466] Operation: The device displays information using a UI (user interface).

[0467] Output: A list of available properties, renovation plans, sentiment-based plan revision suggestions, and local information presented in a visually easy-to-understand format.

[0468] (Application example 2)

[0469] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0470] Conventional renovation plan generation systems identify suitable properties based on the user's basic information and living conditions, and then provide a renovation plan. However, they are unable to optimize the plan to reflect the user's emotions or provide visual confirmation using 3D models, making it difficult to increase user satisfaction. Furthermore, they are also inadequate in providing information about life after relocation (job information and public facility information). Therefore, there is a need for a system that can dynamically optimize renovation plans based on the user's emotions, enable visual confirmation using AR technology, and also provide local information.

[0471] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic information and housing conditions; means for receiving the input information; means for searching a nationwide real estate database based on the received information to identify properties that meet the user's conditions; means for driving a generative model to generate a renovation plan for the identified property; means for visually displaying the generated renovation plan on a visual display worn by the user; means for recognizing the user's emotions in real time using an emotion engine; means for optimizing the renovation plan based on the recognized emotions; means for collecting employment information and public facility information for a specified area; and means for displaying the collected information and the generated plan on the user's terminal. This allows the user to visually confirm the renovation plan optimized based on their emotions while also obtaining local information all at once.

[0472] "Basic information of the user" includes information such as the user's age, sex, occupation, desired floor plan, desired area, and budget.

[0473] "Housing conditions" are conditions such as floor plan, area, budget, etc. related to the housing desired by the user.

[0474] The "means for inputting" refers to a means for the user to input the basic information and residential conditions described above, and includes voice recognition, gesture input, and the like.

[0475] The "receiving means" is a means by which the server receives information input by the user.

[0476] A "real estate database" is a database that stores information on vacant houses and data related to real estate properties.

[0477] A "generative model" is a model that uses artificial intelligence to automatically generate renovation plans.

[0478] A "visual display" is a display device worn by a user, such as smart glasses or a head-mounted display.

[0479] The "emotion engine" is an engine that analyzes the user's facial expressions and voice in real time to recognize the user's emotional state.

[0480] The "means for recognizing" is a means for recognizing the user's emotions in real time using an emotion engine.

[0481] The "optimizing means" is a means for dynamically optimizing the renovation plan based on the recognized sentiment.

[0482] "Employment Information" means job information in a designated area.

[0483] "Public facility information" is information about public facilities such as schools, hospitals, and parks in a designated area.

[0484] "Means of collection" means the means for collecting employment information and public facilities information for the designated area.

[0485] The "display means" is a means for displaying the collected information and the generated plan on the user's terminal.

[0486] A "terminal" is a device used by a user, such as a smartphone or tablet.

[0487] The present invention is a system that allows users to input their basic information and housing requirements, and then identifies the most suitable vacant property based on that information and generates a renovation plan.The system also incorporates an emotion engine, which can optimize the renovation plan based on the user's emotions and provide local information.Specific embodiments for implementing the present invention are described below.

[0488] Entering user information

[0489] Users wear smart glasses or a head-mounted display and use voice commands or gestures to input their basic information (age, gender, occupation, etc.) and housing requirements (floor plan, area, budget, etc.). This information is then sent from the user device to the server.

[0490] Receiving and retrieving data

[0491] The server searches a nationwide real estate database based on the received user information, thereby identifying properties that meet the user's criteria.

[0492] Generate renovation plans

[0493] The server inputs the identified property information into a generative AI model and automatically generates a renovation plan, which includes a 3D image of the interior and a detailed breakdown of costs.

[0494] Emotion recognition by emotion engine

[0495] Using the camera and microphone built into the smart glasses or head-mounted display worn by the user, the emotion engine analyzes the user's facial expressions and voice in real time, thereby recognizing the user's emotional state.

[0496] Emotion-Based Optimization

[0497] Based on the emotions recognized, renovation plans are dynamically optimized: for example, if a user expresses dissatisfaction with a particular design, alternative design ideas are instantly suggested.

[0498] Providing local information

[0499] The server also collects information on job openings and public facilities in the designated area, allowing users to obtain comprehensive information on their living environment after relocating.

[0500] Final display of information

[0501] Finally, all the information collected by the server (vacant house lists, renovation plans, emotion-based optimization plans, and local information) is visually displayed on the user's smart glasses or head-mounted display.

[0502] Specific use cases

[0503] For example, suppose a 35-year-old male engineer is looking for a 3LDK apartment in Tokyo with a budget of less than 50 million yen. In this case, the user might use the following prompt:

[0504] "User Information:

[0505] Age: 35

[0506] Gender: Male

[0507] Occupation: Engineer

[0508] Desired layout: 3LDK

[0509] Preferred area: Tokyo

[0510] Budget: 50 million yen

[0511] Identify vacant properties that fit your criteria, generate renovation plans, and suggest new plans when users express dissatisfaction with the sentiment engine.

[0512] Based on these prompts, the server identifies vacant properties and generates renovation plans. When the user reviews the proposed plans on a wearable visual display, the emotion engine reads the user's emotions from their facial expressions and voice and provides optimized design proposals in real time. It can also provide information on job openings and public facilities in the specified area.

[0513] This allows users to efficiently obtain renovation plans customized based on their emotions and information about their living environment after moving.

[0514] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0515] Step 1: Enter your basic information and residential conditions

[0516] The user wears smart glasses or a head-mounted display and uses voice commands or gestures to input information such as age, gender, occupation, desired layout, desired area, budget, etc. This input information is then sent from the user terminal to the server.

[0517] Input: User's basic information and housing requirements (age, gender, occupation, desired layout, area, budget)

[0518] Output: User information sent to the server

[0519] Step 2: Receive user information and search the real estate database

[0520] The server searches the real estate database based on the received user information to identify properties that meet the user's criteria. This process involves generating an SQL query to search the database.

[0521] Input: User information sent to the server

[0522] Output: List of properties that match the criteria

[0523] Step 3: Generate renovation plans

[0524] Based on the identified property information, the server runs a generative AI model to generate a renovation plan, which inputs the property information as prompts and outputs a 3D image of the interior and a detailed cost breakdown.

[0525] Input: List of properties that match your criteria

[0526] Output: Renovation plan generated by the AI ​​model (3D image, cost breakdown)

[0527] Step 4: Visualize your renovation plans

[0528] The generated renovation plan is visually displayed on the user's smart glasses or head-mounted display using an AR library.

[0529] Input: Generated renovation plan (3D image, cost details)

[0530] Output: Renovation plan displayed on a visual display

[0531] Step 5: Recognize the user's emotions

[0532] While the user is reviewing the renovation plan, the emotion engine uses the camera and microphone built into the smart glasses or head-mounted display to analyze the user's facial expressions and voice in real time and recognize the user's emotional state.

[0533] Input: User facial and voice data

[0534] Output: Recognized emotional state of the user

[0535] Step 6: Optimize your renovation plan based on emotions

[0536] The server dynamically optimizes renovation plans based on the recognized emotions. For example, if a user expresses dissatisfaction with a particular interior design, the server will again drive the generative AI model to generate and display alternative plans.

[0537] Input: Recognized user emotional state, original renovation plan

[0538] Output: Emotionally optimized renovation plan

[0539] Step 7: Gather local information

[0540] The server collects job listings and public facility information for a specified area, which includes performing queries against a local job database and a local public facility database.

[0541] Input: specified region

[0542] Output: Collected job and public facility information

[0543] Step 8: View the collected information and optimized plan

[0544] The server displays the collected local information and optimized renovation plans on the user's smart glasses or head-mounted display in a visually easy-to-understand format.

[0545] Input: Collected local information and optimized renovation plans

[0546] Output: Local information and renovation plans displayed on a visual display

[0547] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0548] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0549] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0550] [Second embodiment]

[0551] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0552] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0553] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0554] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0555] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0556] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0557] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0558] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0559] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0560] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0561] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0562] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0563] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and generates a renovation plan. It also provides job information and public facility information for the specified area. Specific embodiments are described below.

[0564] System Overview

[0565] Enter user information

[0566] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[0567] Data collection

[0568] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[0569] Renovation plan generation

[0570] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[0571] Regional information provision

[0572] The server also collects job listings and public facility information for the specified area, which is obtained by querying a local job database and a local public facility database.

[0573] Information display

[0574] Finally, the server sends all the collected information (vacant house list, renovation plans, local information) to the user's device, which displays this information in a visually easy-to-understand format.

[0575] Specific examples

[0576] Below is a concrete example of how this system works in practice.

[0577] 1. When a user enters information

[0578] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[0579] 2. When sending data to the server

[0580] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[0581] 3. When a vacant house is identified

[0582] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[0583] 4. When a renovation plan is generated

[0584] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[0585] 5. When local information is provided

[0586] The server collects local information for Tokyo, including information on local job openings and public facilities (schools, hospitals, parks, etc.).

[0587] 6. When information is displayed to the user

[0588] Ultimately, all this information is sent from the server to the user's device, which displays a list of vacant homes, details of renovation plans, local job listings, and information about public facilities in a visually easy-to-understand format.

[0589] This system allows users to easily find the housing and renovation plan that best suits their needs, and provides comprehensive support for life planning after moving in. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[0590] The processing flow will be explained below.

[0591] Step 1:

[0592] A user starts the application and enters basic information and housing requirements.

[0593] The user enters detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[0594] Step 2:

[0595] The terminal temporarily stores the user's input information and sends it to the server.

[0596] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[0597] Step 3:

[0598] The server receives the information from the user and searches a real estate database.

[0599] The server generates an SQL query based on the received information and extracts vacant properties from the database that match conditions such as the desired area, budget, and floor plan.

[0600] Step 4:

[0601] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[0602] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[0603] Step 5:

[0604] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[0605] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[0606] Step 6:

[0607] The server collects job information and public facility information for a specified area.

[0608] The server queries the local job and public facility databases and compiles the collected information, specifically, local job listings and public facilities such as schools, hospitals, and parks.

[0609] Step 7:

[0610] The server sends all information (vacant house list, renovation plan, local information) to the user's device.

[0611] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[0612] Step 8:

[0613] The terminal formats and displays the information it receives.

[0614] The terminal organizes the received detailed information on vacant houses, renovation plans, local job listings and information on public facilities, and displays it to the user in a visually easy-to-understand format.

[0615] ---

[0616] The above processing flow allows users to easily find vacant properties and renovation plans that suit their needs, and also to obtain comprehensive information necessary for life planning after moving in. This system contributes to the effective use of vacant properties and regional revitalization.

[0617] Example 1

[0618] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0619] Currently, the process of users finding a new home, renovating it, and planning their life in that area requires a lot of manual work, which is extremely time-consuming and labor-intensive. There is a need for a system that can streamline this process and allow users to quickly find the home and renovation plan that is best suited to them, as well as information about the area they are moving to.

[0620] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0621] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate a renovation plan for the identified property, means for using prompt text including the content of the generated renovation plan, means for collecting information on job openings and public facilities in the specified area, and means for displaying the collected information and the generated plan on the user's terminal. This allows a user to easily find a home that suits them, obtain specific and detailed renovation plans for that home, and simultaneously obtain comprehensive information on the living environment of the relocation destination.

[0622] "Basic information" refers to personal attribute information of a user, such as name, age, sex, occupation, and other information for identifying the user.

[0623] "Housing conditions" refer to conditions related to the housing desired by the user, and include specific requirements such as floor plan, area, and budget.

[0624] A "real estate database" refers to a database system that stores and allows searching of property information from across the country.

[0625] A "generative AI model" refers to a program that uses artificial intelligence technology to analyze data and generate renovation plans.

[0626] A "prompt" refers to text that contains instructions or questions given to a generative AI model.

[0627] "Job Information" means information about employment opportunities in a designated area.

[0628] "Public facility information" refers to information about public facilities such as schools, hospitals, and parks located in a designated area.

[0629] The system aims to help users plan their future life in their new home by providing information on job openings and public facilities in the area, based on the user's basic information and housing requirements.

[0630] First, when a user starts the application, a screen appears where they can enter basic information (such as name, age, gender, and occupation) and desired housing conditions (such as floor plan, area, and budget). The user enters this information, and the device sends the input information to the server in JSON format.

[0631] Based on the received information, the server generates an SQL query for the real estate database and filters the nationwide vacant house data based on the conditions. The server performs the search using a database management system (e.g., MySQL). For example, it identifies vacant properties that meet the conditions "Tokyo," "under 50 million yen," and "3LDK."

[0632] Next, the information about the identified vacant property is input into a generative AI model (e.g., OpenAI GPT-4) to generate a renovation plan. The prompt sent to the generative AI model is as follows:

[0633] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[0634] The generated renovation plan includes interior design images and detailed cost breakdowns, allowing users to visualize the specific renovation process.

[0635] Additionally, the server collects job listings and public accommodation information for the specified area by querying a local job database (e.g., Indeed API) and collecting public accommodation information as well. For example, it executes an API query like this:

[0636] python

[0637] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[0638] The server sends this information to the user's device, which then displays it in a visually easy-to-understand format using HTML5 and CSS3. Users can easily view a list of vacant homes, details of renovation plans, local job listings, and information on public facilities.

[0639] As a specific example, suppose a user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen). Based on this information, the server searches a real estate database using the criteria "Tokyo," "under 50 million yen," and "3LDK," and inputs the information on identified vacant properties into a generative AI model to generate a renovation plan. The generated plan includes a design for an open kitchen with an expanded living room and a detailed cost breakdown. The server then collects job information and public facility information for the specified area and sends all of this information to the device. The device displays this information in an easy-to-understand format, allowing the user to obtain all the information they need.

[0640] This system allows users to efficiently find the most suitable housing and renovation plan, and provides comprehensive support for life planning after relocating. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[0641] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0642] Step 1: Enter your user information

[0643] When a user launches the application, a screen appears where they can enter their basic information and housing requirements. Specifically, the user enters information such as their name, age, gender, occupation, desired layout, area, and budget. The input data is converted to JSON format and is ready to be sent to the server in the next step.

[0644] Input: Name, age, gender, occupation, floor plan, area, budget

[0645] Output: User information in JSON format

[0646] Step 2: Sending data to the server

[0647] The terminal receives the information entered by the user and sends it to the server in the form of an HTTP POST request, which the server receives and begins preparing a database search.

[0648] Input: User information in JSON format

[0649] Output: HTTP POST request to the server

[0650] Specific behavior:

[0651] When the user presses the "Submit" button, the device sends an HTTP POST request to the server that looks like this:

[0652] http

[0653] POST / submit-user-info HTTP / 1.1

[0654] Host: example.com

[0655] Content-Type: application / json

[0656] {

[0657] "name": "Yamada Taro",

[0658] "age": 35,

[0659] "gender": "male",

[0660] "occupation": "teacher",

[0661] "layout": "3LDK",

[0662] "region": "Tokyo",

[0663] "budget": 5000

[0664] }

[0665] Step 3: Search for vacant properties

[0666] The server executes an SQL query against the real estate database based on the received user information. The query is generated based on the user's criteria and identifies properties that match the criteria from nationwide vacant home data. This generates a list of properties that match the criteria.

