System

Abstract

A system is provided.SOLUTION: The system includes a means for allowing a user to create an ideal floor plan, a means for reading a floor plan image close to the ideal, a means for analyzing the ideal floor plan or the read floor plan image to extract rooms and facility conditions, a means for acquiring similar rental property information from a database on the basis of the conditions, and a means for displaying the acquired rental property information to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] For those who are looking for a residential rental property but are having difficulty finding one with their ideal floor plan, or those who want to renovate a used property they plan to purchase or a property they currently live in but are unsure how close they can get to their ideal floor plan, it is difficult to efficiently find their ideal property or renovation plan. For this reason, there is a demand for a system that allows users to easily create their ideal floor plan, analyze existing floor plans to obtain information on similar properties, and propose realistic renovation plans. [Means for solving the problem]

[0005] The present invention provides a system including the following means.

[0006] The system includes a means for a user to create an ideal floor plan, a means for loading an image of a floor plan that is close to the ideal, a means for analyzing the ideal floor plan or the loaded floor plan image to extract room and facility conditions, a means for acquiring similar rental property information from a database based on the conditions, and a means for displaying the acquired rental property information to the user, allowing the user to efficiently obtain information on the ideal rental property.

[0007] Furthermore, the system includes means for reading the floor plan of a property to be purchased or currently occupied, means for generating a realistically possible renovation plan based on the floor plan of the property and an ideal floor plan, means for rendering the generated renovation plan as a three-dimensional image, means for the user to check the three-dimensional image and provide feedback, and means for regenerating and updating the renovation plan based on the feedback, so that the user can be given a specific proposal of a renovation plan that is close to their ideal, allowing them to smoothly proceed with subsequent decision-making.

[0008] Furthermore, the system includes a means for generating and displaying an image of the interior and furniture layout as a three-dimensional image in an ideal floor plan or renovation plan, allowing the user to visually enhance the image of the final home and make a satisfactory selection.

[0009] "User" refers to the entity that operates the system, creates ideal floor plans, provides property information, and receives proposals for renovation plans.

[0010] "Terminal" refers to a device such as a computer, smartphone, or tablet operated by a user, which acts as an interface with the system.

[0011] "Server" refers to a remote computer system that accepts information sent by users and provides functionality such as analysis, processing, database lookup, and rendering.

[0012] A "floor plan" refers to a drawing that shows the layout, size, and location of facilities in a house.

[0013] "Room and facility conditions" refers to specific attributes related to the layout of the home, such as the purpose and size of each room, and the location and type of facilities.

[0014] "Rental property information" refers to detailed information about a rental property, including floor plan, rent, location, facilities, etc.

[0015] A "renovation plan" refers to specific designs and proposals for renovating and improving the current floor plan and bringing it closer to the ideal state.

[0016] "Three-dimensional image" refers to the three-dimensional model display generated on the system, which allows users to visually check the layout and interior of a room.

[0017] "Feedback" refers to opinions, requests, and instructions for corrections that users give to the system.

[0018] "Database" refers to a collection of information that stores information on rental properties and renovations in an organized manner and manages it in a searchable and usable format.

[0019] "Analysis" refers to the process of identifying rooms and equipment conditions from the input floor plan and extracting the necessary information.

[0020] "Rendering" refers to the process of generating three-dimensional images based on designed renovation plans and floor plans.

[0021] "Interior and furniture" refers to the elements that make up the living space, such as the decorations, equipment, and furniture arrangement inside the home. [Brief explanation of the drawings]

[0022] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2]1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0023] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0024] First, the terms used in the following description will be explained.

[0025] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0026] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0027] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0028] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0029] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0033] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0034] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0035] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0036] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0037] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0040] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0041] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0042] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0043] The system of the present invention allows users to create their ideal floor plan or load an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring a property they are planning to purchase or currently living in closer to their ideal floor plan.

[0044] Overall system overview

[0045] The system consists of three main components: the user, the terminal, and the server. The user mainly operates the terminal, and the server performs data analysis and plan generation in the backend.

[0046] User-created and imported floor plans

[0047] 1. User: Create your ideal floor plan through the system's UI, which features drag-and-drop functionality, allowing you to intuitively manipulate the layout and size of rooms.

[0048] 2. Terminal: Captures the floor plan created by the user and sends it to the server. Users can also upload images of existing floor plans.

[0049] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[0050] Providing information on similar rental properties

[0051] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[0052] 5. Terminal: The user checks the list of similar rental properties sent from the server and displays detailed information (e.g., floor plan, rent, address).

[0053] Renovation plan proposal

[0054] 6. User: Upload floor plans of properties you currently live in or are considering purchasing.

[0055] 7. Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. It then generates a realistic renovation plan, which typically includes specific modifications such as removing walls or adding new rooms.

[0056] 8. Server: The generated renovation plan is rendered as a 3D image, generating a concrete image including the interior and furniture layout.

[0057] Review and feedback on the proposed plan

[0058] 9. Terminal: The user can view a 3D image of the proposed renovation plan, including details such as the interior design, furniture layout, and room color scheme.

[0059] 10. User: Provides feedback and sends specific requests to the server, such as "I want to change the color of the walls" or "Can I rearrange this furniture?"

[0060] 11. Server: Receive feedback, re-render, and update / re-propose the renovation plan.

[0061] 12. Device: Redisplay the updated plan to the user for final confirmation.

[0062] Specific examples

[0063] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[0064] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout.

[0065] If the user checks the 3D image and sends feedback that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again, thus finally providing the user with a satisfactory renovation plan.

[0066] The present invention provides a method that allows users to efficiently realize their ideal floor plan using such a system.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] Users can create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing intuitive placement and size of the devices. It is also possible to upload an image of an existing floor plan.

[0070] Step 2:

[0071] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[0072] Step 3:

[0073] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[0074] Step 4:

[0075] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[0076] Step 5:

[0077] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[0078] Step 6:

[0079] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[0080] Step 7:

[0081] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[0082] Step 8:

[0083] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[0084] Step 9:

[0085] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[0086] Step 10:

[0087] The server renders the generated renovation plan as a 3D image, allowing users to visualize the layout of furniture and interior décor in concrete terms.

[0088] Step 11:

[0089] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[0090] Step 12:

[0091] The user sends feedback about the renovation plan to the server via their device, for example, by inputting requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[0092] Step 13:

[0093] Based on the feedback received by the server, the renovation plan is regenerated and updated, for example by re-rendering a plan with a different wall color.

[0094] Step 14:

[0095] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[0096] This process allows users to efficiently find their ideal rental property and also obtain specific renovation plans to bring the layout closer to their ideal one.

[0097] Example 1

[0098] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0099] Conventional floor plan creation and analysis systems have the drawback of requiring a lot of time and effort when users create their ideal floor plan or obtain rental property information and renovation plans based on existing floor plans. Furthermore, when proposing renovation plans, the system lacks the technology to flexibly update plans based on user feedback, resulting in an unsatisfactory user experience.

