system

Abstract

To provide a system.SOLUTION: The system includes: generation means for inputting a specific prompt sentence into a generative AI model, thereby automatically generating a blueprint of a housing desired by a user on the basis of user house-related information including the design, the style and the condition of the house and real estate information; means for proposing the housing on the basis of the generated blueprint; means for adjusting the interior design and the layout in the blueprint of the housing on the basis of an emotion engine for recognizing the emotion of the user and the emotion; and means for displaying the adjusted blueprint by using a virtual reality display device.SELECTED DRAWING: Figure 1

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When a user designs a house according to their preferences and wishes, it is necessary to consider a lot of information, and the process is complex. Also, it is difficult to appropriately utilize real estate information for house design.

Means for Solving the Problems

[0005] As a means to solve this problem, the present invention includes a generation means that automatically generates a blueprint of a house based on user housing-related information including the user's preferred house design, style and conditions, and real estate information, by inputting a specific prompt sentence into a generating AI model; a means for proposing the house based on the generated blueprint; an emotion engine that recognizes the user's emotions; a means for adjusting the interior and layout included in the blueprint of the house based on the emotions; and a means for displaying the adjusted blueprint using a virtual reality display device. [Brief explanation of the drawing]

[0006] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 1 of Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of Embodiment 2. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2. [Figure 15] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 3 of Example 3. [Figure 16] This is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3. [Figure 17] This is a sequence diagram showing the processing flow of the data processing system in Example 1 of the Form 1 when an emotion engine is combined. [Figure 18] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of the Form 2 when an emotion engine is combined. [Figure 20] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] This is a sequence diagram showing the processing flow of the data processing system in Example 3 of the Form 3 when an emotion engine is combined. [Figure 22] This is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. [Modes for carrying out the invention]

[0007] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0008] ru.

[0009] First, the terms used in the following description will be explained.

[0010] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)), etc.

[0011] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0012] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0013] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0014] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0015] [First Embodiment]

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

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

[0018] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

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

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

[0025] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0026] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0027] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0028] "Example of form 1"

[0029] In one embodiment of the system, a user saves images of their preferred homes from social media such as Instagram and inputs the image information into the system. The user also inputs information about their family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment. Based on this preference and desired information, the system automatically generates a blueprint for the home.

[0030] "Example of form 2"

[0031] Furthermore, this system acquires land and building information from real estate information websites and automatically generates house designs based on this information. Specifically, it proposes window orientations, sizes, floor plans, etc., taking into account the shape of the land and building, location conditions, etc.

[0032] "Example of form 3"

[0033] For example, if a user inputs an image of a modern exterior saved from Instagram, along with information such as being a family of four, wanting a detached house in Tokyo, and having a budget of 50 million yen, the system will automatically generate a blueprint for a detached house in Tokyo with a modern exterior based on this information. Furthermore, it will suggest window orientations, sizes, floor plans, etc., based on land and building information in Tokyo obtained from real estate information websites.

[0034] The following describes the processing flow for each example of the form.

[0035] "Example of form 1"

[0036] Step 1: The user saves images of their favorite houses from social media such as Instagram.

[0037] Step 2: The user inputs the saved image information into this system.

[0038] Step 3: The user enters their family structure, desired address, price range, whether or not they want renovations, and other desired information such as a house or apartment into the system.

[0039] Step 4: This system automatically generates house plans based on these preference and desired information.

[0040] "Example of form 2"

[0041] Step 1: This system obtains land and building information from real estate information websites.

[0042] Step 2: This system automatically generates house plans based on the acquired land and building information. Specifically, it proposes window orientations, sizes, floor plans, etc., taking into account the shape of the land and building, location conditions, etc.

[0043] "Example of form 3"

[0044] Step 1: The user enters images of modern exteriors saved from Instagram, along with information such as being a family of four, wanting a detached house in Tokyo, and having a budget of 50 million yen.

[0045] Step 2: Based on this information, the system automatically generates a blueprint for a modern-looking detached house in Tokyo.

[0046] Step 3: This system uses land and building information in Tokyo obtained from real estate information websites to suggest window orientations, sizes, floor plans, etc.

[0047] (Example 1)

[0048] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0049] Conventional housing design systems have struggled to automatically generate blueprints that reflect the user's preferences and desires. Furthermore, a lack of effective means to utilize image information obtained from social media meant that the user's specific preferences could not be reflected in the design. Additionally, when proposing housing designs based on the generated blueprints, it was difficult to provide proposals that matched the user's wishes.

[0050] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design drawing based on this information, means for receiving image information saved by the user as input and analyzing this information to identify the user's preferences, means for generating and inputting prompt sentences to the generation AI model, and means for making house proposals based on the generated design drawing. This makes it possible to automatically generate a house design drawing that reflects the user's specific preferences and desires, and to make house proposals that match the user's desires.

[0051] "User preference information" refers to information about the housing designs and styles that users prefer, and includes images and text data obtained from social media.

[0052] "Desired information" refers to the specific conditions and requirements that the user desires regarding housing, including information such as family structure, desired address, price range, whether renovations are planned, and whether it is a detached house or an apartment.

[0053] "Image information" refers to image data of houses that users obtain from social media or other sources and upload to the system.

[0054] A "generative AI model" is an artificial intelligence model that automatically generates house blueprints based on user preferences and desired information, and utilizes natural language processing and image analysis technologies.

[0055] A "prompt message" is an instruction given to the AI ​​generation model, and it is generated based on the user's preferences and desired information.

[0056] A "house design plan" is a design drawing of a house generated based on the user's preferences and desired information, and includes specific layouts and designs.

[0057] A "housing proposal" is a proposal made to a user based on the generated housing blueprints, and includes content that matches the user's wishes.

[0058] This invention is based on the premise that users save images of their preferred homes from social media such as Instagram and input that image information into the system. Users also input their family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment. Based on this information, the system automatically generates a blueprint for the house.

[0059] Hardware and software to be used

[0060] The server receives image information and request information entered by the user and stores it in a database. Specifically, it uses the following hardware and software:

[0061] Server: High-performance cloud server (e.g., Amazon Web Services, Google Cloud Platform)

[0062] Database: Relational database (e.g., MySQL®, PostgreSQL)

[0063] Generative AI models: AI models that utilize natural language processing and image analysis technologies (e.g., OpenAI®'s GPT-4®, DALL-E)

[0064] Image analysis software: Computer vision technology (e.g., TENSORFLOW®, PyTorch)

[0065] Data processing and data calculation

[0066] The server receives image files uploaded by the user and requested information, and stores this data in a database. Based on the stored data, it generates prompt messages for the AI ​​model and inputs them. The AI ​​model generates house blueprints based on the prompt messages and provides them to the user via the server.

[0067] Specific example

[0068] As a concrete example, suppose a user saves an image of a modern-designed house from Instagram and enters the following desired information:

[0069] Family composition: 4 people (2 adults, 2 children)

[0070] Desired address: Tokyo

[0071] Price range: Under 50 million yen

[0072] Renovation status: Yes

[0073] House or apartment: House

[0074] Based on this information, the server inputs the following prompt message into the AI ​​model:

[0075] Based on images of modern-designed homes saved by the user from Instagram, please generate blueprints for a home that matches the following requirements.

[0076] Family composition: 4 people (2 adults, 2 children)

[0077] Desired address: Tokyo

[0078] Price range: Under 50 million yen

[0079] Renovation status: Yes

[0080] House or apartment: House

[0081] Based on this prompt, the generation AI model generates a house design that matches the user's preferences and provides it to the user via the server. The user can review the received design on their device and, if necessary, modify their preferences to generate a new design.

[0082] In this way, it becomes possible to automatically generate house designs that reflect the user's specific preferences and desires, and to propose houses that match the user's wishes.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users save images of their favorite houses from social media such as Instagram. Users use their smartphones or computers to find and save images of their favorite houses from social media such as Instagram. The input is image data obtained from social media, and the output is an image file saved on the user's device.

[0086] Step 2:

[0087] The user uploads saved images to the system. The user accesses the system's website or application and uploads saved images of their home. Specifically, they click an upload button and select the saved image file. The input is the image file stored on the user's device, and the output is the image data sent to the server.

[0088] Step 3:

[0089] The user enters their desired information, such as family structure, preferred address, price range, whether renovations are needed, and whether they want a house or an apartment. The user enters their desired information into the system's input form, such as family structure (e.g., 2 adults, 2 children), preferred address (e.g., Tokyo), price range (e.g., under 50 million yen), whether renovations are needed (e.g., yes), and whether they want a house or an apartment (e.g., house). The input is the desired information entered by the user, and the output is the desired information sent to the server.

[0090] Step 4:

[0091] The server receives image information and request information from the user and stores it in the database. The server receives uploaded image files and input request information from the user and stores this data in the database. When saving, the data is managed in association with the user ID. The input is the image information and request information sent by the user, and the output is the data stored in the database.

[0092] Step 5:

[0093] The server generates prompt messages for the AI ​​model based on the stored data and inputs them. The server generates prompt messages to input to the AI ​​model based on image information and desired information stored in the database. For example, it generates prompt messages like the following:

[0094] Based on images of modern-designed homes saved by the user from Instagram, please generate blueprints for a home that matches the following requirements.

[0095] Family composition: 4 people (2 adults, 2 children)

[0096] Desired address: Tokyo

[0097] Price range: Under 50 million yen

[0098] Renovation status: Yes

[0099] House or apartment: House

[0100] The input consists of image information and desired information stored in a database, and the output is a prompt message that is input to the generating AI model.

[0101] Step 6:

[0102] The generative AI model generates a house design based on the prompt text. The generative AI model (e.g., OpenAI's GPT-4 or DALL-E) generates the house design based on the prompt text sent from the server. The generative AI model utilizes image analysis and natural language processing techniques to create a design that meets the user's needs. The input is the prompt text, and the output is the generated house design.

[0103] Step 7:

[0104] The server sends the generated blueprint to the user's terminal. The server sends the blueprint received from the generated AI model to the user's terminal. The user can download or view the blueprint through the system's website or application. The input is the generated house blueprint, and the output is the blueprint sent to the user's terminal.

[0105] Step 8:

[0106] The user reviews the blueprint. The user reviews the blueprint received on their device. They can check if the blueprint meets their requirements and, if necessary, modify the required information to generate a new blueprint. The input is the blueprint sent to the user's device, and the output is the user's review result.

[0107] (Application Example 1)

[0108] Next, we will describe Application Example 1 of Form 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."

[0109] Conventional home design systems struggled to automatically generate blueprints that reflected users' preferences and desires. In particular, if a user had a specific image in mind, specialized knowledge was required to translate that image into a blueprint. Furthermore, real-time blueprint generation and display were difficult when users viewed home designs in physical showrooms. This led to decreased user satisfaction and delays in home purchase decisions.

[0110] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0111] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that analyzes a house image taken by the user and extracts its features; a server that generates prompt text based on the extracted features and the user's desired information and generates a house design using a generation AI model; and a server that presents the generated design to the user through a display device. This enables the generation of a house design that reflects the user's specific image in real time and allows for verification at a physical store.

[0112] "User preference information" refers to information that indicates a user's personal preferences and design tastes regarding housing.

[0113] "Desired information" refers to information that indicates the specific requests and conditions that the user has regarding housing (family structure, desired address, price range, whether or not renovations are planned, whether it's a detached house or an apartment, etc.).

[0114] "Real estate information" refers to information that provides detailed data about a real estate property (location, price, floor plan, year built, etc.).

[0115] A "house design drawing" is a diagram that specifically shows the structure, layout, and design of a house.

[0116] "Means of automatic generation" refers to devices or programs that have the function of automatically creating design drawings using algorithms or AI models based on input information.

[0117] "Means of making proposals" refers to devices or programs that have the function of making housing proposals to users based on the generated blueprints.

[0118] "House images" refer to photographs or image data of houses taken by users.

[0119] "Means of analysis" refers to devices or programs that have the function of analyzing input image data and extracting its features.

[0120] "Means for extracting features" refer to devices or programs that have the function of extracting important features from data obtained through image analysis.

[0121] A "prompt statement" is a text-based input statement used to give instructions to a generative AI model.

[0122] A "generative AI model" is an artificial intelligence model that generates blueprints and other data based on input prompts.

[0123] A "display device" is a device (such as a display or VR headset) used to visually present a generated design to a user.

[0124] A system for carrying out this invention includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for analyzing a house image taken by the user and extracting its features; means for generating prompt sentences based on the extracted features and the user's desired information and generating a house design using a generation AI model; and means for presenting the generated design to the user through a display device.

[0125] Hardware and software to use

[0126] hardware

[0127] Smartphone or tablet (iOS or Android®): Used by the user to take pictures of the house and input information.

[0128] Smart glasses (e.g., Google Glass®): Used to analyze images taken by the user in real time.

[0129] Large screen display or VR headset (e.g., Oculus Rift): Used to present the generated blueprints to the user.

[0130] software

[0131] Image recognition libraries (e.g., OpenCV): Used to analyze residential images taken by the user and extract their features.

[0132] Generative AI models (e.g., GPT-4, DALL-E): Used to generate house blueprints based on prompt statements.

[0133] Database (e.g., Firebase): Used to store and manage user preferences, requests, and property information.

[0134] Frontend frameworks (e.g., React Native): Used to build user interfaces.

[0135] Processing flow

[0136] 1. User input

[0137] Users use their smartphones or tablets to take pictures of their preferred homes and upload them to the application. They also enter information such as family size, desired address, price range, whether renovations are needed, and whether they want a house or an apartment.

[0138] 2. Image Analysis

[0139] The server uses an image recognition library (OpenCV) to analyze uploaded images of houses and extract their features.

[0140] 3. Generating prompt statements

[0141] The server generates prompt messages for the generative AI model (GPT-4) based on the extracted features and user preferences.

[0142] Example of a prompt

[0143] Based on the images and desired information provided by the user, please generate a blueprint for a house that meets the following conditions:

[0144] Family composition: 4 people

[0145] Desired address: Tokyo

[0146] Price range: Under 50 million yen

[0147] Renovation: Yes

[0148] Detached house

[0149] Modern design

[0150] 4. Generating blueprints

[0151] The server uses a generative AI model (DALL-E) to generate house blueprints based on prompt messages.

[0152] 5. Displaying the results

[0153] The generated blueprints are presented to the user via a large screen display or VR headset. Users can then view their ideal home design in real time at a physical store.

[0154] Specific example

[0155] For example, a user uploads an image of a modern living room taken with their smartphone and enters their desired information as "Family composition: 4 people, Desired address: Tokyo, Price range: under 50 million yen, Renovation: Yes, Detached house." Based on this information, the server generates a blueprint for a modern detached house in Tokyo that is under 50 million yen, suitable for a family of four, and allows for renovation, and presents it to the user.

[0156] In this way, users can check their ideal home design in real time at a physical store.

[0157] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0158] Step 1:

[0159] Users use their smartphones or tablets to take pictures of their preferred homes and upload them to the application. They also enter information such as family size, desired address, price range, whether renovations are needed, and whether they want a house or an apartment.

[0160] Input: Housing images, family composition, desired address, price range, whether renovation is needed, desired type of housing (house or apartment), etc.

[0161] Output: Uploaded house images and desired information

[0162] Step 2:

[0163] The server uses an image recognition library (OpenCV) to analyze uploaded images of houses and extract their features.

[0164] Input: Uploaded house images

[0165] Output: Extracted image features

[0166] Specific operation: Using an image recognition library, perform edge detection and color analysis on residential images and extract features.

[0167] Step 3:

[0168] The server generates prompt messages for the generative AI model (GPT-4) based on the extracted features and user preferences.

[0169] Input: Extracted image features, desired information

[0170] Output: Generated prompt message

[0171] Specific operation: Combine the extracted features and desired information to create prompt sentences for input into the generating AI model.

[0172] Step 4:

[0173] The server uses a generative AI model (DALL-E) to generate house blueprints based on prompt messages.

[0174] Input: Generated prompt message

[0175] Output: Generated house blueprints

[0176] Specific operation: Input prompt text into the generation AI model and generate a blueprint for a house.

[0177] Step 5:

[0178] The server presents the generated blueprints to the user via a large screen display or VR headset.

[0179] Input: Generated house blueprints

[0180] Output: Design drawings presented to the user

[0181] Specific operation: The generated design drawings are sent to a display or VR headset so that the user can visually confirm them.

[0182] In this way, users can check their ideal home design in real time at a physical store.

[0183] (Example 2)

[0184] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0185] Conventional residential design systems had the problem of requiring a great deal of time and effort to reflect the user's preferences and desired information. Furthermore, it was difficult to efficiently acquire real estate information and automatically generate optimal residential designs based on it. As a result, it was difficult to quickly provide residential designs that satisfied users.

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

[0187] In this invention, the server includes means for acquiring land and building information from a real estate information provision site, means for storing the acquired information in a data frame and processing the data, means for generating prompt sentences to be input to a generation AI model based on the processed data, means for automatically generating house blueprints using the generation AI model, and means for making house proposals based on the generated blueprints. This makes it possible to quickly and efficiently provide house blueprints that reflect the user's preferences and desired information.

[0188] A "real estate information website" is a website that provides information about land and buildings.

[0189] "Land and building information" refers to detailed data such as the shape of the land, the location of the building, the direction and size of the windows, and the floor plan.

[0190] A "data frame" is a two-dimensional data structure consisting of rows and columns, used for storing and processing data.

[0191] "Data processing" is the process of transforming acquired data into a format that is easy to analyze and use, and includes processes such as imputing missing values ​​and normalizing data.

[0192] A "generative AI model" is a model that uses artificial intelligence to perform a specific task, and in this case, it is used to automatically generate blueprints for a house.

[0193] A "prompt message" is an instruction message used to input into a generation AI model, and it is generated based on information about the land and buildings.

[0194] "House design drawings" are diagrams that show the layout and structure of a house, and they form the basis of the building plan.

[0195] A "housing proposal" refers to a suggestion made to the user regarding the design and layout of a house, based on the generated blueprints.

[0196] Modes for carrying out the invention

[0197] This invention relates to a system that obtains land and building information from real estate information websites and automatically generates house blueprints based on this information. A specific embodiment of this system is described below.

[0198] 1. Program generation

[0199] The server generates a program to retrieve land and building information from real estate information websites. This program is developed using Python and performs web scraping using libraries such as BeautifulSoup and Selenium.

[0200] 2. Data acquisition and processing

[0201] The server executes the generated program and retrieves land and building information from real estate information websites. Specifically, it collects data such as land shape, building location, window orientation and size, and floor plan. The collected data is stored in a dataframe using the Pandas library, and necessary data processing is performed. For example, missing values ​​are imputed and data normalization is performed.

[0202] 3. Generating prompt sentences for the generative AI model

[0203] The server generates prompt statements to input into the AI ​​model based on the processed data. These prompt statements include information such as the shape of the land and building, location conditions, window orientation, size, and floor plan.

[0204] Example of a prompt:

[0205] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[0206] Land shape: Rectangle

[0207] Building location: South-facing

[0208] Window orientation: South-facing

[0209] Window size: Large

[0210] Floor plan: 3LDK

[0211] 4. Generating house design plans

[0212] The server inputs the generated prompt text into a generation AI model (for example, a generation AI model) and generates a blueprint for a house. The generation AI model then proposes the optimal blueprint based on the prompt text.

[0213] 5. Displaying the results

[0214] The server displays the generated house design plans on the user's terminal. The user can review the proposed design plans and request revisions as needed.

[0215] Specific example

[0216] If a user requests to "generate a house design based on land information in Shibuya Ward, Tokyo," the server will input the following prompt into the AI ​​model.

[0217] Example of a prompt:

[0218] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[0219] Land shape: Rectangle

[0220] Building location: South-facing

[0221] Window orientation: South-facing

[0222] Window size: Large

[0223] Floor plan: 3LDK

[0224] The AI ​​model generates a house design based on this prompt. The proposed design is displayed on the device for the user to review.

[0225] In this way, the present invention makes it possible to quickly and efficiently provide residential design plans that reflect the user's preferences and desired information.

[0226] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0227] Program processing flow

[0228] Step 1: Obtaining real estate information

[0229] The server retrieves land and building information from real estate information websites. Specifically, it uses Python and libraries such as BeautifulSoup and Selenium to perform web scraping.

[0230] Input: URL of the real estate information website

[0231] Output: Land and building information (e.g., land shape, building location, window orientation, size, floor plan)

[0232] Specific actions:

[0233] The server uses Selenium to automate browser operations and access a specified URL. Next, it uses BeautifulSoup to parse the HTML and extract the necessary information.

[0234] Step 2: Processing of the oars

[0235] The server stores the acquired real estate information in a dataframe using the Pandas library and performs necessary data processing. For example, it might impute missing values ​​or normalize the data.

[0236] Input: Land and building information

[0237] Output: Processed data frame

[0238] Specific actions:

[0239] The server converts the retrieved data into a DataFrame using the Pandas read_html function. Next, it imputes missing values ​​using the fillna function and normalizes the data with the normalize function.

[0240] Step 3: Generating prompts for the generative AI model

[0241] The server generates prompt statements to input into the AI ​​model based on the processed data. These prompt statements include information such as the shape of the land and building, location conditions, window orientation, size, and floor plan.

[0242] Input: Processed data frame

[0243] Output: Prompt message

[0244] Specific actions:

[0245] The server extracts the necessary information from the data frame and generates a prompt message like the following:

[0246] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[0247] Land shape: Rectangle

[0248] Building location: South-facing

[0249] Window orientation: South-facing

[0250] Window size: Large

[0251] Floor plan: 3LDK

[0252] Step 4: Generating the house design plans

[0253] The server inputs the generated prompt text into a generation AI model (for example, a generation AI model) and generates a blueprint for a house. The generation AI model then proposes the optimal blueprint based on the prompt text.

[0254] Input: Prompt message

[0255] Output: House blueprints

[0256] Specific actions:

[0257] The server sends prompts to the API for generating AI models and receives blueprint suggestions in return. For example, it sends prompts using the openai.Completion.create function.

[0258] Step 5: Displaying the results

[0259] The server displays the generated house design plans on the user's terminal. The user can review the proposed design plans and request revisions as needed.

[0260] Input: House blueprints

[0261] Output: Blueprint displayed on the user's terminal

[0262] Specific actions:

[0263] The server formats the generated blueprint into HTML and sends it to the user's terminal. The user then views the blueprint through their browser.

[0264] (Application Example 2)

[0265] Next, we will describe Application Example 2 of Form 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."