[0667] Input: User information in JSON format

[0668] Output: List of properties that match the criteria (SQL query results)

[0669] Specific behavior:

[0670] The server generates an SQL query like this and runs it against the real estate database:

[0671] sql

[0672] SELECT FROM properties WHERE region='Tokyo' AND price <= 50000000 AND layout='3LDK';

[0673] The results obtained from the database are organized in a list format and passed to the next step.

[0674] Step 4: Generate a renovation plan

[0675] Based on the information on the identified vacant property, the server inputs a prompt statement into the generative AI model to generate a renovation plan. This prompt statement contains specific renovation requests, and the AI ​​model automatically generates a plan based on that.

[0676] Input: List of properties that match the criteria, prompt text

[0677] Output: Generated renovation plan

[0678] Specific behavior:

[0679] The server sends the following prompt to the generative AI model:

[0680] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[0681] The AI ​​model generates a renovation plan and returns the results to the server, including interior design images and cost breakdowns.

[0682] Step 5: Gather local information

[0683] The server collects job information and public facility information for the specified area by issuing API queries to the local job database and public facility database to obtain the required information.

[0684] Input: User's desired region information

[0685] Output: Local job information, public facility information

[0686] Specific behavior:

[0687] The server sends the following request to the local jobs API:

[0688] python

[0689] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[0690] Similarly, API queries are issued to collect public facility information and retrieve data.

[0691] Step 6: Sending information to the device and displaying it

[0692] The server then sends all the collected information (vacant house lists, renovation plans, and local information) to the user's device, which receives it and displays it in a visually easy-to-understand format.

[0693] Input: Vacant house list, renovation plan, local information

[0694] Output: Final display data to the terminal

[0695] Specific behavior:

[0696] The server sends the following HTTP response to the device:

[0697] http

[0698] HTTP / 1.1 200 OK

[0699] Content-Type: application / json

[0700] {

[0701] "properties": [...],

[0702] "renovation_plan": {...},

[0703] "jobs": [...],

[0704] "public_facilities": {...}

[0705] }

[0706] The device visually displays the received data using HTML5 and CSS3, making it easy for users to view.

[0707] Through a step-by-step process, the system can provide users with the best available vacant properties and renovation plans, as well as comprehensive information on living in the designated area.

[0708] (Application example 1)

[0709] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0710] Conventional real estate search systems were limited to identifying properties based on user-specified criteria, and lacked the ability to generate renovation plans or provide local information. Furthermore, there was no way to provide users with property search results, renovation plans, and local information in a visually easy-to-understand format. Furthermore, when properties were being shown in physical stores, it was difficult for users to immediately grasp detailed information and renovation plans. These issues made it difficult for users to select the appropriate property and determine the appropriate renovation plan.

[0711] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0712] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate renovation plans for the identified properties, means for collecting job information and public facility information for a specified area, means for displaying the collected information and the generated plans on the user's terminal, and means for displaying the collected information and the generated plans in augmented reality through smart glasses. This allows users to visually check specific property information, renovation plans, and local information using augmented reality even in physical stores.

[0713] "User basic information" refers to personal data provided by the user, including information such as age, gender, occupation, and contact details.

[0714] "Housing conditions" refer to the specifications and characteristics of the property desired by the user, such as floor plan, budget, location, and facilities.

[0715] A "real estate database" is a database system that registers property information from all over the country, and includes data such as property addresses, prices, floor plans, and photos.

[0716] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to generate new information or plans from data.

[0717] "Job Information" means information about employment opportunities and job postings in a specified area, including data such as job type, salary, and location.

[0718] "Public facility information" refers to information about public infrastructure and service facilities within a specific area, such as schools, hospitals, parks, and libraries.

[0719] "Smart glasses" are wearable devices equipped with augmented reality technology, and are glasses-type terminals with built-in displays.

[0720] "Augmented reality" is a technology that overlays digital information onto the real environment, displaying virtual information alongside real objects in the user's field of vision.

[0721] A "renovation plan" is a plan for renovating and remodeling an existing building, and includes blueprints, interior design drawings, and cost details.

[0722] "Means for displaying information in a visually easy-to-understand manner" refers to methods and tools for providing information graphically so that users can easily understand the information, and is a display means that includes diagrams and image illustrations.

[0723] The present invention provides a system that allows users to visually check property information and renovation plans in a physical store using smart glasses. Specific embodiments are described in detail below.

[0724] System Program and Processing Overview

[0725] The server uses voice and gesture recognition technology to input the user's basic information and living conditions. The user puts on the smart glasses and inputs their conditions through voice commands or gestures. This information is then sent from the smart glasses to the server.

[0726] The server uses the received information to search a nationwide real estate database and identify properties that meet the user's criteria. The search results include the property's address, price, floor plan, photos, and more.

[0727] The server runs a generative AI model to generate a renovation plan for the identified property. The generative AI model automatically generates a renovation plan based on the input property information, providing interior image drawings and detailed cost breakdowns.

[0728] The server then queries a relevant database to gather job and public facility information for the specified area, providing detailed information about employment opportunities and public infrastructure in the area.

[0729] The collected information and generated plans are displayed on the user's device (smart glasses), which uses augmented reality technology to visually display property details, renovation plans, and local information.

[0730] This allows users to use augmented reality to check detailed property information, renovation plans, and local information even in physical stores, and even make specific decisions on the spot.

[0731] Hardware and software used

[0732] Hardware: Smart glasses (e.g. Microsoft HoloLens)

[0733] Software: AR libraries (e.g., ARCore, ARKit), cloud databases (e.g., Firebase, AWS), generative AI models (e.g., GPT-4)

[0734] Natural language explanation of the process

[0735] The server uses a voice recognition engine (e.g., Google Speech-to-Text) and gesture recognition (e.g., OpenCV) to collect data from users entering basic information and housing requirements. This information is sent to the cloud and searched through a nationwide real estate database. The search results include basic information such as the property's address, floor plan, price, and photos.

[0736] The server inputs the acquired property information into a generative AI model to generate a renovation plan. Using a generative AI model (e.g., GPT-4), a renovation plan is automatically generated based on the user's criteria, and interior design drawings and detailed cost estimates are provided.

[0737] Additionally, the server retrieves job and public facility information for the specified area from a relational database, allowing the user to view information about job opportunities and public services in the area.

[0738] This information is sent to the smart glasses and displayed visually using the AR library, allowing users to intuitively understand detailed property information and renovation plans even in a physical store.

[0739] Examples of concrete examples and prompts

[0740] Example: A user can wear smart glasses in a physical store and input voice commands such as "Tell me about 3LDK properties," "Show me renovation plans for open kitchens," and "Show me information about nearby hospitals," and appropriate property information, renovation plans, and local information will be displayed using AR.

[0741] Prompt Sentence Examples

[0742] "Tell me about a 3LDK property."

[0743] "I'd like to see your open kitchen renovation plan."

[0744] "Show me information about nearby hospitals"

[0745] These features improve the user experience and make property selection and renovation planning more efficient.

[0746] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0747] Step 1:

[0748] The user puts on the smart glasses and inputs basic information and housing requirements using voice commands and gestures. The glasses' built-in voice recognition engine (e.g., Google Speech-to-Text) and gesture recognition software (e.g., OpenCV) are used to capture voice and movement data. This provides input data such as age, gender, occupation, desired floor plan, desired area, and budget. This data is then sent from the device to a server.

[0749] Step 2:

[0750] The server performs a real estate database search based on the received user information. It generates an SQL query to filter the database and retrieve property listings that match the specified criteria. Input data includes the user's desired layout, area, and budget, and output data includes relevant property information (e.g., address, price, layout, and photos).

[0751] Step 3:

[0752] The server uses the acquired property information as input data for a generative AI model (e.g., GPT-4) to generate a renovation plan. The generative AI model analyzes the property's floor plan and photos, and automatically generates a renovation plan that meets the user's needs. The input data is the property information and the user's desired conditions, and the output data is the renovation plan (e.g., interior design drawings and detailed cost breakdowns).

[0753] Step 4:

[0754] The server queries a relational database to gather job and public facility information for a given area, using the user-specified area as input and providing information about job opportunities and public facilities (schools, hospitals, parks, etc.) in that area as output.

[0755] Step 5:

[0756] The server sends the collected information and generated renovation plans to the user's smart glasses. Specifically, it uses an AR library (e.g., ARCore, ARKit) to process the data to display the information in a visually understandable way. The input data is property information, renovation plans, and local information, and the output data is the AR content displayed on the smart glasses.

[0757] Step 6:

[0758] The device receives the transmitted data and displays it in augmented reality on the smart glasses' display. Property details, renovation plans, and local information are superimposed on the user's field of vision, allowing the user to see the property's image and renovation possibilities in real time.

[0759] This series of processes allows users to intuitively check detailed property information, renovation plans, and local information even in physical stores using augmented reality technology.

[0760] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0761] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments are described below.

[0762] System Overview

[0763] Enter user information

[0764] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[0765] Data collection

[0766] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[0767] Renovation plan generation

[0768] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[0769] Emotion recognition by emotion engine

[0770] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to evaluate their satisfaction and stress level.

[0771] Emotion-Based Optimization

[0772] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[0773] Regional information provision

[0774] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[0775] Information display

[0776] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[0777] Specific examples

[0778] Below is a concrete example of how this system works in practice.

[0779] 1. When a user enters information

[0780] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[0781] 2. When sending data to the server

[0782] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[0783] 3. When a vacant house is identified

[0784] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[0785] 4. When a renovation plan is generated

[0786] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[0787] 5. When the emotion engine recognizes the user's emotions

[0788] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[0789] 6. Optimizing your renovation plan based on emotions

[0790] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[0791] 7. When local information is provided

[0792] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[0793] 8. When information is displayed to the user

[0794] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[0795] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[0796] The processing flow will be explained below.

[0797] Step 1:

[0798] A user starts the application and enters basic information and housing requirements.

[0799] Users enter detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[0800] Step 2:

[0801] The terminal temporarily stores the user's input information and sends it to the server.

[0802] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[0803] Step 3:

[0804] The server receives the information from the user and searches a real estate database.

[0805] The server generates an SQL query based on the received information and extracts vacant properties from the database that match the desired area, budget, and floor plan.

[0806] Step 4:

[0807] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[0808] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[0809] Step 5:

[0810] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[0811] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[0812] Step 6:

[0813] The emotion engine recognizes the user's emotions.

[0814] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice in real time to assess their happiness or dissatisfaction.

[0815] Step 7:

[0816] Optimize renovation plans based on an emotion engine.

[0817] Based on the emotions recognized, the system evaluates the user's preferences and stress level and suggests modifications to the renovation plan accordingly. For example, if the user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design.

[0818] Step 8:

[0819] The server collects job information and public facility information for a specified area.

[0820] The server queries the job and public facility databases for the area and compiles the collected information. Specifically, it retrieves information on local jobs and public facilities such as schools, hospitals, and parks. The emotion engine takes into account the user's preferences and stress level and provides the most appropriate local information based on the results.

[0821] Step 9:

[0822] The server sends all information (vacant house list, renovation plan, emotion-based optimization plan, local information) to the user's device.

[0823] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[0824] Step 10:

[0825] The terminal formats and displays the information it receives.

[0826] The device organizes the received information about vacant houses, renovation plans, suggested revisions to the plans based on emotions, local job information, and information about public facilities, and displays it to the user in a visually easy-to-understand format.

[0827] ---

[0828] This detailed processing flowchart allows users to easily find the best vacant property and renovation plan, and furthermore, by utilizing the emotion engine, they can select a home that will give them the highest level of satisfaction. Furthermore, they can obtain comprehensive information necessary for planning their life after moving. This system will greatly contribute to the effective use of vacant properties and regional revitalization.

[0829] Example 2

[0830] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0831] Conventional housing selection and renovation plan generation systems lack the ability to recognize the user's emotional state and optimize the plan based on that, making it difficult to maximize user satisfaction. Furthermore, they lacked a means to provide comprehensive local information, resulting in insufficient information for selecting a relocation destination. This made it difficult for users to select the optimal housing that best suited their needs and emotions.

[0832] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0833] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving an artificial intelligence model to generate a renovation plan for the identified property, means for analyzing the user's facial expressions and voice to recognize their emotional state, means for optimizing the renovation plan based on the recognized emotional state, means for collecting job information and public facility information in a specified area, and means for displaying the collected information and the generated plan on the user's terminal. This makes it possible to provide an optimal renovation plan based on the user's emotional state and comprehensive local information.

[0834] "User information" is data including the user's basic information and desired housing conditions.

[0835] "Housing conditions" include the layout, area, budget, and other conditions of the property desired by the user.

[0836] A "terminal" is a device through which a user inputs information and receives information from a server.

[0837] A "server" is a computer system that receives user information, searches the database, and generates renovation plans.

[0838] The "real estate database" is a database that stores information on vacant houses and properties across the country.

[0839] An "SQL query" is a Structured Query Language command issued to a database to perform a search.

[0840] A "generative AI model" is an artificial intelligence model that generates renovation plans based on input data.

[0841] A "renovation plan" is a detailed plan including proposed interior design drawings and cost breakdowns for a specified property.

[0842] An "emotion engine" is a software engine that has the function of analyzing a user's facial expressions and voice and recognizing their emotional state.

[0843] "Emotional state" refers to a user's psychological state, such as their satisfaction level or stress level.

[0844] A "job database" is a database that stores job information for a specified area.

[0845] The "public facility database" is a database that stores information on public facilities such as schools, hospitals, and parks in a specified area.

[0846] "Regional information" is data including job information and public facility information related to a specified region.

[0847] "Means for displaying information in a visually easy-to-understand manner" is a function for displaying information in a format that is easily understandable to the user.

[0848] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments of the present invention are described below.

[0849] System Overview

[0850] Enter user information

[0851] When a user starts the application, a screen appears on the device where the user can enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[0852] Data collection

[0853] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[0854] Renovation plan generation

[0855] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[0856] Emotion recognition by emotion engine

[0857] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to assess their satisfaction and stress level.

[0858] Emotion-Based Optimization

[0859] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[0860] Regional information provision

[0861] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[0862] Information display

[0863] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[0864] Specific examples

[0865] Below is a concrete example of how this system works in practice.

[0866] 1. When a user enters information

[0867] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[0868] 2. When sending data to the server

[0869] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[0870] 3. When a vacant house is identified

[0871] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[0872] 4. When a renovation plan is generated

[0873] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[0874] 5. When the emotion engine recognizes the user's emotions

[0875] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[0876] 6. Optimizing your renovation plan based on emotions

[0877] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[0878] 7. When local information is provided

[0879] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[0880] 8. When information is displayed to the user

[0881] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[0882] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[0883] Examples of prompt statements

[0884] "Please suggest the best renovation plan and local information for a user who is a woman in her 30s looking for a 3LDK property in Tokyo with a budget of 50 million yen or less."