[0100] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0101] In this invention, the server includes: means for allowing a user to create an ideal floor plan; means for loading an image of a floor plan close to the ideal; means for analyzing the ideal floor plan or the loaded floor plan image to extract room and equipment conditions; means for retrieving similar rental property information from a database based on the conditions; means for displaying the retrieved rental property information to the user; means for receiving feedback from the user; means for updating the proposal based on the feedback; means for generating and displaying a 3D image of the proposed interior and furniture arrangement; means for loading a floor plan of a property to be purchased or currently occupied; means for generating a realistically feasible renovation plan based on the floor plan of the property and the ideal floor plan; means for rendering the generated renovation plan as a 3D image; means for the user to review the 3D image and provide feedback; and means for regenerating and updating the renovation plan based on the feedback. This enables users to intuitively and efficiently create their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[0102] 1. An "ideal floor plan" is a drawing that reflects the user's desired room layout and size.

[0103] 2. "Floor plan image" is an image file showing the layout of rooms in an existing property.

[0104] 3. "Room and facility conditions" refers to information about the layout of rooms and their facilities, such as the living room, kitchen, bedrooms, and bathrooms, that appear on the floor plan.

[0105] 4. "Database" means an information system that stores information on various rental properties.

[0106] 5. "Three-dimensional images" are images that have physical depth and a sense of three-dimensionality and are visually consistent.

[0107] 6. A "renovation plan" is a specific proposal for renovating an existing property to bring it closer to the user's ideals.

[0108] 7. "Feedback" means any opinions or comments regarding suggestions or requested changes provided by a User.

[0109] 8. "Rendering" is the process of generating three-dimensional images using computer graphics.

[0110] MODE FOR CARRYING OUT THE INVENTION

[0111] The system of the present invention consists of three main components: a user, a terminal, and a server. Each component and its function will be explained in detail below.

[0112] User-created and imported floor plans

[0113] 1. User: The user creates their ideal floor plan through the system's UI. This UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. For example, the user can place the living room in the center, the kitchen on the right, and the bedroom on the left.

[0114] 2. Terminal: The terminal captures the floor plan created by the user and sends it to the server as image data. The user can also select and upload an existing floor plan image. The terminal performs the file upload process and sends the floor plan data to the server according to the user's operation.

[0115] 3. Server: The server analyzes the received floor plan image. It uses image processing libraries such as OpenCV for image analysis and deep learning libraries such as TENSORFLOW (registered trademark) and Keras to classify the room type. For example, it extracts information such as living room, kitchen, bedroom, and bathroom.

[0116] Providing information on similar rental properties

[0117] 1. Server: The server searches the database based on the analysis results and extracts rental property information that matches the conditions of the floor plan created by the user. It uses SQL queries to search the property information in the database and identifies properties that meet the conditions. Conditions include the number of rooms, room layout, and facility layout.

[0118] 2. Terminal: The terminal receives the list of similar rental properties sent from the server and displays it to the user. This list includes information such as floor plans, rent, and address. Front-end technologies such as React and Angular can be used to display the details.

[0119] Renovation plan proposal

[0120] 1. User: A user uploads a floor plan of a property they are currently living in or planning to purchase. For example, they click the "Upload Floor Plan" button on the property information page and select a file.

[0121] 2. Server: The server analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment and generates a realistic renovation plan. For example, it makes specific renovation suggestions, such as demolishing a wall to expand the living room.

[0122] 3. Server: The generated renovation plan is rendered as a 3D image. Blender and Unreal Engine are used for rendering, and the 3D image is generated and provided to the user. The generated 3D image includes the interior and furniture layout.

[0123] Review and feedback on the proposed plan

[0124] 1. Terminal: The terminal allows users to view a 3D image of the proposed renovation plan. Using the 3D viewer, users can freely change the viewpoint.

[0125] 2. User: The user provides feedback and sends a specific request to the server, for example, "I want to change the color of the walls." Feedback is provided through the UI, for example, by text input.

[0126] 3. Server: The server receives feedback from the user and re-renders the renovation plan. The updated plan is then regenerated as a 3D image and provided to the user.

[0127] Specific examples

[0128] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[0129] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it may generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout. If the user reviews the 3D image and then sends feedback indicating that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again.

[0130] Example prompts for generative AI models

[0131] "Analyze the floor plan below to determine the layout of the living room, kitchen, and bedrooms, then search for rental properties that meet similar criteria. Then, display them in a list."

[0132] The system of this invention enables users to efficiently realize their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[0133] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0134] Specific processing flow of the system program

[0135] User-created and imported floor plans

[0136] Step 1:

[0137] User: Accesses the system's UI and creates an ideal floor plan. The user uses the drag-and-drop function to determine the shape, layout, and size of the rooms.

[0138] Input: User actions

[0139] Output: Ideal floor plan

[0140] Step 2:

[0141] Terminal: Captures floor plans created by users and sends them to the server as image data. Users can also select and upload existing floor plan images.

[0142] Input: Ideal floor plan, existing floor plan image

[0143] Output: Floor plan image data

[0144] Step 3:

[0145] Server: Analyzes the received floor plan image. Image processing libraries such as OpenCV are used for image analysis, and deep learning libraries such as TensorFlow and Keras are used to classify room types. The layout and type of rooms (e.g., living room, kitchen, bedroom) are identified, and relevant information is extracted.

[0146] Input: Floor plan image data

[0147] Output: Analysis results (room and equipment conditions)

[0148] Providing information on similar rental properties

[0149] Step 4:

[0150] Server: Searches the database based on the analysis results and extracts rental property information that matches the floor plan created by the user. Searches the database for property information using SQL queries to identify properties that match the criteria.

[0151] Input: Analysis results (room and equipment conditions)

[0152] Output: List of similar rental properties

[0153] Step 5:

[0154] Terminal: The user receives a list of similar rental properties sent from the server and checks them on the UI. The list includes information such as floor plans, rents, and addresses, and includes a link to display more detailed information. The display is done using front-end technologies (e.g., React or Angular).

[0155] Input: List of similar rental properties

[0156] Output: The detailed information screen that the user sees

[0157] Renovation plan proposal

[0158] Step 6:

[0159] Users: Upload floor plans for properties they currently live in or are considering purchasing. Click the "Upload Floor Plan" button on the property information page, select the file, and submit.

[0160] Input: Image data of the property floor plan

[0161] Output: Uploaded data

[0162] Step 7:

[0163] Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment, and generates a realistic renovation plan. It then creates specific renovation proposals (e.g., moving walls, rearranging furniture).

[0164] Input: Image data of the property floor plan, information on the ideal floor plan

[0165] Output: Generated renovation plan

[0166] Step 8:

[0167] Server: The generated renovation plan is rendered as a 3D image. Using Blender and Unreal Engine, a concrete visual image is created and provided as a 3D image including the interior and furniture layout.

[0168] Input: Generated renovation plan

[0169] Output: 3D video

[0170] Review and feedback on the proposed plan

[0171] Step 9:

[0172] Terminal: The user views a 3D image of the proposed renovation plan. Using a 3D viewer displayed on a web browser, the user can freely change the viewpoint to view the interior.

[0173] Input: 3D video

[0174] Output: Confirmation screen

[0175] Step 10:

[0176] User: The user provides feedback and sends a specific change request to the server, for example, "I want to change the wall color." They enter the change request in text form through the UI and press the submit button.