[0266] Conventional residential design systems have difficulty reflecting user preferences and desires, and the automatic generation of design plans based on real estate information has been limited. Furthermore, interior design for physical stores requires specialized knowledge and is not easily accessible to the average user. Therefore, there is a need for a system that allows users to easily design houses and stores that meet their specific needs.

[0267] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for automatically generating interior designs for physical stores based on information obtained from real estate information provision sites; means for creating prompt statements for generating design drawings using a generation AI model; and means for generating actual design drawings using a generation AI model. This makes it possible for users to easily design houses and stores that suit their preferences.

[0268] "User preference information" refers to information about the style, functions, and design that users desire when designing houses or shops.

[0269] "Desired information" refers to information about the specific conditions and requirements that users have in mind when designing houses or shops.

[0270] "Real estate information" refers to information about the shape, location, and area of ​​land and buildings.

[0271] A "design drawing" is a diagram that shows the layout of a house or shop, the direction and size of windows, the interior design, and so on.

[0272] A "real estate information providing site" is a website that provides information about land and buildings on the Internet.

[0273] "Interior design" refers to planning the layout and design of the interior space of a store or house.

[0274] A "generative AI model" is an algorithm or program for automatically generating design drawings and designs using artificial intelligence.

[0275] A "prompt text" is an instruction text for inputting into a generative AI model, and is a text containing conditions and requirements for generating design drawings and designs.

[0276] The system for implementing this invention includes a server, a user terminal, and a generative AI model. The specific embodiments of this system will be described below.

[0277] First, the user terminal receives the user's preference information and desired information as inputs. This information relates to the style, functions, and designs that the user desires in the design of a house or store. The user terminal transmits this information to the server.

[0278] Next, the server acquires real estate information from a real estate information providing site. This real estate information includes the shape of the land and building, location conditions, area, etc. The server automatically generates design drawings of a house or store based on the acquired real estate information.

[0279] The server creates a prompt text for generating a design drawing using the generative AI model. This prompt text includes the user's preference information, desired information, and real estate information. For example, a prompt text like the following is generated.

[0280] "Shape of land: rectangular, Location conditions: urban area, Window orientation: south-facing, Lighting position: center of ceiling"

[0281] Based on the generated prompt text, the generative AI model generates the actual design drawing. As the generative AI model, for example, OpenAI's GPT-3 (registered trademark) etc. are used. This model receives the prompt text as input and outputs the design drawing.

[0282] The generated design drawing is sent from the server to the user terminal and presented to the user. The user can check the design of the house or store based on the presented design drawing and make corrections if necessary.

[0283] With this system, the user can easily design a house or store according to their wishes. Specifically, the user can easily generate and check the design drawing using a smartphone or a personal computer. Thus, even without specialized knowledge, the user can realize a design that meets their wishes.

[0284] The above is the specific form for implementing this invention.

[0285] The flow of the specific process in Application Example 2 will be described using FIG. 14.

[0286] Step 1:

[0287] The user terminal receives the user's preference information and wish information as input. The user uses a smartphone or a personal computer to input information regarding the style, functions, and design desired in the design of the house or store. The input information is stored in the user terminal.

[0288] Step 2:

[0289] The user terminal sends the input preference information and wish information to the server. The sent information is stored in the database in the server.

[0290] Step 3:

[0291] The server retrieves real estate information from real estate information websites. The server uses an API to send requests to these websites, obtaining information such as the shape, location, and area of ​​the land and buildings. The retrieved real estate information is then stored on the server.

[0292] Step 4:

[0293] The server generates prompt statements to create a blueprint based on acquired real estate information and user preferences and requests. These prompt statements include information such as the shape of the land, location, window orientation, and lighting position. For example, a prompt statement like "Land shape: Rectangle, Location: Urban area, Window orientation: South-facing, Lighting position: Center of ceiling" might be generated.

[0294] Step 5:

[0295] The server uses a generative AI model to take prompt text as input and generate a blueprint. For example, OpenAI's GPT-3 is used as the generative AI model. The generative AI model, upon receiving prompt text as input, outputs a blueprint. The generated blueprint is then saved to the server.

[0296] Step 6:

[0297] The server sends the generated blueprint to the user's terminal. The user's terminal displays the received blueprint to the user. The user can then view the blueprint on their smartphone or computer screen.

[0298] Step 7:

[0299] Users can review the provided blueprints for houses and shops and make modifications as needed. The modified information is sent back to the server, and the blueprints are regenerated. This allows users to realize a design that meets their needs.

[0300] (Example 3)

[0301] Next, Example 3 of Embodiment 3 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0302] In a conventional housing design system, it is difficult to automatically generate a design drawing that reflects the user's preferences and wishes, and it is also impossible to make an optimal design proposal based on real estate information. Therefore, there is a demand for efficiently providing a housing design that meets the user's needs.

[0303] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0304] In this invention, the server includes means for receiving the user's preference information and wish information as inputs and automatically generating a housing design drawing based on these information, means for receiving real estate information as an input and automatically generating a housing a housing design drawing based on these information, means for making a housing proposal based on the generated design drawing, means for transmitting a prompt sentence and an image to the generation AI model to generate a design drawing, means for acquiring land and building information from a real estate information providing site, means for making an optimal design proposal based on the acquired real estate information, and means for displaying the generated design drawing and proposal content to the user. Thereby, it becomes possible to automatically generate a housing design drawing that reflects the user's preferences and wishes and make an optimal design proposal based on real estate information.

[0305] The "user's preference information" is information indicating the user's personal preferences such as the design, style, and functions desired in housing design.

[0306] The "wish information" is information on specific conditions and requirements sought by the user in housing design, such as family composition, budget, location, etc.

[0307] The "real estate information" is detailed data on the price, area, surrounding environment, etc. of land and buildings.

[0308] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate blueprints based on user input information.

[0309] A "prompt statement" is a text-based input statement used to give instructions to a generative AI model.

[0310] A "design drawing" is a diagram that shows the structure, layout, and design of a house.

[0311] A "real estate information website" is an online platform that provides information about land and buildings.

[0312] "Optimal design proposal" refers to proposing the most suitable residential design based on the user's preferences, desires, and real estate information.

[0313] "Means of display" refers to methods or devices for visually providing users with generated design drawings or proposed content.

[0314] This invention is a system that automatically generates house blueprints based on user preference and desired information, and provides optimal design suggestions based on real estate information. A specific embodiment of this system is described below.

[0315] System Configuration

[0316] This system consists of three main elements: a server, a terminal, and a user. The server receives input information from the user, generates blueprints using a generative AI model, and provides optimal design suggestions based on real estate information. The terminal provides an interface for the user to input information and check the results. The user accesses the system through the terminal and inputs the necessary information.

[0317] Hardware and software to be used

[0318] Server: A server with high-performance computing capabilities is required. Specifically, a cloud-based server (e.g., Amazon Web Services or Google Cloud Platform) should be used.

[0319] Terminal: A device used by a user to input information. This includes internet-connected devices such as personal computers, tablets, and smartphones.

[0320] Generative AI Models: Advanced artificial intelligence models such as OpenAI's GPT-4 and DALL-E are used as generative AI models.

[0321] Real estate information websites: Use online platforms (e.g., SUUMO or At Home) to obtain real estate information.

[0322] Data processing and calculations

[0323] 1. User Information Input: The user accesses a form on a web browser using their device and uploads a modern-looking image saved from Instagram. Next, they enter their family composition (4-person family), desired area (Tokyo), and budget (50 million yen).

[0324] 2. Prompt Generation: The server receives the information entered by the user and generates prompts for input into the generated AI model. Specifically, it generates prompts like the following:

[0325] "Based on images of modern exteriors saved by users on Instagram, please automatically generate blueprints for a detached house in Tokyo suitable for a family of four, with a budget of under 50 million yen."

[0326] 3. Sending to the Generating AI Model: The server sends the generated prompt text and the user-uploaded image to the Generating AI model. This transmission is done via API.

[0327] 4. Blueprint Generation: The generation AI model generates a blueprint for a modern-looking detached house in Tokyo based on the received prompt text and image. The blueprint includes details such as the orientation and size of windows and the floor plan. The generated blueprint is sent back to the server.

[0328] 5. Acquisition of Real Estate Information: The server uses the API of a real estate information provider site to acquire information on land and buildings in Tokyo. The information acquired includes land prices, building area, and surrounding environment.

[0329] 6. Optimal Design Proposal: Based on the acquired real estate information, the server proposes the optimal window orientation, size, and layout for the generated design drawings. For example, by proposing a design drawing with many south-facing windows, it provides a living environment with plenty of sunlight.

[0330] 7. Displaying Results: The server displays the final design and proposal to the user. The user can review this information in a web browser and make modifications or regenerate it as needed. An interactive UI is used for the display to ensure ease of use for the user.

[0331] Specific example

[0332] If the user enters the following information:

[0333] Modern exterior images saved from Instagram

[0334] family of 4

[0335] I want a detached house in Tokyo.

[0336] The budget is 50 million yen.

[0337] The server generates the following prompt:

[0338] "Based on images of modern exteriors saved by users on Instagram, please automatically generate blueprints for a detached house in Tokyo suitable for a family of four, with a budget of under 50 million yen."

[0339] The AI ​​model generates a design drawing based on this prompt text and image, and the server proposes the optimal window orientation, size, and floor plan based on data obtained from a real estate information website. The specific processing flow in Example 3 will be explained using Figure 15.

[0340] Step 1:

[0341] The user enters information.

[0342] The user accesses a form on a web browser using their device and uploads a modern-looking image saved from Instagram. Next, they enter their family size (four people), desired location (within Tokyo), and budget (50 million yen). This information is then sent to the server.

[0343] Input: Images saved from Instagram, family composition, desired region, budget

[0344] Output: User preference information and desired information

[0345] Step 2:

[0346] The server generates the prompt message.

[0347] The server receives the information entered by the user and generates prompt messages for input into the generated AI model. Specifically, it generates prompt messages like the following:

[0348] "Based on images of modern exteriors saved by users on Instagram, please automatically generate blueprints for a detached house in Tokyo suitable for a family of four, with a budget of under 50 million yen."

[0349] Input: User preferences and desired information

[0350] Output: Prompt message to send to the generating AI model

[0351] Step 3:

[0352] The server sends prompt text and images to the generated AI model.

[0353] The server sends the generated prompt text and the user-uploaded image to the AI ​​model. This transmission is done via API.

[0354] Input: Prompt text, user-uploaded image

[0355] Output: Input data for the generative AI model

[0356] Step 4:

[0357] The generative AI model generates the blueprint.

[0358] The generation AI model generates a blueprint of a modern-looking detached house in Tokyo based on the received prompt text and image. The blueprint includes details such as the direction and size of windows and the floor plan. The generated blueprint is then sent back to the server.

[0359] Input: Prompt text, user-uploaded image

[0360] Output: Generated blueprint

[0361] Step 5:

[0362] The server retrieves real estate information.

[0363] The server uses the API of a real estate information website to retrieve information on land and buildings in Tokyo. The information retrieved includes land prices, building area, and surrounding environment.

[0364] Input: API of a real estate information provider website

[0365] Output: Acquired real estate information

[0366] Step 6:

[0367] The server will propose the optimal design.

[0368] Based on the acquired real estate information, the server proposes optimal window orientations, sizes, and floor plans for the generated blueprints. For example, by proposing blueprints with many south-facing windows, it provides a living environment with plenty of sunlight.

[0369] Input: Generated blueprints, acquired property information

[0370] Output: Optimal design proposal

[0371] Step 7:

[0372] The server displays the results to the user.

[0373] The server displays the final design blueprints and proposals to the user. The user can review this information in a web browser and modify or regenerate it as needed. An interactive UI is used for display to ensure user-friendliness.

[0374] Input: Final design drawings, proposed content

[0375] Output: Results displayed to the user

[0376] (Application Example 3)

[0377] Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0378] Conventional residential design systems struggled to automatically generate blueprints that reflected user preferences and desires, and were unable to effectively utilize real estate information to propose blueprints. Furthermore, they could not utilize images saved by users or information from social media, making it difficult to provide blueprints that met specific user needs. This resulted in a challenge in increasing user satisfaction.

[0379] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0380] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that generates prompt text based on images saved by the user and generates a design using a generation AI model; and a server that proposes window orientation and size, floor plan, etc., based on land and building information obtained from a real estate information provision site. This enables the automatic generation of design plans that meet the user's specific needs and the effective use of real estate information.

[0381] "User preference information" refers to information about the design and style that users desire, and is obtained from sources such as social media and saved images.

[0382] "Desired information" refers to information about the conditions and requirements of the housing that the user desires, including specific preferences such as family structure, budget, and location.

[0383] A "house design drawing" is a diagram showing the exterior, floor plan, window orientation and size, etc., of a house, and is automatically generated based on the user's preferences and requests.

[0384] "Real estate information" refers to information about land and buildings, and is obtained from real estate information websites and other sources.

[0385] A "generative AI model" is a model that uses artificial intelligence to generate blueprints or proposals from specific input information.

[0386] A "prompt message" is an instruction message to be input into a generation AI model, and it is generated based on the user's preferences and desired information.

[0387] A "real estate information website" is a website that provides information about land and buildings, and users can access and obtain this information.

[0388] "Window orientation, size, and floor plan" are important elements in house design and are proposed based on the user's wishes and real estate information.

[0389] The system for implementing this invention includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for generating prompt text based on images saved by the user and generating a design using a generation AI model; and means for proposing window orientation and size, floor plan, etc., based on land and building information obtained from a real estate information provision site.

[0390] System program

[0391] The server receives preference and desired information entered by the user via a device such as a smartphone or computer. This includes images obtained from social media such as Instagram, as well as information such as family structure, budget, and desired region. Next, the server generates prompt statements based on this information. These prompt statements are input into a generation AI model and serve as instructions for generating a house design.

[0392] Based on the generated prompt text, the AI ​​model automatically creates a blueprint for a house. This blueprint reflects the user's preferences and desires, and includes specific exterior details and floor plans. Furthermore, the server suggests window orientations and sizes, floor plans, and other details based on land and building information obtained from real estate information websites.

[0393] Hardware and software to be used

[0394] This system uses the following hardware and software:

[0395] Hardware: Servers, user terminals (smartphones, personal computers, etc.)

[0396] Software: Generative AI models (e.g., OpenAI's GPT-3), prompt generation programs, image acquisition programs (e.g., requests, PIL)

[0397] Specific example

[0398] For example, if the user enters the following conditions:

[0399] Instagram image URL: https: / / example.com / instagram_image.jpg

[0400] Family structure: 4 people family

[0401] Desired area: Tokyo

[0402] Budget: 50 million yen

[0403] The generated prompt will look like this:

[0404] Based on images of modern exteriors saved by the user on Instagram, we need a design for a detached house in Tokyo for a family of four with a budget of 50 million yen. Please generate a blueprint for a detached house with a modern exterior based on this information.

[0405] When this prompt is entered into the AI ​​model, the model automatically generates a house design that meets the user's preferences. The generated design reflects the user's desired modern exterior and a floor plan suitable for the family structure. In addition, based on land and building information obtained from real estate information websites, the model also makes specific suggestions regarding window orientation and size, floor plan, and other details.

[0406] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0407] Step 1:

[0408] Users input their preferences and desired information from devices such as smartphones and computers. This includes image URLs obtained from social media such as Instagram, as well as information such as family structure, budget, and desired region. The entered information is sent to the server.

[0409] Input: Instagram image URL, family composition, budget, desired region

[0410] Output: User preference information and desired information sent to the server

[0411] Step 2:

[0412] The server receives preference and request information sent by the user. Based on the received information, it performs data processing to generate prompt messages. Specifically, it retrieves image URLs and converts information such as family structure, budget, and desired region into text format.

[0413] Input: User preferences and desired information

[0414] Output: Data for prompt message generation

[0415] Step 3:

[0416] The server downloads the image based on the retrieved image URL and loads it as an image object. This process uses the requests library and the PIL library.

[0417] Input: Image URL

[0418] Output: Image object

[0419] Step 4:

[0420] The server generates prompt messages based on image objects and user information in text format. These generated prompt messages are instructions to be input into the AI ​​model.

[0421] Input: Image object, user information in text format

[0422] Output: Prompt message

[0423] Step 5:

[0424] The server inputs the generated prompt text into a generative AI model to automatically generate a house design. This process uses generative AI models such as OpenAI's GPT-3.

[0425] Input: Prompt message

[0426] Output: Auto-generated house blueprints

[0427] Step 6:

[0428] The server retrieves land and building information from real estate information websites. This information includes details such as the orientation and size of windows and the floor plan.

[0429] Input: URL of the real estate information website

[0430] Output: Information about land and buildings

[0431] Step 7:

[0432] Based on the acquired real estate information, the server makes specific suggestions regarding window orientation, size, floor plan, and other details for the generated house blueprints.

[0433] Input: Land and building information, automatically generated house blueprints.

[0434] Output: Residential blueprints including specific proposals

[0435] Step 8:

[0436] The server sends the final design to the user's terminal and provides a proposal to the user. The user can review the proposed design and make modifications or regenerate it as needed.

[0437] Input: House design plans including specific proposals

[0438] Output: Final design drawings sent to the user's terminal.

[0439] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0440] "Example of form 1"

[0441] One embodiment of the present invention incorporates an emotion engine that recognizes the user's emotions. This emotion engine recognizes the user's emotions and adjusts the house design based on those emotions. Specifically, when the user is feeling happy, it suggests interiors with bright colors and an open floor plan. On the other hand, when the user is feeling depressed, it suggests interiors with calm colors and a floor plan that prioritizes privacy.

[0442] "Example of form 2"

[0443] Furthermore, the emotion engine adjusts housing suggestions based on the user's emotions. Specifically, when the user is feeling happy, it suggests luxurious homes. On the other hand, when the user is feeling down, it suggests simple and functional homes.

[0444] "Example of form 3"

[0445] As a concrete example, when a user is happy because they have landed a new job, the emotion engine recognizes that happiness and automatically generates blueprints for a luxurious house. These blueprints feature large windows, a spacious living room, and high-quality interior materials. On the other hand, when a user is depressed because they have lost their job, the emotion engine recognizes that depression and automatically generates blueprints for a simple, functional house. These blueprints have only the bare minimum number of rooms and functions, keeping costs down.

[0446] The following describes the processing flow for each example of the form.

[0447] "Example of form 1"

[0448] Step 1: The emotion engine recognizes the user's emotions.

[0449] Step 2: The emotion engine adjusts the house design based on the user's emotions. Specifically, when the user is feeling happy, it suggests bright interior colors and an open floor plan.

[0450] Step 3: On the other hand, when the user is feeling down, suggest interiors with calming colors and floor plans that prioritize privacy.

[0451] "Example of form 2"

[0452] Step 1: The emotion engine recognizes the user's emotions.

[0453] Step 2: The emotion engine adjusts housing suggestions based on the user's emotions. Specifically, when the user is feeling happy, it suggests luxurious homes.

[0454] Step 3: On the other hand, when the user is feeling down, propose a simple and functional home.

[0455] "Example of form 3"

[0456] Step 1: When a user feels joy from getting a new job, the emotion engine recognizes that joy.

[0457] Step 2: The emotion engine automatically generates blueprints for a luxurious house. These blueprints feature large windows, a spacious living room, and high-quality interior materials.

[0458] Step 3: On the other hand, when a user is depressed after losing their job, the emotion engine recognizes that depression.

[0459] Step 4: The emotion engine automatically generates a simple and functional house design. This design has the minimum necessary number of rooms and functions, keeping costs down.

[0460] (Example 1)

[0461] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0462] Conventional housing design systems have struggled to automatically generate blueprints that reflect user preferences and desires. Furthermore, they fail to adjust blueprints to accommodate user emotions, resulting in lower user satisfaction. Additionally, they lack effective means of utilizing information from social media and real estate information websites. This has led to challenges in creating housing designs that meet diverse user needs.

[0463] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0464] This invention includes a server that receives user preference and desire information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that proposes a house based on the generated design; a server that recognizes the user's emotions and adjusts the house design based on those emotions; and a server that proposes interior design and floor plans based on the user's emotions. This enables the automatic generation of house design plans that reflect the user's preferences and desires, and further allows for adjustments to the design plans that take the user's emotions into consideration, thereby increasing user satisfaction. In addition, by effectively utilizing information from social media and real estate information websites, it is possible to realize house designs that meet the diverse needs of users.

[0465] "User preference information" refers to images and text information about housing that users have obtained from social media and other sources on the internet.

[0466] "Desired information" refers to specific requests entered by the user, such as family structure, desired address, price range, whether or not renovations are needed, and whether they prefer a detached house or an apartment.

[0467] "Real estate information" refers to detailed property information obtained from real estate information websites and other databases.

[0468] "House blueprints" refer to drawings of the house's floor plan, interior, and exterior that are automatically generated based on the user's preferences, desired features, and real estate information.

[0469] "Means of recognizing emotions" refers to algorithms and software that analyze emotions from a user's facial expressions or entered text and determine their emotional state.

[0470] "Means of adjusting the blueprint" refers to algorithms or software used to change or modify the content of a house's blueprint based on recognized user emotions.

[0471] "Methods for proposing interior design and floor plans" refers to algorithms and software that propose optimal interior designs and floor plans based on the user's emotions and preferences.

[0472] "Social media" refers to a platform on the internet for users to share information.

[0473] A "real estate information website" refers to a website or online service that provides detailed information about properties.

[0474] Modes for carrying out the invention

[0475] This invention is a system that automatically generates house blueprints based on user preference and desired information, and further adjusts the blueprints to take the user's emotions into consideration. This system consists of a server, a terminal, and a user.

[0476] System Configuration

[0477] 1. User actions

[0478] Users save their favorite house images from social media on the internet and upload them to the system.

[0479] Users input their preferences into the system, including family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment.

[0480] 2. Server processing

[0481] The server receives the residential images uploaded by the user and extracts image features using image recognition algorithms (e.g., TensorFlow, OpenCV).

[0482] The server analyzes the user's input and desired information using a natural language processing engine (e.g., GPT-3) and organizes it as structured data.

[0483] The server integrates data obtained from image recognition algorithms and natural language processing engines to generate blueprints for a house.

[0484] The server uses an emotion engine to recognize the user's emotions and analyzes them from the user's facial expressions and entered text.

[0485] The server adjusts the design based on the user's emotions it perceives. For example, if the user is feeling happy, it might suggest bright interior colors and an open floor plan.

[0486] The server generates the final, adjusted blueprint and provides it to the user.