[0885] The above is a specific embodiment of the present invention.

[0886] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0887] Step 1:

[0888] The user starts the application.

[0889] Input: Nothing in particular.

[0890] Action: A user taps an application on their device to launch it.

[0891] Output: The application's welcome screen is displayed.

[0892] Step 2:

[0893] The terminal displays a screen for the user to input basic information and desired housing conditions.

[0894] Input: None (based on application default settings).

[0895] How it works: The device displays a form for entering basic information and housing requirements.

[0896] Output: The user input form (name, age, gender, floor plan, area, budget, etc.) is displayed on the screen.

[0897] Step 3:

[0898] The user enters basic information and desired housing conditions.

[0899] Input: Name, age, gender, desired layout (e.g. 3LDK), desired area (e.g. Tokyo), budget (e.g. 50 million yen).

[0900] What happens: A user enters information into a form and taps the "Submit" button.

[0901] Output: The entered information is saved on the device.

[0902] Step 4:

[0903] The terminal transmits the input information to the server.

[0904] Input: Basic information and housing requirements entered by the user.

[0905] Operation: The device converts the input information into JSON format and sends it to the server.

[0906] Output: The server stores the received user information in a database.

[0907] Step 5:

[0908] Based on the user information received by the server, an SQL query is generated to search the real estate database.

[0909] Input: User's basic information and living conditions.

[0910] What it does: The server generates an SQL query of the form "SELECT FROM real estate database WHERE...".

[0911] Output: The generated SQL query.

[0912] Step 6:

[0913] The server runs SQL queries against a real estate database to identify vacant properties that meet the criteria.

[0914] Input: The generated SQL query.

[0915] How it works: The server queries the database to retrieve a list of available properties that fit the criteria.

[0916] Output: A list of identified vacant properties.

[0917] Step 7:

[0918] The server inputs the identified vacant house information into the generative AI model.

[0919] Input: Information about the identified vacant house.

[0920] How it works: The server inputs vacant house information into the generative AI model along with the prompt, "Please propose a renovation plan based on the user's requests."

[0921] Output: The prompt sentence and vacant house information input to the generative AI model.

[0922] Step 8:

[0923] The generative AI model generates a renovation plan (interior image and detailed cost breakdown).

[0924] Input: Prompt statement and vacant house information.

[0925] How it works: A generative AI model builds renovation plans, producing interior design images and a breakdown of the costs involved.

[0926] Output: The generated renovation plan.

[0927] Step 9:

[0928] The server temporarily saves the generated renovation plan.

[0929] Input: Generated renovation plan.

[0930] How it works: The server stores the generated plan in a temporary database.

[0931] Output: Renovation plans saved in a temporary database.

[0932] Step 10:

[0933] The user views the proposed renovation plan.

[0934] Input: Generated renovation plan.

[0935] Operation: The device displays the plan information received from the server.

[0936] Output: Renovation plan displayed on the device.

[0937] Step 11:

[0938] The emotion engine analyzes the user's facial expressions and voice to recognize their emotional state (satisfaction, stress level).

[0939] Input: User's facial expression video and audio data.

[0940] How it works: The emotion engine uses real-time facial recognition and voice analysis to assess emotional state.

[0941] Output: Emotional state (e.g., satisfaction level, dissatisfaction level).

[0942] Step 12:

[0943] The emotion engine sends the emotional state to the server.

[0944] Input: Evaluated emotional state.

[0945] How it works: The emotion engine sends the emotional state in JSON format to the server.

[0946] Output: Emotional state sent to the server.

[0947] Step 13:

[0948] Based on the emotional state received by the server, correction conditions are input into the generative AI model to generate a new renovation plan.

[0949] Input: Emotional state data, vacant house information.

[0950] How it works: The server inputs the prompt statement "The user is dissatisfied, so please propose a different renovation plan" and the correction conditions into the generative AI model.

[0951] Output: The modified conditions and prompt sentences fed into the generative AI model.

[0952] Step 14:

[0953] The generative AI model generates a revised renovation plan.

[0954] Input: Prompt statement and correction condition.

[0955] How it works: A generative AI model builds new renovation plans, generating new interior renderings and revised cost breakdowns.

[0956] Output: The newly generated renovation plan.

[0957] Step 15:

[0958] The server transmits the revised renovation plan to the user's terminal.

[0959] Input: Revised renovation plan.

[0960] How it works: The server sends a remediation plan in JSON format to the user's device.

[0961] Output: The revised renovation plan sent to the device.

[0962] Step 16:

[0963] The server generates an SQL query to search the local job database and public facility database based on the user's desired area.

[0964] Input: User's preferred region data.

[0965] What it does: The server generates SQL queries of the form "SELECT FROM job database WHERE region=..." and "SELECT FROM utility database WHERE region=...".

[0966] Output: The generated SQL query.

[0967] Step 17:

[0968] The server runs SQL queries to retrieve job listings and public facility information.

[0969] Input: The generated SQL query.

[0970] How it works: The server runs SQL queries against the database to retrieve a list of jobs and public accommodations.

[0971] Output: A list of the job and public facility information retrieved.

[0972] Step 18:

[0973] The server temporarily saves the acquired regional information.

[0974] Input: Retrieved job information and public facility information.

[0975] How it works: The server stores the location information in a temporary database.

[0976] Output: Region information stored in a temporary database.

[0977] Step 19:

[0978] The emotion engine takes into account the user's stress level and selects the most appropriate local information.

[0979] Input: Retrieved local information, user's stress level.

[0980] How it works: The emotion engine selects local information based on stress levels and creates a candidate list.

[0981] Output: A list of selected locality candidates.

[0982] Step 20:

[0983] The server finally sends all the information (vacant house list, renovation plan, emotion-based optimization plan, and local information) to the user's device.

[0984] Input: vacant home listings, renovation plans, sentiment-based plans, local information.

[0985] How it works: The server aggregates the information and sends it to the user's device in JSON format.

[0986] Output: Comprehensive information sent to the terminal.

[0987] Step 21:

[0988] The device displays this information in a visually easy-to-understand format.

[0989] Input: General information sent from the server.

[0990] Operation: The device displays information using a UI (user interface).

[0991] Output: A list of available properties, renovation plans, sentiment-based plan revision suggestions, and local information presented in a visually easy-to-understand format.

[0992] (Application example 2)

[0993] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0994] Conventional renovation plan generation systems identify suitable properties based on the user's basic information and living conditions, and then provide a renovation plan. However, they are unable to optimize the plan to reflect the user's emotions or provide visual confirmation using 3D models, making it difficult to increase user satisfaction. Furthermore, they are also inadequate in providing information about life after relocation (job information and public facility information). Therefore, there is a need for a system that can dynamically optimize renovation plans based on the user's emotions, enable visual confirmation using AR technology, and also provide local information.

[0995] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic information and housing conditions; means for receiving the input information; means for searching a nationwide real estate database based on the received information to identify properties that meet the user's conditions; means for driving a generative model to generate a renovation plan for the identified property; means for visually displaying the generated renovation plan on a visual display worn by the user; means for recognizing the user's emotions in real time using an emotion engine; means for optimizing the renovation plan based on the recognized emotions; means for collecting employment information and public facility information for a specified area; and means for displaying the collected information and the generated plan on the user's terminal. This allows the user to visually confirm the renovation plan optimized based on their emotions while also obtaining local information all at once.

[0996] "Basic information of the user" includes information such as the user's age, sex, occupation, desired floor plan, desired area, and budget.

[0997] "Housing conditions" are conditions such as floor plan, area, budget, etc. related to the housing desired by the user.

[0998] The "means for inputting" refers to a means for the user to input the basic information and residential conditions described above, and includes voice recognition, gesture input, and the like.

[0999] The "receiving means" is a means by which the server receives information input by the user.

[1000] A "real estate database" is a database that stores information on vacant houses and data related to real estate properties.

[1001] A "generative model" is a model that uses artificial intelligence to automatically generate renovation plans.

[1002] A "visual display" is a display device worn by a user, such as smart glasses or a head-mounted display.

[1003] The "emotion engine" is an engine that analyzes the user's facial expressions and voice in real time to recognize the user's emotional state.

[1004] The "means for recognizing" is a means for recognizing the user's emotions in real time using an emotion engine.

[1005] The "optimizing means" is a means for dynamically optimizing the renovation plan based on the recognized sentiment.

[1006] "Employment Information" means job information in a designated area.

[1007] "Public facility information" is information about public facilities such as schools, hospitals, and parks in a designated area.

[1008] "Means of collection" means the means for collecting employment information and public facilities information for the designated area.

[1009] The "display means" is a means for displaying the collected information and the generated plan on the user's terminal.

[1010] A "terminal" is a device used by a user, such as a smartphone or tablet.

[1011] The present invention is a system that allows users to input their basic information and housing requirements, and then identifies the most suitable vacant property based on that information and generates a renovation plan.The system also incorporates an emotion engine, which can optimize the renovation plan based on the user's emotions and provide local information.Specific embodiments for implementing the present invention are described below.

[1012] Entering user information

[1013] Users wear smart glasses or a head-mounted display and use voice commands or gestures to input their basic information (age, gender, occupation, etc.) and housing requirements (floor plan, area, budget, etc.). This information is then sent from the user device to the server.

[1014] Receiving and retrieving data

[1015] The server searches a nationwide real estate database based on the received user information, thereby identifying properties that meet the user's criteria.

[1016] Generate renovation plans

[1017] The server inputs the identified property information into a generative AI model and automatically generates a renovation plan, which includes a 3D image of the interior and a detailed breakdown of costs.

[1018] Emotion recognition by emotion engine

[1019] Using the camera and microphone built into the smart glasses or head-mounted display worn by the user, the emotion engine analyzes the user's facial expressions and voice in real time, thereby recognizing the user's emotional state.

[1020] Emotion-Based Optimization

[1021] Based on the emotions recognized, renovation plans are dynamically optimized: for example, if a user expresses dissatisfaction with a particular design, alternative design ideas are instantly suggested.

[1022] Providing local information

[1023] The server also collects information on job openings and public facilities in the designated area, allowing users to obtain comprehensive information on their living environment after relocating.

[1024] Final display of information

[1025] Finally, all the information collected by the server (vacant house lists, renovation plans, emotion-based optimization plans, and local information) is visually displayed on the user's smart glasses or head-mounted display.

[1026] Specific use cases

[1027] For example, suppose a 35-year-old male engineer is looking for a 3LDK apartment in Tokyo with a budget of less than 50 million yen. In this case, the user might use the following prompt:

[1028] "User Information:

[1029] Age: 35

[1030] Gender: Male

[1031] Occupation: Engineer

[1032] Desired layout: 3LDK

[1033] Preferred area: Tokyo

[1034] Budget: 50 million yen

[1035] Identify vacant properties that fit your criteria, generate renovation plans, and suggest new plans when users express dissatisfaction with the sentiment engine.

[1036] Based on these prompts, the server identifies vacant properties and generates renovation plans. When the user reviews the proposed plans on a wearable visual display, the emotion engine reads the user's emotions from their facial expressions and voice and provides optimized design proposals in real time. It can also provide information on job openings and public facilities in the specified area.

[1037] This allows users to efficiently obtain renovation plans customized based on their emotions and information about their living environment after moving.

[1038] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1039] Step 1: Enter your basic information and residential conditions

[1040] The user wears smart glasses or a head-mounted display and uses voice commands or gestures to input information such as age, gender, occupation, desired layout, desired area, budget, etc. This input information is then sent from the user terminal to the server.

[1041] Input: User's basic information and housing requirements (age, gender, occupation, desired layout, area, budget)

[1042] Output: User information sent to the server

[1043] Step 2: Receive user information and search the real estate database

[1044] The server searches the real estate database based on the received user information to identify properties that meet the user's criteria. This process involves generating an SQL query to search the database.

[1045] Input: User information sent to the server

[1046] Output: List of properties that match the criteria

[1047] Step 3: Generate renovation plans

[1048] Based on the identified property information, the server runs a generative AI model to generate a renovation plan, which inputs the property information as prompts and outputs a 3D image of the interior and a detailed cost breakdown.

[1049] Input: List of properties that match your criteria

[1050] Output: Renovation plan generated by the AI ​​model (3D image, cost breakdown)

[1051] Step 4: Visualize your renovation plans

[1052] The generated renovation plan is visually displayed on the user's smart glasses or head-mounted display using an AR library.

[1053] Input: Generated renovation plan (3D image, cost details)

[1054] Output: Renovation plan displayed on a visual display

[1055] Step 5: Recognize the user's emotions

[1056] While the user is reviewing the renovation plan, the emotion engine uses the camera and microphone built into the smart glasses or head-mounted display to analyze the user's facial expressions and voice in real time and recognize the user's emotional state.

[1057] Input: User facial and voice data

[1058] Output: Recognized emotional state of the user

[1059] Step 6: Optimize your renovation plan based on emotions

[1060] The server dynamically optimizes renovation plans based on the recognized emotions. For example, if a user expresses dissatisfaction with a particular interior design, the server will again drive the generative AI model to generate and display alternative plans.

[1061] Input: Recognized user emotional state, original renovation plan

[1062] Output: Emotionally optimized renovation plan

[1063] Step 7: Gather local information

[1064] The server collects job listings and public facility information for a specified area, which includes performing queries against a local job database and a local public facility database.

[1065] Input: specified region

[1066] Output: Collected job and public facility information

[1067] Step 8: View the collected information and optimized plan

[1068] The server displays the collected local information and optimized renovation plans on the user's smart glasses or head-mounted display in a visually easy-to-understand format.

[1069] Input: Collected local information and optimized renovation plans

[1070] Output: Local information and renovation plans displayed on a visual display

[1071] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1072] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1073] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1074] [Third embodiment]

[1075] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1076] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1077] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1078] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1079] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1080] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1081] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1082] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1083] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1084] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1085] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1086] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1087] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and generates a renovation plan. It also provides job information and public facility information for the specified area. Specific embodiments are described below.

[1088] System Overview

[1089] Enter user information

[1090] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[1091] Data collection

[1092] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[1093] Renovation plan generation

[1094] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[1095] Regional information provision

[1096] The server also collects job listings and public facility information for the specified area, which is obtained by querying a local job database and a local public facility database.

[1097] Information display

[1098] Finally, the server sends all the collected information (vacant house list, renovation plans, local information) to the user's device, which displays this information in a visually easy-to-understand format.

[1099] Specific examples

[1100] Below is a concrete example of how this system works in practice.

[1101] 1. When a user enters information

[1102] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[1103] 2. When sending data to the server

[1104] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[1105] 3. When a vacant house is identified

[1106] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[1107] 4. When a renovation plan is generated

[1108] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[1109] 5. When local information is provided

[1110] The server collects local information for Tokyo, including information on local job openings and public facilities (schools, hospitals, parks, etc.).