[0177] Input: User feedback

[0178] Output: Feedback data

[0179] Step 11:

[0180] Server: Receives feedback, re-renders, and updates the renovation plan. Generates new 3D images based on the feedback using Blender or similar software, and provides them to the user again.

[0181] Input: Feedback data

[0182] Output: 3D image of the updated renovation plan

[0183] Step 12:

[0184] On the device: The updated plan is displayed again to the user, who can then review the proposed plan again and repeat the process until they are finally satisfied.

[0185] Input: Updated 3D image

[0186] Output: Final confirmation screen

[0187] (Application example 1)

[0188] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0189] Conventional floor plan creation and renovation plan generation systems have limited means for users to specifically check the image of their ideal space, making it difficult to reflect and confirm feedback. Furthermore, the lack of an interface that reflects user feedback in real time and allows intuitive operation has led to low satisfaction with the final plan.

[0190] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0191] In this invention, the server includes means for allowing a user to create an ideal floor plan, means for loading an image of a floor plan close to the ideal, means for analyzing the ideal floor plan or the loaded floor plan image and extracting room and facility conditions, means for retrieving similar real estate property information from a database based on the conditions, means for displaying the retrieved real estate property information to the user, and means for the user to check and operate the renovation plan in three-dimensional space using a virtual visual device, thereby enabling feedback to be reflected in real time and intuitive operation.

[0192] "User" means an individual or organization that uses the System to create floor plans and view and manipulate renovation plans.

[0193] An "ideal floor plan" is a drawing that expresses the layout of the building and the arrangement of rooms that the user desires.

[0194] "Loading" means inputting an existing floor plan image into the system and having it recognized as data.

[0195] "Analysis" refers to the act of extracting information about rooms and facilities from the loaded floor plan image and classifying and recognizing them based on certain conditions.

[0196] "Room and facility conditions" refers to information about the location, size, shape, and facility layout of each room in the floor plan.

[0197] A "database" is a collection of information that stores and makes searchable similar real estate property information based on the user's criteria.

[0198] "Real estate property information" refers to attribute information of actual buildings that are available for rent or purchase, including floor plans, rent, location, etc.

[0199] A "virtual visual device" is a device that allows users to view and manipulate floor plans and renovation plans in three-dimensional space.

[0200] A "three-dimensional image" is a three-dimensional image that has a three-dimensional appearance and can be visually perceived by a user.

[0201] "Feedback" refers to opinions and requests from users, and includes information that includes instructions for adjusting or changing the renovation plan.

[0202] A "generative AI model" is an algorithm that receives user feedback and automatically generates and updates floor plans and renovation plans.

[0203] A "prompt" is text that describes specific instructions or requests that a user inputs to a generative AI model.

[0204] MODE FOR CARRYING OUT THE INVENTION

[0205] Overall structure

[0206] The system of the present invention consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, and the server performs data analysis and plan generation on the back end.

[0207] User-created and imported floor plans

[0208] Users create their ideal floor plan through the system's user interface (UI). The UI features a drag-and-drop function, allowing intuitive manipulation of room layout and size. Users can also upload images of existing floor plans. The device captures the floor plan created by the user and sends it to the server.

[0209] Data analysis by server

[0210] The server analyzes the received floor plan image and extracts the room and facility conditions, for example, identifying the living room, kitchen, bathroom, etc. This analysis uses an image analysis algorithm, such as deep learning technology.

[0211] Providing rental property information

[0212] Based on the analysis results, the server searches the database to extract real estate information that matches the user's specified criteria. These criteria include the number of rooms, room layout, and facility layout. The retrieved real estate information is sent to the terminal, where the user can view it as a list.

[0213] 3D display using virtual visual equipment

[0214] Users can wear virtual vision devices (e.g., smart glasses) and experience the renovation plan in a virtual three-dimensional space. The server then renders the renovation plan as a three-dimensional image, generating a concrete image including the interior and furniture layout.

[0215] Feedback and regeneration processes

[0216] The user views the 3D image through a virtual viewing device and provides specific feedback, such as "I want to change the wall color to red." This feedback is sent to the server in the form of a prompt. The server then uses a generative AI model to regenerate and update the renovation plan based on this feedback.

[0217] Specific examples

[0218] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK real estate properties that meet similar criteria and provides them to the user as a list. Similarly, if a user plans to purchase a 3LDK apartment and uploads a floor plan for that property, the server analyzes the floor plan, understands the current state of the apartment, and generates a renovation plan for renovating it into the ideal 2LDK apartment. For example, it generates a plan to remove a wall to create a larger living space or add new storage space.

[0219] An example of a prompt is "Please change the wall color to FF0000 (red)." Based on this instruction, the server updates the renovation plan. The updated plan is again provided to the user as a 3D image, allowing the user to immediately confirm the changes.

[0220] Hardware and software used

[0221] The system of the present invention uses a server, a user device, and a virtual visual device (such as smart glasses). The software includes THREE.js (for 3D rendering), WebRTC (for real-time rendering and user interaction), and a generative AI model (to generate and update plans based on user feedback).

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

[0223] Step 1:

[0224] Users create their ideal floor plan using the device's user interface (UI). The drag-and-drop function allows intuitive manipulation of room layout and size. The input is UI data that the user manipulates, and the output is floor plan data.

[0225] Step 2:

[0226] The device captures the ideal floor plan data created by the user and sends it to the server. This process converts the UI data into images or other formats, and then makes an API call to send it to the server. The input is the floor plan data, and the output is the data sent to the server.

[0227] Step 3:

[0228] The server receives the floor plan data and analyzes it using image analysis algorithms such as deep learning technology, thereby extracting the room and equipment conditions. The input is the floor plan data, and the output is the analysis results including the room and equipment conditions.

[0229] Step 4:

[0230] Based on the analysis results, the server searches the database and extracts real estate property information that matches the user's specified criteria. This process searches for suitable properties in the database using criteria such as the number of rooms, room layout, and facility layout. The input is the analysis result criteria data, and the output is similar real estate property information.

[0231] Step 5:

[0232] The server sends the extracted property information to the terminal, which displays the information in a list format to the user. The user can then check the list and view detailed information (e.g., floor plan, rent, address). The input is property information from the server, and the output is the information displayed on the user's terminal.

[0233] Step 6:

[0234] Users wear virtual vision devices (such as smart glasses) to experience renovation plans in a three-dimensional space. Through the virtual vision device, users can visually confirm the floor plan in three-dimensional images. The input is the user's wearing information and the virtual vision device's setting data, and the output is a three-dimensional image.

[0235] Step 7:

[0236] The user checks the 3D image provided through the virtual visual device and provides specific feedback, such as "I want to change the color of the wall to red." This feedback is sent from the terminal to the server in the form of a prompt sentence. The input is the user's feedback prompt sentence, and the output is the prompt sentence data sent from the terminal to the server.

[0237] Step 8:

[0238] The server uses a generative AI model based on the received prompt sentence to regenerate and update the renovation plan. The input is the prompt sentence data and the existing renovation plan, and the output is the updated renovation plan.

[0239] Step 9:

[0240] The server renders the updated renovation plan again as a 3D image and provides it to the user via the terminal and virtual viewing device. The input is the updated renovation plan data, and the output is the 3D image displayed to the user.