[0487] Hardware and software to use

[0488] Hardware: High-performance servers (e.g., servers with NVIDIA GPUs)

[0489] Software: Image recognition algorithms (e.g., TensorFlow, OpenCV), natural language processing engines (e.g., GPT-3), emotion recognition engines

[0490] Specific example

[0491] For example, suppose a user uploads a modern house design image saved from Instagram to the system and inputs their desired information, such as family size (four people), desired address (Tokyo), price range (under 50 million yen), whether renovation is needed (yes), and whether they want a house or apartment (house).

[0492] The server first uses an image recognition algorithm to extract modern design features from images of houses. Next, it uses a natural language processing engine to analyze the user's preferences and generates floor plans suitable for a family of four, designs suitable for residential areas in Tokyo, specifications that can be realized within 50 million yen, designs that take renovation into consideration, and plans for detached houses.

[0493] Furthermore, if the emotion engine recognizes the user's emotion as "joy," the server will suggest interiors with bright colors and an open living room. Finally, the server integrates this information to provide the user with a blueprint for the ideal home.

[0494] Example of a prompt

[0495] The user provided images of modern-designed houses saved from social media, along with their family size (4 people), desired address (Tokyo), price range (under 50 million yen), whether renovations are desired (yes), and whether they prefer a house or apartment (house). Based on this information, please generate a house design. If the user's emotion is "joy," please suggest a bright interior color scheme and an open floor plan.

[0496] In this way, the system can automatically generate house plans based on the user's preferences and desires, and can further adjust the plans to take the user's emotions into consideration.

[0497] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0498] Step 1:

[0499] Users save images of their favorite houses and input them into the system.

[0500] Specifically, the user downloads images of houses they like from social media on the internet and uploads those images through the system's interface.

[0501] Input: Residential images obtained from social media

[0502] Output: Residential images uploaded to the system

[0503] Step 2:

[0504] The user enters the desired information into the system.

[0505] In terms of specific operations, the user inputs desired information such as family structure, desired address, price range, whether or not renovations are needed, and whether they prefer a house or apartment, through the system interface.

[0506] Input: Family composition, desired address, price range, whether renovation is required, desired type of property (house or apartment), etc.

[0507] Output: Desired information entered into the system

[0508] Step 3:

[0509] The server analyzes residential images using an image recognition algorithm.

[0510] In terms of specific operations, the server receives uploaded images of houses and extracts image features using image recognition algorithms (e.g., TensorFlow, OpenCV). For example, it analyzes information such as the building's exterior, interior style, and color scheme.

[0511] Input: Residential images uploaded to the system

[0512] Output: Image feature data (building exterior, interior style, color tone, etc.)

[0513] Step 4:

[0514] The server uses a natural language processing engine to analyze the desired information.

[0515] In terms of specific operations, the server analyzes the user's input preferences using a natural language processing engine (e.g., GPT-3) and organizes them as structured data. For example, it understands information such as family structure, desired address, and price range, and stores it in a database.

[0516] Input: Desired information entered into the system

[0517] Output: Structured desired information data

[0518] Step 5:

[0519] The server integrates the analysis results and generates blueprints for the house.

[0520] In terms of specific operations, the server integrates data obtained from image recognition algorithms and natural language processing engines to generate blueprints for a house. For example, it designs the floor plan, interior, and exterior based on the user's preferences and desires.

[0521] Input: Image feature data, structured desired information data

[0522] Output: House blueprints

[0523] Step 6:

[0524] The server uses an emotion engine to recognize the user's emotions.

[0525] Specifically, the server uses an emotion engine to recognize the user's emotions. It analyzes the text and facial expression data entered by the user into the system to determine the user's current emotional state.

[0526] Input: User text input, facial expression data

[0527] Output: User emotional state data

[0528] Step 7:

[0529] The server adjusts the design based on the user's emotions.

[0530] In practice, the server adjusts the design based on the user's perceived emotions. For example, if the user is feeling happy, it suggests bright interior colors and an open layout. On the other hand, if the user is feeling depressed, it suggests calm interior colors and a layout that prioritizes privacy.

[0531] Input: User emotional state data, house blueprints

[0532] Output: Adjusted house blueprints

[0533] Step 8:

[0534] The server provides the user with the final design blueprint.

[0535] Specifically, the server generates a final, adjusted blueprint and provides it to the user. The user can review the blueprint through the system interface and provide feedback as needed.

[0536] Input: Adjusted house blueprints

[0537] Output: Final design drawings provided to the user

[0538] (Application Example 1)

[0539] Next, we will describe Application Example 1 of Form 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."

[0540] Traditional home design systems could generate blueprints based on user preferences and requests, but they lacked the ability to adjust the blueprints to reflect the user's emotions. Furthermore, it was difficult to provide real-time, emotionally responsive suggestions when users consulted with design and renovation companies in person. This resulted in a challenge in increasing user satisfaction.

[0541] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0542] In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for recognizing the user's emotions and adjusting the house design based on those emotions; and means for analyzing the user's facial expressions using a smart device and recognizing emotions. This makes it possible to generate and propose house design plans that reflect the user's emotions in real time.

[0543] "User preference information" refers to images related to housing obtained by users from social media such as Instagram, as well as information indicating the user's personal preferences.

[0544] "Desired information" refers to information that indicates the user's specific requests, such as desired family structure, address, price range, whether or not renovations are needed, and whether they prefer a detached house or an apartment.

[0545] "Real estate information" refers to detailed information about a property, such as its location, price, floor plan, and year of construction, obtained from real estate information websites.

[0546] An "automatic blueprint generation method" refers to a system or algorithm for automatically generating blueprints for a house based on user preference information, desired information, and real estate information.

[0547] A "proposal means" refers to a system or algorithm for making housing proposals to users based on the generated blueprints.

[0548] An "emotion recognition tool" is a system or algorithm that recognizes a user's emotions and adjusts the design plans of a house based on those emotions.

[0549] A "smart device" is a device, such as a smartphone or smart glasses, that analyzes a user's facial expressions and recognizes their emotions.

[0550] "Facial expression analysis means" refers to a system or algorithm that uses a smart device to analyze a user's facial expressions and recognize their emotions.

[0551] The system for implementing this invention automatically generates a house design based on the user's preference information, desired information, and real estate information, and adjusts the design based on the user's emotions. Specific embodiments are shown below.

[0552] System Configuration

[0553] 1. Hardware:

[0554] Smart devices: Devices such as smartphones and smart glasses that analyze a user's facial expressions and recognize their emotions.

[0555] Server: A server used for data processing and generating blueprints.

[0556] 2. Software:

[0557] Emotion recognition model: A machine learning model that analyzes a user's facial expressions and recognizes their emotions (e.g., an emotion recognition model using Keras).

[0558] Blueprint generation algorithm: An algorithm that automatically generates blueprints for houses based on user preferences, desired features, and real estate information.

[0559] Data Acquisition Module: A module for acquiring necessary information from social media and real estate information websites.

[0560] Processing flow

[0561] 1. Input of user preference and desired information:

[0562] Users upload images of houses they've saved from social media like Instagram to the app and enter information such as family composition, desired address, price range, whether renovations are needed, and whether it's a house or an apartment.

[0563] 2. Obtaining real estate information:

[0564] The server retrieves detailed information such as the property's location, price, floor plan, and year of construction from real estate information websites.

[0565] 3. Emotion recognition:

[0566] The system analyzes the user's facial expressions using smart devices and recognizes the user's emotions using an emotion recognition model.

[0567] 4. Automatic generation of blueprints:

[0568] The server automatically generates house blueprints using a blueprint generation algorithm, based on the user's preference information, desired information, real estate information, and recognized emotional information.

[0569] 5. Proposal:

[0570] Based on the generated blueprints, we propose housing designs to the user. This includes suggesting interior designs and floor plans that align with the user's preferences.

[0571] Specific example

[0572] For example, a user uploads an image saved from Instagram to the app and enters their desired address and price range. The app analyzes the user's facial expressions through smart glasses and recognizes their emotions. Based on this information, the server automatically generates a design plan and proposes it to the user.

[0573] Example of a prompt

[0574] Users upload images of houses they've saved from Instagram and enter information such as family composition, desired address, price range, whether renovations are needed, and whether it's a house or apartment. The system analyzes facial expressions through smart glasses to recognize emotions. Based on this information, it automatically generates an optimal house design.

[0575] In this way, a housing design assistant system based on the user's emotions and preferences can be realized.

[0576] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0577] Step 1:

[0578] Users upload images of houses they have saved from social media such as Instagram to their devices.

[0579] Input: Image file of a house

[0580] Output: Uploaded image data

[0581] Specific operation: The user uploads saved images of their home to the application using their smartphone or smart glasses. The application sends the image data to the server.

[0582] Step 2:

[0583] The user enters information such as family structure, desired address, price range, whether or not renovations are needed, and whether they prefer a house or apartment into the terminal.

[0584] Input: Family composition, address, price range, whether or not renovations have been done, type of housing

[0585] Output: User's requested information data

[0586] Specific operation: The user enters the desired information into the application's input form and presses the submit button. The application sends the entered data to the server.

[0587] Step 3:

[0588] The server retrieves detailed information such as the property's location, price, floor plan, and year of construction from a real estate information website.

[0589] Input: API of a real estate information provider website

[0590] Output: Real estate information data

[0591] Specific operation: The server calls the API of a real estate information website to retrieve the necessary real estate information. The retrieved data is stored in an internal database.

[0592] Step 4:

[0593] The device uses a smart device to analyze the user's facial expressions and recognizes the user's emotions using an emotion recognition model.

[0594] Input: User's facial expression image

[0595] Output: User sentiment data

[0596] Specific operation: The smart device's camera captures the user's facial expressions and sends the image data to the server. The server analyzes the facial image using an emotion recognition model and recognizes the user's emotions.

[0597] Step 5:

[0598] The server automatically generates house blueprints using a blueprint generation algorithm based on the user's preferences, desires, real estate information, and emotional information.

[0599] Input: User preference information, desired information, real estate information, emotional information

[0600] Output: Auto-generated house blueprints

[0601] Specific operation: The server integrates all input data and executes the blueprint generation algorithm. The algorithm generates blueprints that take into account the user's emotions regarding interior design and floor plans.

[0602] Step 6:

[0603] The server generates blueprints and then proposes housing designs to the user.

[0604] Input: Auto-generated house blueprints

[0605] Output: Suggestions for the user

[0606] Specific operation: The server presents the generated blueprints to the user and makes suggestions for interior design and floor plans that respond to their emotions. The user can review the suggestions through the application.

[0607] (Example 2)

[0608] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0609] Conventional housing design systems can generate blueprints based on user preferences and requests, but they have the problem of not being able to make suggestions that take user emotions into consideration. Furthermore, it was difficult to effectively utilize real estate information in housing design, making it impossible to provide optimal suggestions to users. Moreover, there was a need to improve user satisfaction by offering housing suggestions that resonated with users' emotions.

[0610] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0611] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; and a server that analyzes the user's emotions and adjusts the house proposals based on the analysis results. This makes it possible to propose an optimal house design that is not only based on the user's preferences and desired information but also on their emotions.

[0612] "User preference information" refers to information that indicates a user's personal preferences and desires regarding housing.

[0613] "Desired information" refers to information that indicates the specific conditions and requests that users have for their home.

[0614] "Real estate information" refers to information that includes detailed data on land and buildings, such as their shape, location, and price.

[0615] A "design drawing" is a diagram that shows the layout and structure of a house, as well as the direction and size of the windows.

[0616] A "proposal" is a specific plan regarding the design and layout of a house that is provided to the user.

[0617] "Analyzing emotions" means identifying and evaluating a user's emotional state based on their facial expressions, behavior, input data, and other factors.

[0618] "Adjusting" means modifying and optimizing the proposed content based on the analysis results.

[0619] This invention is a system that automatically generates house designs and provides optimal housing proposals by taking into account the user's preferences, desires, real estate information, and emotions. A specific embodiment of this system is described below.

[0620] System Configuration

[0621] 1. Obtaining real estate information

[0622] The server retrieves land and building information from real estate information websites. In this process, the server uses specific APIs to collect data. For example, it might utilize the API of a real estate information website.

[0623] 2. Data Analysis and Processing

[0624] The server analyzes the acquired land and building information and extracts data such as shape and location conditions. This is done using a data analysis library.

[0625] 3. Automatic generation of residential building plans

[0626] The server automatically generates house blueprints based on the analyzed data. Specifically, it considers the shape and location of the land and proposes window orientations and sizes, as well as floor plans. This process uses the API of design software.

[0627] 4. Adjustment by the Emotion Engine

[0628] The device analyzes the user's emotions using an emotion engine. This emotion engine utilizes an emotion analysis API. If the user is feeling happy, the device suggests a luxurious home. Conversely, if the user is feeling depressed, it suggests a simple and functional home.

[0629] Specific example

[0630] Example 1: Acquisition of real estate information

[0631] The server uses the API of a real estate information provider to retrieve land information for a specific area. For example, it sends an API request like the following:

[0632] "Retrieve land information for San Francisco and generate blueprints that suggest luxurious homes if the user is happy, and simple homes if they are depressed."

[0633] Example 2: Data Analysis and Processing

[0634] The server analyzes the acquired data using a data analysis library. For example, it extracts information about the land's shape and location and prepares it for use in the next step.

[0635] Example 3: Automatic generation of residential building plans

[0636] The server generates design drawings using the design software's API. For example, it considers the shape and location of the land and proposes window orientations and sizes, as well as floor plans.

[0637] Example 4: Adjustment by an emotional engine

[0638] The device uses an emotion analysis API to analyze the user's emotions. For example, if the user is happy, it suggests a luxurious house; if they are depressed, it suggests a simple house.

[0639] In this way, it becomes possible to propose optimal house designs that not only reflect the user's preferences and desires, but also their emotions. This system can improve user satisfaction.

[0640] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0641] Step 1:

[0642] The server retrieves land and building information from real estate information websites. Specifically, the server sends an API request and receives JSON data containing land information for a specified area. The input is the parameters of the API request (e.g., area, property type), and the output is the retrieved real estate information in JSON data.

[0643] Step 2:

[0644] The server converts the retrieved JSON data into a data frame using a data analysis library. Specifically, the server uses the pandas library to read the JSON data and convert it into a data frame. The input is the retrieved JSON data, and the output is real estate information in data frame format.

[0645] Step 3:

[0646] The server extracts the necessary data from the data frame. Specifically, it extracts information such as land shape and location conditions and prepares it for use in the next step. The input is real estate information in data frame format, and the output is the extracted data on land shape and location conditions.

[0647] Step 4:

[0648] The server generates house blueprints using the API of design software. Specifically, it considers the shape and location of the land and proposes window orientations and sizes, floor plans, and other details. The input is extracted data on the shape and location of the land, and the output is the generated house blueprints.

[0649] Step 5:

[0650] The device analyzes the user's emotions using an emotion analysis API. Specifically, it identifies and evaluates the emotional state from the user's facial expressions, actions, and input data. The input is the user's image and text data, and the output is the analyzed emotion data.

[0651] Step 6:

[0652] The device adjusts housing suggestions based on the analysis results. Specifically, it suggests a luxurious house if the user is happy, and a simple house if they are depressed. The input is the analyzed emotion data and the generated house blueprints, and the output is the adjusted housing suggestion.

[0653] In this way, by clearly defining the specific actions, inputs, and outputs performed at each processing step, the processing flow of the system program was explained in detail.

[0654] (Application Example 2)

[0655] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0656] Conventional housing design systems could automatically generate blueprints based on user preferences, desired information, and real estate data, but they could not adjust proposals to reflect user emotions or display blueprints using virtual reality. Therefore, it was difficult to provide housing proposals that resonated with users' emotions or offer a more realistic experience. This resulted in a challenge in increasing user satisfaction.

[0657] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0658] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that receives user emotional information as input and adjusts the house proposals based on this information; and a server that displays the generated design using a virtual reality display device. This makes it possible to adjust house proposals according to the user's emotions and to provide a realistic experience using virtual reality.

[0659] "User preference information" refers to information that indicates a user's personal preferences and desires regarding housing.

[0660] "Desired information" refers to information that indicates the specific conditions and requests that users have for their home.

[0661] "Real estate information" refers to information that includes detailed data about land and buildings.

[0662] A "house design drawing" is a detailed drawing showing the layout, structure, and facilities of a house.

[0663] "Emotional information" refers to information that indicates the user's current emotional state.

[0664] A "virtual reality display device" is a device used to visually display a virtual space.

[0665] "Means of automatic generation" refers to devices or programs that have the function of automatically creating design drawings based on input information.

[0666] "Means for adjusting suggestions" refers to devices or programs that have the function of modifying and optimizing the content of suggestions based on the user's emotional information.

[0667] "Means of display" refers to devices or programs that have the function of visually presenting the generated design drawings to the user.

[0668] The system for implementing this invention automatically generates a house design based on the user's preference information, desired information, real estate information, and emotional information, and presents it to the user using a virtual reality display device. Specific embodiments are shown below.

[0669] System Configuration

[0670] The system consists of the following main components:

[0671] 1. User terminal: A device such as a smartphone or head-mounted display collects user input information and displays it in virtual reality.

[0672] 2. Server: Receives user preference information, desired information, real estate information, and emotional information, and automatically generates house blueprints.

[0673] 3. Emotion Engine: Analyzes user emotional information and adjusts housing suggestions accordingly.

[0674] 4. Design Generation Engine: Generates house blueprints based on real estate information, user preferences, and desired information.

[0675] 5. Virtual reality display device: Displays the generated blueprint in a virtual reality space.

[0676] Program processing

[0677] The server processes the data in the following steps:

[0678] 1. Data Acquisition: Acquire preference information, desired information, and real estate information from the user's device. Acquire user sentiment information using the sentiment engine.

[0679] 2. Blueprint Generation: Using a blueprint generation engine, blueprints for the house are automatically generated based on the acquired information.

[0680] 3. Proposal Adjustment: Using an emotion engine, housing suggestions are adjusted based on the user's emotional information.

[0681] 4. Virtual reality display: The generated blueprint is presented to the user using a virtual reality display device.

[0682] Hardware and software to be used

[0683] Hardware: Smartphones, head-mounted displays, servers

[0684] Software: EmotionEngine (emotion engine), DesignGenerator (design generation engine), VRDisplay (virtual reality display engine)

[0685] Specific example

[0686] For example, when a user experiences designing a house using a smartphone, a luxurious house is suggested when the user is happy, and a simple, functional house is suggested when the user is depressed. The user wears a head-mounted display and can realistically experience the design blueprints generated in a virtual reality space.

[0687] Example of a prompt

[0688] "Generate blueprints for luxurious homes that will delight the user."

[0689] "Please generate blueprints for a simple and functional home that will be suitable for users who are feeling down."

[0690] In this way, we can provide housing proposals that respond to the user's emotions and realistic experiences using virtual reality.

[0691] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0692] Step 1:

[0693] The user terminal receives user preference and desired information as input. Users input their housing preferences and specific requests using a smartphone or head-mounted display. This information is then sent to the server.

[0694] Input: User preference information, desired information

[0695] Output: User preference information and desired information sent to the server

[0696] Step 2:

[0697] The server retrieves real estate information from real estate information websites. The server accesses the sites via APIs and collects detailed data about land and buildings.

[0698] Input: URL of the real estate information website

[0699] Output: Acquired real estate information

[0700] Step 3:

[0701] The user terminal uses an emotion engine to acquire the user's emotional information. It analyzes the user's facial expressions and voice to detect their current emotional state. The emotional information is then sent to the server.

[0702] Input: User's facial expressions, voice

[0703] Output: Sentiment information sent to the server

[0704] Step 4:

[0705] The server uses a design generation engine to automatically generate house blueprints based on acquired preference information, desired information, and real estate information. The design generation engine analyzes this information and designs the optimal floor plan and structure.

[0706] Input: User preferences, desired information, real estate information

[0707] Output: Generated house blueprints

[0708] Step 5:

[0709] The server uses an emotion engine to adjust housing suggestions based on the user's emotional information. For example, if the user is happy, it will suggest a luxurious house; if they are depressed, it will suggest a simple and functional house.

[0710] Input: Generated house blueprints, emotional information

[0711] Output: Proposal for a modified house

[0712] Step 6:

[0713] The server uses a virtual reality display to present the generated blueprints to the user. The user wears a head-mounted display and can realistically experience the blueprints in a virtual reality space.

[0714] Input: Adapted housing proposal

[0715] Output: Blueprint of a house displayed in a virtual reality space

[0716] In this way, we can provide housing proposals that respond to the user's emotions and realistic experiences using virtual reality.

[0717] (Example 3)

[0718] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0719] Conventional housing design systems have difficulty automatically generating blueprints that reflect user preferences and desires, and generating blueprints that take real estate information into account is also time-consuming. Furthermore, they cannot generate blueprints that take into account the user's emotional state, thus failing to enhance user psychological satisfaction. There is a need for a system that solves these problems and automatically generates housing blueprints that meet the diverse needs of users.

[0720] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0721] In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; and means for recognizing the user's emotional state and adjusting the house design according to that emotional state. This makes it possible to automatically generate a house design that takes into account the user's preferences and desired information, real estate information, and even their emotional state.

[0722] "User preference information" refers to information about the designs and styles that users prefer, and is obtained from sources such as social media.

[0723] "Desired information" refers to information about the user's specific requirements, such as the location of the house they want, their budget, and their family structure.

[0724] "Real estate information" refers to information about land and buildings obtained from real estate information websites.

[0725] "Emotional state" refers to information that indicates the user's current psychological state and is recognized by the emotion engine.

[0726] A "design drawing" is a diagram that shows the structure, layout, and orientation and size of windows of a house.

[0727] "Automatic generation" refers to the process where a system automatically creates a blueprint based on user input, property information, and emotional state.

[0728] A "proposal" is the process of showing the user a specific design and layout of a house based on the generated blueprints.

[0729] Modes for carrying out the invention

[0730] This invention is a system that automatically generates and proposes house designs to users based on their preferences, desires, real estate information, and emotional state. A specific embodiment of this system is shown below.

[0731] Hardware and software to use

[0732] Hardware: Servers, user terminals (PCs, smartphones)

[0733] Software: Generative AI models (e.g., GPT-4), emotion recognition engine, database management system (e.g., MySQL), real estate information site API

[0734] System Operation Overview

[0735] 1. Enter user information

[0736] Users use their devices to input information such as images saved from Instagram, family composition, desired housing location (within Tokyo), and budget (50 million yen).

[0737] Specific example input: "We are a family of four, looking for a modern-looking detached house in Tokyo, with a budget of 50 million yen."

[0738] 2. Data transmission and analysis

[0739] The terminal sends the entered information to the server.

[0740] The server analyzes the received information and inputs it as a prompt message into the generating AI model.