[1111] 6. When information is displayed to the user

[1112] Ultimately, all this information is sent from the server to the user's device, which displays a list of vacant homes, details of renovation plans, local job listings, and information about public facilities in a visually easy-to-understand format.

[1113] This system allows users to easily find the housing and renovation plan that best suits their needs, and provides comprehensive support for life planning after moving in. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[1114] The processing flow will be explained below.

[1115] Step 1:

[1116] A user starts the application and enters basic information and housing requirements.

[1117] The user enters detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[1118] Step 2:

[1119] The terminal temporarily stores the user's input information and sends it to the server.

[1120] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[1121] Step 3:

[1122] The server receives the information from the user and searches a real estate database.

[1123] The server generates an SQL query based on the received information and extracts vacant properties from the database that match conditions such as the desired area, budget, and floor plan.

[1124] Step 4:

[1125] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[1126] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[1127] Step 5:

[1128] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[1129] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[1130] Step 6:

[1131] The server collects job information and public facility information for a specified area.

[1132] The server queries the local job and public facility databases and compiles the collected information, specifically, local job listings and public facilities such as schools, hospitals, and parks.

[1133] Step 7:

[1134] The server sends all information (vacant house list, renovation plan, local information) to the user's device.

[1135] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[1136] Step 8:

[1137] The terminal formats and displays the information it receives.

[1138] The terminal organizes the received detailed information on vacant houses, renovation plans, local job listings and information on public facilities, and displays it to the user in a visually easy-to-understand format.

[1139] ---

[1140] The above processing flow allows users to easily find vacant properties and renovation plans that suit their needs, and also to obtain comprehensive information necessary for life planning after moving in. This system contributes to the effective use of vacant properties and regional revitalization.

[1141] Example 1

[1142] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1143] Currently, the process of users finding a new home, renovating it, and planning their life in that area requires a lot of manual work, which is extremely time-consuming and labor-intensive. There is a need for a system that can streamline this process and allow users to quickly find the home and renovation plan that is best suited to them, as well as information about the area they are moving to.

[1144] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1145] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate a renovation plan for the identified property, means for using prompt text including the content of the generated renovation plan, means for collecting information on job openings and public facilities in the specified area, and means for displaying the collected information and the generated plan on the user's terminal. This allows a user to easily find a home that suits them, obtain specific and detailed renovation plans for that home, and simultaneously obtain comprehensive information on the living environment of the relocation destination.

[1146] "Basic information" refers to personal attribute information of a user, such as name, age, sex, occupation, and other information for identifying the user.

[1147] "Housing conditions" refer to conditions related to the housing desired by the user, and include specific requirements such as floor plan, area, and budget.

[1148] A "real estate database" refers to a database system that stores and allows searching of property information from across the country.

[1149] A "generative AI model" refers to a program that uses artificial intelligence technology to analyze data and generate renovation plans.

[1150] A "prompt" refers to text that contains instructions or questions given to a generative AI model.

[1151] "Job Information" means information about employment opportunities in a designated area.

[1152] "Public facility information" refers to information about public facilities such as schools, hospitals, and parks located in a designated area.

[1153] The system aims to help users plan their future life in their new home by providing information on job openings and public facilities in the area, based on the user's basic information and housing requirements.

[1154] First, when a user starts the application, a screen appears where they can enter basic information (such as name, age, gender, and occupation) and desired housing conditions (such as floor plan, area, and budget). The user enters this information, and the device sends the input information to the server in JSON format.

[1155] Based on the received information, the server generates an SQL query for the real estate database and filters the nationwide vacant house data based on the conditions. The server performs the search using a database management system (e.g., MySQL). For example, it identifies vacant properties that meet the conditions "Tokyo," "under 50 million yen," and "3LDK."

[1156] Next, the information about the identified vacant property is input into a generative AI model (e.g., OpenAI GPT-4) to generate a renovation plan. The prompt sent to the generative AI model is as follows:

[1157] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[1158] The generated renovation plan includes interior design images and detailed cost breakdowns, allowing users to visualize the specific renovation process.

[1159] Additionally, the server collects job listings and public accommodation information for the specified area by querying a local job database (e.g., Indeed API) and collecting public accommodation information as well. For example, it executes an API query like this:

[1160] python

[1161] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[1162] The server sends this information to the user's device, which then displays it in a visually easy-to-understand format using HTML5 and CSS3. Users can easily view a list of vacant homes, details of renovation plans, local job listings, and information on public facilities.

[1163] As a specific example, suppose a user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen). Based on this information, the server searches a real estate database using the criteria "Tokyo," "under 50 million yen," and "3LDK," and inputs the information on identified vacant properties into a generative AI model to generate a renovation plan. The generated plan includes a design for an open kitchen with an expanded living room and a detailed cost breakdown. The server then collects job information and public facility information for the specified area and sends all of this information to the device. The device displays this information in an easy-to-understand format, allowing the user to obtain all the information they need.

[1164] This system allows users to efficiently find the most suitable housing and renovation plan, and provides comprehensive support for life planning after relocating. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[1165] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1166] Step 1: Enter your user information

[1167] When a user launches the application, a screen appears where they can enter their basic information and housing requirements. Specifically, the user enters information such as their name, age, gender, occupation, desired layout, area, and budget. The input data is converted to JSON format and is ready to be sent to the server in the next step.

[1168] Input: Name, age, gender, occupation, floor plan, area, budget

[1169] Output: User information in JSON format

[1170] Step 2: Sending data to the server

[1171] The terminal receives the information entered by the user and sends it to the server in the form of an HTTP POST request, which the server receives and begins preparing a database search.

[1172] Input: User information in JSON format

[1173] Output: HTTP POST request to the server

[1174] Specific behavior:

[1175] When the user presses the "Submit" button, the device sends an HTTP POST request to the server that looks like this:

[1176] http

[1177] POST / submit-user-info HTTP / 1.1

[1178] Host: example.com

[1179] Content-Type: application / json

[1180] {

[1181] "name": "Yamada Taro",

[1182] "age": 35,

[1183] "gender": "male",

[1184] "occupation": "teacher",

[1185] "layout": "3LDK",

[1186] "region": "Tokyo",

[1187] "budget": 5000

[1188] }

[1189] Step 3: Search for vacant properties

[1190] The server executes an SQL query against the real estate database based on the received user information. The query is generated based on the user's criteria and identifies properties that match the criteria from nationwide vacant home data. This generates a list of properties that match the criteria.

[1191] Input: User information in JSON format

[1192] Output: List of properties that match the criteria (SQL query results)

[1193] Specific behavior:

[1194] The server generates an SQL query like this and runs it against the real estate database:

[1195] sql

[1196] SELECT FROM properties WHERE region='Tokyo' AND price <= 50000000 AND layout='3LDK';

[1197] The results obtained from the database are organized in a list format and passed to the next step.

[1198] Step 4: Generate a renovation plan

[1199] Based on the information on the identified vacant property, the server inputs a prompt statement into the generative AI model to generate a renovation plan. This prompt statement contains specific renovation requests, and the AI ​​model automatically generates a plan based on that.

[1200] Input: List of properties that match the criteria, prompt text

[1201] Output: Generated renovation plan

[1202] Specific behavior:

[1203] The server sends the following prompt to the generative AI model:

[1204] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[1205] The AI ​​model generates a renovation plan and returns the results to the server, including interior design images and cost breakdowns.

[1206] Step 5: Gather local information

[1207] The server collects job information and public facility information for the specified area by issuing API queries to the local job database and public facility database to obtain the required information.

[1208] Input: User's desired region information

[1209] Output: Local job information, public facility information

[1210] Specific behavior:

[1211] The server sends the following request to the local jobs API:

[1212] python

[1213] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[1214] Similarly, API queries are issued to collect public facility information and retrieve data.

[1215] Step 6: Sending information to the device and displaying it

[1216] The server then sends all the collected information (vacant house lists, renovation plans, and local information) to the user's device, which receives it and displays it in a visually easy-to-understand format.

[1217] Input: Vacant house list, renovation plan, local information

[1218] Output: Final display data to the terminal

[1219] Specific behavior:

[1220] The server sends the following HTTP response to the device:

[1221] http

[1222] HTTP / 1.1 200 OK

[1223] Content-Type: application / json

[1224] {

[1225] "properties": [...],

[1226] "renovation_plan": {...},

[1227] "jobs": [...],

[1228] "public_facilities": {...}

[1229] }

[1230] The device visually displays the received data using HTML5 and CSS3, making it easy for users to view.

[1231] Through a step-by-step process, the system can provide users with the best available vacant properties and renovation plans, as well as comprehensive information on living in the designated area.

[1232] (Application example 1)

[1233] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1234] Conventional real estate search systems were limited to identifying properties based on user-specified criteria, and lacked the ability to generate renovation plans or provide local information. Furthermore, there was no way to provide users with property search results, renovation plans, and local information in a visually easy-to-understand format. Furthermore, when properties were being shown in physical stores, it was difficult for users to immediately grasp detailed information and renovation plans. These issues made it difficult for users to select the appropriate property and determine the appropriate renovation plan.

[1235] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1236] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate renovation plans for the identified properties, means for collecting job information and public facility information for a specified area, means for displaying the collected information and the generated plans on the user's terminal, and means for displaying the collected information and the generated plans in augmented reality through smart glasses. This allows users to visually check specific property information, renovation plans, and local information using augmented reality even in physical stores.

[1237] "User basic information" refers to personal data provided by the user, including information such as age, gender, occupation, and contact details.

[1238] "Housing conditions" refer to the specifications and characteristics of the property desired by the user, such as floor plan, budget, location, and facilities.

[1239] A "real estate database" is a database system that registers property information from all over the country, and includes data such as property addresses, prices, floor plans, and photos.

[1240] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to generate new information or plans from data.

[1241] "Job Information" means information about employment opportunities and job postings in a specified area, including data such as job type, salary, and location.

[1242] "Public facility information" refers to information about public infrastructure and service facilities within a specific area, such as schools, hospitals, parks, and libraries.

[1243] "Smart glasses" are wearable devices equipped with augmented reality technology, and are glasses-type terminals with built-in displays.

[1244] "Augmented reality" is a technology that overlays digital information onto the real environment, displaying virtual information alongside real objects in the user's field of vision.

[1245] A "renovation plan" is a plan for renovating and remodeling an existing building, and includes blueprints, interior design drawings, and cost details.

[1246] "Means for displaying information in a visually easy-to-understand manner" refers to methods and tools for providing information graphically so that users can easily understand the information, and is a display means that includes diagrams and image illustrations.

[1247] The present invention provides a system that allows users to visually check property information and renovation plans in a physical store using smart glasses. Specific embodiments are described in detail below.

[1248] System Program and Processing Overview

[1249] The server uses voice and gesture recognition technology to input the user's basic information and living conditions. The user puts on the smart glasses and inputs their conditions through voice commands or gestures. This information is then sent from the smart glasses to the server.

[1250] The server uses the received information to search a nationwide real estate database and identify properties that meet the user's criteria. The search results include the property's address, price, floor plan, photos, and more.

[1251] The server runs a generative AI model to generate a renovation plan for the identified property. The generative AI model automatically generates a renovation plan based on the input property information, providing interior image drawings and detailed cost breakdowns.

[1252] The server then queries a relevant database to gather job and public facility information for the specified area, providing detailed information about employment opportunities and public infrastructure in the area.

[1253] The collected information and generated plans are displayed on the user's device (smart glasses), which uses augmented reality technology to visually display property details, renovation plans, and local information.

[1254] This allows users to use augmented reality to check detailed property information, renovation plans, and local information even in physical stores, and even make specific decisions on the spot.

[1255] Hardware and software used

[1256] Hardware: Smart glasses (e.g. Microsoft HoloLens)

[1257] Software: AR libraries (e.g., ARCore, ARKit), cloud databases (e.g., Firebase, AWS), generative AI models (e.g., GPT-4)

[1258] Natural language explanation of the process

[1259] The server uses a voice recognition engine (e.g., Google Speech-to-Text) and gesture recognition (e.g., OpenCV) to collect data from users entering basic information and housing requirements. This information is sent to the cloud and searched through a nationwide real estate database. The search results include basic information such as the property's address, floor plan, price, and photos.

[1260] The server inputs the acquired property information into a generative AI model to generate a renovation plan. Using a generative AI model (e.g., GPT-4), a renovation plan is automatically generated based on the user's criteria, and interior design drawings and detailed cost estimates are provided.

[1261] Additionally, the server retrieves job and public facility information for the specified area from a relational database, allowing the user to view information about job opportunities and public services in the area.

[1262] This information is sent to the smart glasses and displayed visually using the AR library, allowing users to intuitively understand detailed property information and renovation plans even in a physical store.

[1263] Examples of concrete examples and prompts

[1264] Example: A user can wear smart glasses in a physical store and input voice commands such as "Tell me about 3LDK properties," "Show me renovation plans for open kitchens," and "Show me information about nearby hospitals," and appropriate property information, renovation plans, and local information will be displayed using AR.

[1265] Prompt Sentence Examples

[1266] "Tell me about a 3LDK property."

[1267] "I'd like to see your open kitchen renovation plan."

[1268] "Show me information about nearby hospitals"

[1269] These features improve the user experience and make property selection and renovation planning more efficient.

[1270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1271] Step 1:

[1272] The user puts on the smart glasses and inputs basic information and housing requirements using voice commands and gestures. The glasses' built-in voice recognition engine (e.g., Google Speech-to-Text) and gesture recognition software (e.g., OpenCV) are used to capture voice and movement data. This provides input data such as age, gender, occupation, desired floor plan, desired area, and budget. This data is then sent from the device to a server.

[1273] Step 2:

[1274] The server performs a real estate database search based on the received user information. It generates an SQL query to filter the database and retrieve property listings that match the specified criteria. Input data includes the user's desired layout, area, and budget, and output data includes relevant property information (e.g., address, price, layout, and photos).

[1275] Step 3:

[1276] The server uses the acquired property information as input data for a generative AI model (e.g., GPT-4) to generate a renovation plan. The generative AI model analyzes the property's floor plan and photos, and automatically generates a renovation plan that meets the user's needs. The input data is the property information and the user's desired conditions, and the output data is the renovation plan (e.g., interior design drawings and detailed cost breakdowns).

[1277] Step 4:

[1278] The server queries a relational database to gather job and public facility information for a given area, using the user-specified area as input and providing information about job opportunities and public facilities (schools, hospitals, parks, etc.) in that area as output.

[1279] Step 5:

[1280] The server sends the collected information and generated renovation plans to the user's smart glasses. Specifically, it uses an AR library (e.g., ARCore, ARKit) to process the data to display the information in a visually understandable way. The input data is property information, renovation plans, and local information, and the output data is the AR content displayed on the smart glasses.