[0241] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0242] The system of the present invention allows users to create their ideal floor plan or import an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring the floor plan of a property they are planning to purchase or currently living in closer to their ideal floor plan. Furthermore, by combining it with an emotion engine, the system also has the function of recognizing the user's emotional state in real time and adjusting the proposal content based on that.

[0243] Overall system overview

[0244] The system consists of three main components: the user, the device, and the server. The user mainly operates the device, while the server performs data analysis and plan generation in the backend. The emotion engine also analyzes the user's emotional state in real time.

[0245] User-created and imported floor plans

[0246] 1. User: Create your ideal floor plan through the system's UI. The UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. You can also upload an image of an existing floor plan.

[0247] 2. Device: Captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[0248] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[0249] Providing information on similar rental properties

[0250] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[0251] 5. Server: Using the user's emotion engine, search results are prioritized based on the user's preferences. The emotion engine evaluates the user's emotions by analyzing past choices, current facial expressions, and voice.

[0252] 6. Terminal: The user is presented with a list of similar rental property information sent from the server. The user can review this list and view detailed information (e.g., floor plan, rent, address).

[0253] Renovation plan proposal

[0254] 7. User: Upload floor plans of properties you currently live in or are considering purchasing.

[0255] 8. Server: Analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. Based on the analysis results, evaluates the possibility of renovation.

[0256] 9. Server: Compares the user's ideal floor plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[0257] 10. Server: The generated renovation plan is rendered as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[0258] 11. Terminal: Displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[0259] Review and feedback on the proposed plan

[0260] 12. User: Sends feedback on the renovation plan to the server via the terminal. For example, inputs specific requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[0261] 13. Server: The emotion engine analyzes the user's emotional state at the time of feedback and determines whether further adjustments are necessary. Based on the received feedback, the renovation plan is regenerated and updated.

[0262] 14. Device: The updated renovation plan is displayed again to the user, who can then review the 3D image again and make a final decision or provide further feedback.

[0263] Specific examples

[0264] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[0265] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is shown a concrete visual of the interior and furniture layout. The emotion engine analyzes the user's reactions to these suggestions in real time and presents the optimal plan.

[0266] If a user checks the 3D image and then sends feedback requesting a change to the wall color, the emotion engine will analyze the user's emotional state at the time of the feedback and further adjust the suggestions as necessary. For example, it may suggest bolder design ideas to a user who expresses positive emotions, and more conservative ideas to a user who expresses caution.

[0267] By combining emotion engines in this way, the present invention is able to provide optimal rental property information and propose renovation plans that are tailored to the user's emotional state.

[0268] The processing flow will be explained below.

[0269] Step 1:

[0270] Users create their ideal floor plan using the system's UI, which features a drag-and-drop function that allows intuitive configuration of room placement and size. Users can also upload images of existing floor plans.

[0271] Step 2:

[0272] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[0273] Step 3:

[0274] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[0275] Step 4:

[0276] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[0277] Step 5:

[0278] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[0279] Step 6:

[0280] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[0281] Step 7:

[0282] The emotion engine recognizes the user's real-time emotions and assesses their interests and preferences by analyzing their facial expressions and voice.

[0283] Step 8:

[0284] The server receives feedback from the emotion engine and adjusts the prioritization of rental listings to display based on customer preferences, for example, displaying properties that the user has expressed interest in at the top of the list.

[0285] Step 9:

[0286] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[0287] Step 10:

[0288] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[0289] Step 11:

[0290] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[0291] Step 12:

[0292] The server renders the generated renovation plan as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[0293] Step 13:

[0294] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[0295] Step 14:

[0296] The emotion engine analyzes the user's emotional state during feedback in real time and determines whether further updates are needed.

[0297] Step 15:

[0298] The server regenerates and updates the renovation plan based on the feedback it receives, for example re-rendering the plan with a changed wall color.

[0299] Step 16:

[0300] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[0301] This process allows users to efficiently find their ideal rental property and at the same time receive proposals for renovation plans that take into account the user's emotional state.

[0302] Example 2

[0303] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0304] Conventional floor plan creation tools and rental property search systems often do not take into account the user's individual preferences or emotional state, resulting in proposed properties and plans that do not meet the user's expectations. Furthermore, when proposing renovation plans, there was an insufficient mechanism for fully reflecting user feedback. Therefore, in order to improve user satisfaction, flexible proposals that respond to the user's emotional state are required.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0306] In this invention, the server includes an emotion engine means for recognizing the user's emotional state in real time and adjusting the proposed content, a means for regenerating and updating renovation plans based on the feedback and the emotional state, and a means for evaluating the user's emotional state using the emotion engine, thereby making it possible to provide rental property information and propose renovation plans appropriate to the user's emotional state.

[0307] A "user" is an individual or organization that operates the system to create desired floor plans, search for rental property information, or check renovation plans.

[0308] A "floor plan" is a drawing that shows the layout and structure of a building or room, and represents the layout of the rooms and the location of equipment.

[0309] The "server" is a computer system that analyzes data provided by users, extracts floor plan information, and generates rental property information and renovation plans.

[0310] An "emotion engine" is a combination of software or hardware that recognizes a user's emotional state in real time and adjusts suggestions based on that information.

[0311] "Feedback" refers to the opinions and reactions users provide to proposed renovation plans and rental property information, and is information used to readjust the system.

[0312] A "renovation plan" is a specific proposal or plan for renovating or rearranging an existing property to bring it closer to the user's ideals.

[0313] "Three-dimensional images" are images that represent renovation plans and floor plans in three dimensions, and are rendered so that users can visually confirm them.

[0314] A "database" is an information system that organizes and stores information on rental properties and floor plans, and manages it so that it can be searched and retrieved as needed.

[0315] "Analysis" is the process in which the server processes the input floor plan data and images and extracts information such as the layout of rooms and equipment.

[0316] The system of the present invention consists of three main components: a user, a terminal, and a server. The following will specifically explain how to implement the system.

[0317] System Overview

[0318] The system allows users to create and load their ideal floor plan, and the server analyzes it to provide information on similar rental properties and propose renovation plans. Furthermore, by combining it with an emotion engine, the system can recognize the user's emotional state in real time and adjust the proposals accordingly.

[0319] Creating and loading floor plans

[0320] 1. Users create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing them to intuitively arrange the living room, kitchen, bedroom, etc. Users can also upload an image of an existing floor plan.

[0321] 2. The device captures the floor plan data created by the user and the floor plan images uploaded by the user and sends them to the server using a secure communication protocol (e.g., HTTPS).

[0322] Providing rental property information

[0323] 3. The server analyzes the received floor plan data using an image analysis algorithm (e.g., OpenCV) to identify rooms and facilities such as the living room, kitchen, and bathroom.

[0324] 4. Based on the analysis results, the server searches the database and extracts rental property information that matches the conditions specified by the user.

[0325] 5. The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preferences. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis.

[0326] 6. The terminal receives the list of similar rental property information sent from the server and displays it to the user.

[0327] Providing renovation plans

[0328] 7. Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are accepted, including image files and PDFs.

[0329] 8. The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions.