[0741] Specific prompt example: "The user has saved an image of a modern exterior from Instagram. They are a family of four looking for a detached house in Tokyo with a budget of 50 million yen. Please generate a design plan based on this information."

[0742] 3. Generating blueprints

[0743] The server inputs prompt messages into the generated AI model and generates a blueprint.

[0744] The server uses information on land and buildings in Tokyo obtained from real estate information websites to suggest window orientations, sizes, floor plans, and other layouts.

[0745] 4. Emotion Recognition and Adjustment of the Blueprint

[0746] The server uses an emotion engine to recognize the user's emotional state.

[0747] The server adjusts the blueprint based on the results of the emotion engine.

[0748] Specific prompt example: "The user is delighted to have a new job. Please generate blueprints for a luxurious house with large windows, a spacious living room, and high-quality interior materials."

[0749] 5. Provision of design drawings

[0750] The server sends the generated blueprint to the user's terminal.

[0751] The terminal displays the received blueprints to the user.

[0752] Specific example

[0753] User input: "We are a family of four and would like a modern-looking detached house in Tokyo. Our budget is 50 million yen."

[0754] Prompt: "The user has saved an image of a modern exterior from Instagram. They are a family of four looking for a detached house in Tokyo with a budget of 50 million yen. Please generate a blueprint based on this information."

[0755] Emotion recognition prompt message: "The user is happy to have a new job. Please generate blueprints for a luxurious house with large windows, a spacious living room, and high-quality interior materials."

[0756] This system enables the automatic generation of house designs that take into account the user's preferences, desired information, real estate information, and even their emotional state. This allows for house designs that meet the diverse needs of users. The specific processing flow in Example 3 will be explained using Figure 21.

[0757] Step 1:

[0758] Entering user information

[0759] The user uses their device to input information such as images saved from Instagram, family composition, desired housing location (within Tokyo), and budget (50 million yen).

[0760] Input: User preferences and desired information

[0761] Output: The entered information is saved to the device.

[0762] Specific action: The user enters information into the input form on the device and clicks the "Submit" button.

[0763] Step 2:

[0764] Data transmission and analysis

[0765] The terminal sends the entered information to the server.

[0766] Input: Information entered by the user

[0767] Output: User information sent to the server

[0768] Specific operation: The terminal uses an HTTP request to send the input data to the server.

[0769] The server analyzes the received information and inputs it as a prompt message into the generating AI model.

[0770] Input: User information sent from the device

[0771] Output: Prompt text to input to the generated AI model

[0772] Specific operation: The server analyzes the data and generates a prompt message like the following: "The user has saved an image of a modern exterior from Instagram, and they are looking for a detached house in Tokyo for a family of four, with a budget of 50 million yen. Please generate a blueprint based on this."

[0773] Step 3:

[0774] Design drawing generation

[0775] The server inputs prompt messages into the generated AI model and generates a blueprint.

[0776] Input: Prompt message

[0777] Output: Generated design data

[0778] Specific operation: The server sends prompt messages to the generated AI model (e.g., GPT-4) and receives blueprint data returned from the model.

[0779] The server uses information on land and buildings in Tokyo obtained from real estate information websites to suggest window orientations, sizes, floor plans, and other layouts.

[0780] Input: Information obtained from a real estate information website.

[0781] Output: Proposed window orientation and size, floor plan, etc.

[0782] Specific operation: The server uses an API to retrieve real estate information and reflects it in the design plans.

[0783] Step 4:

[0784] Emotion recognition and blueprint adjustment

[0785] The server uses an emotion engine to recognize the user's emotional state.

[0786] Input: User sentiment data

[0787] Output: Recognized emotional state

[0788] Specific operation: The server sends user emotion data to the emotion engine, which then analyzes the emotional state.

[0789] The server adjusts the blueprint based on the results of the emotion engine.

[0790] Input: Recognized emotional state

[0791] Output: Adjusted blueprint

[0792] Specific operation: The server receives the result from the emotion engine and generates a prompt message like this: "The user is happy to have a new job. Please generate blueprints for a luxurious house with large windows, a spacious living room, and high-quality interior materials."

[0793] Step 5:

[0794] Provision of design drawings

[0795] The server sends the generated blueprint to the user's terminal.

[0796] Input: Generated design drawing data

[0797] Output: Blueprint sent to the user terminal

[0798] Specific operation: The server sends the design data to the user's terminal as an HTTP response.

[0799] The terminal displays the received blueprints to the user.

[0800] Input: Design drawing data sent from the server

[0801] Output: Blueprint displayed to the user

[0802] Specific operation: The terminal analyzes the received design data and displays it on the user interface.

[0803] (Application Example 3)

[0804] Next, we will explain Application Example 3 of Form Example 3. In the following explanation, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0805] Conventional residential design systems struggled to automatically generate blueprints that reflected user preferences and desires, and their proposals based on real estate information were limited. Furthermore, they lacked the means to generate blueprints that considered the user's emotional state, or to visually confirm the generated blueprints as 3D models. As a result, it was difficult to increase user satisfaction.

[0806] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0807] In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for receiving the user's emotional state as input and automatically generating a house design based on this; and means for displaying the generated design as a 3D model. This enables the automatic generation of house design plans that reflect the user's preferences, desires, and emotional state, as well as visual confirmation.

[0808] "User preference information" refers to information about the designs and styles that users prefer, and is obtained from social media and image storage services.

[0809] "Desired information" refers to information about the conditions and specifications of a house that the user desires, including family structure, budget, and location.

[0810] "Real estate information" refers to information about land and buildings obtained from real estate information websites, including details such as price, area, and location.

[0811] "Emotional state" refers to information that indicates the user's current emotions and mood, including feelings such as joy and sadness.

[0812] A "design plan" is a drawing that shows the structure, layout, and design of a house, and is automatically generated based on the user's preferences, desires, real estate information, and emotional state.

[0813] A "3D model" is a three-dimensional visual model created based on design drawings, allowing users to view the exterior and interior of a house in three dimensions.

[0814] "Automatic generation" refers to the process by which a system automatically creates design drawings and 3D models based on user input and acquired data.

[0815] A "proposal" is the act of showing the user specific features of a house, such as the orientation and size of windows and the floor plan, based on the generated design drawings.

[0816] The system for implementing this invention automatically generates a house design based on the user's preferences, desires, real estate information, and emotional state, and displays it as a 3D model. A specific embodiment is shown below.

[0817] System Configuration

[0818] The system consists of user terminals, a server, and a display device. User terminals include smartphones and head-mounted displays (HMDs). The server performs data processing and automatically generates design drawings using a generational AI model. The display device is used to display the generated design drawings as 3D models.

[0819] Hardware and software to be used

[0820] Hardware: Smartphones, head-mounted displays (HMDs), servers

[0821] Software: Python, OpenAI API, 3D modeling libraries

[0822] Data processing and data calculation

[0823] 1. Receiving user input:

[0824] The user terminal receives user preference information (e.g., images obtained from social media), desired information (e.g., family structure, budget, location), and emotional state (e.g., joy or sadness) as input.

[0825] 2. Obtaining real estate information:

[0826] The server retrieves information about land and buildings in Tokyo from real estate information websites. This includes details such as price, area, and location.

[0827] 3. Automatic generation of blueprints:

[0828] The server uses a generative AI model (e.g., OpenAI's GPT-3) to automatically generate house blueprints based on user input and acquired real estate information. An example of a prompt message for the generative AI model is as follows:

[0829] User input: {'image': 'modern_house_image.jpg', 'family_size': 4, 'location': 'Tokyo', 'budget': 5000, 'emotion': 'happy'}

[0830] Real estate data: {'Land information': '...', 'Building information': '...'}

[0831] Please generate the blueprints.

[0832] 4. Creating and displaying 3D models:

[0833] The server creates a 3D model using a 3D modeling library based on the generated blueprints. The created 3D model is then displayed on the user's device (smartphone or HMD).

[0834] Specific example

[0835] If a user provides an image of a modern exterior saved from Instagram, enters that they are a family of four looking for a detached house in Tokyo with a budget of 50 million yen, the server will automatically generate a blueprint for a modern-looking detached house in Tokyo based on this information. Furthermore, when a user is feeling happy about getting a new job, the emotion engine recognizes that happiness and automatically generates a blueprint for a luxurious home. This blueprint will feature large windows, a spacious living room, and high-quality interior materials.

[0836] In this way, it becomes possible to automatically generate and visually confirm house designs that reflect the user's preferences, desires, and emotional state.

[0837] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0838] Step 1:

[0839] Users input their preferences (e.g., images from social media), desired information (e.g., family structure, budget, location), and emotional state (e.g., joy or sadness) using a smartphone or head-mounted display (HMD).

[0840] Input: User preferences, desires, and emotional state.

[0841] Output: User input data

[0842] Specific action: The user enters information into the application's input form and presses the submit button.

[0843] Step 2:

[0844] The server retrieves information about land and buildings in Tokyo from real estate information websites.

[0845] Input: User's desired information (e.g., location)

[0846] Output: Real estate information data

[0847] Specific operation: The server uses an API to send requests to real estate information websites and retrieve the necessary data.

[0848] Step 3:

[0849] The server uses a generated AI model (e.g., OpenAI's GPT-3) to automatically generate house blueprints based on user input and acquired real estate information.

[0850] Input: User input data, real estate information data

[0851] Output: House design drawing data

[0852] Specific operation: The server sends prompt messages to the generated AI model to generate the blueprint. An example of a prompt message is as follows:

[0853] User input: {'image': 'modern_house_image.jpg', 'family_size': 4, 'location': 'Tokyo', 'budget': 5000, 'emotion': 'happy'}

[0854] Real estate data: {'Land information': '...', 'Building information': '...'}

[0855] Please generate the blueprints.

[0856] Step 4:

[0857] The server creates a 3D model using a 3D modeling library based on the generated blueprint.

[0858] Input: House design drawing data

[0859] Output: 3D model data

[0860] Specific operation: The server inputs design data into the 3D modeling library and generates a 3D model.

[0861] Step 5:

[0862] The server sends the generated 3D model to the user's terminal, and the user's terminal displays it.

[0863] Input: 3D model data

[0864] Output: 3D model displayed on the user's terminal

[0865] Specific operation: The server sends 3D model data to the user's terminal, and the user's terminal displays it on a display device (smartphone or HMD).

[0866] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0867] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence).

[0868] One example of a data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include those mentioned above.

[0869] The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives prompts containing instructions, as well as inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 performs inference on the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0870] Other examples of generative AI include Gemini® (registered trademark) (Internet search). <url: https: gemini.google.com ?hl="ja">) are some examples.

[0871] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0872] [Second Embodiment]

[0873] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0874] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0875] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0876] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0877] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0878] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0879] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0880] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0881] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0882] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0883] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0884] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0885] "Example of form 1"

[0886] In one embodiment of the system, a user saves images of their preferred homes from social media such as Instagram and inputs the image information into the system. The user also inputs information about their family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment. Based on this preference and desired information, the system automatically generates a blueprint for the home.

[0887] "Example of form 2"

[0888] Furthermore, this system acquires land and building information from real estate information websites and automatically generates house designs based on this information. Specifically, it proposes window orientations, sizes, floor plans, etc., taking into account the shape of the land and building, location conditions, etc.

[0889] "Example of form 3"

[0890] For example, if a user inputs an image of a modern exterior saved from Instagram, along with information such as being a family of four, wanting a detached house in Tokyo, and having a budget of 50 million yen, the system will automatically generate a blueprint for a detached house in Tokyo with a modern exterior based on this information. Furthermore, it will suggest window orientations, sizes, floor plans, etc., based on land and building information in Tokyo obtained from real estate information websites.

[0891] The following describes the processing flow for each example of the form.

[0892] "Example of form 1"

[0893] Step 1: The user saves images of their favorite houses from social media such as Instagram.

[0894] Step 2: The user inputs the saved image information into this system.

[0895] Step 3: The user enters their family structure, desired address, price range, whether or not they want renovations, and other desired information such as a house or apartment into the system.

[0896] Step 4: This system automatically generates house plans based on these preference and desired information.

[0897] "Example of form 2"

[0898] Step 1: This system obtains land and building information from real estate information websites.

[0899] Step 2: This system automatically generates house plans based on the acquired land and building information. Specifically, it proposes window orientations, sizes, floor plans, etc., taking into account the shape of the land and building, location conditions, etc.

[0900] "Example of form 3"

[0901] Step 1: The user enters images of modern exteriors saved from Instagram, along with information such as being a family of four, wanting a detached house in Tokyo, and having a budget of 50 million yen.

[0902] Step 2: Based on this information, the system automatically generates a blueprint for a modern-looking detached house in Tokyo.

[0903] Step 3: This system uses land and building information in Tokyo obtained from real estate information websites to suggest window orientations, sizes, floor plans, etc.

[0904] (Example 1)

[0905] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0906] Conventional housing design systems have struggled to automatically generate blueprints that reflect the user's preferences and desires. Furthermore, a lack of effective means to utilize image information obtained from social media meant that the user's specific preferences could not be reflected in the design. Additionally, when proposing housing designs based on the generated blueprints, it was difficult to provide proposals that matched the user's wishes.

[0907] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design drawing based on this information, means for receiving image information saved by the user as input and analyzing this information to identify the user's preferences, means for generating and inputting prompt sentences to the generation AI model, and means for making house proposals based on the generated design drawing. This makes it possible to automatically generate a house design drawing that reflects the user's specific preferences and desires, and to make house proposals that match the user's desires.

[0908] "User preference information" refers to information about the housing designs and styles that users prefer, and includes images and text data obtained from social media.

[0909] "Desired information" refers to the specific conditions and requirements that the user desires regarding housing, including information such as family structure, desired address, price range, whether renovations are planned, and whether it is a detached house or an apartment.

[0910] "Image information" refers to image data of houses that users obtain from social media or other sources and upload to the system.

[0911] A "generative AI model" is an artificial intelligence model that automatically generates house blueprints based on user preferences and desired information, and utilizes natural language processing and image analysis technologies.

[0912] A "prompt message" is an instruction given to the AI ​​generation model, and it is generated based on the user's preferences and desired information.

[0913] A "house design plan" is a design drawing of a house generated based on the user's preferences and desired information, and includes specific layouts and designs.

[0914] A "housing proposal" is a proposal made to a user based on the generated housing blueprints, and includes content that matches the user's wishes.

[0915] This invention is based on the premise that users save images of their preferred homes from social media such as Instagram and input that image information into the system. Users also input their family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment. Based on this information, the system automatically generates a blueprint for the house.

[0916] Hardware and software to be used

[0917] The server receives image information and request information entered by the user and stores it in a database. Specifically, it uses the following hardware and software:

[0918] Server: High-performance cloud server (e.g., Amazon Web Services, Google Cloud Platform)

[0919] Database: Relational database (e.g., MySQL, PostgreSQL)

[0920] Generative AI models: AI models that utilize natural language processing and image analysis techniques (e.g., OpenAI's GPT-4, DALL-E)

[0921] Image analysis software: Computer vision technology (e.g., TensorFlow, PyTorch)

[0922] Data processing and data calculation

[0923] The server receives image files uploaded by the user and requested information, and stores this data in a database. Based on the stored data, it generates prompt messages for the AI ​​model and inputs them. The AI ​​model generates house blueprints based on the prompt messages and provides them to the user via the server.

[0924] Specific example

[0925] As a concrete example, suppose a user saves an image of a modern-designed house from Instagram and enters the following desired information:

[0926] Family composition: 4 people (2 adults, 2 children)

[0927] Desired address: Tokyo

[0928] Price range: Under 50 million yen

[0929] Renovation status: Yes

[0930] House or apartment: House

[0931] Based on this information, the server inputs the following prompt message into the AI ​​model:

[0932] Based on images of modern-designed homes saved by the user from Instagram, please generate blueprints for a home that matches the following requirements.

[0933] Family composition: 4 people (2 adults, 2 children)

[0934] Desired address: Tokyo

[0935] Price range: Under 50 million yen

[0936] Renovation status: Yes

[0937] House or apartment: House

[0938] Based on this prompt, the generation AI model generates a house design that matches the user's preferences and provides it to the user via the server. The user can review the received design on their device and, if necessary, modify their preferences to generate a new design.

[0939] In this way, it becomes possible to automatically generate house designs that reflect the user's specific preferences and desires, and to propose houses that match the user's wishes.

[0940] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0941] Step 1:

[0942] Users save images of their favorite houses from social media such as Instagram. Users use their smartphones or computers to find and save images of their favorite houses from social media such as Instagram. The input is image data obtained from social media, and the output is an image file saved on the user's device.

[0943] Step 2:

[0944] The user uploads saved images to the system. The user accesses the system's website or application and uploads saved images of their home. Specifically, they click an upload button and select the saved image file. The input is the image file stored on the user's device, and the output is the image data sent to the server.

[0945] Step 3:

[0946] The user enters their desired information, such as family structure, preferred address, price range, whether renovations are needed, and whether they want a house or an apartment. The user enters their desired information into the system's input form, such as family structure (e.g., 2 adults, 2 children), preferred address (e.g., Tokyo), price range (e.g., under 50 million yen), whether renovations are needed (e.g., yes), and whether they want a house or an apartment (e.g., house). The input is the desired information entered by the user, and the output is the desired information sent to the server.

[0947] Step 4:

[0948] The server receives image information and request information from the user and stores it in the database. The server receives uploaded image files and input request information from the user and stores this data in the database. When saving, the data is managed in association with the user ID. The input is the image information and request information sent by the user, and the output is the data stored in the database.

[0949] Step 5:

[0950] The server generates prompt messages for the AI ​​model based on the stored data and inputs them. The server generates prompt messages to input to the AI ​​model based on image information and desired information stored in the database. For example, it generates prompt messages like the following:

[0951] Based on images of modern-designed homes saved by the user from Instagram, please generate blueprints for a home that matches the following requirements.

[0952] Family composition: 4 people (2 adults, 2 children)

[0953] Desired address: Tokyo

[0954] Price range: Under 50 million yen

[0955] Renovation status: Yes

[0956] House or apartment: House

[0957] The input consists of image information and desired information stored in a database, and the output is a prompt message that is input to the generating AI model.

[0958] Step 6:

[0959] The generative AI model generates a house design based on the prompt text. The generative AI model (e.g., OpenAI's GPT-4 or DALL-E) generates the house design based on the prompt text sent from the server. The generative AI model utilizes image analysis and natural language processing techniques to create a design that meets the user's needs. The input is the prompt text, and the output is the generated house design.

[0960] Step 7:

[0961] The server sends the generated blueprint to the user's terminal. The server sends the blueprint received from the generated AI model to the user's terminal. The user can download or view the blueprint through the system's website or application. The input is the generated house blueprint, and the output is the blueprint sent to the user's terminal.

[0962] Step 8:

[0963] The user reviews the blueprint. The user reviews the blueprint received on their device. They can check if the blueprint meets their requirements and, if necessary, modify the required information to generate a new blueprint. The input is the blueprint sent to the user's device, and the output is the user's review result.

[0964] (Application Example 1)

[0965] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0966] Conventional home design systems struggled to automatically generate blueprints that reflected users' preferences and desires. In particular, if a user had a specific image in mind, specialized knowledge was required to translate that image into a blueprint. Furthermore, real-time blueprint generation and display were difficult when users viewed home designs in physical showrooms. This led to decreased user satisfaction and delays in home purchase decisions.

[0967] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0968] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that analyzes a house image taken by the user and extracts its features; a server that generates prompt text based on the extracted features and the user's desired information and generates a house design using a generation AI model; and a server that presents the generated design to the user through a display device. This enables the generation of a house design that reflects the user's specific image in real time and allows for verification at a physical store.

[0969] "User preference information" refers to information that indicates a user's personal preferences and design tastes regarding housing.

[0970] "Desired information" refers to information that indicates the specific requests and conditions that the user has regarding housing (family structure, desired address, price range, whether or not renovations are planned, whether it's a detached house or an apartment, etc.).

[0971] "Real estate information" refers to information that provides detailed data about a real estate property (location, price, floor plan, year built, etc.).

[0972] A "house design drawing" is a diagram that specifically shows the structure, layout, and design of a house.

[0973] "Means of automatic generation" refers to devices or programs that have the function of automatically creating design drawings using algorithms or AI models based on input information.

[0974] "Means of making proposals" refers to devices or programs that have the function of making housing proposals to users based on the generated blueprints.

[0975] "House images" refer to photographs or image data of houses taken by users.

[0976] "Means of analysis" refers to devices or programs that have the function of analyzing input image data and extracting its features.

[0977] "Means for extracting features" refer to devices or programs that have the function of extracting important features from data obtained through image analysis.

[0978] A "prompt statement" is a text-based input statement used to give instructions to a generative AI model.

[0979] A "generative AI model" is an artificial intelligence model that generates blueprints and other data based on input prompts.

[0980] A "display device" is a device (such as a display or VR headset) used to visually present a generated design to a user.

[0981] A system for carrying out this invention includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for analyzing a house image taken by the user and extracting its features; means for generating prompt sentences based on the extracted features and the user's desired information and generating a house design using a generation AI model; and means for presenting the generated design to the user through a display device.

[0982] Hardware and software to use

[0983] hardware

[0984] Smartphone or tablet (iOS or Android): Used by the user to take pictures of the house and input information.

[0985] Smart glasses (e.g., Google Glass): Used to analyze images taken by the user in real time.

[0986] Large screen display or VR headset (e.g., Oculus Rift): Used to present the generated blueprints to the user.

[0987] software

[0988] Image recognition libraries (e.g., OpenCV): Used to analyze residential images taken by the user and extract their features.

[0989] Generative AI models (e.g., GPT-4, DALL-E): Used to generate house blueprints based on prompt statements.

[0990] Database (e.g., Firebase): Used to store and manage user preferences, requests, and property information.

[0991] Frontend frameworks (e.g., React Native): Used to build user interfaces.

[0992] Processing flow

[0993] 1. User input

[0994] Users use their smartphones or tablets to take pictures of their preferred homes and upload them to the application. They also enter information such as family size, desired address, price range, whether renovations are needed, and whether they want a house or an apartment.

[0995] 2. Image Analysis

[0996] The server uses an image recognition library (OpenCV) to analyze uploaded images of houses and extract their features.

[0997] 3. Generating prompt statements

[0998] The server generates prompt messages for the generative AI model (GPT-4) based on the extracted features and user preferences.

[0999] Example of a prompt

[1000] Based on the images and desired information provided by the user, please generate a blueprint for a house that meets the following conditions:

[1001] Family composition: 4 people

[1002] Desired address: Tokyo

[1003] Price range: Under 50 million yen

[1004] Renovation: Yes

[1005] Detached house

[1006] Modern design

[1007] 4. Generating blueprints

[1008] The server uses a generative AI model (DALL-E) to generate house blueprints based on prompt messages.