[1281] Step 6:

[1282] The device receives the transmitted data and displays it in augmented reality on the smart glasses' display. Property details, renovation plans, and local information are superimposed on the user's field of vision, allowing the user to see the property's image and renovation possibilities in real time.

[1283] This series of processes allows users to intuitively check detailed property information, renovation plans, and local information even in physical stores using augmented reality technology.

[1284] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1285] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments are described below.

[1286] System Overview

[1287] Enter user information

[1288] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[1289] Data collection

[1290] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[1291] Renovation plan generation

[1292] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[1293] Emotion recognition by emotion engine

[1294] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to evaluate their satisfaction and stress level.

[1295] Emotion-Based Optimization

[1296] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[1297] Regional information provision

[1298] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[1299] Information display

[1300] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[1301] Specific examples

[1302] Below is a concrete example of how this system works in practice.

[1303] 1. When a user enters information

[1304] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[1305] 2. When sending data to the server

[1306] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[1307] 3. When a vacant house is identified

[1308] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[1309] 4. When a renovation plan is generated

[1310] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[1311] 5. When the emotion engine recognizes the user's emotions

[1312] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[1313] 6. Optimizing your renovation plan based on emotions

[1314] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[1315] 7. When local information is provided

[1316] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[1317] 8. When information is displayed to the user

[1318] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[1319] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[1320] The processing flow will be explained below.

[1321] Step 1:

[1322] A user starts the application and enters basic information and housing requirements.

[1323] Users enter detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[1324] Step 2:

[1325] The terminal temporarily stores the user's input information and sends it to the server.

[1326] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[1327] Step 3:

[1328] The server receives the information from the user and searches a real estate database.

[1329] The server generates an SQL query based on the received information and extracts vacant properties from the database that match the desired area, budget, and floor plan.

[1330] Step 4:

[1331] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[1332] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[1333] Step 5:

[1334] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[1335] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[1336] Step 6:

[1337] The emotion engine recognizes the user's emotions.

[1338] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice in real time to assess their happiness or dissatisfaction.

[1339] Step 7:

[1340] Optimize renovation plans based on an emotion engine.

[1341] Based on the emotions recognized, the system evaluates the user's preferences and stress level and suggests modifications to the renovation plan accordingly. For example, if the user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design.

[1342] Step 8:

[1343] The server collects job information and public facility information for a specified area.

[1344] The server queries the job and public facility databases for the area and compiles the collected information. Specifically, it retrieves information on local jobs and public facilities such as schools, hospitals, and parks. The emotion engine takes into account the user's preferences and stress level and provides the most appropriate local information based on the results.

[1345] Step 9:

[1346] The server sends all information (vacant house list, renovation plan, emotion-based optimization plan, local information) to the user's device.

[1347] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[1348] Step 10:

[1349] The terminal formats and displays the information it receives.

[1350] The device organizes the received information about vacant houses, renovation plans, suggested revisions to the plans based on emotions, local job information, and information about public facilities, and displays it to the user in a visually easy-to-understand format.

[1351] ---

[1352] This detailed processing flowchart allows users to easily find the best vacant property and renovation plan, and furthermore, by utilizing the emotion engine, they can select a home that will give them the highest level of satisfaction. Furthermore, they can obtain comprehensive information necessary for planning their life after moving. This system will greatly contribute to the effective use of vacant properties and regional revitalization.

[1353] Example 2

[1354] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1355] Conventional housing selection and renovation plan generation systems lack the ability to recognize the user's emotional state and optimize the plan based on that, making it difficult to maximize user satisfaction. Furthermore, they lacked a means to provide comprehensive local information, resulting in insufficient information for selecting a relocation destination. This made it difficult for users to select the optimal housing that best suited their needs and emotions.

[1356] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1357] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving an artificial intelligence model to generate a renovation plan for the identified property, means for analyzing the user's facial expressions and voice to recognize their emotional state, means for optimizing the renovation plan based on the recognized emotional state, means for collecting job information and public facility information in a specified area, and means for displaying the collected information and the generated plan on the user's terminal. This makes it possible to provide an optimal renovation plan based on the user's emotional state and comprehensive local information.

[1358] "User information" is data including the user's basic information and desired housing conditions.

[1359] "Housing conditions" include the layout, area, budget, and other conditions of the property desired by the user.

[1360] A "terminal" is a device through which a user inputs information and receives information from a server.

[1361] A "server" is a computer system that receives user information, searches the database, and generates renovation plans.

[1362] The "real estate database" is a database that stores information on vacant houses and properties across the country.

[1363] An "SQL query" is a Structured Query Language command issued to a database to perform a search.

[1364] A "generative AI model" is an artificial intelligence model that generates renovation plans based on input data.

[1365] A "renovation plan" is a detailed plan including proposed interior design drawings and cost breakdowns for a specified property.

[1366] An "emotion engine" is a software engine that has the function of analyzing a user's facial expressions and voice and recognizing their emotional state.

[1367] "Emotional state" refers to a user's psychological state, such as their satisfaction level or stress level.

[1368] A "job database" is a database that stores job information for a specified area.

[1369] The "public facility database" is a database that stores information on public facilities such as schools, hospitals, and parks in a specified area.

[1370] "Regional information" is data including job information and public facility information related to a specified region.

[1371] "Means for displaying information in a visually easy-to-understand manner" is a function for displaying information in a format that is easily understandable to the user.

[1372] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments of the present invention are described below.

[1373] System Overview

[1374] Enter user information

[1375] When a user starts the application, a screen appears on the device where the user can enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[1376] Data collection

[1377] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[1378] Renovation plan generation

[1379] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[1380] Emotion recognition by emotion engine

[1381] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to assess their satisfaction and stress level.

[1382] Emotion-Based Optimization

[1383] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[1384] Regional information provision

[1385] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[1386] Information display

[1387] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[1388] Specific examples

[1389] Below is a concrete example of how this system works in practice.

[1390] 1. When a user enters information

[1391] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[1392] 2. When sending data to the server

[1393] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[1394] 3. When a vacant house is identified

[1395] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[1396] 4. When a renovation plan is generated

[1397] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[1398] 5. When the emotion engine recognizes the user's emotions

[1399] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[1400] 6. Optimizing your renovation plan based on emotions

[1401] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[1402] 7. When local information is provided

[1403] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[1404] 8. When information is displayed to the user

[1405] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[1406] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[1407] Examples of prompt statements

[1408] "Please suggest the best renovation plan and local information for a user who is a woman in her 30s looking for a 3LDK property in Tokyo with a budget of 50 million yen or less."

[1409] The above is a specific embodiment of the present invention.

[1410] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1411] Step 1:

[1412] The user starts the application.

[1413] Input: Nothing in particular.

[1414] Action: A user taps an application on their device to launch it.

[1415] Output: The application's welcome screen is displayed.

[1416] Step 2:

[1417] The terminal displays a screen for the user to input basic information and desired housing conditions.

[1418] Input: None (based on application default settings).

[1419] How it works: The device displays a form for entering basic information and housing requirements.

[1420] Output: The user input form (name, age, gender, floor plan, area, budget, etc.) is displayed on the screen.

[1421] Step 3:

[1422] The user enters basic information and desired housing conditions.

[1423] Input: Name, age, gender, desired layout (e.g. 3LDK), desired area (e.g. Tokyo), budget (e.g. 50 million yen).

[1424] What happens: A user enters information into a form and taps the "Submit" button.

[1425] Output: The entered information is saved on the device.

[1426] Step 4:

[1427] The terminal transmits the input information to the server.

[1428] Input: Basic information and housing requirements entered by the user.

[1429] Operation: The device converts the input information into JSON format and sends it to the server.

[1430] Output: The server stores the received user information in a database.

[1431] Step 5:

[1432] Based on the user information received by the server, an SQL query is generated to search the real estate database.

[1433] Input: User's basic information and living conditions.

[1434] What it does: The server generates an SQL query of the form "SELECT FROM real estate database WHERE...".

[1435] Output: The generated SQL query.

[1436] Step 6:

[1437] The server runs SQL queries against a real estate database to identify vacant properties that meet the criteria.

[1438] Input: The generated SQL query.

[1439] How it works: The server queries the database to retrieve a list of available properties that fit the criteria.

[1440] Output: A list of identified vacant properties.

[1441] Step 7:

[1442] The server inputs the identified vacant house information into the generative AI model.

[1443] Input: Information about the identified vacant house.

[1444] How it works: The server inputs vacant house information into the generative AI model along with the prompt, "Please propose a renovation plan based on the user's requests."

[1445] Output: The prompt sentence and vacant house information input to the generative AI model.

[1446] Step 8:

[1447] The generative AI model generates a renovation plan (interior image and detailed cost breakdown).

[1448] Input: Prompt statement and vacant house information.

[1449] How it works: A generative AI model builds renovation plans, producing interior design images and a breakdown of the costs involved.

[1450] Output: The generated renovation plan.

[1451] Step 9:

[1452] The server temporarily saves the generated renovation plan.

[1453] Input: Generated renovation plan.

[1454] How it works: The server stores the generated plan in a temporary database.

[1455] Output: Renovation plans saved in a temporary database.

[1456] Step 10:

[1457] The user views the proposed renovation plan.

[1458] Input: Generated renovation plan.

[1459] Operation: The device displays the plan information received from the server.

[1460] Output: Renovation plan displayed on the device.

[1461] Step 11:

[1462] The emotion engine analyzes the user's facial expressions and voice to recognize their emotional state (satisfaction, stress level).

[1463] Input: User's facial expression video and audio data.

[1464] How it works: The emotion engine uses real-time facial recognition and voice analysis to assess emotional state.

[1465] Output: Emotional state (e.g., satisfaction level, dissatisfaction level).

[1466] Step 12:

[1467] The emotion engine sends the emotional state to the server.

[1468] Input: Evaluated emotional state.

[1469] How it works: The emotion engine sends the emotional state in JSON format to the server.

[1470] Output: Emotional state sent to the server.

[1471] Step 13:

[1472] Based on the emotional state received by the server, correction conditions are input into the generative AI model to generate a new renovation plan.

[1473] Input: Emotional state data, vacant house information.

[1474] How it works: The server inputs the prompt statement "The user is dissatisfied, so please propose a different renovation plan" and the correction conditions into the generative AI model.

[1475] Output: The modified conditions and prompt sentences fed into the generative AI model.

[1476] Step 14:

[1477] The generative AI model generates a revised renovation plan.

[1478] Input: Prompt statement and correction condition.

[1479] How it works: A generative AI model builds new renovation plans, generating new interior renderings and revised cost breakdowns.

[1480] Output: The newly generated renovation plan.

[1481] Step 15:

[1482] The server transmits the revised renovation plan to the user's terminal.

[1483] Input: Revised renovation plan.

[1484] How it works: The server sends a remediation plan in JSON format to the user's device.

[1485] Output: The revised renovation plan sent to the device.

[1486] Step 16:

[1487] The server generates an SQL query to search the local job database and public facility database based on the user's desired area.

[1488] Input: User's preferred region data.

[1489] What it does: The server generates SQL queries of the form "SELECT FROM job database WHERE region=..." and "SELECT FROM utility database WHERE region=...".

[1490] Output: The generated SQL query.

[1491] Step 17:

[1492] The server runs SQL queries to retrieve job listings and public facility information.

[1493] Input: The generated SQL query.

[1494] How it works: The server runs SQL queries against the database to retrieve a list of jobs and public accommodations.

[1495] Output: A list of the job and public facility information retrieved.

[1496] Step 18:

[1497] The server temporarily saves the acquired regional information.

[1498] Input: Retrieved job information and public facility information.

[1499] How it works: The server stores the location information in a temporary database.

[1500] Output: Region information stored in a temporary database.

[1501] Step 19:

[1502] The emotion engine takes into account the user's stress level and selects the most appropriate local information.

[1503] Input: Retrieved local information, user's stress level.

[1504] How it works: The emotion engine selects local information based on stress levels and creates a candidate list.

[1505] Output: A list of selected locality candidates.

[1506] Step 20:

[1507] The server finally sends all the information (vacant house list, renovation plan, emotion-based optimization plan, and local information) to the user's device.

[1508] Input: vacant home listings, renovation plans, sentiment-based plans, local information.

[1509] How it works: The server aggregates the information and sends it to the user's device in JSON format.

[1510] Output: Comprehensive information sent to the terminal.

[1511] Step 21:

[1512] The device displays this information in a visually easy-to-understand format.

[1513] Input: General information sent from the server.

[1514] Operation: The device displays information using a UI (user interface).

[1515] Output: A list of available properties, renovation plans, sentiment-based plan revision suggestions, and local information presented in a visually easy-to-understand format.

[1516] (Application example 2)

[1517] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1518] Conventional renovation plan generation systems identify suitable properties based on the user's basic information and living conditions, and then provide a renovation plan. However, they are unable to optimize the plan to reflect the user's emotions or provide visual confirmation using 3D models, making it difficult to increase user satisfaction. Furthermore, they are also inadequate in providing information about life after relocation (job information and public facility information). Therefore, there is a need for a system that can dynamically optimize renovation plans based on the user's emotions, enable visual confirmation using AR technology, and also provide local information.

[1519] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic information and housing conditions; means for receiving the input information; means for searching a nationwide real estate database based on the received information to identify properties that meet the user's conditions; means for driving a generative model to generate a renovation plan for the identified property; means for visually displaying the generated renovation plan on a visual display worn by the user; means for recognizing the user's emotions in real time using an emotion engine; means for optimizing the renovation plan based on the recognized emotions; means for collecting employment information and public facility information for a specified area; and means for displaying the collected information and the generated plan on the user's terminal. This allows the user to visually confirm the renovation plan optimized based on their emotions while also obtaining local information all at once.

[1520] "Basic information of the user" includes information such as the user's age, sex, occupation, desired floor plan, desired area, and budget.

[1521] "Housing conditions" are conditions such as floor plan, area, budget, etc. related to the housing desired by the user.

[1522] The "means for inputting" refers to a means for the user to input the basic information and residential conditions described above, and includes voice recognition, gesture input, and the like.

[1523] The "receiving means" is a means by which the server receives information input by the user.

[1524] A "real estate database" is a database that stores information on vacant houses and data related to real estate properties.

[1525] A "generative model" is a model that uses artificial intelligence to automatically generate renovation plans.

[1526] A "visual display" is a display device worn by a user, such as smart glasses or a head-mounted display.

[1527] The "emotion engine" is an engine that analyzes the user's facial expressions and voice in real time to recognize the user's emotional state.

[1528] The "means for recognizing" is a means for recognizing the user's emotions in real time using an emotion engine.

[1529] The "optimizing means" is a means for dynamically optimizing the renovation plan based on the recognized sentiment.

[1530] "Employment Information" means job information in a designated area.

[1531] "Public facility information" is information about public facilities such as schools, hospitals, and parks in a designated area.

[1532] "Means of collection" means the means for collecting employment information and public facilities information for the designated area.