[0330] 9. Based on the analysis results, the server compares the user's ideal floor plan and generates multiple realistic renovation plans, taking into account things like removing rooms, adding walls, and changing fixtures.

[0331] 10. The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine).

[0332] 11. The device displays the rendered 3D image to the user, allowing the user to examine it in detail and get a concrete idea of ​​the renovation plan.

[0333] 12. The user sends feedback about the renovation plan to the server via their device. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture."

[0334] Re-adjusting the plan

[0335] 13. The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed: if the engine indicates a positive emotion, it will make bold design suggestions, but if it indicates a cautious emotion, it will make more conservative suggestions.

[0336] 14. The device displays the reworked renovation plan to the user again, who can review the updated 3D image and make a final decision or provide further feedback.

[0337] Specific examples

[0338] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[0339] Prompt Sentence Examples

[0340] If you were to use a generative AI model to prompt the system for this sequence, you could use a prompt like this:

[0341] The system allows users to create and import their ideal floor plan, provides rental property information that matches it, and proposes renovation plans. Please explain the process in detail.

[0342] The above is an embodiment of the present invention. The purpose of the present invention is to improve user satisfaction by providing suggestions and information according to the user's emotional state through the combination of an emotion engine.

[0343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0344] Step 1:

[0345] Users create their ideal floor plan using the system's UI. This UI allows them to intuitively arrange living rooms, kitchens, bedrooms, etc. using the drag-and-drop function. Users can also upload existing floor plan images. The input here is the floor plan data created by the user or an uploaded image file, and the output is this data ready to be sent to the server.

[0346] Step 2:

[0347] The device captures floor plan data created by the user and floor plan images uploaded by the user and sends them to the server. A secure communication protocol (e.g., HTTPS) is used for data transmission. The input is the user's floor plan data, and the output is the completion of data transmission to the server.

[0348] Step 3:

[0349] The server analyzes the received floor plan data. This analysis uses an image analysis algorithm (e.g., OpenCV) to identify the layout of rooms and facilities such as living rooms, kitchens, and bathrooms. The input is the floor plan data sent from the device, and the output is the layout information of rooms and facilities as a result of the analysis.

[0350] Step 4:

[0351] The server searches the database based on the analysis results and extracts rental property information that matches the user's specified criteria. The input here is the analysis results, and the output is rental property information based on the criteria.

[0352] Step 5:

[0353] The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preference. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis. The input is rental property information and the user's emotional data, and the output is prioritized rental property information that takes emotions into account.

[0354] Step 6:

[0355] The terminal receives the list of similar rental property information sent from the server and displays it to the user. The input is the rental property information from the server, and the output is a list of rental property information that the user can check.

[0356] Step 7:

[0357] Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are allowed, including image files and PDFs. The input is the user's property floor plan data, and the output is this data ready to be sent to the server.

[0358] Step 8:

[0359] The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. The input is the uploaded floor plan data, and the output is the analysis results, including the current room layout and equipment conditions.

[0360] Step 9:

[0361] Based on the analysis results, the server compares them with the user's ideal floor plan and generates multiple realistic renovation plans. This involves removing rooms, adding walls, changing fixtures, etc. The input is the analysis results and the ideal floor plan, and the output is multiple renovation plans.

[0362] Step 10:

[0363] The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine). The input is the renovation plan, and the output is the 3D image.

[0364] Step 11:

[0365] The terminal receives the rendered 3D image and displays it to the user. The input is the 3D image from the server, and the output is the 3D image that the user can visually confirm.

[0366] Step 12:

[0367] Users send feedback about the renovation plan to the server via their devices. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture." The input is the user's feedback, and the output is the feedback data sent to the server.

[0368] Step 13:

[0369] The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed. If the engine indicates a positive emotion, it makes bold design suggestions, and if it indicates a cautious emotion, it makes more conservative suggestions. The input is the feedback and the user's emotional data, and the output is the readjusted renovation plan.

[0370] Step 14:

[0371] The terminal displays the re-adjusted renovation plan to the user again. The input is the re-adjusted renovation plan from the server, and the output is an updated 3D image that the user can view.

[0372] (Application example 2)

[0373] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0374] Currently, it is difficult to customize the interior layout of an autonomous vehicle based on the preferences and feelings of each individual user. Furthermore, there is a lack of tools to collect vehicle information that closely matches the ideal layout desired by the user or to receive suggestions for renovating existing vehicles. As a result, users face the challenge of finding the optimal interior and layout that suits their preferences.

[0375] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0376] In this invention, the server includes a means for allowing a user to create an ideal spatial layout, a means for loading a layout image close to the ideal, and a means for analyzing the ideal layout or the loaded layout image to extract spatial and equipment conditions, thereby enabling the proposal and customization of a vehicle interior layout based on the user's emotional state. The server also includes a means for acquiring similar property information from a data storage device, a means for displaying the acquired property information to the user, an emotion analysis means for analyzing the user's emotional state in real time, and a means for adjusting the priority of similar property information based on the analysis results. This allows the user to create an ideal vehicle interior layout and receive proposals for optimal property information and renovation plans based on that layout.

[0377] A "user" is a person who operates the system to create an ideal spatial layout or load an existing layout.

[0378] "Spatial layout" refers to drawings or designs that show the arrangement of rooms and facilities.

[0379] A "layout image" is image data that visually represents a spatial layout.

[0380] "Analysis" refers to the process of extracting room and equipment conditions from the input layout image.

[0381] "Space and equipment conditions" refers to layout characteristics such as room arrangement, size, and equipment placement.

[0382] "Property information" refers to detailed data about the spatial layout in which a user is interested.

[0383] A "data storage device" is a device that stores data long-term and allows it to be accessed as needed.

[0384] "Emotional state" refers to a state that indicates the user's state of mind or mood.

[0385] "Emotion analysis means" refers to means for assessing a user's emotional state by analyzing their facial expressions and vocal tone.

[0386] "Means for adjusting priority" refers to means for changing the order and importance of information to be displayed based on the results of sentiment analysis.

[0387] "3D video" refers to digital images that visually recreate objects and environments in three-dimensional space.

[0388] "Visualization" is the process of visually representing data or information.

[0389] "Opinions" are feedback and improvement requests provided by users.

[0390] The system for realizing this invention mainly consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, while the server performs data analysis and plan generation on the backend. In addition, an emotion analysis means analyzes the user's emotional state in real time.

[0391] 1. User-created and loaded spatial layouts

[0392] Users wear a head-mounted display (HMD) and create their ideal spatial layout using an intuitive UI with drag-and-drop functionality. Alternatively, by uploading an image of an existing layout, the system analyzes the image and extracts spatial and facility conditions.

[0393] 2. Layout analysis and provision of similar property information

[0394] The terminal captures the layout created or imported by the user and sends it to the server. The server analyzes the received layout image and performs image analysis processing to identify the conditions of the rooms and facilities. This process uses the OpenCV library. Based on the analysis results, similar property information is searched for in the data storage device and provided to the user. Furthermore, an emotion analysis means evaluates the user's emotional state and adjusts the priority of property information based on the user's preferences.