[1009] 5. Displaying the results

[1010] The generated blueprints are presented to the user via a large screen display or VR headset. Users can then view their ideal home design in real time at a physical store.

[1011] Specific example

[1012] For example, a user uploads an image of a modern living room taken with their smartphone and enters their desired information as "Family composition: 4 people, Desired address: Tokyo, Price range: under 50 million yen, Renovation: Yes, Detached house." Based on this information, the server generates a blueprint for a modern detached house in Tokyo that is under 50 million yen, suitable for a family of four, and allows for renovation, and presents it to the user.

[1013] In this way, users can check their ideal home design in real time at a physical store.

[1014] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1015] Step 1:

[1016] Users use their smartphones or tablets to take pictures of their preferred homes and upload them to the application. They also enter information such as family size, desired address, price range, whether renovations are needed, and whether they want a house or an apartment.

[1017] Input: Housing images, family composition, desired address, price range, whether renovation is needed, desired type of housing (house or apartment), etc.

[1018] Output: Uploaded house images and desired information

[1019] Step 2:

[1020] The server uses an image recognition library (OpenCV) to analyze uploaded images of houses and extract their features.

[1021] Input: Uploaded house images

[1022] Output: Extracted image features

[1023] Specific operation: Using an image recognition library, perform edge detection and color analysis on residential images and extract features.

[1024] Step 3:

[1025] The server generates prompt messages for the generative AI model (GPT-4) based on the extracted features and user preferences.

[1026] Input: Extracted image features, desired information

[1027] Output: Generated prompt message

[1028] Specific operation: Combine the extracted features and desired information to create prompt sentences for input into the generating AI model.

[1029] Step 4:

[1030] The server uses a generative AI model (DALL-E) to generate house blueprints based on prompt messages.

[1031] Input: Generated prompt message

[1032] Output: Generated house blueprints

[1033] Specific operation: Input prompt text into the generation AI model and generate a blueprint for a house.

[1034] Step 5:

[1035] The server presents the generated blueprints to the user via a large screen display or VR headset.

[1036] Input: Generated house blueprints

[1037] Output: Design drawings presented to the user

[1038] Specific operation: The generated design drawings are sent to a display or VR headset so that the user can visually confirm them.

[1039] In this way, users can check their ideal home design in real time at a physical store.

[1040] (Example 2)

[1041] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1042] Conventional residential design systems had the problem of requiring a great deal of time and effort to reflect the user's preferences and desired information. Furthermore, it was difficult to efficiently acquire real estate information and automatically generate optimal residential designs based on it. As a result, it was difficult to quickly provide residential designs that satisfied users.

[1043] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1044] In this invention, the server includes means for acquiring land and building information from a real estate information provision site, means for storing the acquired information in a data frame and processing the data, means for generating prompt sentences to be input to a generation AI model based on the processed data, means for automatically generating house blueprints using the generation AI model, and means for making house proposals based on the generated blueprints. This makes it possible to quickly and efficiently provide house blueprints that reflect the user's preferences and desired information.

[1045] A "real estate information website" is a website that provides information about land and buildings.

[1046] "Land and building information" refers to detailed data such as the shape of the land, the location of the building, the direction and size of the windows, and the floor plan.

[1047] A "data frame" is a two-dimensional data structure consisting of rows and columns, used for storing and processing data.

[1048] "Data processing" is the process of transforming acquired data into a format that is easy to analyze and use, and includes processes such as imputing missing values ​​and normalizing data.

[1049] A "generative AI model" is a model that uses artificial intelligence to perform a specific task, and in this case, it is used to automatically generate blueprints for a house.

[1050] A "prompt message" is an instruction message used to input into a generation AI model, and it is generated based on information about the land and buildings.

[1051] "House design drawings" are diagrams that show the layout and structure of a house, and they form the basis of the building plan.

[1052] A "housing proposal" refers to a suggestion made to the user regarding the design and layout of a house, based on the generated blueprints.

[1053] Modes for carrying out the invention

[1054] This invention relates to a system that obtains land and building information from real estate information websites and automatically generates house blueprints based on this information. A specific embodiment of this system is described below.

[1055] 1. Program generation

[1056] The server generates a program to retrieve land and building information from real estate information websites. This program is developed using Python and performs web scraping using libraries such as BeautifulSoup and Selenium.

[1057] 2. Data acquisition and processing

[1058] The server executes the generated program and retrieves land and building information from real estate information websites. Specifically, it collects data such as land shape, building location, window orientation and size, and floor plan. The collected data is stored in a dataframe using the Pandas library, and necessary data processing is performed. For example, missing values ​​are imputed and data normalization is performed.

[1059] 3. Generating prompt sentences for the generative AI model

[1060] The server generates prompt statements to input into the AI ​​model based on the processed data. These prompt statements include information such as the shape of the land and building, location conditions, window orientation, size, and floor plan.

[1061] Example of a prompt:

[1062] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[1063] Land shape: Rectangle

[1064] Building location: South-facing

[1065] Window orientation: South-facing

[1066] Window size: Large

[1067] Floor plan: 3LDK

[1068] 4. Generating house design plans

[1069] The server inputs the generated prompt text into a generation AI model (for example, a generation AI model) and generates a blueprint for a house. The generation AI model then proposes the optimal blueprint based on the prompt text.

[1070] 5. Displaying the results

[1071] The server displays the generated house design plans on the user's terminal. The user can review the proposed design plans and request revisions as needed.

[1072] Specific example

[1073] If a user requests to "generate a house design based on land information in Shibuya Ward, Tokyo," the server will input the following prompt into the AI ​​model.

[1074] Example of a prompt:

[1075] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[1076] Land shape: Rectangle

[1077] Building location: South-facing

[1078] Window orientation: South-facing

[1079] Window size: Large

[1080] Floor plan: 3LDK

[1081] The AI ​​model generates a house design based on this prompt. The proposed design is displayed on the device for the user to review.

[1082] In this way, the present invention makes it possible to quickly and efficiently provide residential design plans that reflect the user's preferences and desired information.

[1083] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1084] Program processing flow

[1085] Step 1: Obtaining real estate information

[1086] The server retrieves land and building information from real estate information websites. Specifically, it uses Python and libraries such as BeautifulSoup and Selenium to perform web scraping.

[1087] Input: URL of the real estate information website

[1088] Output: Land and building information (e.g., land shape, building location, window orientation, size, floor plan)

[1089] Specific actions:

[1090] The server uses Selenium to automate browser operations and access a specified URL. Next, it uses BeautifulSoup to parse the HTML and extract the necessary information.

[1091] Step 2: Processing of the oars

[1092] The server stores the acquired real estate information in a dataframe using the Pandas library and performs necessary data processing. For example, it might impute missing values ​​or normalize the data.

[1093] Input: Land and building information

[1094] Output: Processed data frame

[1095] Specific actions:

[1096] The server converts the retrieved data into a DataFrame using the Pandas read_html function. Next, it imputes missing values ​​using the fillna function and normalizes the data with the normalize function.

[1097] Step 3: Generating prompts for the generative AI model

[1098] The server generates prompt statements to input into the AI ​​model based on the processed data. These prompt statements include information such as the shape of the land and building, location conditions, window orientation, size, and floor plan.

[1099] Input: Processed data frame

[1100] Output: Prompt message

[1101] Specific actions:

[1102] The server extracts the necessary information from the data frame and generates a prompt message like the following:

[1103] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[1104] Land shape: Rectangle

[1105] Building location: South-facing

[1106] Window orientation: South-facing

[1107] Window size: Large

[1108] Floor plan: 3LDK

[1109] Step 4: Generating the house design plans

[1110] The server inputs the generated prompt text into a generation AI model (for example, a generation AI model) and generates a blueprint for a house. The generation AI model then proposes the optimal blueprint based on the prompt text.

[1111] Input: Prompt message

[1112] Output: House blueprints

[1113] Specific actions:

[1114] The server sends prompts to the API for generating AI models and receives blueprint suggestions in return. For example, it sends prompts using the openai.Completion.create function.

[1115] Step 5: Displaying the results

[1116] The server displays the generated house design plans on the user's terminal. The user can review the proposed design plans and request revisions as needed.

[1117] Input: House blueprints

[1118] Output: Blueprint displayed on the user's terminal

[1119] Specific actions:

[1120] The server formats the generated blueprint into HTML and sends it to the user's terminal. The user then views the blueprint through their browser.

[1121] (Application Example 2)

[1122] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[1123] Conventional residential design systems have difficulty reflecting user preferences and desires, and the automatic generation of design plans based on real estate information has been limited. Furthermore, interior design for physical stores requires specialized knowledge and is not easily accessible to the average user. Therefore, there is a need for a system that allows users to easily design houses and stores that meet their specific needs.

[1124] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for automatically generating interior designs for physical stores based on information obtained from real estate information provision sites; means for creating prompt statements for generating design drawings using a generation AI model; and means for generating actual design drawings using a generation AI model. This makes it possible for users to easily design houses and stores that suit their preferences.

[1125] "User preference information" refers to information about the style, functions, and design that users desire when designing houses or shops.

[1126] "Desired information" refers to information about the specific conditions and requirements that users have in mind when designing houses or shops.

[1127] "Real estate information" refers to information about the shape, location, and area of ​​land and buildings.

[1128] A "design drawing" is a diagram that shows the layout of a house or shop, the direction and size of windows, the interior design, and so on.

[1129] A "real estate information website" is a website that provides information about land and buildings on the internet.

[1130] "Interior design" refers to planning the layout and design of the interior spaces of shops and residences.

[1131] A "generative AI model" is an algorithm or program that uses artificial intelligence to automatically generate blueprints and designs.

[1132] A "prompt statement" is an instruction statement used to input into a generative AI model, and it is a sentence that includes conditions and requirements for generating blueprints or designs.

[1133] A system for carrying out this invention includes a server, a user terminal, and a generated AI model. Specific embodiments of this system are described below.

[1134] First, the user terminal receives user preference and desired information as input. This information concerns the style, functions, and design the user desires for the design of their home or store. The user terminal then sends this information to the server.

[1135] Next, the server retrieves real estate information from a real estate information website. This real estate information includes the shape of the land and building, location conditions, and area. Based on the retrieved real estate information, the server automatically generates blueprints for houses and shops.

[1136] The server uses a generative AI model to create prompt statements for generating blueprints. These prompt statements include user preference information, desired information, and real estate information. For example, prompt statements like the following are generated:

[1137] "Land shape: Rectangle, Location: Urban area, Window orientation: South-facing, Lighting position: Center of ceiling"

[1138] Based on the generated prompt text, the generative AI model generates the actual design drawing. For example, OpenAI's GPT-3 is used as the generative AI model. This model takes the prompt text as input and outputs the design drawing.

[1139] The generated blueprints are sent from the server to the user's terminal and presented to the user. Based on the presented blueprints, the user can review the design of the house or store and make modifications as needed.

[1140] This system allows users to easily design houses and shops that meet their specific needs. Specifically, users can easily generate and review design plans using their smartphones or computers. This enables them to realize their desired designs even without specialized knowledge.

[1141] The above describes specific embodiments for carrying out this invention.

[1142] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1143] Step 1:

[1144] The user terminal receives user preference and desired information as input. Users use smartphones or computers to input information about their desired style, functions, and design for residential or commercial buildings. The entered information is stored on the user terminal.

[1145] Step 2:

[1146] The user terminal sends the entered preference and desired information to the server. The transmitted information is stored in a database on the server.

[1147] Step 3:

[1148] The server retrieves real estate information from real estate information websites. The server uses an API to send requests to these websites, obtaining information such as the shape, location, and area of ​​the land and buildings. The retrieved real estate information is then stored on the server.

[1149] Step 4:

[1150] The server generates prompt statements to create a blueprint based on acquired real estate information and user preferences and requests. These prompt statements include information such as the shape of the land, location, window orientation, and lighting position. For example, a prompt statement like "Land shape: Rectangle, Location: Urban area, Window orientation: South-facing, Lighting position: Center of ceiling" might be generated.

[1151] Step 5:

[1152] The server uses a generative AI model to take prompt text as input and generate a blueprint. For example, OpenAI's GPT-3 is used as the generative AI model. The generative AI model, upon receiving prompt text as input, outputs a blueprint. The generated blueprint is then saved to the server.

[1153] Step 6:

[1154] The server sends the generated blueprint to the user's terminal. The user's terminal displays the received blueprint to the user. The user can then view the blueprint on their smartphone or computer screen.

[1155] Step 7:

[1156] Users can review the provided blueprints for houses and shops and make modifications as needed. The modified information is sent back to the server, and the blueprints are regenerated. This allows users to realize a design that meets their needs.

[1157] (Example 3)

[1158] Next, we will describe Embodiment 3 of Embodiment Example 3. 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".

[1159] Conventional residential design systems have difficulty automatically generating blueprints that reflect user preferences and desires, and have been unable to provide optimal design proposals based on real estate information. Therefore, there is a need to efficiently provide residential designs that meet user needs.

[1160] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1161] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that sends prompt text and images to a generation AI model and generates a design; a server that obtains land and building information from a real estate information provision site; a server that makes optimal design proposals based on the obtained real estate information; and a server that displays the generated design and proposal content to the user. This makes it possible to automatically generate a house design that reflects the user's preferences and desires and to make optimal design proposals based on real estate information.

[1162] "User preference information" refers to information that indicates a user's personal preferences regarding design, style, and functionality in residential design.

[1163] "Desired information" refers to specific conditions and requirements that users seek in home design, such as family structure, budget, and location.

[1164] "Real estate information" refers to detailed data about land and buildings, such as price, area, and surrounding environment.

[1165] A "generative AI model" is an algorithm or system that uses artificial intelligence to generate blueprints based on user input information.

[1166] A "prompt statement" is a text-based input statement used to give instructions to a generative AI model.

[1167] A "design drawing" is a diagram that shows the structure, layout, and design of a house.

[1168] A "real estate information website" is an online platform that provides information about land and buildings.

[1169] "Optimal design proposal" refers to proposing the most suitable residential design based on the user's preferences, desires, and real estate information.

[1170] "Means of display" refers to methods or devices for visually providing users with generated design drawings or proposed content.

[1171] This invention is a system that automatically generates house blueprints based on user preference and desired information, and provides optimal design suggestions based on real estate information. A specific embodiment of this system is described below.

[1172] System Configuration

[1173] This system consists of three main elements: a server, a terminal, and a user. The server receives input information from the user, generates blueprints using a generative AI model, and provides optimal design suggestions based on real estate information. The terminal provides an interface for the user to input information and check the results. The user accesses the system through the terminal and inputs the necessary information.

[1174] Hardware and software to be used

[1175] Server: A server with high-performance computing capabilities is required. Specifically, a cloud-based server (e.g., Amazon Web Services or Google Cloud Platform) should be used.

[1176] Terminal: A device used by a user to input information. This includes internet-connected devices such as personal computers, tablets, and smartphones.

[1177] Generative AI Models: Advanced artificial intelligence models such as OpenAI's GPT-4 and DALL-E are used as generative AI models.

[1178] Real estate information websites: Use online platforms (e.g., SUUMO or At Home) to obtain real estate information.

[1179] Data processing and calculations

[1180] 1. User Information Input: The user accesses a form on a web browser using their device and uploads a modern-looking image saved from Instagram. Next, they enter their family composition (4-person family), desired area (Tokyo), and budget (50 million yen).

[1181] 2. Prompt Generation: The server receives the information entered by the user and generates prompts for input into the generated AI model. Specifically, it generates prompts like the following:

[1182] "Based on images of modern exteriors saved by users on Instagram, please automatically generate blueprints for a detached house in Tokyo suitable for a family of four, with a budget of under 50 million yen."

[1183] 3. Sending to the Generating AI Model: The server sends the generated prompt text and the user-uploaded image to the Generating AI model. This transmission is done via API.

[1184] 4. Blueprint Generation: The generation AI model generates a blueprint for a modern-looking detached house in Tokyo based on the received prompt text and image. The blueprint includes details such as the orientation and size of windows and the floor plan. The generated blueprint is sent back to the server.

[1185] 5. Acquisition of Real Estate Information: The server uses the API of a real estate information provider site to acquire information on land and buildings in Tokyo. The information acquired includes land prices, building area, and surrounding environment.

[1186] 6. Optimal Design Proposal: Based on the acquired real estate information, the server proposes the optimal window orientation, size, and layout for the generated design drawings. For example, by proposing a design drawing with many south-facing windows, it provides a living environment with plenty of sunlight.

[1187] 7. Displaying Results: The server displays the final design and proposal to the user. The user can review this information in a web browser and make modifications or regenerate it as needed. An interactive UI is used for the display to ensure ease of use for the user.

[1188] Specific example

[1189] If the user enters the following information:

[1190] Modern exterior images saved from Instagram

[1191] family of 4

[1192] I want a detached house in Tokyo.

[1193] The budget is 50 million yen.

[1194] The server generates the following prompt:

[1195] "Based on images of modern exteriors saved by users on Instagram, please automatically generate blueprints for a detached house in Tokyo suitable for a family of four, with a budget of under 50 million yen."

[1196] The AI ​​model generates a design drawing based on this prompt text and image, and the server proposes the optimal window orientation, size, and floor plan based on data obtained from a real estate information website. The specific processing flow in Example 3 will be explained using Figure 15.

[1197] Step 1:

[1198] The user enters information.

[1199] The user accesses a form on a web browser using their device and uploads a modern-looking image saved from Instagram. Next, they enter their family size (four people), desired location (within Tokyo), and budget (50 million yen). This information is then sent to the server.

[1200] Input: Images saved from Instagram, family composition, desired region, budget

[1201] Output: User preference information and desired information

[1202] Step 2:

[1203] The server generates the prompt message.

[1204] The server receives the information entered by the user and generates prompt messages for input into the generated AI model. Specifically, it generates prompt messages like the following:

[1205] "Based on images of modern exteriors saved by users on Instagram, please automatically generate blueprints for a detached house in Tokyo suitable for a family of four, with a budget of under 50 million yen."

[1206] Input: User preferences and desired information

[1207] Output: Prompt message to send to the generating AI model

[1208] Step 3:

[1209] The server sends prompt text and images to the generated AI model.

[1210] The server sends the generated prompt text and the user-uploaded image to the AI ​​model. This transmission is done via API.

[1211] Input: Prompt text, user-uploaded image

[1212] Output: Input data for the generative AI model

[1213] Step 4:

[1214] The generative AI model generates the blueprint.

[1215] The generation AI model generates a blueprint of a modern-looking detached house in Tokyo based on the received prompt text and image. The blueprint includes details such as the direction and size of windows and the floor plan. The generated blueprint is then sent back to the server.

[1216] Input: Prompt text, user-uploaded image

[1217] Output: Generated blueprint

[1218] Step 5:

[1219] The server retrieves real estate information.

[1220] The server uses the API of a real estate information website to retrieve information on land and buildings in Tokyo. The information retrieved includes land prices, building area, and surrounding environment.

[1221] Input: API of a real estate information provider website

[1222] Output: Acquired real estate information

[1223] Step 6:

[1224] The server will propose the optimal design.

[1225] Based on the acquired real estate information, the server proposes optimal window orientations, sizes, and floor plans for the generated blueprints. For example, by proposing blueprints with many south-facing windows, it provides a living environment with plenty of sunlight.

[1226] Input: Generated blueprints, acquired property information

[1227] Output: Optimal design proposal

[1228] Step 7:

[1229] The server displays the results to the user.

[1230] The server displays the final design blueprints and proposals to the user. The user can review this information in a web browser and modify or regenerate it as needed. An interactive UI is used for display to ensure user-friendliness.

[1231] Input: Final design drawings, proposed content

[1232] Output: Results displayed to the user

[1233] (Application Example 3)

[1234] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[1235] Conventional residential design systems struggled to automatically generate blueprints that reflected user preferences and desires, and were unable to effectively utilize real estate information to propose blueprints. Furthermore, they could not utilize images saved by users or information from social media, making it difficult to provide blueprints that met specific user needs. This resulted in a challenge in increasing user satisfaction.

[1236] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1237] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that generates prompt text based on images saved by the user and generates a design using a generation AI model; and a server that proposes window orientation and size, floor plan, etc., based on land and building information obtained from a real estate information provision site. This enables the automatic generation of design plans that meet the user's specific needs and the effective use of real estate information.

[1238] "User preference information" refers to information about the design and style that users desire, and is obtained from sources such as social media and saved images.

[1239] "Desired information" refers to information about the conditions and requirements of the housing that the user desires, including specific preferences such as family structure, budget, and location.

[1240] A "house design drawing" is a diagram showing the exterior, floor plan, window orientation and size, etc., of a house, and is automatically generated based on the user's preferences and requests.

[1241] "Real estate information" refers to information about land and buildings, and is obtained from real estate information websites and other sources.

[1242] A "generative AI model" is a model that uses artificial intelligence to generate blueprints or proposals from specific input information.

[1243] A "prompt message" is an instruction message to be input into a generation AI model, and it is generated based on the user's preferences and desired information.

[1244] A "real estate information website" is a website that provides information about land and buildings, and users can access and obtain this information.

[1245] "Window orientation, size, and floor plan" are important elements in house design and are proposed based on the user's wishes and real estate information.

[1246] The system for implementing this invention includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for generating prompt text based on images saved by the user and generating a design using a generation AI model; and means for proposing window orientation and size, floor plan, etc., based on land and building information obtained from a real estate information provision site.

[1247] System program

[1248] The server receives preference and desired information entered by the user via a device such as a smartphone or computer. This includes images obtained from social media such as Instagram, as well as information such as family structure, budget, and desired region. Next, the server generates prompt statements based on this information. These prompt statements are input into a generation AI model and serve as instructions for generating a house design.

[1249] Based on the generated prompt text, the AI ​​model automatically creates a blueprint for a house. This blueprint reflects the user's preferences and desires, and includes specific exterior details and floor plans. Furthermore, the server suggests window orientations and sizes, floor plans, and other details based on land and building information obtained from real estate information websites.

[1250] Hardware and software to be used

[1251] This system uses the following hardware and software:

[1252] Hardware: Servers, user terminals (smartphones, personal computers, etc.)