[1533] The "display means" is a means for displaying the collected information and the generated plan on the user's terminal.

[1534] A "terminal" is a device used by a user, such as a smartphone or tablet.

[1535] The present invention is a system that allows users to input their basic information and housing requirements, and then identifies the most suitable vacant property based on that information and generates a renovation plan.The system also incorporates an emotion engine, which can optimize the renovation plan based on the user's emotions and provide local information.Specific embodiments for implementing the present invention are described below.

[1536] Entering user information

[1537] Users wear smart glasses or a head-mounted display and use voice commands or gestures to input their basic information (age, gender, occupation, etc.) and housing requirements (floor plan, area, budget, etc.). This information is then sent from the user device to the server.

[1538] Receiving and retrieving data

[1539] The server searches a nationwide real estate database based on the received user information, thereby identifying properties that meet the user's criteria.

[1540] Generate renovation plans

[1541] The server inputs the identified property information into a generative AI model and automatically generates a renovation plan, which includes a 3D image of the interior and a detailed breakdown of costs.

[1542] Emotion recognition by emotion engine

[1543] Using the camera and microphone built into the smart glasses or head-mounted display worn by the user, the emotion engine analyzes the user's facial expressions and voice in real time, thereby recognizing the user's emotional state.

[1544] Emotion-Based Optimization

[1545] Based on the emotions recognized, renovation plans are dynamically optimized: for example, if a user expresses dissatisfaction with a particular design, alternative design ideas are instantly suggested.

[1546] Providing local information

[1547] The server also collects information on job openings and public facilities in the designated area, allowing users to obtain comprehensive information on their living environment after relocating.

[1548] Final display of information

[1549] Finally, all the information collected by the server (vacant house lists, renovation plans, emotion-based optimization plans, and local information) is visually displayed on the user's smart glasses or head-mounted display.

[1550] Specific use cases

[1551] For example, suppose a 35-year-old male engineer is looking for a 3LDK apartment in Tokyo with a budget of less than 50 million yen. In this case, the user might use the following prompt:

[1552] "User Information:

[1553] Age: 35

[1554] Gender: Male

[1555] Occupation: Engineer

[1556] Desired layout: 3LDK

[1557] Preferred area: Tokyo

[1558] Budget: 50 million yen

[1559] Identify vacant properties that fit your criteria, generate renovation plans, and suggest new plans when users express dissatisfaction with the sentiment engine.

[1560] Based on these prompts, the server identifies vacant properties and generates renovation plans. When the user reviews the proposed plans on a wearable visual display, the emotion engine reads the user's emotions from their facial expressions and voice and provides optimized design proposals in real time. It can also provide information on job openings and public facilities in the specified area.

[1561] This allows users to efficiently obtain renovation plans customized based on their emotions and information about their living environment after moving.

[1562] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1563] Step 1: Enter your basic information and residential conditions

[1564] The user wears smart glasses or a head-mounted display and uses voice commands or gestures to input information such as age, gender, occupation, desired layout, desired area, budget, etc. This input information is then sent from the user terminal to the server.

[1565] Input: User's basic information and housing requirements (age, gender, occupation, desired layout, area, budget)

[1566] Output: User information sent to the server

[1567] Step 2: Receive user information and search the real estate database

[1568] The server searches the real estate database based on the received user information to identify properties that meet the user's criteria. This process involves generating an SQL query to search the database.

[1569] Input: User information sent to the server

[1570] Output: List of properties that match the criteria

[1571] Step 3: Generate renovation plans

[1572] Based on the identified property information, the server runs a generative AI model to generate a renovation plan, which inputs the property information as prompts and outputs a 3D image of the interior and a detailed cost breakdown.

[1573] Input: List of properties that match your criteria

[1574] Output: Renovation plan generated by the AI ​​model (3D image, cost breakdown)

[1575] Step 4: Visualize your renovation plans

[1576] The generated renovation plan is visually displayed on the user's smart glasses or head-mounted display using an AR library.

[1577] Input: Generated renovation plan (3D image, cost details)

[1578] Output: Renovation plan displayed on a visual display

[1579] Step 5: Recognize the user's emotions

[1580] While the user is reviewing the renovation plan, the emotion engine uses the camera and microphone built into the smart glasses or head-mounted display to analyze the user's facial expressions and voice in real time and recognize the user's emotional state.

[1581] Input: User facial and voice data

[1582] Output: Recognized emotional state of the user

[1583] Step 6: Optimize your renovation plan based on emotions

[1584] The server dynamically optimizes renovation plans based on the recognized emotions. For example, if a user expresses dissatisfaction with a particular interior design, the server will again drive the generative AI model to generate and display alternative plans.

[1585] Input: Recognized user emotional state, original renovation plan

[1586] Output: Emotionally optimized renovation plan

[1587] Step 7: Gather local information

[1588] The server collects job listings and public facility information for a specified area, which includes performing queries against a local job database and a local public facility database.

[1589] Input: specified region

[1590] Output: Collected job and public facility information

[1591] Step 8: View the collected information and optimized plan

[1592] The server displays the collected local information and optimized renovation plans on the user's smart glasses or head-mounted display in a visually easy-to-understand format.

[1593] Input: Collected local information and optimized renovation plans

[1594] Output: Local information and renovation plans displayed on a visual display

[1595] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1596] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1597] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1598] [Fourth embodiment]

[1599] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1600] 7, a 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.

[1601] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1602] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1603] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1604] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1605] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1606] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1607] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1608] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1609] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1610] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1611] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1612] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and generates a renovation plan. It also provides job information and public facility information for the specified area. Specific embodiments are described below.

[1613] System Overview

[1614] Enter user information

[1615] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[1616] Data collection

[1617] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[1618] Renovation plan generation

[1619] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[1620] Regional information provision

[1621] The server also collects job listings and public facility information for the specified area, which is obtained by querying a local job database and a local public facility database.

[1622] Information display

[1623] Finally, the server sends all the collected information (vacant house list, renovation plans, local information) to the user's device, which displays this information in a visually easy-to-understand format.

[1624] Specific examples

[1625] Below is a concrete example of how this system works in practice.

[1626] 1. When a user enters information

[1627] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[1628] 2. When sending data to the server

[1629] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[1630] 3. When a vacant house is identified

[1631] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[1632] 4. When a renovation plan is generated

[1633] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[1634] 5. When local information is provided

[1635] The server collects local information for Tokyo, including information on local job openings and public facilities (schools, hospitals, parks, etc.).

[1636] 6. When information is displayed to the user

[1637] Ultimately, all this information is sent from the server to the user's device, which displays a list of vacant homes, details of renovation plans, local job listings, and information about public facilities in a visually easy-to-understand format.

[1638] This system allows users to easily find the housing and renovation plan that best suits their needs, and provides comprehensive support for life planning after moving in. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[1639] The processing flow will be explained below.

[1640] Step 1:

[1641] A user starts the application and enters basic information and housing requirements.

[1642] The user enters detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[1643] Step 2:

[1644] The terminal temporarily stores the user's input information and sends it to the server.

[1645] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[1646] Step 3:

[1647] The server receives the information from the user and searches a real estate database.

[1648] The server generates an SQL query based on the received information and extracts vacant properties from the database that match conditions such as the desired area, budget, and floor plan.

[1649] Step 4:

[1650] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[1651] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[1652] Step 5:

[1653] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[1654] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[1655] Step 6:

[1656] The server collects job information and public facility information for a specified area.

[1657] The server queries the local job and public facility databases and compiles the collected information, specifically, local job listings and public facilities such as schools, hospitals, and parks.

[1658] Step 7:

[1659] The server sends all information (vacant house list, renovation plan, local information) to the user's device.

[1660] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[1661] Step 8:

[1662] The terminal formats and displays the information it receives.

[1663] The terminal organizes the received detailed information on vacant houses, renovation plans, local job listings and information on public facilities, and displays it to the user in a visually easy-to-understand format.

[1664] ---

[1665] The above processing flow allows users to easily find vacant properties and renovation plans that suit their needs, and also to obtain comprehensive information necessary for life planning after moving in. This system contributes to the effective use of vacant properties and regional revitalization.

[1666] Example 1

[1667] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1668] Currently, the process of users finding a new home, renovating it, and planning their life in that area requires a lot of manual work, which is extremely time-consuming and labor-intensive. There is a need for a system that can streamline this process and allow users to quickly find the home and renovation plan that is best suited to them, as well as information about the area they are moving to.

[1669] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1670] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate a renovation plan for the identified property, means for using prompt text including the content of the generated renovation plan, means for collecting information on job openings and public facilities in the specified area, and means for displaying the collected information and the generated plan on the user's terminal. This allows a user to easily find a home that suits them, obtain specific and detailed renovation plans for that home, and simultaneously obtain comprehensive information on the living environment of the relocation destination.

[1671] "Basic information" refers to personal attribute information of a user, such as name, age, sex, occupation, and other information for identifying the user.

[1672] "Housing conditions" refer to conditions related to the housing desired by the user, and include specific requirements such as floor plan, area, and budget.

[1673] A "real estate database" refers to a database system that stores and allows searching of property information from across the country.

[1674] A "generative AI model" refers to a program that uses artificial intelligence technology to analyze data and generate renovation plans.

[1675] A "prompt" refers to text that contains instructions or questions given to a generative AI model.

[1676] "Job Information" means information about employment opportunities in a designated area.

[1677] "Public facility information" refers to information about public facilities such as schools, hospitals, and parks located in a designated area.

[1678] The system aims to help users plan their future life in their new home by providing information on job openings and public facilities in the area, based on the user's basic information and housing requirements.

[1679] First, when a user starts the application, a screen appears where they can enter basic information (such as name, age, gender, and occupation) and desired housing conditions (such as floor plan, area, and budget). The user enters this information, and the device sends the input information to the server in JSON format.

[1680] Based on the received information, the server generates an SQL query for the real estate database and filters the nationwide vacant house data based on the conditions. The server performs the search using a database management system (e.g., MySQL). For example, it identifies vacant properties that meet the conditions "Tokyo," "under 50 million yen," and "3LDK."

[1681] Next, the information about the identified vacant property is input into a generative AI model (e.g., OpenAI GPT-4) to generate a renovation plan. The prompt sent to the generative AI model is as follows:

[1682] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[1683] The generated renovation plan includes interior design images and detailed cost breakdowns, allowing users to visualize the specific renovation process.

[1684] Additionally, the server collects job listings and public accommodation information for the specified area by querying a local job database (e.g., Indeed API) and collecting public accommodation information as well. For example, it executes an API query like this:

[1685] python

[1686] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[1687] The server sends this information to the user's device, which then displays it in a visually easy-to-understand format using HTML5 and CSS3. Users can easily view a list of vacant homes, details of renovation plans, local job listings, and information on public facilities.

[1688] As a specific example, suppose a user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen). Based on this information, the server searches a real estate database using the criteria "Tokyo," "under 50 million yen," and "3LDK," and inputs the information on identified vacant properties into a generative AI model to generate a renovation plan. The generated plan includes a design for an open kitchen with an expanded living room and a detailed cost breakdown. The server then collects job information and public facility information for the specified area and sends all of this information to the device. The device displays this information in an easy-to-understand format, allowing the user to obtain all the information they need.

[1689] This system allows users to efficiently find the most suitable housing and renovation plan, and provides comprehensive support for life planning after relocating. It is also expected to contribute to the effective use of vacant houses and revitalization of local communities.

[1690] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1691] Step 1: Enter your user information

[1692] When a user launches the application, a screen appears where they can enter their basic information and housing requirements. Specifically, the user enters information such as their name, age, gender, occupation, desired layout, area, and budget. The input data is converted to JSON format and is ready to be sent to the server in the next step.

[1693] Input: Name, age, gender, occupation, floor plan, area, budget

[1694] Output: User information in JSON format

[1695] Step 2: Sending data to the server

[1696] The terminal receives the information entered by the user and sends it to the server in the form of an HTTP POST request, which the server receives and begins preparing a database search.

[1697] Input: User information in JSON format

[1698] Output: HTTP POST request to the server

[1699] Specific behavior:

[1700] When the user presses the "Submit" button, the device sends an HTTP POST request to the server that looks like this:

[1701] http

[1702] POST / submit-user-info HTTP / 1.1

[1703] Host: example.com

[1704] Content-Type: application / json

[1705] {

[1706] "name": "Yamada Taro",

[1707] "age": 35,

[1708] "gender": "male",

[1709] "occupation": "teacher",

[1710] "layout": "3LDK",

[1711] "region": "Tokyo",

[1712] "budget": 5000

[1713] }

[1714] Step 3: Search for vacant properties

[1715] The server executes an SQL query against the real estate database based on the received user information. The query is generated based on the user's criteria and identifies properties that match the criteria from nationwide vacant home data. This generates a list of properties that match the criteria.

[1716] Input: User information in JSON format

[1717] Output: List of properties that match the criteria (SQL query results)

[1718] Specific behavior:

[1719] The server generates an SQL query like this and runs it against the real estate database:

[1720] sql

[1721] SELECT FROM properties WHERE region='Tokyo' AND price <= 50000000 AND layout='3LDK';

[1722] The results obtained from the database are organized in a list format and passed to the next step.

[1723] Step 4: Generate a renovation plan

[1724] Based on the information on the identified vacant property, the server inputs a prompt statement into the generative AI model to generate a renovation plan. This prompt statement contains specific renovation requests, and the AI ​​model automatically generates a plan based on that.

[1725] Input: List of properties that match the criteria, prompt text

[1726] Output: Generated renovation plan

[1727] Specific behavior:

[1728] The server sends the following prompt to the generative AI model:

[1729] "Please propose a plan for renovating a 30-year-old apartment in Tokyo with a 3LDK. Please also provide a design for an open kitchen that expands the living room, along with a breakdown of costs."

[1730] The AI ​​model generates a renovation plan and returns the results to the server, including interior design images and cost breakdowns.

[1731] Step 5: Gather local information

[1732] The server collects job information and public facility information for the specified area by issuing API queries to the local job database and public facility database to obtain the required information.

[1733] Input: User's desired region information

[1734] Output: Local job information, public facility information

[1735] Specific behavior:

[1736] The server sends the following request to the local jobs API:

[1737] python

[1738] response = requests.get("https: / / api.example.com / jobs?q=&l=Tokyo")

[1739] Similarly, API queries are issued to collect public facility information and retrieve data.

[1740] Step 6: Sending information to the device and displaying it

[1741] The server then sends all the collected information (vacant house lists, renovation plans, and local information) to the user's device, which receives it and displays it in a visually easy-to-understand format.

[1742] Input: Vacant house list, renovation plan, local information

[1743] Output: Final display data to the terminal

[1744] Specific behavior:

[1745] The server sends the following HTTP response to the device:

[1746] http

[1747] HTTP / 1.1 200 OK

[1748] Content-Type: application / json

[1749] {

[1750] "properties": [...],

[1751] "renovation_plan": {...},

[1752] "jobs": [...],

[1753] "public_facilities": {...}

[1754] }

[1755] The device visually displays the received data using HTML5 and CSS3, making it easy for users to view.