[0395] 3. Proposal of renovation plan

[0396] When a user uploads an existing property layout, the device sends the layout to the server. The server analyzes the layout to determine the current room arrangement and equipment conditions. Based on the analysis results, a realistic renovation plan is generated by comparing it with the ideal layout. This may include removing walls, adding rooms, or changing equipment. The renovation plan is then rendered as a 3D image using Unity 3D.

[0397] 4. User feedback and plan regeneration

[0398] The user can view the 3D image in detail through the HMD and provide feedback, which is then sent to the server via the device. The server then uses emotion analysis to reassess the user's emotional state and regenerate and update the renovation plan as necessary.

[0399] Hardware and software used

[0400] Head-mounted display (HMD): Use Meta Quest 2, HTC Vive, etc.

[0401] Image Analysis Library: Analyzes layout images using OpenCV.

[0402] 3D video rendering software: Real-time rendering using Unity 3D.

[0403] Sentiment analysis method: Affectiva SDK is used to analyze the user's emotional state in real time.

[0404] Examples and prompts

[0405] As a concrete example, we will show a scenario in which a user creates an interior layout for an autonomous vehicle and receives suggestions for similar properties and renovation plans based on that layout.

[0406] Example prompt sentence:

[0407] "In an interior layout design app for autonomous vehicles, provide a function that allows users to wear an HMD and create, load, and customize their ideal layout. At this time, please add a function that uses emotion analysis means to analyze the user's emotional state in real time and adjust the proposal content based on their emotion."

[0408] This system allows users to create their ideal interior layout and receive optimal property information and renovation plan suggestions based on that.

[0409] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0410] Step 1:

[0411] The user wears a head-mounted display (HMD) and creates an ideal spatial layout using a UI with drag-and-drop functionality. It is also possible to upload an existing layout image. The input is the user's operation data or the uploaded layout image. The output is the generated ideal layout data or the uploaded layout image.

[0412] Step 2:

[0413] The terminal captures layout data created by the user or a layout image loaded by the user and transmits it to the server. The input here is the layout data created or uploaded by the user, and the output is the data transmitted to the server.

[0414] Step 3:

[0415] The server analyzes the received layout image and extracts the spatial and equipment conditions. This process uses the OpenCV library. The input is the received layout image data, and the output is the extracted spatial and equipment condition data. Specifically, the server applies an image analysis algorithm to identify the layout of rooms and equipment.

[0416] Step 4:

[0417] The server searches for similar property information from its data storage device based on the analysis results. The input is the extracted spatial and facility condition data, and the output is similar property information. Specifically, the server executes a query to efficiently search for data that matches the conditions.

[0418] Step 5:

[0419] The server uses emotion analysis to evaluate the user's emotional state in real time and adjust the priority of the retrieved property information. The input is the user's emotional data (facial expression, tone of voice, etc.) and the property information from the search results, and the output is a prioritized property list. Specifically, the server uses an emotion analysis algorithm to dynamically change the display order of properties based on the retrieved data.

[0420] Step 6:

[0421] The information sent from the server is displayed to the user on the terminal. The input is a prioritized property list, and the output is visual information displayed on the HMD. Specifically, the property information is displayed in the user's field of vision using the HMD display.

[0422] Step 7:

[0423] When a user uploads an existing property layout, the terminal sends the layout to the server. The input is the property layout data uploaded by the user, and the output is the data sent to the server.

[0424] Step 8:

[0425] The server analyzes the uploaded layout and determines the current room arrangement and equipment conditions. The input is the layout data sent, and the output is the analysis results data. Specifically, the server again uses the OpenCV library to identify the arrangement of each room in the layout.

[0426] Step 9:

[0427] The server compares the ideal layout with the data and generates a realistic renovation plan. The input is the analysis result data and the ideal layout data, and the output is the renovation plan. Specifically, it uses the generative AI model to create the necessary renovation plan.

[0428] Step 10:

[0429] The server uses Unity 3D to render the generated renovation plan as a 3D image and sends it to the HMD. The input is the renovation plan data, and the output is the 3D image data. Specifically, it uses Unity 3D's rendering function to create a visually detailed 3D image.

[0430] Step 11:

[0431] The user can view the 3D image in detail through the HMD and provide feedback. The input is the 3D image, and the output is the feedback data from the user.

[0432] Step 12:

[0433] The feedback is sent to the server via the device, and the server uses emotion analysis means to reassess the user's emotional state and regenerate and update the renovation plan as necessary. The input is the user's feedback data and emotion data, and the output is a regenerated renovation plan. Specifically, the renovation plan is adjusted and updated using an emotion analysis algorithm and a generative AI model.

[0434] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0435] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0436] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0437] [Second embodiment]

[0438] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0439] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0440] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0441] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0442] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0443] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0444] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0445] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0446] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0447] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0448] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0449] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0450] The system of the present invention allows users to create their ideal floor plan or load an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring a property they are planning to purchase or currently living in closer to their ideal floor plan.

[0451] Overall system overview

[0452] The system consists of three main components: the user, the terminal, and the server. The user mainly operates the terminal, and the server performs data analysis and plan generation in the backend.

[0453] User-created and imported floor plans

[0454] 1. User: Create your ideal floor plan through the system's UI, which features drag-and-drop functionality, allowing you to intuitively manipulate the layout and size of rooms.

[0455] 2. Terminal: Captures the floor plan created by the user and sends it to the server. Users can also upload images of existing floor plans.

[0456] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[0457] Providing information on similar rental properties

[0458] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[0459] 5. Terminal: The user checks the list of similar rental properties sent from the server and displays detailed information (e.g., floor plan, rent, address).

[0460] Renovation plan proposal

[0461] 6. User: Upload floor plans of properties you currently live in or are considering purchasing.

[0462] 7. Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. It then generates a realistic renovation plan, which typically includes specific modifications such as removing walls or adding new rooms.

[0463] 8. Server: The generated renovation plan is rendered as a 3D image, generating a concrete image including the interior and furniture layout.

[0464] Review and feedback on the proposed plan

[0465] 9. Terminal: The user can view a 3D image of the proposed renovation plan, including details such as the interior design, furniture layout, and room color scheme.

[0466] 10. User: Provides feedback and sends specific requests to the server, such as "I want to change the color of the walls" or "Can I rearrange this furniture?"

[0467] 11. Server: Receive feedback, re-render, and update / re-propose the renovation plan.

[0468] 12. Device: Redisplay the updated plan to the user for final confirmation.

[0469] Specific examples

[0470] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[0471] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout.

[0472] If the user checks the 3D image and sends feedback that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again, thus finally providing the user with a satisfactory renovation plan.

[0473] The present invention provides a method that allows users to efficiently realize their ideal floor plan using such a system.

[0474] The processing flow will be explained below.

[0475] Step 1:

[0476] Users can create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing intuitive placement and size of the devices. It is also possible to upload an image of an existing floor plan.

[0477] Step 2:

[0478] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[0479] Step 3:

[0480] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[0481] Step 4:

[0482] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[0483] Step 5:

[0484] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[0485] Step 6:

[0486] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[0487] Step 7:

[0488] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[0489] Step 8:

[0490] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[0491] Step 9:

[0492] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[0493] Step 10:

[0494] The server renders the generated renovation plan as a 3D image, allowing users to visualize the layout of furniture and interior décor in concrete terms.