[1253] Software: Generative AI models (e.g., OpenAI's GPT-3), prompt generation programs, image acquisition programs (e.g., requests, PIL)

[1254] Specific example

[1255] For example, if the user enters the following conditions:

[1256] Instagram image URL: https: / / example.com / instagram_image.jpg

[1257] Family structure: 4 people family

[1258] Desired area: Tokyo

[1259] Budget: 50 million yen

[1260] The generated prompt will look like this:

[1261] Based on images of modern exteriors saved by the user on Instagram, we need a design for a detached house in Tokyo for a family of four with a budget of 50 million yen. Please generate a blueprint for a detached house with a modern exterior based on this information.

[1262] When this prompt is entered into the AI ​​model, the model automatically generates a house design that meets the user's preferences. The generated design reflects the user's desired modern exterior and a floor plan suitable for the family structure. In addition, based on land and building information obtained from real estate information websites, the model also makes specific suggestions regarding window orientation and size, floor plan, and other details.

[1263] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[1264] Step 1:

[1265] Users input their preferences and desired information from devices such as smartphones and computers. This includes image URLs obtained from social media such as Instagram, as well as information such as family structure, budget, and desired region. The entered information is sent to the server.

[1266] Input: Instagram image URL, family composition, budget, desired region

[1267] Output: User preference information and desired information sent to the server

[1268] Step 2:

[1269] The server receives preference and request information sent by the user. Based on the received information, it performs data processing to generate prompt messages. Specifically, it retrieves image URLs and converts information such as family structure, budget, and desired region into text format.

[1270] Input: User preferences and desired information

[1271] Output: Data for prompt message generation

[1272] Step 3:

[1273] The server downloads the image based on the retrieved image URL and loads it as an image object. This process uses the requests library and the PIL library.

[1274] Input: Image URL

[1275] Output: Image object

[1276] Step 4:

[1277] The server generates prompt messages based on image objects and user information in text format. These generated prompt messages are instructions to be input into the AI ​​model.

[1278] Input: Image object, user information in text format

[1279] Output: Prompt message

[1280] Step 5:

[1281] The server inputs the generated prompt text into a generative AI model to automatically generate a house design. This process uses generative AI models such as OpenAI's GPT-3.

[1282] Input: Prompt message

[1283] Output: Auto-generated house blueprints

[1284] Step 6:

[1285] The server retrieves land and building information from real estate information websites. This information includes details such as the orientation and size of windows and the floor plan.

[1286] Input: URL of the real estate information website

[1287] Output: Information about land and buildings

[1288] Step 7:

[1289] Based on the acquired real estate information, the server makes specific suggestions regarding window orientation, size, floor plan, and other details for the generated house blueprints.

[1290] Input: Land and building information, automatically generated house blueprints.

[1291] Output: Residential blueprints including specific proposals

[1292] Step 8:

[1293] The server sends the final design to the user's terminal and provides a proposal to the user. The user can review the proposed design and make modifications or regenerate it as needed.

[1294] Input: House design plans including specific proposals

[1295] Output: Final design drawings sent to the user's terminal.

[1296] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1297] "Example of form 1"

[1298] One embodiment of the present invention incorporates an emotion engine that recognizes the user's emotions. This emotion engine recognizes the user's emotions and adjusts the house design based on those emotions. Specifically, when the user is feeling happy, it suggests interiors with bright colors and an open floor plan. On the other hand, when the user is feeling depressed, it suggests interiors with calm colors and a floor plan that prioritizes privacy.

[1299] "Example of form 2"

[1300] Furthermore, the emotion engine adjusts housing suggestions based on the user's emotions. Specifically, when the user is feeling happy, it suggests luxurious homes. On the other hand, when the user is feeling down, it suggests simple and functional homes.

[1301] "Example of form 3"

[1302] As a concrete example, when a user is happy because they have landed a new job, the emotion engine recognizes that happiness and automatically generates blueprints for a luxurious house. These blueprints feature large windows, a spacious living room, and high-quality interior materials. On the other hand, when a user is depressed because they have lost their job, the emotion engine recognizes that depression and automatically generates blueprints for a simple, functional house. These blueprints have only the bare minimum number of rooms and functions, keeping costs down.

[1303] The following describes the processing flow for each example of the form.

[1304] "Example of form 1"

[1305] Step 1: The emotion engine recognizes the user's emotions.

[1306] Step 2: The emotion engine adjusts the house design based on the user's emotions. Specifically, when the user is feeling happy, it suggests bright interior colors and an open floor plan.

[1307] Step 3: On the other hand, when the user is feeling down, suggest interiors with calming colors and floor plans that prioritize privacy.

[1308] "Example of form 2"

[1309] Step 1: The emotion engine recognizes the user's emotions.

[1310] Step 2: The emotion engine adjusts housing suggestions based on the user's emotions. Specifically, when the user is feeling happy, it suggests luxurious homes.

[1311] Step 3: On the other hand, when the user is feeling down, propose a simple and functional home.

[1312] "Example of form 3"

[1313] Step 1: When a user feels joy from getting a new job, the emotion engine recognizes that joy.

[1314] Step 2: The emotion engine automatically generates blueprints for a luxurious house. These blueprints feature large windows, a spacious living room, and high-quality interior materials.

[1315] Step 3: On the other hand, when a user is depressed after losing their job, the emotion engine recognizes that depression.

[1316] Step 4: The emotion engine automatically generates a simple and functional house design. This design has the minimum necessary number of rooms and functions, keeping costs down.

[1317] (Example 1)

[1318] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1319] Conventional housing design systems have struggled to automatically generate blueprints that reflect user preferences and desires. Furthermore, they fail to adjust blueprints to accommodate user emotions, resulting in lower user satisfaction. Additionally, they lack effective means of utilizing information from social media and real estate information websites. This has led to challenges in creating housing designs that meet diverse user needs.

[1320] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1321] This invention includes a server that receives user preference and desire information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that proposes a house based on the generated design; a server that recognizes the user's emotions and adjusts the house design based on those emotions; and a server that proposes interior design and floor plans based on the user's emotions. This enables the automatic generation of house design plans that reflect the user's preferences and desires, and further allows for adjustments to the design plans that take the user's emotions into consideration, thereby increasing user satisfaction. In addition, by effectively utilizing information from social media and real estate information websites, it is possible to realize house designs that meet the diverse needs of users.

[1322] "User preference information" refers to images and text information about housing that users have obtained from social media and other sources on the internet.

[1323] "Desired information" refers to specific requests entered by the user, such as family structure, desired address, price range, whether or not renovations are needed, and whether they prefer a detached house or an apartment.

[1324] "Real estate information" refers to detailed property information obtained from real estate information websites and other databases.

[1325] "House blueprints" refer to drawings of the house's floor plan, interior, and exterior that are automatically generated based on the user's preferences, desired features, and real estate information.

[1326] "Means of recognizing emotions" refers to algorithms and software that analyze emotions from a user's facial expressions or entered text and determine their emotional state.

[1327] "Means of adjusting the blueprint" refers to algorithms or software used to change or modify the content of a house's blueprint based on recognized user emotions.

[1328] "Methods for proposing interior design and floor plans" refers to algorithms and software that propose optimal interior designs and floor plans based on the user's emotions and preferences.

[1329] "Social media" refers to a platform on the internet for users to share information.

[1330] A "real estate information website" refers to a website or online service that provides detailed information about properties.

[1331] Modes for carrying out the invention

[1332] This invention is a system that automatically generates house blueprints based on user preference and desired information, and further adjusts the blueprints to take the user's emotions into consideration. This system consists of a server, a terminal, and a user.

[1333] System Configuration

[1334] 1. User actions

[1335] Users save their favorite house images from social media on the internet and upload them to the system.

[1336] Users input their preferences into the system, including family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment.

[1337] 2. Server processing

[1338] The server receives the residential images uploaded by the user and extracts image features using image recognition algorithms (e.g., TensorFlow, OpenCV).

[1339] The server analyzes the user's input and desired information using a natural language processing engine (e.g., GPT-3) and organizes it as structured data.

[1340] The server integrates data obtained from image recognition algorithms and natural language processing engines to generate blueprints for a house.

[1341] The server uses an emotion engine to recognize the user's emotions and analyzes them from the user's facial expressions and entered text.

[1342] The server adjusts the design based on the user's emotions it perceives. For example, if the user is feeling happy, it might suggest bright interior colors and an open floor plan.

[1343] The server generates the final, adjusted blueprint and provides it to the user.

[1344] Hardware and software to use

[1345] Hardware: High-performance servers (e.g., servers with NVIDIA GPUs)

[1346] Software: Image recognition algorithms (e.g., TensorFlow, OpenCV), natural language processing engines (e.g., GPT-3), emotion recognition engines

[1347] Specific example

[1348] For example, suppose a user uploads a modern house design image saved from Instagram to the system and inputs their desired information, such as family size (four people), desired address (Tokyo), price range (under 50 million yen), whether renovation is needed (yes), and whether they want a house or apartment (house).

[1349] The server first uses an image recognition algorithm to extract modern design features from images of houses. Next, it uses a natural language processing engine to analyze the user's preferences and generates floor plans suitable for a family of four, designs suitable for residential areas in Tokyo, specifications that can be realized within 50 million yen, designs that take renovation into consideration, and plans for detached houses.

[1350] Furthermore, if the emotion engine recognizes the user's emotion as "joy," the server will suggest interiors with bright colors and an open living room. Finally, the server integrates this information to provide the user with a blueprint for the ideal home.

[1351] Example of a prompt

[1352] The user provided images of modern-designed houses saved from social media, along with their family size (4 people), desired address (Tokyo), price range (under 50 million yen), whether renovations are desired (yes), and whether they prefer a house or apartment (house). Based on this information, please generate a house design. If the user's emotion is "joy," please suggest a bright interior color scheme and an open floor plan.

[1353] In this way, the system can automatically generate house plans based on the user's preferences and desires, and can further adjust the plans to take the user's emotions into consideration.

[1354] The flow of the specific processing in Example 1 will be explained using Figure 17.

[1355] Step 1:

[1356] Users save images of their favorite houses and input them into the system.

[1357] Specifically, the user downloads images of houses they like from social media on the internet and uploads those images through the system's interface.

[1358] Input: Residential images obtained from social media

[1359] Output: Residential images uploaded to the system

[1360] Step 2:

[1361] The user enters the desired information into the system.

[1362] In terms of specific operations, the user inputs desired information such as family structure, desired address, price range, whether or not renovations are needed, and whether they prefer a house or apartment, through the system interface.

[1363] Input: Family composition, desired address, price range, whether renovation is required, desired type of property (house or apartment), etc.

[1364] Output: Desired information entered into the system

[1365] Step 3:

[1366] The server analyzes residential images using an image recognition algorithm.

[1367] In terms of specific operations, the server receives uploaded images of houses and extracts image features using image recognition algorithms (e.g., TensorFlow, OpenCV). For example, it analyzes information such as the building's exterior, interior style, and color scheme.

[1368] Input: Residential images uploaded to the system

[1369] Output: Image feature data (building exterior, interior style, color tone, etc.)

[1370] Step 4:

[1371] The server uses a natural language processing engine to analyze the desired information.

[1372] In terms of specific operations, the server analyzes the user's input preferences using a natural language processing engine (e.g., GPT-3) and organizes them as structured data. For example, it understands information such as family structure, desired address, and price range, and stores it in a database.

[1373] Input: Desired information entered into the system

[1374] Output: Structured desired information data

[1375] Step 5:

[1376] The server integrates the analysis results and generates blueprints for the house.

[1377] In terms of specific operations, the server integrates data obtained from image recognition algorithms and natural language processing engines to generate blueprints for a house. For example, it designs the floor plan, interior, and exterior based on the user's preferences and desires.

[1378] Input: Image feature data, structured desired information data

[1379] Output: House blueprints

[1380] Step 6:

[1381] The server uses an emotion engine to recognize the user's emotions.

[1382] Specifically, the server uses an emotion engine to recognize the user's emotions. It analyzes the text and facial expression data entered by the user into the system to determine the user's current emotional state.

[1383] Input: User text input, facial expression data

[1384] Output: User emotional state data

[1385] Step 7:

[1386] The server adjusts the design based on the user's emotions.

[1387] In practice, the server adjusts the design based on the user's perceived emotions. For example, if the user is feeling happy, it suggests bright interior colors and an open layout. On the other hand, if the user is feeling depressed, it suggests calm interior colors and a layout that prioritizes privacy.

[1388] Input: User emotional state data, house blueprints

[1389] Output: Adjusted house blueprints

[1390] Step 8:

[1391] The server provides the user with the final design blueprint.

[1392] Specifically, the server generates a final, adjusted blueprint and provides it to the user. The user can review the blueprint through the system interface and provide feedback as needed.

[1393] Input: Adjusted house blueprints

[1394] Output: Final design drawings provided to the user

[1395] (Application Example 1)

[1396] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1397] Traditional home design systems could generate blueprints based on user preferences and requests, but they lacked the ability to adjust the blueprints to reflect the user's emotions. Furthermore, it was difficult to provide real-time, emotionally responsive suggestions when users consulted with design and renovation companies in person. This resulted in a challenge in increasing user satisfaction.

[1398] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1399] In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for recognizing the user's emotions and adjusting the house design based on those emotions; and means for analyzing the user's facial expressions using a smart device and recognizing emotions. This makes it possible to generate and propose house design plans that reflect the user's emotions in real time.

[1400] "User preference information" refers to images related to housing obtained by users from social media such as Instagram, as well as information indicating the user's personal preferences.

[1401] "Desired information" refers to information that indicates the user's specific requests, such as desired family structure, address, price range, whether or not renovations are needed, and whether they prefer a detached house or an apartment.

[1402] "Real estate information" refers to detailed information about a property, such as its location, price, floor plan, and year of construction, obtained from real estate information websites.

[1403] An "automatic blueprint generation method" refers to a system or algorithm for automatically generating blueprints for a house based on user preference information, desired information, and real estate information.

[1404] A "proposal means" refers to a system or algorithm for making housing proposals to users based on the generated blueprints.

[1405] An "emotion recognition tool" is a system or algorithm that recognizes a user's emotions and adjusts the design plans of a house based on those emotions.

[1406] A "smart device" is a device, such as a smartphone or smart glasses, that analyzes a user's facial expressions and recognizes their emotions.

[1407] "Facial expression analysis means" refers to a system or algorithm that uses a smart device to analyze a user's facial expressions and recognize their emotions.

[1408] The system for implementing this invention automatically generates a house design based on the user's preference information, desired information, and real estate information, and adjusts the design based on the user's emotions. Specific embodiments are shown below.

[1409] System Configuration

[1410] 1. Hardware:

[1411] Smart devices: Devices such as smartphones and smart glasses that analyze a user's facial expressions and recognize their emotions.

[1412] Server: A server used for data processing and generating blueprints.

[1413] 2. Software:

[1414] Emotion recognition model: A machine learning model that analyzes a user's facial expressions and recognizes their emotions (e.g., an emotion recognition model using Keras).

[1415] Blueprint generation algorithm: An algorithm that automatically generates blueprints for houses based on user preferences, desired features, and real estate information.

[1416] Data Acquisition Module: A module for acquiring necessary information from social media and real estate information websites.

[1417] Processing flow

[1418] 1. Input of user preference and desired information:

[1419] Users upload images of houses they've saved from social media like Instagram to the app and enter information such as family composition, desired address, price range, whether renovations are needed, and whether it's a house or an apartment.

[1420] 2. Obtaining real estate information:

[1421] The server retrieves detailed information such as the property's location, price, floor plan, and year of construction from real estate information websites.

[1422] 3. Emotion recognition:

[1423] The system analyzes the user's facial expressions using smart devices and recognizes the user's emotions using an emotion recognition model.

[1424] 4. Automatic generation of blueprints:

[1425] The server automatically generates house blueprints using a blueprint generation algorithm, based on the user's preference information, desired information, real estate information, and recognized emotional information.

[1426] 5. Proposal:

[1427] Based on the generated blueprints, we propose housing designs to the user. This includes suggesting interior designs and floor plans that align with the user's preferences.

[1428] Specific example

[1429] For example, a user uploads an image saved from Instagram to the app and enters their desired address and price range. The app analyzes the user's facial expressions through smart glasses and recognizes their emotions. Based on this information, the server automatically generates a design plan and proposes it to the user.

[1430] Example of a prompt

[1431] Users upload images of houses they've saved from Instagram and enter information such as family composition, desired address, price range, whether renovations are needed, and whether it's a house or apartment. The system analyzes facial expressions through smart glasses to recognize emotions. Based on this information, it automatically generates an optimal house design.

[1432] In this way, a housing design assistant system based on the user's emotions and preferences can be realized.

[1433] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[1434] Step 1:

[1435] Users upload images of houses they have saved from social media such as Instagram to their devices.

[1436] Input: Image file of a house

[1437] Output: Uploaded image data

[1438] Specific operation: The user uploads saved images of their home to the application using their smartphone or smart glasses. The application sends the image data to the server.

[1439] Step 2:

[1440] The user enters information such as family structure, desired address, price range, whether or not renovations are needed, and whether they prefer a house or apartment into the terminal.

[1441] Input: Family composition, address, price range, whether or not renovations have been done, type of housing

[1442] Output: User's requested information data

[1443] Specific operation: The user enters the desired information into the application's input form and presses the submit button. The application sends the entered data to the server.

[1444] Step 3:

[1445] The server retrieves detailed information such as the property's location, price, floor plan, and year of construction from a real estate information website.

[1446] Input: API of a real estate information provider website

[1447] Output: Real estate information data

[1448] Specific operation: The server calls the API of a real estate information website to retrieve the necessary real estate information. The retrieved data is stored in an internal database.

[1449] Step 4:

[1450] The device uses a smart device to analyze the user's facial expressions and recognizes the user's emotions using an emotion recognition model.

[1451] Input: User's facial expression image

[1452] Output: User sentiment data

[1453] Specific operation: The smart device's camera captures the user's facial expressions and sends the image data to the server. The server analyzes the facial image using an emotion recognition model and recognizes the user's emotions.

[1454] Step 5:

[1455] The server automatically generates house blueprints using a blueprint generation algorithm based on the user's preferences, desires, real estate information, and emotional information.

[1456] Input: User preference information, desired information, real estate information, emotional information

[1457] Output: Auto-generated house blueprints

[1458] Specific operation: The server integrates all input data and executes the blueprint generation algorithm. The algorithm generates blueprints that take into account the user's emotions regarding interior design and floor plans.

[1459] Step 6:

[1460] The server generates blueprints and then proposes housing designs to the user.

[1461] Input: Auto-generated house blueprints

[1462] Output: Suggestions for the user

[1463] Specific operation: The server presents the generated blueprints to the user and makes suggestions for interior design and floor plans that respond to their emotions. The user can review the suggestions through the application.

[1464] (Example 2)

[1465] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1466] Conventional housing design systems can generate blueprints based on user preferences and requests, but they have the problem of not being able to make suggestions that take user emotions into consideration. Furthermore, it was difficult to effectively utilize real estate information in housing design, making it impossible to provide optimal suggestions to users. Moreover, there was a need to improve user satisfaction by offering housing suggestions that resonated with users' emotions.

[1467] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1468] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; and a server that analyzes the user's emotions and adjusts the house proposals based on the analysis results. This makes it possible to propose an optimal house design that is not only based on the user's preferences and desired information but also on their emotions.

[1469] "User preference information" refers to information that indicates a user's personal preferences and desires regarding housing.

[1470] "Desired information" refers to information that indicates the specific conditions and requests that users have for their home.

[1471] "Real estate information" refers to information that includes detailed data on land and buildings, such as their shape, location, and price.

[1472] A "design drawing" is a diagram that shows the layout and structure of a house, as well as the direction and size of the windows.

[1473] A "proposal" is a specific plan regarding the design and layout of a house that is provided to the user.

[1474] "Analyzing emotions" means identifying and evaluating a user's emotional state based on their facial expressions, behavior, input data, and other factors.

[1475] "Adjusting" means modifying and optimizing the proposed content based on the analysis results.

[1476] This invention is a system that automatically generates house designs and provides optimal housing proposals by taking into account the user's preferences, desires, real estate information, and emotions. A specific embodiment of this system is described below.

[1477] System Configuration

[1478] 1. Obtaining real estate information

[1479] The server retrieves land and building information from real estate information websites. In this process, the server uses specific APIs to collect data. For example, it might utilize the API of a real estate information website.

[1480] 2. Data analysis and processing

[1481] The server analyzes the acquired land and building information and extracts data such as shape and location conditions. This is done using a data analysis library.

[1482] 3. Automatic generation of residential building plans

[1483] The server automatically generates house blueprints based on the analyzed data. Specifically, it considers the shape and location of the land and proposes window orientations and sizes, as well as floor plans. This process uses the API of design software.

[1484] 4. Adjustment by the Emotion Engine

[1485] The device analyzes the user's emotions using an emotion engine. This emotion engine utilizes an emotion analysis API. If the user is feeling happy, the device suggests a luxurious home. Conversely, if the user is feeling depressed, it suggests a simple and functional home.

[1486] Specific example

[1487] Example 1: Acquisition of real estate information

[1488] The server uses the API of a real estate information provider to retrieve land information for a specific area. For example, it sends an API request like the following:

[1489] "Retrieve land information for San Francisco and generate blueprints that suggest luxurious homes if the user is happy, and simple homes if they are depressed."

[1490] Example 2: Data Analysis and Processing

[1491] The server analyzes the acquired data using a data analysis library. For example, it extracts information about the land's shape and location and prepares it for use in the next step.

[1492] Example 3: Automatic generation of residential building plans

[1493] The server generates design drawings using the design software's API. For example, it considers the shape and location of the land and proposes window orientations and sizes, as well as floor plans.

[1494] Example 4: Adjustment by an emotional engine

[1495] The device uses an emotion analysis API to analyze the user's emotions. For example, if the user is happy, it suggests a luxurious house; if they are depressed, it suggests a simple house.

[1496] In this way, it becomes possible to propose optimal house designs that not only reflect the user's preferences and desires, but also their emotions. This system can improve user satisfaction.

[1497] The flow of the specific processing in Example 2 will be explained using Figure 19.

[1498] Step 1:

[1499] The server retrieves land and building information from real estate information websites. Specifically, the server sends an API request and receives JSON data containing land information for a specified area. The input is the parameters of the API request (e.g., area, property type), and the output is the retrieved real estate information in JSON data.

[1500] Step 2:

[1501] The server converts the retrieved JSON data into a data frame using a data analysis library. Specifically, the server uses the pandas library to read the JSON data and convert it into a data frame. The input is the retrieved JSON data, and the output is real estate information in data frame format.

[1502] Step 3:

[1503] The server extracts the necessary data from the data frame. Specifically, it extracts information such as land shape and location conditions and prepares it for use in the next step. The input is real estate information in data frame format, and the output is the extracted data on land shape and location conditions.