[1756] Through a step-by-step process, the system can provide users with the best available vacant properties and renovation plans, as well as comprehensive information on living in the designated area.

[1757] (Application example 1)

[1758] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1759] Conventional real estate search systems were limited to identifying properties based on user-specified criteria, and lacked the ability to generate renovation plans or provide local information. Furthermore, there was no way to provide users with property search results, renovation plans, and local information in a visually easy-to-understand format. Furthermore, when properties were being shown in physical stores, it was difficult for users to immediately grasp detailed information and renovation plans. These issues made it difficult for users to select the appropriate property and determine the appropriate renovation plan.

[1760] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1761] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving a generative AI model to generate renovation plans for the identified properties, means for collecting job information and public facility information for a specified area, means for displaying the collected information and the generated plans on the user's terminal, and means for displaying the collected information and the generated plans in augmented reality through smart glasses. This allows users to visually check specific property information, renovation plans, and local information using augmented reality even in physical stores.

[1762] "User basic information" refers to personal data provided by the user, including information such as age, gender, occupation, and contact details.

[1763] "Housing conditions" refer to the specifications and characteristics of the property desired by the user, such as floor plan, budget, location, and facilities.

[1764] A "real estate database" is a database system that registers property information from all over the country, and includes data such as property addresses, prices, floor plans, and photos.

[1765] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to generate new information or plans from data.

[1766] "Job Information" means information about employment opportunities and job postings in a specified area, including data such as job type, salary, and location.

[1767] "Public facility information" refers to information about public infrastructure and service facilities within a specific area, such as schools, hospitals, parks, and libraries.

[1768] "Smart glasses" are wearable devices equipped with augmented reality technology, and are glasses-type terminals with built-in displays.

[1769] "Augmented reality" is a technology that overlays digital information onto the real environment, displaying virtual information alongside real objects in the user's field of vision.

[1770] A "renovation plan" is a plan for renovating and remodeling an existing building, and includes blueprints, interior design drawings, and cost details.

[1771] "Means for displaying information in a visually easy-to-understand manner" refers to methods and tools for providing information graphically so that users can easily understand the information, and is a display means that includes diagrams and image illustrations.

[1772] The present invention provides a system that allows users to visually check property information and renovation plans in a physical store using smart glasses. Specific embodiments are described in detail below.

[1773] System Program and Processing Overview

[1774] The server uses voice and gesture recognition technology to input the user's basic information and living conditions. The user puts on the smart glasses and inputs their conditions through voice commands or gestures. This information is then sent from the smart glasses to the server.

[1775] The server uses the received information to search a nationwide real estate database and identify properties that meet the user's criteria. The search results include the property's address, price, floor plan, photos, and more.

[1776] The server runs a generative AI model to generate a renovation plan for the identified property. The generative AI model automatically generates a renovation plan based on the input property information, providing interior image drawings and detailed cost breakdowns.

[1777] The server then queries a relevant database to gather job and public facility information for the specified area, providing detailed information about employment opportunities and public infrastructure in the area.

[1778] The collected information and generated plans are displayed on the user's device (smart glasses), which uses augmented reality technology to visually display property details, renovation plans, and local information.

[1779] This allows users to use augmented reality to check detailed property information, renovation plans, and local information even in physical stores, and even make specific decisions on the spot.

[1780] Hardware and software used

[1781] Hardware: Smart glasses (e.g. Microsoft HoloLens)

[1782] Software: AR libraries (e.g., ARCore, ARKit), cloud databases (e.g., Firebase, AWS), generative AI models (e.g., GPT-4)

[1783] Natural language explanation of the process

[1784] The server uses a voice recognition engine (e.g., Google Speech-to-Text) and gesture recognition (e.g., OpenCV) to collect data from users entering basic information and housing requirements. This information is sent to the cloud and searched through a nationwide real estate database. The search results include basic information such as the property's address, floor plan, price, and photos.

[1785] The server inputs the acquired property information into a generative AI model to generate a renovation plan. Using a generative AI model (e.g., GPT-4), a renovation plan is automatically generated based on the user's criteria, and interior design drawings and detailed cost estimates are provided.

[1786] Additionally, the server retrieves job and public facility information for the specified area from a relational database, allowing the user to view information about job opportunities and public services in the area.

[1787] This information is sent to the smart glasses and displayed visually using the AR library, allowing users to intuitively understand detailed property information and renovation plans even in a physical store.

[1788] Examples of concrete examples and prompts

[1789] Example: A user can wear smart glasses in a physical store and input voice commands such as "Tell me about 3LDK properties," "Show me renovation plans for open kitchens," and "Show me information about nearby hospitals," and appropriate property information, renovation plans, and local information will be displayed using AR.

[1790] Prompt Sentence Examples

[1791] "Tell me about a 3LDK property."

[1792] "I'd like to see your open kitchen renovation plan."

[1793] "Show me information about nearby hospitals"

[1794] These features improve the user experience and make property selection and renovation planning more efficient.

[1795] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1796] Step 1:

[1797] The user puts on the smart glasses and inputs basic information and housing requirements using voice commands and gestures. The glasses' built-in voice recognition engine (e.g., Google Speech-to-Text) and gesture recognition software (e.g., OpenCV) are used to capture voice and movement data. This provides input data such as age, gender, occupation, desired floor plan, desired area, and budget. This data is then sent from the device to a server.

[1798] Step 2:

[1799] The server performs a real estate database search based on the received user information. It generates an SQL query to filter the database and retrieve property listings that match the specified criteria. Input data includes the user's desired layout, area, and budget, and output data includes relevant property information (e.g., address, price, layout, and photos).

[1800] Step 3:

[1801] The server uses the acquired property information as input data for a generative AI model (e.g., GPT-4) to generate a renovation plan. The generative AI model analyzes the property's floor plan and photos, and automatically generates a renovation plan that meets the user's needs. The input data is the property information and the user's desired conditions, and the output data is the renovation plan (e.g., interior design drawings and detailed cost breakdowns).

[1802] Step 4:

[1803] The server queries a relational database to gather job and public facility information for a given area, using the user-specified area as input and providing information about job opportunities and public facilities (schools, hospitals, parks, etc.) in that area as output.

[1804] Step 5:

[1805] The server sends the collected information and generated renovation plans to the user's smart glasses. Specifically, it uses an AR library (e.g., ARCore, ARKit) to process the data to display the information in a visually understandable way. The input data is property information, renovation plans, and local information, and the output data is the AR content displayed on the smart glasses.

[1806] Step 6:

[1807] The device receives the transmitted data and displays it in augmented reality on the smart glasses' display. Property details, renovation plans, and local information are superimposed on the user's field of vision, allowing the user to see the property's image and renovation possibilities in real time.

[1808] This series of processes allows users to intuitively check detailed property information, renovation plans, and local information even in physical stores using augmented reality technology.

[1809] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1810] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments are described below.

[1811] System Overview

[1812] Enter user information

[1813] When a user starts the application, they are first prompted to enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[1814] Data collection

[1815] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[1816] Renovation plan generation

[1817] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[1818] Emotion recognition by emotion engine

[1819] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to evaluate their satisfaction and stress level.

[1820] Emotion-Based Optimization

[1821] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[1822] Regional information provision

[1823] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[1824] Information display

[1825] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[1826] Specific examples

[1827] Below is a concrete example of how this system works in practice.

[1828] 1. When a user enters information

[1829] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[1830] 2. When sending data to the server

[1831] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[1832] 3. When a vacant house is identified

[1833] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[1834] 4. When a renovation plan is generated

[1835] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[1836] 5. When the emotion engine recognizes the user's emotions

[1837] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[1838] 6. Optimizing your renovation plan based on emotions

[1839] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[1840] 7. When local information is provided

[1841] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[1842] 8. When information is displayed to the user

[1843] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[1844] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[1845] The processing flow will be explained below.

[1846] Step 1:

[1847] A user starts the application and enters basic information and housing requirements.

[1848] Users enter detailed information such as age, gender, occupation, desired layout (e.g., 3LDK), desired area (e.g., Tokyo), and budget (e.g., 50 million yen).

[1849] Step 2:

[1850] The terminal temporarily stores the user's input information and sends it to the server.

[1851] The device formats the input data and sends it to the server in the appropriate format, including the user's basic information and living conditions.

[1852] Step 3:

[1853] The server receives the information from the user and searches a real estate database.

[1854] The server generates an SQL query based on the received information and extracts vacant properties from the database that match the desired area, budget, and floor plan.

[1855] Step 4:

[1856] The server retrieves a list of vacant homes that match the criteria and identifies suitable properties.

[1857] The list of vacant houses obtained by the SQL query is stored in temporary memory on the server side, and properties that meet the user's desired conditions are filtered.

[1858] Step 5:

[1859] The server sends the identified vacant house information to the generation AI, which then generates a renovation plan.

[1860] The server inputs floor plans and photos of the identified vacant homes into the AI ​​model, which then generates a renovation plan (e.g., a design plan for an open kitchen). The generated plan includes interior images and detailed cost breakdowns.

[1861] Step 6:

[1862] The emotion engine recognizes the user's emotions.

[1863] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice in real time to assess their happiness or dissatisfaction.

[1864] Step 7:

[1865] Optimize renovation plans based on an emotion engine.

[1866] Based on the emotions recognized, the system evaluates the user's preferences and stress level and suggests modifications to the renovation plan accordingly. For example, if the user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design.

[1867] Step 8:

[1868] The server collects job information and public facility information for a specified area.

[1869] The server queries the job and public facility databases for the area and compiles the collected information. Specifically, it retrieves information on local jobs and public facilities such as schools, hospitals, and parks. The emotion engine takes into account the user's preferences and stress level and provides the most appropriate local information based on the results.

[1870] Step 9:

[1871] The server sends all information (vacant house list, renovation plan, emotion-based optimization plan, local information) to the user's device.

[1872] The server converts the collected information into an appropriate format and sends it to the user's terminal.

[1873] Step 10:

[1874] The terminal formats and displays the information it receives.

[1875] The device organizes the received information about vacant houses, renovation plans, suggested revisions to the plans based on emotions, local job information, and information about public facilities, and displays it to the user in a visually easy-to-understand format.

[1876] ---

[1877] This detailed processing flowchart allows users to easily find the best vacant property and renovation plan, and furthermore, by utilizing the emotion engine, they can select a home that will give them the highest level of satisfaction. Furthermore, they can obtain comprehensive information necessary for planning their life after moving. This system will greatly contribute to the effective use of vacant properties and regional revitalization.

[1878] Example 2

[1879] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1880] Conventional housing selection and renovation plan generation systems lack the ability to recognize the user's emotional state and optimize the plan based on that, making it difficult to maximize user satisfaction. Furthermore, they lacked a means to provide comprehensive local information, resulting in insufficient information for selecting a relocation destination. This made it difficult for users to select the optimal housing that best suited their needs and emotions.

[1881] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1882] In this invention, the server includes means for inputting a user's basic information and housing requirements, means for receiving the input information, means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements, means for driving an artificial intelligence model to generate a renovation plan for the identified property, means for analyzing the user's facial expressions and voice to recognize their emotional state, means for optimizing the renovation plan based on the recognized emotional state, means for collecting job information and public facility information in a specified area, and means for displaying the collected information and the generated plan on the user's terminal. This makes it possible to provide an optimal renovation plan based on the user's emotional state and comprehensive local information.

[1883] "User information" is data including the user's basic information and desired housing conditions.

[1884] "Housing conditions" include the layout, area, budget, and other conditions of the property desired by the user.

[1885] A "terminal" is a device through which a user inputs information and receives information from a server.

[1886] A "server" is a computer system that receives user information, searches the database, and generates renovation plans.

[1887] The "real estate database" is a database that stores information on vacant houses and properties across the country.

[1888] An "SQL query" is a Structured Query Language command issued to a database to perform a search.

[1889] A "generative AI model" is an artificial intelligence model that generates renovation plans based on input data.

[1890] A "renovation plan" is a detailed plan including proposed interior design drawings and cost breakdowns for a specified property.

[1891] An "emotion engine" is a software engine that has the function of analyzing a user's facial expressions and voice and recognizing their emotional state.

[1892] "Emotional state" refers to a user's psychological state, such as their satisfaction level or stress level.

[1893] A "job database" is a database that stores job information for a specified area.

[1894] The "public facility database" is a database that stores information on public facilities such as schools, hospitals, and parks in a specified area.

[1895] "Regional information" is data including job information and public facility information related to a specified region.

[1896] "Means for displaying information in a visually easy-to-understand manner" is a function for displaying information in a format that is easily understandable to the user.

[1897] The present invention is a system that allows users to input their basic information and housing requirements, identifies the most suitable vacant property based on that information, and then generates a renovation plan. In addition, by incorporating a new emotion engine that recognizes the user's emotions, the system optimizes the renovation plan and suggests local information based on the user's emotions. Specific embodiments of the present invention are described below.

[1898] System Overview

[1899] Enter user information

[1900] When a user starts the application, a screen appears on the device where the user can enter their basic information and desired housing conditions (floor plan, area, budget, etc.). The user enters this information, and the device then sends it to the server.

[1901] Data collection

[1902] The server searches the real estate database based on the received user information, generates an SQL query, and filters nationwide vacant property data based on the user's criteria, thereby identifying vacant properties that match the user's criteria.

[1903] Renovation plan generation

[1904] The server inputs the identified vacant house information into a generative AI model and generates a renovation plan, which includes interior design drawings and detailed cost breakdowns.

[1905] Emotion recognition by emotion engine

[1906] When a user uses the application, the emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotional state. For example, when a user browses a renovation plan, the emotion engine analyzes their facial expressions and tone of voice to assess their satisfaction and stress level.

[1907] Emotion-Based Optimization

[1908] The system optimizes renovation plans based on recognized emotions. The emotion engine evaluates the user's preferences and stress level and suggests modifications to the plans accordingly. For example, if the user is not satisfied with the design of their living room, the emotion engine will suggest an alternative design.

[1909] Regional information provision

[1910] The server also collects job information and public facility information for the specified area by querying the local job database and public facility database. The emotion engine considers the user's preferences and stress level and provides the most appropriate local information based on the results.

[1911] Information display

[1912] Finally, the server sends all the collected information (vacant house listings, renovation plans, sentiment-based optimization plans, and local information) to the user's device, which displays this information in a visually easy-to-understand format.

[1913] Specific examples

[1914] Below is a concrete example of how this system works in practice.

[1915] 1. When a user enters information

[1916] The user opens the app and enters their age, gender, occupation, desired floor plan (e.g., 3LDK), desired area (e.g., Tokyo), budget (e.g., 50 million yen), etc.

[1917] 2. When sending data to the server

[1918] The terminal sends the entered information to the server, which receives the information and performs a conditional search against a real estate database.