[0495] Step 11:

[0496] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[0497] Step 12:

[0498] The user sends feedback about the renovation plan to the server via their device, for example, by inputting requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[0499] Step 13:

[0500] Based on the feedback received by the server, the renovation plan is regenerated and updated, for example by re-rendering a plan with a different wall color.

[0501] Step 14:

[0502] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[0503] This process allows users to efficiently find their ideal rental property and also obtain specific renovation plans to bring the layout closer to their ideal one.

[0504] Example 1

[0505] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0506] Conventional floor plan creation and analysis systems have the drawback of requiring a lot of time and effort when users create their ideal floor plan or obtain rental property information and renovation plans based on existing floor plans. Furthermore, when proposing renovation plans, the system lacks the technology to flexibly update plans based on user feedback, resulting in an unsatisfactory user experience.

[0507] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0508] In this invention, the server includes: means for allowing a user to create an ideal floor plan; means for loading an image of a floor plan close to the ideal; means for analyzing the ideal floor plan or the loaded floor plan image to extract room and equipment conditions; means for retrieving similar rental property information from a database based on the conditions; means for displaying the retrieved rental property information to the user; means for receiving feedback from the user; means for updating the proposal based on the feedback; means for generating and displaying a 3D image of the proposed interior and furniture arrangement; means for loading a floor plan of a property to be purchased or currently occupied; means for generating a realistically feasible renovation plan based on the floor plan of the property and the ideal floor plan; means for rendering the generated renovation plan as a 3D image; means for the user to review the 3D image and provide feedback; and means for regenerating and updating the renovation plan based on the feedback. This enables users to intuitively and efficiently create their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[0509] 1. An "ideal floor plan" is a drawing that reflects the user's desired room layout and size.

[0510] 2. "Floor plan image" is an image file showing the layout of rooms in an existing property.

[0511] 3. "Room and facility conditions" refers to information about the layout of rooms and their facilities, such as the living room, kitchen, bedrooms, and bathrooms, that appear on the floor plan.

[0512] 4. "Database" means an information system that stores information on various rental properties.

[0513] 5. "Three-dimensional images" are images that have physical depth and a sense of three-dimensionality and are visually consistent.

[0514] 6. A "renovation plan" is a specific proposal for renovating an existing property to bring it closer to the user's ideals.

[0515] 7. "Feedback" means any opinions or comments regarding suggestions or requested changes provided by a User.

[0516] 8. "Rendering" is the process of generating three-dimensional images using computer graphics.

[0517] MODE FOR CARRYING OUT THE INVENTION

[0518] The system of the present invention consists of three main components: a user, a terminal, and a server. Each component and its function will be explained in detail below.

[0519] User-created and imported floor plans

[0520] 1. User: The user creates their ideal floor plan through the system's UI. This UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. For example, the user can place the living room in the center, the kitchen on the right, and the bedroom on the left.

[0521] 2. Terminal: The terminal captures the floor plan created by the user and sends it to the server as image data. The user can also select and upload an existing floor plan image. The terminal performs the file upload process and sends the floor plan data to the server according to the user's operation.

[0522] 3. Server: The server analyzes the received floor plan image. It uses image processing libraries such as OpenCV and deep learning libraries such as TensorFlow and Keras to classify the room type. For example, it extracts information such as living room, kitchen, bedroom, and bathroom.

[0523] Providing information on similar rental properties

[0524] 1. Server: The server searches the database based on the analysis results and extracts rental property information that matches the conditions of the floor plan created by the user. It uses SQL queries to search the property information in the database and identifies properties that meet the conditions. Conditions include the number of rooms, room layout, and facility layout.

[0525] 2. Terminal: The terminal receives the list of similar rental properties sent from the server and displays it to the user. This list includes information such as floor plans, rent, and address. Front-end technologies such as React and Angular can be used to display the details.

[0526] Renovation plan proposal

[0527] 1. User: A user uploads a floor plan of a property they are currently living in or planning to purchase. For example, they click the "Upload Floor Plan" button on the property information page and select a file.

[0528] 2. Server: The server analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment and generates a realistic renovation plan. For example, it makes specific renovation suggestions, such as demolishing a wall to expand the living room.

[0529] 3. Server: The generated renovation plan is rendered as a 3D image. Blender and Unreal Engine are used for rendering, and the 3D image is generated and provided to the user. The generated 3D image includes the interior and furniture layout.

[0530] Review and feedback on the proposed plan

[0531] 1. Terminal: The terminal allows users to view a 3D image of the proposed renovation plan. Using the 3D viewer, users can freely change the viewpoint.

[0532] 2. User: The user provides feedback and sends a specific request to the server, for example, "I want to change the color of the walls." Feedback is provided through the UI, for example, by text input.

[0533] 3. Server: The server receives feedback from the user and re-renders the renovation plan. The updated plan is then regenerated as a 3D image and provided to the user.

[0534] Specific examples

[0535] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[0536] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it may generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout. If the user reviews the 3D image and then sends feedback indicating that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again.

[0537] Example prompts for generative AI models

[0538] "Analyze the floor plan below to determine the layout of the living room, kitchen, and bedrooms, then search for rental properties that meet similar criteria. Then, display them in a list."

[0539] The system of this invention enables users to efficiently realize their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[0540] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0541] Specific processing flow of the system program

[0542] User-created and imported floor plans

[0543] Step 1:

[0544] User: Accesses the system's UI and creates an ideal floor plan. The user uses the drag-and-drop function to determine the shape, layout, and size of the rooms.

[0545] Input: User actions

[0546] Output: Ideal floor plan

[0547] Step 2:

[0548] Terminal: Captures floor plans created by users and sends them to the server as image data. Users can also select and upload existing floor plan images.

[0549] Input: Ideal floor plan, existing floor plan image

[0550] Output: Floor plan image data

[0551] Step 3:

[0552] Server: Analyzes the received floor plan image. Image processing libraries such as OpenCV are used for image analysis, and deep learning libraries such as TensorFlow and Keras are used to classify room types. The layout and type of rooms (e.g., living room, kitchen, bedroom) are identified, and relevant information is extracted.

[0553] Input: Floor plan image data

[0554] Output: Analysis results (room and equipment conditions)

[0555] Providing information on similar rental properties

[0556] Step 4:

[0557] Server: Searches the database based on the analysis results and extracts rental property information that matches the floor plan created by the user. Searches the database for property information using SQL queries to identify properties that match the criteria.

[0558] Input: Analysis results (room and equipment conditions)

[0559] Output: List of similar rental properties

[0560] Step 5:

[0561] Terminal: The user receives a list of similar rental properties sent from the server and checks them on the UI. The list includes information such as floor plans, rents, and addresses, and includes a link to display more detailed information. The display is done using front-end technologies (e.g., React or Angular).

[0562] Input: List of similar rental properties

[0563] Output: The detailed information screen that the user sees

[0564] Renovation plan proposal

[0565] Step 6:

[0566] Users: Upload floor plans for properties they currently live in or are considering purchasing. Click the "Upload Floor Plan" button on the property information page, select the file, and submit.