[1504] Step 4:

[1505] The server generates house blueprints using the API of design software. Specifically, it considers the shape and location of the land and proposes window orientations and sizes, floor plans, and other details. The input is extracted data on the shape and location of the land, and the output is the generated house blueprints.

[1506] Step 5:

[1507] The device analyzes the user's emotions using an emotion analysis API. Specifically, it identifies and evaluates the emotional state from the user's facial expressions, actions, and input data. The input is the user's image and text data, and the output is the analyzed emotion data.

[1508] Step 6:

[1509] The device adjusts housing suggestions based on the analysis results. Specifically, it suggests a luxurious house if the user is happy, and a simple house if they are depressed. The input is the analyzed emotion data and the generated house blueprints, and the output is the adjusted housing suggestion.

[1510] In this way, by clearly defining the specific actions, inputs, and outputs performed at each processing step, the processing flow of the system program was explained in detail.

[1511] (Application Example 2)

[1512] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[1513] Conventional housing design systems could automatically generate blueprints based on user preferences, desired information, and real estate data, but they could not adjust proposals to reflect user emotions or display blueprints using virtual reality. Therefore, it was difficult to provide housing proposals that resonated with users' emotions or offer a more realistic experience. This resulted in a challenge in increasing user satisfaction.

[1514] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1515] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that receives user emotional information as input and adjusts the house proposals based on this information; and a server that displays the generated design using a virtual reality display device. This makes it possible to adjust house proposals according to the user's emotions and to provide a realistic experience using virtual reality.

[1516] "User preference information" refers to information that indicates a user's personal preferences and desires regarding housing.

[1517] "Desired information" refers to information that indicates the specific conditions and requests that users have for their home.

[1518] "Real estate information" refers to information that includes detailed data about land and buildings.

[1519] A "house design drawing" is a detailed drawing showing the layout, structure, and facilities of a house.

[1520] "Emotional information" refers to information that indicates the user's current emotional state.

[1521] A "virtual reality display device" is a device used to visually display a virtual space.

[1522] "Means of automatic generation" refers to devices or programs that have the function of automatically creating design drawings based on input information.

[1523] "Means for adjusting suggestions" refers to devices or programs that have the function of modifying and optimizing the content of suggestions based on the user's emotional information.

[1524] "Means of display" refers to devices or programs that have the function of visually presenting the generated design drawings to the user.

[1525] The system for implementing this invention automatically generates a house design based on the user's preference information, desired information, real estate information, and emotional information, and presents it to the user using a virtual reality display device. Specific embodiments are shown below.

[1526] System Configuration

[1527] The system consists of the following main components:

[1528] 1. User terminal: A device such as a smartphone or head-mounted display collects user input information and displays it in virtual reality.

[1529] 2. Server: Receives user preference information, desired information, real estate information, and emotional information, and automatically generates house blueprints.

[1530] 3. Emotion Engine: Analyzes user emotional information and adjusts housing suggestions accordingly.

[1531] 4. Design Generation Engine: Generates house blueprints based on real estate information, user preferences, and desired information.

[1532] 5. Virtual reality display device: Displays the generated blueprint in a virtual reality space.

[1533] Program processing

[1534] The server processes the data in the following steps:

[1535] 1. Data Acquisition: Acquire preference information, desired information, and real estate information from the user's device. Acquire user sentiment information using the sentiment engine.

[1536] 2. Blueprint Generation: Using a blueprint generation engine, blueprints for the house are automatically generated based on the acquired information.

[1537] 3. Proposal Adjustment: Using an emotion engine, housing suggestions are adjusted based on the user's emotional information.

[1538] 4. Virtual reality display: The generated blueprint is presented to the user using a virtual reality display device.

[1539] Hardware and software to be used

[1540] Hardware: Smartphones, head-mounted displays, servers

[1541] Software: EmotionEngine (emotion engine), DesignGenerator (design generation engine), VRDisplay (virtual reality display engine)

[1542] Specific example

[1543] For example, when a user experiences designing a house using a smartphone, a luxurious house is suggested when the user is happy, and a simple, functional house is suggested when the user is depressed. The user wears a head-mounted display and can realistically experience the design blueprints generated in a virtual reality space.

[1544] Example of a prompt

[1545] "Generate blueprints for luxurious homes that will delight the user."

[1546] "Please generate blueprints for a simple and functional home that will be suitable for users who are feeling down."

[1547] In this way, we can provide housing proposals that respond to the user's emotions and realistic experiences using virtual reality.

[1548] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[1549] Step 1:

[1550] The user terminal receives user preference and desired information as input. Users input their housing preferences and specific requests using a smartphone or head-mounted display. This information is then sent to the server.

[1551] Input: User preference information, desired information

[1552] Output: User preference information and desired information sent to the server

[1553] Step 2:

[1554] The server retrieves real estate information from real estate information websites. The server accesses the sites via APIs and collects detailed data about land and buildings.

[1555] Input: URL of the real estate information website

[1556] Output: Acquired real estate information

[1557] Step 3:

[1558] The user terminal uses an emotion engine to acquire the user's emotional information. It analyzes the user's facial expressions and voice to detect their current emotional state. The emotional information is then sent to the server.

[1559] Input: User's facial expressions, voice

[1560] Output: Sentiment information sent to the server

[1561] Step 4:

[1562] The server uses a design generation engine to automatically generate house blueprints based on acquired preference information, desired information, and real estate information. The design generation engine analyzes this information and designs the optimal floor plan and structure.

[1563] Input: User preferences, desired information, real estate information

[1564] Output: Generated house blueprints

[1565] Step 5:

[1566] The server uses an emotion engine to adjust housing suggestions based on the user's emotional information. For example, if the user is happy, it will suggest a luxurious house; if they are depressed, it will suggest a simple and functional house.

[1567] Input: Generated house blueprints, emotional information

[1568] Output: Proposal for a modified house

[1569] Step 6:

[1570] The server uses a virtual reality display to present the generated blueprints to the user. The user wears a head-mounted display and can realistically experience the blueprints in a virtual reality space.

[1571] Input: Adapted housing proposal

[1572] Output: Blueprint of a house displayed in a virtual reality space

[1573] In this way, we can provide housing proposals that respond to the user's emotions and realistic experiences using virtual reality.

[1574] (Example 3)

[1575] Next, we will describe Embodiment 3 of Embodiment Example 3. 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".

[1576] Conventional housing design systems have difficulty automatically generating blueprints that reflect user preferences and desires, and generating blueprints that take real estate information into account is also time-consuming. Furthermore, they cannot generate blueprints that take into account the user's emotional state, thus failing to enhance user psychological satisfaction. There is a need for a system that solves these problems and automatically generates housing blueprints that meet the diverse needs of users.

[1577] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1578] In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; and means for recognizing the user's emotional state and adjusting the house design according to that emotional state. This makes it possible to automatically generate a house design that takes into account the user's preferences and desired information, real estate information, and even their emotional state.

[1579] "User preference information" refers to information about the designs and styles that users prefer, and is obtained from sources such as social media.

[1580] "Desired information" refers to information about the user's specific requirements, such as the location of the house they want, their budget, and their family structure.

[1581] "Real estate information" refers to information about land and buildings obtained from real estate information websites.

[1582] "Emotional state" refers to information that indicates the user's current psychological state and is recognized by the emotion engine.

[1583] A "design drawing" is a diagram that shows the structure, layout, and orientation and size of windows of a house.

[1584] "Automatic generation" refers to the process where a system automatically creates a blueprint based on user input, property information, and emotional state.

[1585] A "proposal" is the process of showing the user a specific design and layout of a house based on the generated blueprints.

[1586] Modes for carrying out the invention

[1587] This invention is a system that automatically generates and proposes house designs to users based on their preferences, desires, real estate information, and emotional state. A specific embodiment of this system is shown below.

[1588] Hardware and software to use

[1589] Hardware: Servers, user terminals (PCs, smartphones)

[1590] Software: Generative AI models (e.g., GPT-4), emotion recognition engine, database management system (e.g., MySQL), real estate information site API

[1591] System Operation Overview

[1592] 1. Enter user information

[1593] Users use their devices to input information such as images saved from Instagram, family composition, desired housing location (within Tokyo), and budget (50 million yen).

[1594] Specific example input: "We are a family of four, looking for a modern-looking detached house in Tokyo, with a budget of 50 million yen."

[1595] 2. Data transmission and analysis

[1596] The terminal sends the entered information to the server.

[1597] The server analyzes the received information and inputs it as a prompt message into the generating AI model.

[1598] Specific prompt example: "The user has saved an image of a modern exterior from Instagram. They are a family of four looking for a detached house in Tokyo with a budget of 50 million yen. Please generate a design plan based on this information."

[1599] 3. Generating blueprints

[1600] The server inputs prompt messages into the generated AI model and generates a blueprint.

[1601] The server uses information on land and buildings in Tokyo obtained from real estate information websites to suggest window orientations, sizes, floor plans, and other layouts.

[1602] 4. Emotion Recognition and Adjustment of the Blueprint

[1603] The server uses an emotion engine to recognize the user's emotional state.

[1604] The server adjusts the blueprint based on the results of the emotion engine.

[1605] Specific prompt example: "The user is delighted to have a new job. Please generate blueprints for a luxurious house with large windows, a spacious living room, and high-quality interior materials."

[1606] 5. Provision of design drawings

[1607] The server sends the generated blueprint to the user's terminal.

[1608] The terminal displays the received blueprints to the user.

[1609] Specific example

[1610] User input: "We are a family of four and would like a modern-looking detached house in Tokyo. Our budget is 50 million yen."

[1611] Prompt: "The user has saved an image of a modern exterior from Instagram. They are a family of four looking for a detached house in Tokyo with a budget of 50 million yen. Please generate a blueprint based on this information."

[1612] Emotion recognition prompt message: "The user is happy to have a new job. Please generate blueprints for a luxurious house with large windows, a spacious living room, and high-quality interior materials."

[1613] This system enables the automatic generation of house designs that take into account the user's preferences, desired information, real estate information, and even their emotional state. This allows for house designs that meet the diverse needs of users. The specific processing flow in Example 3 will be explained using Figure 21.

[1614] Step 1:

[1615] Entering user information

[1616] The user uses their device to input information such as images saved from Instagram, family composition, desired housing location (within Tokyo), and budget (50 million yen).

[1617] Input: User preferences and desired information

[1618] Output: The entered information is saved to the device.

[1619] Specific action: The user enters information into the input form on the device and clicks the "Submit" button.

[1620] Step 2:

[1621] Data transmission and analysis

[1622] The terminal sends the entered information to the server.

[1623] Input: Information entered by the user

[1624] Output: User information sent to the server

[1625] Specific operation: The terminal uses an HTTP request to send the input data to the server.

[1626] The server analyzes the received information and inputs it as a prompt message into the generating AI model.

[1627] Input: User information sent from the device

[1628] Output: Prompt text to input to the generated AI model

[1629] Specific operation: The server analyzes the data and generates a prompt message like the following: "The user has saved an image of a modern exterior from Instagram, and they are looking for a detached house in Tokyo for a family of four, with a budget of 50 million yen. Please generate a blueprint based on this."

[1630] Step 3:

[1631] Design drawing generation

[1632] The server inputs prompt messages into the generated AI model and generates a blueprint.

[1633] Input: Prompt message

[1634] Output: Generated design data

[1635] Specific operation: The server sends prompt messages to the generated AI model (e.g., GPT-4) and receives blueprint data returned from the model.

[1636] The server uses information on land and buildings in Tokyo obtained from real estate information websites to suggest window orientations, sizes, floor plans, and other layouts.

[1637] Input: Information obtained from a real estate information website.

[1638] Output: Proposed window orientation and size, floor plan, etc.

[1639] Specific operation: The server uses an API to retrieve real estate information and reflects it in the design plans.

[1640] Step 4:

[1641] Emotion recognition and blueprint adjustment

[1642] The server uses an emotion engine to recognize the user's emotional state.

[1643] Input: User sentiment data

[1644] Output: Recognized emotional state

[1645] Specific operation: The server sends user emotion data to the emotion engine, which then analyzes the emotional state.

[1646] The server adjusts the blueprint based on the results of the emotion engine.

[1647] Input: Recognized emotional state

[1648] Output: Adjusted blueprint

[1649] Specific operation: The server receives the result from the emotion engine and generates a prompt message like this: "The user is happy to have a new job. Please generate blueprints for a luxurious house with large windows, a spacious living room, and high-quality interior materials."

[1650] Step 5:

[1651] Provision of design drawings

[1652] The server sends the generated blueprint to the user's terminal.

[1653] Input: Generated design drawing data

[1654] Output: Blueprint sent to the user terminal

[1655] Specific operation: The server sends the design data to the user's terminal as an HTTP response.

[1656] The terminal displays the received blueprints to the user.

[1657] Input: Design drawing data sent from the server

[1658] Output: Blueprint displayed to the user

[1659] Specific operation: The terminal analyzes the received design data and displays it on the user interface.

[1660] (Application Example 3)

[1661] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[1662] Conventional residential design systems struggled to automatically generate blueprints that reflected user preferences and desires, and their proposals based on real estate information were limited. Furthermore, they lacked the means to generate blueprints that considered the user's emotional state, or to visually confirm the generated blueprints as 3D models. As a result, it was difficult to increase user satisfaction.

[1663] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1664] In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for receiving the user's emotional state as input and automatically generating a house design based on this; and means for displaying the generated design as a 3D model. This enables the automatic generation of house design plans that reflect the user's preferences, desires, and emotional state, as well as visual confirmation.

[1665] "User preference information" refers to information about the designs and styles that users prefer, and is obtained from social media and image storage services.

[1666] "Desired information" refers to information about the conditions and specifications of a house that the user desires, including family structure, budget, and location.

[1667] "Real estate information" refers to information about land and buildings obtained from real estate information websites, including details such as price, area, and location.

[1668] "Emotional state" refers to information that indicates the user's current emotions and mood, including feelings such as joy and sadness.

[1669] A "design plan" is a drawing that shows the structure, layout, and design of a house, and is automatically generated based on the user's preferences, desires, real estate information, and emotional state.

[1670] A "3D model" is a three-dimensional visual model created based on design drawings, allowing users to view the exterior and interior of a house in three dimensions.

[1671] "Automatic generation" refers to the process by which a system automatically creates design drawings and 3D models based on user input and acquired data.

[1672] A "proposal" is the act of showing the user specific features of a house, such as the orientation and size of windows and the floor plan, based on the generated design drawings.

[1673] The system for implementing this invention automatically generates a house design based on the user's preferences, desires, real estate information, and emotional state, and displays it as a 3D model. A specific embodiment is shown below.

[1674] System Configuration

[1675] The system consists of user terminals, a server, and a display device. User terminals include smartphones and head-mounted displays (HMDs). The server performs data processing and automatically generates design drawings using a generational AI model. The display device is used to display the generated design drawings as 3D models.

[1676] Hardware and software to be used

[1677] Hardware: Smartphones, head-mounted displays (HMDs), servers

[1678] Software: Python, OpenAI API, 3D modeling libraries

[1679] Data processing and data calculation

[1680] 1. Receiving user input:

[1681] The user terminal receives user preference information (e.g., images obtained from social media), desired information (e.g., family structure, budget, location), and emotional state (e.g., joy or sadness) as input.

[1682] 2. Obtaining real estate information:

[1683] The server retrieves information about land and buildings in Tokyo from real estate information websites. This includes details such as price, area, and location.

[1684] 3. Automatic generation of blueprints:

[1685] The server uses a generative AI model (e.g., OpenAI's GPT-3) to automatically generate house blueprints based on user input and acquired real estate information. An example of a prompt message for the generative AI model is as follows:

[1686] User input: {'image': 'modern_house_image.jpg', 'family_size': 4, 'location': 'Tokyo', 'budget': 5000, 'emotion': 'happy'}

[1687] Real estate data: {'Land information': '...', 'Building information': '...'}

[1688] Please generate the blueprints.

[1689] 4. Creating and displaying 3D models:

[1690] The server creates a 3D model using a 3D modeling library based on the generated blueprints. The created 3D model is then displayed on the user's device (smartphone or HMD).

[1691] Specific example

[1692] If a user provides an image of a modern exterior saved from Instagram, enters that they are a family of four looking for a detached house in Tokyo with a budget of 50 million yen, the server will automatically generate a blueprint for a modern-looking detached house in Tokyo based on this information. Furthermore, when a user is feeling happy about getting a new job, the emotion engine recognizes that happiness and automatically generates a blueprint for a luxurious home. This blueprint will feature large windows, a spacious living room, and high-quality interior materials.

[1693] In this way, it becomes possible to automatically generate and visually confirm house designs that reflect the user's preferences, desires, and emotional state.

[1694] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[1695] Step 1:

[1696] Users input their preferences (e.g., images from social media), desired information (e.g., family structure, budget, location), and emotional state (e.g., joy or sadness) using a smartphone or head-mounted display (HMD).

[1697] Input: User preferences, desires, and emotional state.

[1698] Output: User input data

[1699] Specific action: The user enters information into the application's input form and presses the submit button.

[1700] Step 2:

[1701] The server retrieves information about land and buildings in Tokyo from real estate information websites.

[1702] Input: User's desired information (e.g., location)

[1703] Output: Real estate information data

[1704] Specific operation: The server uses an API to send requests to real estate information websites and retrieve the necessary data.

[1705] Step 3:

[1706] The server uses a generated AI model (e.g., OpenAI's GPT-3) to automatically generate house blueprints based on user input and acquired real estate information.

[1707] Input: User input data, real estate information data

[1708] Output: House design drawing data

[1709] Specific operation: The server sends prompt messages to the generated AI model to generate the blueprint. An example of a prompt message is as follows:

[1710] User input: {'image': 'modern_house_image.jpg', 'family_size': 4, 'location': 'Tokyo', 'budget': 5000, 'emotion': 'happy'}

[1711] Real estate data: {'Land information': '...', 'Building information': '...'}

[1712] Please generate the blueprints.

[1713] Step 4:

[1714] The server creates a 3D model using a 3D modeling library based on the generated blueprint.

[1715] Input: House design drawing data

[1716] Output: 3D model data

[1717] Specific operation: The server inputs design data into the 3D modeling library and generates a 3D model.

[1718] Step 5:

[1719] The server sends the generated 3D model to the user's terminal, and the user's terminal displays it.

[1720] Input: 3D model data

[1721] Output: 3D model displayed on the user's terminal

[1722] Specific operation: The server sends 3D model data to the user's terminal, and the user's terminal displays it on a display device (smartphone or HMD).

[1723] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1724] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1725] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[1726] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1727] [Third Embodiment]

[1728] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1729] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1730] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1731] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1732] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1733] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1734] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1735] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1736] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1737] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1738] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1739] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[1740] "Example of form 1"

[1741] In one embodiment of the system, a user saves images of their preferred homes from social media such as Instagram and inputs the image information into the system. The user also inputs information about their family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment. Based on this preference and desired information, the system automatically generates a blueprint for the home.

[1742] "Example of form 2"

[1743] Furthermore, this system acquires land and building information from real estate information websites and automatically generates house designs based on this information. Specifically, it proposes window orientations, sizes, floor plans, etc., taking into account the shape of the land and building, location conditions, etc.

[1744] "Example of form 3"

[1745] For example, if a user inputs an image of a modern exterior saved from Instagram, along with information such as being a family of four, wanting a detached house in Tokyo, and having a budget of 50 million yen, the system will automatically generate a blueprint for a detached house in Tokyo with a modern exterior based on this information. Furthermore, it will suggest window orientations, sizes, floor plans, etc., based on land and building information in Tokyo obtained from real estate information websites.

[1746] The following describes the processing flow for each example of the form.

[1747] "Example of form 1"

[1748] Step 1: The user saves images of their favorite houses from social media such as Instagram.

[1749] Step 2: The user inputs the saved image information into this system.

[1750] Step 3: The user enters their desired information into the system, including their family structure, preferred address, price range, whether or not they want renovations, and whether they want a house or an apartment.

[1751] Step 4: This system automatically generates house plans based on these preference and desired information.

[1752] "Example of form 2"

[1753] Step 1: This system obtains land and building information from real estate information websites.

[1754] Step 2: This system automatically generates house plans based on the acquired land and building information. Specifically, it proposes window orientations, sizes, floor plans, etc., taking into account the shape of the land and building, location conditions, etc.

[1755] "Example of form 3"

[1756] Step 1: The user enters images of modern exteriors saved from Instagram, along with information such as being a family of four, wanting a detached house in Tokyo, and having a budget of 50 million yen.

[1757] Step 2: Based on this information, the system automatically generates a blueprint for a modern-looking detached house in Tokyo.

[1758] Step 3: This system uses land and building information in Tokyo obtained from real estate information websites to suggest window orientations, sizes, floor plans, etc.

[1759] (Example 1)

[1760] Next, we will describe Embodiment 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1761] Conventional housing design systems have struggled to automatically generate blueprints that reflect the user's preferences and desires. Furthermore, a lack of effective means to utilize image information obtained from social media meant that the user's specific preferences could not be reflected in the design. Additionally, when proposing housing designs based on the generated blueprints, it was difficult to provide proposals that matched the user's wishes.

[1762] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design drawing based on this information, means for receiving image information saved by the user as input and analyzing this information to identify the user's preferences, means for generating and inputting prompt sentences to the generation AI model, and means for making house proposals based on the generated design drawing. This makes it possible to automatically generate a house design drawing that reflects the user's specific preferences and desires, and to make house proposals that match the user's desires.

[1763] "User preference information" refers to information about the housing designs and styles that users prefer, and includes images and text data obtained from social media.

[1764] "Desired information" refers to the specific conditions and requirements that the user desires regarding housing, including information such as family structure, desired address, price range, whether renovations are planned, and whether it is a detached house or an apartment.

[1765] "Image information" refers to image data of houses that users obtain from social media or other sources and upload to the system.

[1766] A "generative AI model" is an artificial intelligence model that automatically generates house blueprints based on user preferences and desired information, and utilizes natural language processing and image analysis technologies.

[1767] A "prompt message" is an instruction given to the AI ​​generation model, and it is generated based on the user's preferences and desired information.

[1768] A "house design plan" is a design drawing of a house generated based on the user's preferences and desired information, and includes specific layouts and designs.

[1769] A "housing proposal" is a proposal made to a user based on the generated housing blueprints, and includes content that matches the user's wishes.

[1770] This invention is based on the premise that users save images of their preferred homes from social media such as Instagram and input that image information into the system. Users also input their family structure, desired address, price range, whether or not they want renovations, and whether they want a house or an apartment. Based on this information, the system automatically generates a blueprint for the house.