[1919] 3. When a vacant house is identified

[1920] The server retrieves from the database vacant houses in Tokyo that meet the criteria of "3LDK" and "under 50 million yen."

[1921] 4. When a renovation plan is generated

[1922] The server inputs information about the identified vacant house (e.g., floor plans and photos) into a generative AI model, and a renovation plan is automatically generated. For example, a design plan for an open kitchen with an expanded living room and a detailed cost breakdown are generated.

[1923] 5. When the emotion engine recognizes the user's emotions

[1924] When a user views a proposed renovation plan, the emotion engine analyzes the user's facial expressions and voice to assess their happiness or dissatisfaction.

[1925] 6. Optimizing your renovation plan based on emotions

[1926] For example, if a user expresses dissatisfaction with the kitchen design, the emotion engine will suggest a different kitchen design, and also change the color and layout based on the user's preferences.

[1927] 7. When local information is provided

[1928] The server collects information on local jobs and public facilities (schools, hospitals, parks, etc.) as regional information for Tokyo. The emotion engine evaluates the user's stress level and suggests appropriate job and public facility information.

[1929] 8. When information is displayed to the user

[1930] All this information is sent from the server to the user's device, which displays details of vacant homes, renovation plans, emotion-based plan revision suggestions, local job listings, and public facility information in a visually easy-to-understand format.

[1931] This system allows users to easily find vacant properties and renovation plans that are optimized to their needs and emotions, and to obtain comprehensive information necessary for planning their life after moving in. In addition, the introduction of an emotion engine will significantly improve the quality of the user experience, enabling them to make more satisfying housing choices.

[1932] Examples of prompt statements

[1933] "Please suggest the best renovation plan and local information for a user who is a woman in her 30s looking for a 3LDK property in Tokyo with a budget of 50 million yen or less."

[1934] The above is a specific embodiment of the present invention.

[1935] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1936] Step 1:

[1937] The user starts the application.

[1938] Input: Nothing in particular.

[1939] Action: A user taps an application on their device to launch it.

[1940] Output: The application's welcome screen is displayed.

[1941] Step 2:

[1942] The terminal displays a screen for the user to input basic information and desired housing conditions.

[1943] Input: None (based on application default settings).

[1944] How it works: The device displays a form for entering basic information and housing requirements.

[1945] Output: The user input form (name, age, gender, floor plan, area, budget, etc.) is displayed on the screen.

[1946] Step 3:

[1947] The user enters basic information and desired housing conditions.

[1948] Input: Name, age, gender, desired layout (e.g. 3LDK), desired area (e.g. Tokyo), budget (e.g. 50 million yen).

[1949] What happens: A user enters information into a form and taps the "Submit" button.

[1950] Output: The entered information is saved on the device.

[1951] Step 4:

[1952] The terminal transmits the input information to the server.

[1953] Input: Basic information and housing requirements entered by the user.

[1954] Operation: The device converts the input information into JSON format and sends it to the server.

[1955] Output: The server stores the received user information in a database.

[1956] Step 5:

[1957] Based on the user information received by the server, an SQL query is generated to search the real estate database.

[1958] Input: User's basic information and living conditions.

[1959] What it does: The server generates an SQL query of the form "SELECT FROM real estate database WHERE...".

[1960] Output: The generated SQL query.

[1961] Step 6:

[1962] The server runs SQL queries against a real estate database to identify vacant properties that meet the criteria.

[1963] Input: The generated SQL query.

[1964] How it works: The server queries the database to retrieve a list of available properties that fit the criteria.

[1965] Output: A list of identified vacant properties.

[1966] Step 7:

[1967] The server inputs the identified vacant house information into the generative AI model.

[1968] Input: Information about the identified vacant house.

[1969] How it works: The server inputs vacant house information into the generative AI model along with the prompt, "Please propose a renovation plan based on the user's requests."

[1970] Output: The prompt sentence and vacant house information input to the generative AI model.

[1971] Step 8:

[1972] The generative AI model generates a renovation plan (interior image and detailed cost breakdown).

[1973] Input: Prompt statement and vacant house information.

[1974] How it works: A generative AI model builds renovation plans, producing interior design images and a breakdown of the costs involved.

[1975] Output: The generated renovation plan.

[1976] Step 9:

[1977] The server temporarily saves the generated renovation plan.

[1978] Input: Generated renovation plan.

[1979] How it works: The server stores the generated plan in a temporary database.

[1980] Output: Renovation plans saved in a temporary database.

[1981] Step 10:

[1982] The user views the proposed renovation plan.

[1983] Input: Generated renovation plan.

[1984] Operation: The device displays the plan information received from the server.

[1985] Output: Renovation plan displayed on the device.

[1986] Step 11:

[1987] The emotion engine analyzes the user's facial expressions and voice to recognize their emotional state (satisfaction, stress level).

[1988] Input: User's facial expression video and audio data.

[1989] How it works: The emotion engine uses real-time facial recognition and voice analysis to assess emotional state.

[1990] Output: Emotional state (e.g., satisfaction level, dissatisfaction level).

[1991] Step 12:

[1992] The emotion engine sends the emotional state to the server.

[1993] Input: Evaluated emotional state.

[1994] How it works: The emotion engine sends the emotional state in JSON format to the server.

[1995] Output: Emotional state sent to the server.

[1996] Step 13:

[1997] Based on the emotional state received by the server, correction conditions are input into the generative AI model to generate a new renovation plan.

[1998] Input: Emotional state data, vacant house information.

[1999] How it works: The server inputs the prompt statement "The user is dissatisfied, so please propose a different renovation plan" and the correction conditions into the generative AI model.

[2000] Output: The modified conditions and prompt sentences fed into the generative AI model.

[2001] Step 14:

[2002] The generative AI model generates a revised renovation plan.

[2003] Input: Prompt statement and correction condition.

[2004] How it works: A generative AI model builds new renovation plans, generating new interior renderings and revised cost breakdowns.

[2005] Output: The newly generated renovation plan.

[2006] Step 15:

[2007] The server transmits the revised renovation plan to the user's terminal.

[2008] Input: Revised renovation plan.

[2009] How it works: The server sends a remediation plan in JSON format to the user's device.

[2010] Output: The revised renovation plan sent to the device.

[2011] Step 16:

[2012] The server generates an SQL query to search the local job database and public facility database based on the user's desired area.

[2013] Input: User's preferred region data.

[2014] What it does: The server generates SQL queries of the form "SELECT FROM job database WHERE region=..." and "SELECT FROM utility database WHERE region=...".

[2015] Output: The generated SQL query.

[2016] Step 17:

[2017] The server runs SQL queries to retrieve job listings and public facility information.

[2018] Input: The generated SQL query.

[2019] How it works: The server runs SQL queries against the database to retrieve a list of jobs and public accommodations.

[2020] Output: A list of the job and public facility information retrieved.

[2021] Step 18:

[2022] The server temporarily saves the acquired regional information.

[2023] Input: Retrieved job information and public facility information.

[2024] How it works: The server stores the location information in a temporary database.

[2025] Output: Region information stored in a temporary database.

[2026] Step 19:

[2027] The emotion engine takes into account the user's stress level and selects the most appropriate local information.

[2028] Input: Retrieved local information, user's stress level.

[2029] How it works: The emotion engine selects local information based on stress levels and creates a candidate list.

[2030] Output: A list of selected locality candidates.

[2031] Step 20:

[2032] The server finally sends all the information (vacant house list, renovation plan, emotion-based optimization plan, and local information) to the user's device.

[2033] Input: vacant home listings, renovation plans, sentiment-based plans, local information.

[2034] How it works: The server aggregates the information and sends it to the user's device in JSON format.

[2035] Output: Comprehensive information sent to the terminal.

[2036] Step 21:

[2037] The device displays this information in a visually easy-to-understand format.

[2038] Input: General information sent from the server.

[2039] Operation: The device displays information using a UI (user interface).

[2040] Output: A list of available properties, renovation plans, sentiment-based plan revision suggestions, and local information presented in a visually easy-to-understand format.

[2041] (Application example 2)

[2042] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2043] Conventional renovation plan generation systems identify suitable properties based on the user's basic information and living conditions, and then provide a renovation plan. However, they are unable to optimize the plan to reflect the user's emotions or provide visual confirmation using 3D models, making it difficult to increase user satisfaction. Furthermore, they are also inadequate in providing information about life after relocation (job information and public facility information). Therefore, there is a need for a system that can dynamically optimize renovation plans based on the user's emotions, enable visual confirmation using AR technology, and also provide local information.

[2044] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for inputting a user's basic information and housing conditions; means for receiving the input information; means for searching a nationwide real estate database based on the received information to identify properties that meet the user's conditions; means for driving a generative model to generate a renovation plan for the identified property; means for visually displaying the generated renovation plan on a visual display worn by the user; means for recognizing the user's emotions in real time using an emotion engine; means for optimizing the renovation plan based on the recognized emotions; means for collecting employment information and public facility information for a specified area; and means for displaying the collected information and the generated plan on the user's terminal. This allows the user to visually confirm the renovation plan optimized based on their emotions while also obtaining local information all at once.

[2045] "Basic information of the user" includes information such as the user's age, sex, occupation, desired floor plan, desired area, and budget.

[2046] "Housing conditions" are conditions such as floor plan, area, budget, etc. related to the housing desired by the user.

[2047] The "means for inputting" refers to a means for the user to input the basic information and residential conditions described above, and includes voice recognition, gesture input, and the like.

[2048] The "receiving means" is a means by which the server receives information input by the user.

[2049] A "real estate database" is a database that stores information on vacant houses and data related to real estate properties.

[2050] A "generative model" is a model that uses artificial intelligence to automatically generate renovation plans.

[2051] A "visual display" is a display device worn by a user, such as smart glasses or a head-mounted display.

[2052] The "emotion engine" is an engine that analyzes the user's facial expressions and voice in real time to recognize the user's emotional state.

[2053] The "means for recognizing" is a means for recognizing the user's emotions in real time using an emotion engine.

[2054] The "optimizing means" is a means for dynamically optimizing the renovation plan based on the recognized sentiment.

[2055] "Employment Information" means job information in a designated area.

[2056] "Public facility information" is information about public facilities such as schools, hospitals, and parks in a designated area.

[2057] "Means of collection" means the means for collecting employment information and public facilities information for the designated area.

[2058] The "display means" is a means for displaying the collected information and the generated plan on the user's terminal.

[2059] A "terminal" is a device used by a user, such as a smartphone or tablet.

[2060] The present invention is a system that allows users to input their basic information and housing requirements, and then identifies the most suitable vacant property based on that information and generates a renovation plan.The system also incorporates an emotion engine, which can optimize the renovation plan based on the user's emotions and provide local information.Specific embodiments for implementing the present invention are described below.

[2061] Entering user information

[2062] Users wear smart glasses or a head-mounted display and use voice commands or gestures to input their basic information (age, gender, occupation, etc.) and housing requirements (floor plan, area, budget, etc.). This information is then sent from the user device to the server.

[2063] Receiving and retrieving data

[2064] The server searches a nationwide real estate database based on the received user information, thereby identifying properties that meet the user's criteria.

[2065] Generate renovation plans

[2066] The server inputs the identified property information into a generative AI model and automatically generates a renovation plan, which includes a 3D image of the interior and a detailed breakdown of costs.

[2067] Emotion recognition by emotion engine

[2068] Using the camera and microphone built into the smart glasses or head-mounted display worn by the user, the emotion engine analyzes the user's facial expressions and voice in real time, thereby recognizing the user's emotional state.

[2069] Emotion-Based Optimization

[2070] Based on the emotions recognized, renovation plans are dynamically optimized: for example, if a user expresses dissatisfaction with a particular design, alternative design ideas are instantly suggested.

[2071] Providing local information

[2072] The server also collects information on job openings and public facilities in the designated area, allowing users to obtain comprehensive information on their living environment after relocating.

[2073] Final display of information

[2074] Finally, all the information collected by the server (vacant house lists, renovation plans, emotion-based optimization plans, and local information) is visually displayed on the user's smart glasses or head-mounted display.

[2075] Specific use cases

[2076] For example, suppose a 35-year-old male engineer is looking for a 3LDK apartment in Tokyo with a budget of less than 50 million yen. In this case, the user might use the following prompt:

[2077] "User Information:

[2078] Age: 35

[2079] Gender: Male

[2080] Occupation: Engineer

[2081] Desired layout: 3LDK

[2082] Preferred area: Tokyo

[2083] Budget: 50 million yen

[2084] Identify vacant properties that fit your criteria, generate renovation plans, and suggest new plans when users express dissatisfaction with the sentiment engine.

[2085] Based on these prompts, the server identifies vacant properties and generates renovation plans. When the user reviews the proposed plans on a wearable visual display, the emotion engine reads the user's emotions from their facial expressions and voice and provides optimized design proposals in real time. It can also provide information on job openings and public facilities in the specified area.

[2086] This allows users to efficiently obtain renovation plans customized based on their emotions and information about their living environment after moving.

[2087] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2088] Step 1: Enter your basic information and residential conditions

[2089] The user wears smart glasses or a head-mounted display and uses voice commands or gestures to input information such as age, gender, occupation, desired layout, desired area, budget, etc. This input information is then sent from the user terminal to the server.

[2090] Input: User's basic information and housing requirements (age, gender, occupation, desired layout, area, budget)

[2091] Output: User information sent to the server

[2092] Step 2: Receive user information and search the real estate database

[2093] The server searches the real estate database based on the received user information to identify properties that meet the user's criteria. This process involves generating an SQL query to search the database.

[2094] Input: User information sent to the server

[2095] Output: List of properties that match the criteria

[2096] Step 3: Generate renovation plans

[2097] Based on the identified property information, the server runs a generative AI model to generate a renovation plan, which inputs the property information as prompts and outputs a 3D image of the interior and a detailed cost breakdown.

[2098] Input: List of properties that match your criteria

[2099] Output: Renovation plan generated by the AI ​​model (3D image, cost breakdown)

[2100] Step 4: Visualize your renovation plans

[2101] The generated renovation plan is visually displayed on the user's smart glasses or head-mounted display using an AR library.

[2102] Input: Generated renovation plan (3D image, cost details)

[2103] Output: Renovation plan displayed on a visual display

[2104] Step 5: Recognize the user's emotions

[2105] While the...

Claims

1. A means for inputting basic information and residential conditions of the user; means for receiving input information; A means for searching a nationwide real estate database based on the received information to identify properties that meet the user's requirements; means for driving an artificial intelligence model to generate a renovation plan for the identified property; A means of collecting job information and public facility information for a designated area; means for displaying the collected information and the generated plan on a user's terminal; A system including:

2. 10. The system of claim 1, further comprising means for providing a detailed cost breakdown of the renovation plan.

3. The system according to claim 1 , further comprising means for visually displaying the generated renovation plan and local information in an easy-to-understand manner.

Images