[1771] Hardware and software to be used

[1772] The server receives image information and request information entered by the user and stores it in a database. Specifically, it uses the following hardware and software:

[1773] Server: High-performance cloud server (e.g., Amazon Web Services, Google Cloud Platform)

[1774] Database: Relational database (e.g., MySQL, PostgreSQL)

[1775] Generative AI models: AI models that utilize natural language processing and image analysis techniques (e.g., OpenAI's GPT-4, DALL-E)

[1776] Image analysis software: Computer vision technology (e.g., TensorFlow, PyTorch)

[1777] Data processing and data calculation

[1778] The server receives image files uploaded by the user and requested information, and stores this data in a database. Based on the stored data, it generates prompt messages for the AI ​​model and inputs them. The AI ​​model generates house blueprints based on the prompt messages and provides them to the user via the server.

[1779] Specific example

[1780] As a concrete example, suppose a user saves an image of a modern-designed house from Instagram and enters the following desired information:

[1781] Family composition: 4 people (2 adults, 2 children)

[1782] Desired address: Tokyo

[1783] Price range: Under 50 million yen

[1784] Renovation status: Yes

[1785] House or apartment: House

[1786] Based on this information, the server inputs the following prompt message into the AI ​​model:

[1787] Based on images of modern-designed homes saved by the user from Instagram, please generate blueprints for a home that matches the following requirements.

[1788] Family composition: 4 people (2 adults, 2 children)

[1789] Desired address: Tokyo

[1790] Price range: Under 50 million yen

[1791] Renovation status: Yes

[1792] House or apartment: House

[1793] Based on this prompt, the generation AI model generates a house design that meets the user's preferences and provides it to the user via the server. The user can review the received design on their device and, if necessary, modify their preferences to generate a new design.

[1794] In this way, it becomes possible to automatically generate house designs that reflect the user's specific preferences and desires, and to propose houses that match the user's wishes.

[1795] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1796] Step 1:

[1797] Users save images of their favorite houses from social media such as Instagram. Users use their smartphones or computers to find and save images of their favorite houses from social media such as Instagram. The input is image data obtained from social media, and the output is an image file saved on the user's device.

[1798] Step 2:

[1799] The user uploads saved images to the system. The user accesses the system's website or application and uploads saved images of their home. Specifically, they click an upload button and select the saved image file. The input is the image file stored on the user's device, and the output is the image data sent to the server.

[1800] Step 3:

[1801] The user enters their desired information, such as family structure, preferred address, price range, whether renovations are needed, and whether they want a house or an apartment. The user enters their desired information into the system's input form, such as family structure (e.g., 2 adults, 2 children), preferred address (e.g., Tokyo), price range (e.g., under 50 million yen), whether renovations are needed (e.g., yes), and whether they want a house or an apartment (e.g., house). The input is the desired information entered by the user, and the output is the desired information sent to the server.

[1802] Step 4:

[1803] The server receives image information and request information from the user and stores it in the database. The server receives uploaded image files and input request information from the user and stores this data in the database. When saving, the data is managed in association with the user ID. The input is the image information and request information sent by the user, and the output is the data stored in the database.

[1804] Step 5:

[1805] The server generates prompt messages for the AI ​​model based on the stored data and inputs them. The server generates prompt messages to input to the AI ​​model based on image information and desired information stored in the database. For example, it generates prompt messages like the following:

[1806] Based on images of modern-designed homes saved by the user from Instagram, please generate blueprints for a home that matches the following requirements.

[1807] Family composition: 4 people (2 adults, 2 children)

[1808] Desired address: Tokyo

[1809] Price range: Under 50 million yen

[1810] Renovation status: Yes

[1811] House or apartment: House

[1812] The input consists of image information and desired information stored in a database, and the output is a prompt message that is input to the generating AI model.

[1813] Step 6:

[1814] A generative AI model generates a house design based on prompt text. The generative AI model (e.g., OpenAI's GPT-4 or DALL-E) generates a house design based on prompt text sent from the server. The generative AI model utilizes image analysis and natural language processing techniques to create a design that meets the user's needs. The input is prompt text, and the output is the generated house design.

[1815] Step 7:

[1816] The server sends the generated blueprint to the user's terminal. The server sends the blueprint received from the generated AI model to the user's terminal. The user can download or view the blueprint through the system's website or application. The input is the generated house blueprint, and the output is the blueprint sent to the user's terminal.

[1817] Step 8:

[1818] The user reviews the blueprint. The user reviews the blueprint received on their device. They can check if the blueprint meets their requirements and, if necessary, modify the required information to generate a new blueprint. The input is the blueprint sent to the user's device, and the output is the user's review result.

[1819] (Application Example 1)

[1820] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1821] Conventional home design systems struggled to automatically generate blueprints that reflected users' preferences and desires. In particular, if a user had a specific image in mind, specialized knowledge was required to translate that image into a blueprint. Furthermore, real-time blueprint generation and display were difficult when users viewed home designs in physical showrooms. This led to decreased user satisfaction and delays in home purchase decisions.

[1822] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1823] This invention includes a server that receives user preference information and desired information as input and automatically generates a house design based on this information; a server that receives real estate information as input and automatically generates a house design based on this information; a server that makes house proposals based on the generated design; a server that analyzes a house image taken by the user and extracts its features; a server that generates prompt text based on the extracted features and the user's desired information and generates a house design using a generation AI model; and a server that presents the generated design to the user through a display device. This enables the generation of a house design that reflects the user's specific image in real time and allows for verification at a physical store.

[1824] "User preference information" refers to information that indicates a user's personal preferences and design tastes regarding housing.

[1825] "Desired information" refers to information that indicates the specific requests and conditions that the user has regarding housing (family structure, desired address, price range, whether or not renovations are planned, whether it's a detached house or an apartment, etc.).

[1826] "Real estate information" refers to information that provides detailed data about a real estate property (location, price, floor plan, year built, etc.).

[1827] A "house design drawing" is a diagram that specifically shows the structure, layout, and design of a house.

[1828] "Means of automatic generation" refers to devices or programs that have the function of automatically creating design drawings using algorithms or AI models based on input information.

[1829] "Means of making proposals" refers to devices or programs that have the function of making housing proposals to users based on the generated blueprints.

[1830] "House images" refer to photographs or image data of houses taken by users.

[1831] "Means of analysis" refers to devices or programs that have the function of analyzing input image data and extracting its features.

[1832] "Means for extracting features" refer to devices or programs that have the function of extracting important features from data obtained through image analysis.

[1833] A "prompt statement" is a text-based input statement used to give instructions to a generative AI model.

[1834] A "generative AI model" is an artificial intelligence model that generates blueprints and other data based on input prompts.

[1835] A "display device" is a device (such as a display or VR headset) used to visually present a generated design to a user.

[1836] A system for carrying out this invention includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for analyzing a house image taken by the user and extracting its features; means for generating prompt sentences based on the extracted features and the user's desired information and generating a house design using a generation AI model; and means for presenting the generated design to the user through a display device.

[1837] Hardware and software to use

[1838] hardware

[1839] Smartphone or tablet (iOS or Android): Used by the user to take pictures of the house and input information.

[1840] Smart glasses (e.g., Google Glass): Used to analyze images taken by the user in real time.

[1841] Large screen display or VR headset (e.g., Oculus Rift): Used to present the generated blueprints to the user.

[1842] software

[1843] Image recognition libraries (e.g., OpenCV): Used to analyze residential images taken by the user and extract their features.

[1844] Generative AI models (e.g., GPT-4, DALL-E): Used to generate house blueprints based on prompt statements.

[1845] Database (e.g., Firebase): Used to store and manage user preferences, requests, and property information.

[1846] Frontend frameworks (e.g., React Native): Used to build user interfaces.

[1847] Processing flow

[1848] 1. User input

[1849] Users use their smartphones or tablets to take pictures of their preferred homes and upload them to the application. They also enter information such as family size, desired address, price range, whether renovations are needed, and whether they want a house or an apartment.

[1850] 2. Image Analysis

[1851] The server uses an image recognition library (OpenCV) to analyze uploaded images of houses and extract their features.

[1852] 3. Generating prompt statements

[1853] The server generates prompt messages for the generative AI model (GPT-4) based on the extracted features and user preferences.

[1854] Example of a prompt

[1855] Based on the images and desired information provided by the user, please generate a blueprint for a house that meets the following conditions:

[1856] Family composition: 4 people

[1857] Desired address: Tokyo

[1858] Price range: Under 50 million yen

[1859] Renovation: Yes

[1860] Detached house

[1861] Modern design

[1862] 4. Generating blueprints

[1863] The server uses a generative AI model (DALL-E) to generate house blueprints based on prompt messages.

[1864] 5. Displaying the results

[1865] The generated blueprints are presented to the user via a large screen display or VR headset. Users can then view their ideal home design in real time at a physical store.

[1866] Specific example

[1867] For example, a user uploads an image of a modern living room taken with their smartphone and enters their desired information as "Family composition: 4 people, Desired address: Tokyo, Price range: under 50 million yen, Renovation: Yes, Detached house." Based on this information, the server generates a blueprint for a modern detached house in Tokyo that is under 50 million yen, suitable for a family of four, and allows for renovation, and presents it to the user.

[1868] In this way, users can check their ideal home design in real time at a physical store.

[1869] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1870] Step 1:

[1871] Users use their smartphones or tablets to take pictures of their preferred homes and upload them to the application. They also enter information such as family size, desired address, price range, whether renovations are needed, and whether they want a house or an apartment.

[1872] Input: Housing images, family composition, desired address, price range, whether renovation is needed, desired type of housing (house or apartment), etc.

[1873] Output: Uploaded house images and desired information

[1874] Step 2:

[1875] The server uses an image recognition library (OpenCV) to analyze uploaded images of houses and extract their features.

[1876] Input: Uploaded house images

[1877] Output: Extracted image features

[1878] Specific operation: Using an image recognition library, perform edge detection and color analysis on residential images and extract features.

[1879] Step 3:

[1880] The server generates prompt messages for the generative AI model (GPT-4) based on the extracted features and user preferences.

[1881] Input: Extracted image features, desired information

[1882] Output: Generated prompt message

[1883] Specific operation: Combine the extracted features and desired information to create prompt sentences for input into the generating AI model.

[1884] Step 4:

[1885] The server uses a generative AI model (DALL-E) to generate house blueprints based on prompt messages.

[1886] Input: Generated prompt message

[1887] Output: Generated house blueprints

[1888] Specific operation: Input prompt text into the generation AI model and generate a blueprint for a house.

[1889] Step 5:

[1890] The server presents the generated blueprints to the user via a large screen display or VR headset.

[1891] Input: Generated house blueprints

[1892] Output: Design drawings presented to the user

[1893] Specific operation: The generated design drawings are sent to a display or VR headset so that the user can visually confirm them.

[1894] In this way, users can check their ideal home design in real time at a physical store.

[1895] (Example 2)

[1896] Next, we will describe Example 2 of the Form Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1897] Conventional residential design systems had the problem of requiring a great deal of time and effort to reflect the user's preferences and desired information. Furthermore, it was difficult to efficiently acquire real estate information and automatically generate optimal residential designs based on it. As a result, it was difficult to quickly provide residential designs that satisfied users.

[1898] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1899] In this invention, the server includes means for acquiring land and building information from a real estate information provision site, means for storing the acquired information in a data frame and processing the data, means for generating prompt sentences to be input to a generation AI model based on the processed data, means for automatically generating house blueprints using the generation AI model, and means for making house proposals based on the generated blueprints. This makes it possible to quickly and efficiently provide house blueprints that reflect the user's preferences and desired information.

[1900] A "real estate information website" is a website that provides information about land and buildings.

[1901] "Land and building information" refers to detailed data such as the shape of the land, the location of the building, the direction and size of the windows, and the floor plan.

[1902] A "data frame" is a two-dimensional data structure consisting of rows and columns, used for storing and processing data.

[1903] "Data processing" is the process of transforming acquired data into a format that is easy to analyze and use, and includes processes such as imputing missing values ​​and normalizing data.

[1904] A "generative AI model" is a model that uses artificial intelligence to perform a specific task, and in this case, it is used to automatically generate blueprints for a house.

[1905] A "prompt message" is an instruction message used to input into a generation AI model, and it is generated based on information about the land and buildings.

[1906] "House design drawings" are diagrams that show the layout and structure of a house, and they form the basis of the building plan.

[1907] A "housing proposal" refers to a suggestion made to the user regarding the design and layout of a house, based on the generated blueprints.

[1908] Modes for carrying out the invention

[1909] This invention relates to a system that obtains land and building information from real estate information websites and automatically generates house blueprints based on this information. A specific embodiment of this system is described below.

[1910] 1. Program generation

[1911] The server generates a program to retrieve land and building information from real estate information websites. This program is developed using Python and performs web scraping using libraries such as BeautifulSoup and Selenium.

[1912] 2. Data acquisition and processing

[1913] The server executes the generated program and retrieves land and building information from real estate information websites. Specifically, it collects data such as land shape, building location, window orientation and size, and floor plan. The collected data is stored in a dataframe using the Pandas library, and necessary data processing is performed. For example, missing values ​​are imputed and data normalization is performed.

[1914] 3. Generating prompt sentences for the generative AI model

[1915] The server generates prompt statements to input into the AI ​​model based on the processed data. These prompt statements include information such as the shape of the land and building, location conditions, window orientation, size, and floor plan.

[1916] Example of a prompt:

[1917] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[1918] Land shape: Rectangle

[1919] Building location: South-facing

[1920] Window orientation: South-facing

[1921] Window size: Large

[1922] Floor plan: 3LDK

[1923] 4. Generating house design plans

[1924] The server inputs the generated prompt text into a generation AI model (for example, a generation AI model) and generates a blueprint for a house. The generation AI model then proposes the optimal blueprint based on the prompt text.

[1925] 5. Displaying the results

[1926] The server displays the generated house design plans on the user's terminal. The user can review the proposed design plans and request revisions as needed.

[1927] Specific example

[1928] If a user requests to "generate a house design based on land information in Shibuya Ward, Tokyo," the server will input the following prompt into the AI ​​model.

[1929] Example of a prompt:

[1930] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[1931] Land shape: Rectangle

[1932] Building location: South-facing

[1933] Window orientation: South-facing

[1934] Window size: Large

[1935] Floor plan: 3LDK

[1936] The AI ​​model generates a house design based on this prompt. The proposed design is displayed on the device for the user to review.

[1937] In this way, the present invention makes it possible to quickly and efficiently provide residential design plans that reflect the user's preferences and desired information.

[1938] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1939] Program processing flow

[1940] Step 1: Obtaining real estate information

[1941] The server retrieves land and building information from real estate information websites. Specifically, it uses Python and libraries such as BeautifulSoup and Selenium to perform web scraping.

[1942] Input: URL of the real estate information website

[1943] Output: Land and building information (e.g., land shape, building location, window orientation, size, floor plan)

[1944] Specific actions:

[1945] The server uses Selenium to automate browser operations and access a specified URL. Next, it uses BeautifulSoup to parse the HTML and extract the necessary information.

[1946] Step 2: Processing of the oars

[1947] The server stores the acquired real estate information in a dataframe using the Pandas library and performs necessary data processing, such as imputing missing values ​​and normalizing the data.

[1948] Input: Land and building information

[1949] Output: Processed data frame

[1950] Specific actions:

[1951] The server converts the retrieved data into a DataFrame using the Pandas read_html function. Next, it imputes missing values ​​using the fillna function and normalizes the data with the normalize function.

[1952] Step 3: Generating prompts for the generative AI model

[1953] The server generates prompt statements to input into the AI ​​model based on the processed data. These prompt statements include information such as the shape of the land and building, location conditions, window orientation, size, and floor plan.

[1954] Input: Processed data frame

[1955] Output: Prompt message

[1956] Specific actions:

[1957] The server extracts the necessary information from the data frame and generates a prompt message like the following:

[1958] Based on land information in Shibuya Ward, Tokyo, please generate a house design plan considering the following conditions.

[1959] Land shape: Rectangle

[1960] Building location: South-facing

[1961] Window orientation: South-facing

[1962] Window size: Large

[1963] Floor plan: 3LDK

[1964] Step 4: Generating the house design plans

[1965] The server inputs the generated prompt text into a generation AI model (for example, a generation AI model) and generates a blueprint for a house. The generation AI model then proposes the optimal blueprint based on the prompt text.

[1966] Input: Prompt message

[1967] Output: House blueprints

[1968] Specific actions:

[1969] The server sends prompts to the API for generating AI models and receives blueprint suggestions in return. For example, it sends prompts using the openai.Completion.create function.

[1970] Step 5: Displaying the results

[1971] The server displays the generated house design plans on the user's terminal. The user can review the proposed design plans and request revisions as needed.

[1972] Input: House blueprints

[1973] Output: Blueprint displayed on the user's terminal

[1974] Specific actions:

[1975] The server formats the generated blueprint in HTML format and sends it to the user's terminal. The user then views the blueprint through their browser.

[1976] (Application Example 2)

[1977] Next, we will describe application example 2 of form 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."

[1978] Conventional residential design systems have difficulty reflecting user preferences and desires, and the automatic generation of design plans based on real estate information has been limited. Furthermore, interior design for physical stores requires specialized knowledge and is not easily accessible to the average user. Therefore, there is a need for a system that allows users to easily design homes and stores that meet their specific needs.

[1979] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user preference information and desired information as input and automatically generating a house design based on this information; means for receiving real estate information as input and automatically generating a house design based on this information; means for making house proposals based on the generated design; means for automatically generating interior designs for physical stores based on information obtained from real estate information provision sites; means for creating prompt statements for generating design drawings using a generation AI model; and means for generating actual design drawings using a generation AI model. This makes it possible for users to easily design houses and stores that suit their preferences.

[1980] "User preference information" refers to information about the style, functions, and design that users desire when designing houses or shops.

[1981] "Desired information" refers to information about the specific conditions and requirements that users have in mind when designing houses or shops.

[1982] "Real estate information" refers to information about the shape, location, and area of ​​land and buildings.

[1983] A "design drawing" is a diagram that shows the layout of a house or shop, the direction and size of windows, the interior design, and so on.

[1984] A "real estate information website" is a website that provides information about land and buildings on the internet.

[1985] "Interior design" refers to planning the layout and design of the interior spaces of shops and residences.

[1986] A "generative AI model" is an algorithm or program that uses artificial intelligence to automatically generate blueprints and designs.

[1987] A "prompt statement" is an instruction statement used to input into a generative AI model, and it is a sentence that includes conditions and requirements for generating blueprints or designs.

[1988] A system for carrying out this invention includes a server, a user terminal, and a generated AI model. Specific embodiments of this system are described below.

[1989] First, the user terminal receives user preference and desired information as input. This information concerns the style, functions, and design the user desires for the design of their home or store. The user terminal then sends this information to the server.

[1990] Next, the server retrieves real estate information from a real estate information website. This real estate information includes the shape of the land and building, location conditions, and area. Based on the retrieved real estate information, the server automatically generates blueprints for houses and shops.

[1991] The server uses a generative AI model to create prompt statements for generating blueprints. These prompt statements include user preference information, desired information, and real estate information. For example, prompt statements like the following are generated:

[1992] "Land shape: Rectangle, Location: Urban area, Window orientation: South-facing, Lighting position: Center of ceiling"

[1993] Based on the generated prompt text, the generative AI model generates the actual design drawing. For example, OpenAI's GPT-3 is used as the generative AI model. This model takes the prompt text as input and outputs the design drawing.

[1994] The generated blueprints are sent from the server to the user's terminal and presented to the user. Based on the presented blueprints, the user can review the design of the house or store and make modifications as needed.

[1995] This system allows users to easily design houses and shops that meet their specific needs. Specifically, users can easily generate and review design plans using their smartphones or computers. This enables them to realize their desired designs even without specialized knowledge.

[1996] The above describes specific embodiments for carrying out this invention.

[1997] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1998] Step 1:

[1999] The user terminal receives user preference and desired information as input. Users use smartphones or computers to input information about their desired style, function, and design for residential or commercial buildings. The entered information is stored on the user terminal.

[2000] Step 2:

[2001] The user terminal sends the entered preference and desired information to the server. The transmitted information is stored in a database on the server.

[2002] Step 3:

[2003] The server retrieves real estate information from real estate information websites. The server uses an API to send requests to these websites, obtaining information such as the shape, location, and area of ​​the land and buildings. The retrieved real estate information is then stored on the server.

[2004] Step 4:

[2005] The server generates prompt statements to create a blueprint based on acquired real estate information and user preferences and requests. These prompt statements include information such as the shape of the land, location, window orientation, and lighting position. For example, a prompt statement like "Land shape: Rectangle, Location: Urban area, Window orientation: South-facing, Lighting position: Center of ceiling" might be generated.

[2006] Step 5:

[2007] The server uses a generative AI model to take prompt text as input and generate a blueprint. For example, OpenAI's GPT-3 is used as the generative AI model. The generative AI model, upon receiving prompt text as input, outputs a blueprint. The generated blueprint is then saved to the server.

[2008] Step 6:

[2009] The server sends the generated blueprint to the user's terminal. The user's terminal displays the received blueprint to the user. The user can then view the blueprint on their smartphone or computer screen.

[2010] Step 7:

[2011] Users can review the provided blueprints for houses and shops and make modifications as needed. The modified information is sent back to the server, and the blueprints are regenerated. This allows users to realize a design that meets their needs.

[2012] (Example 3)

[2013] Next, we will describe Embodiment 3 of Embodiment Example 3. 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."

[2014] Conventional residential design systems have difficulty automatically generating blueprints that reflect user preferences and desires, and have been unable to provide optimal design proposals based on real estate information. Therefore, there is a need to efficiently provide residential designs that meet user needs.

[2015] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[2016] This i...

Claims

1. A means for analyzing a residential image uploaded by a user using image recognition and extracting features; a prompt generation means for generating a specific prompt sentence based on the extracted features and the user's desired information; A generation means that, by inputting the aforementioned specific prompt sentence into a generation AI model, automatically generates a design drawing of the house based on user housing-related information, including the user's preferred housing design, style, and conditions, and real estate information. A means for proposing the house based on the generated design drawings, The emotion engine that recognizes the user's emotions, A means for adjusting the interior and floor plan included in the design drawings of the house based on the aforementioned emotions, A means for displaying the adjusted design drawing using a virtual reality display device, A system that includes this.

2. The system according to claim 1, wherein the generation means acquires the user's housing-related information obtained by the user from social media.

3. The system according to claim 1, wherein the generation means obtains the real estate information from a real estate information provision site.

Images