[0567] Input: Image data of the property floor plan

[0568] Output: Uploaded data

[0569] Step 7:

[0570] Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment, and generates a realistic renovation plan. It then creates specific renovation proposals (e.g., moving walls, rearranging furniture).

[0571] Input: Image data of the property floor plan, information on the ideal floor plan

[0572] Output: Generated renovation plan

[0573] Step 8:

[0574] Server: The generated renovation plan is rendered as a 3D image. Using Blender and Unreal Engine, a concrete visual image is created and provided as a 3D image including the interior and furniture layout.

[0575] Input: Generated renovation plan

[0576] Output: 3D video

[0577] Review and feedback on the proposed plan

[0578] Step 9:

[0579] Terminal: The user views a 3D image of the proposed renovation plan. Using a 3D viewer displayed on a web browser, the user can freely change the viewpoint to view the interior.

[0580] Input: 3D video

[0581] Output: Confirmation screen

[0582] Step 10:

[0583] User: The user provides feedback and sends a specific change request to the server, for example, "I want to change the wall color." They enter the change request in text form through the UI and press the submit button.

[0584] Input: User feedback

[0585] Output: Feedback data

[0586] Step 11:

[0587] Server: Receives feedback, re-renders, and updates the renovation plan. Generates new 3D images based on the feedback using Blender or similar software, and provides them to the user again.

[0588] Input: Feedback data

[0589] Output: 3D image of the updated renovation plan

[0590] Step 12:

[0591] On the device: The updated plan is displayed again to the user, who can then review the proposed plan again and repeat the process until they are finally satisfied.

[0592] Input: Updated 3D image

[0593] Output: Final confirmation screen

[0594] (Application example 1)

[0595] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0596] Conventional floor plan creation and renovation plan generation systems have limited means for users to specifically check the image of their ideal space, making it difficult to reflect and confirm feedback. Furthermore, the lack of an interface that reflects user feedback in real time and allows intuitive operation has led to low satisfaction with the final plan.

[0597] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0598] In this invention, the server includes means for allowing a user to create an ideal floor plan, means for loading an image of a floor plan close to the ideal, means for analyzing the ideal floor plan or the loaded floor plan image and extracting room and facility conditions, means for retrieving similar real estate property information from a database based on the conditions, means for displaying the retrieved real estate property information to the user, and means for the user to check and operate the renovation plan in three-dimensional space using a virtual visual device, thereby enabling feedback to be reflected in real time and intuitive operation.

[0599] "User" means an individual or organization that uses the System to create floor plans and view and manipulate renovation plans.

[0600] An "ideal floor plan" is a drawing that expresses the layout of the building and the arrangement of rooms that the user desires.

[0601] "Loading" means inputting an existing floor plan image into the system and having it recognized as data.

[0602] "Analysis" refers to the act of extracting information about rooms and facilities from the loaded floor plan image and classifying and recognizing them based on certain conditions.

[0603] "Room and facility conditions" refers to information about the location, size, shape, and facility layout of each room in the floor plan.

[0604] A "database" is a collection of information that stores and makes searchable similar real estate property information based on the user's criteria.

[0605] "Real estate property information" refers to attribute information of actual buildings that are available for rent or purchase, including floor plans, rent, location, etc.

[0606] A "virtual visual device" is a device that allows users to view and manipulate floor plans and renovation plans in three-dimensional space.

[0607] A "three-dimensional image" is a three-dimensional image that has a three-dimensional appearance and can be visually perceived by a user.

[0608] "Feedback" refers to opinions and requests from users, and includes information that includes instructions for adjusting or changing the renovation plan.

[0609] A "generative AI model" is an algorithm that receives user feedback and automatically generates and updates floor plans and renovation plans.

[0610] A "prompt" is text that describes specific instructions or requests that a user inputs to a generative AI model.

[0611] MODE FOR CARRYING OUT THE INVENTION

[0612] Overall structure

[0613] The system of the present invention consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, and the server performs data analysis and plan generation on the back end.

[0614] User-created and imported floor plans

[0615] Users create their ideal floor plan through the system's user interface (UI). The UI features a drag-and-drop function, allowing intuitive manipulation of room layout and size. Users can also upload images of existing floor plans. The device captures the floor plan created by the user and sends it to the server.

[0616] Data analysis by server

[0617] The server analyzes the received floor plan image and extracts the room and facility conditions, for example, identifying the living room, kitchen, bathroom, etc. This analysis uses an image analysis algorithm, such as deep learning technology.

[0618] Providing rental property information

[0619] Based on the analysis results, the server searches the database to extract real estate information that matches the user's specified criteria. These criteria include the number of rooms, room layout, and facility layout. The retrieved real estate information is sent to the terminal, where the user can view it as a list.

[0620] 3D display using virtual visual equipment

[0621] Users can wear virtual vision devices (e.g., smart glasses) and experience the renovation plan in a virtual three-dimensional space. The server then renders the renovation plan as a three-dimensional image, generating a concrete image including the interior and furniture layout.

[0622] Feedback and regeneration processes

[0623] The user views the 3D image through a virtual viewing device and provides specific feedback, such as "I want to change the wall color to red." This feedback is sent to the server in the form of a prompt. The server then uses a generative AI model to regenerate and update the renovation plan based on this feedback.

[0624] Specific examples

[0625] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK real estate properties that meet similar criteria and provides them to the user as a list. Similarly, if a user plans to purchase a 3LDK apartment and uploads a floor plan for that property, the server analyzes the floor plan, understands the current state of the apartment, and generates a renovation plan for renovating it into the ideal 2LDK apartment. For example, it generates a plan to remove a wall to create a larger living space or add new storage space.

[0626] An example of a prompt is "Please change the wall color to FF0000 (red)." Based on this instruction, the server updates the renovation plan. The updated plan is again provided to the user as a 3D image, allowing the user to immediately confirm the changes.

[0627] Hardware and software used

[0628] The system of the present invention uses a server, a user device, and a virtual visual device (such as smart glasses). The software includes THREE.js (for 3D rendering), WebRTC (for real-time rendering and user interaction), and a generative AI model (to generate and update plans based on user feedback).

[0629] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0630] Step 1:

[0631] Users create their ideal floor plan using the device's user interface (UI). The drag-and-drop function allows intuitive manipulation of room layout and size. The input is UI data that the user manipulates, and the output is floor plan data.

[0632] Step 2:

[0633] The device captures the ideal floor plan data created by the user and sends it to the server. This process converts the UI data into images or other formats, and then makes an API call to send it to the server. The input is the floor plan data, and the output is the data sent to the server.

[0634] Step 3:

[0635] The server receives the floor plan data and analyzes it using image analysis algorithms such as deep learning technology, thereby extracting the room and equipment conditions. The input is the floor plan data, and the output is the analysis results including the room and equipment conditions.

[0636] Step 4:

[0637] Based on the analysis results, the server searches the database and extracts real estate property information that matches the user's specified criteria. This process searches for suitable properties in the database using criteria such as the number of rooms, room layout, and facility layout. The input is the analysis result criteria data, and the output is similar real estate property information.

[0638] Step 5:

[0639] The server sends the extracted property information to the terminal, which displays the information in a list format to the user. The user can then check the list and view detailed information (e.g., floor plan, rent, address). The input is property information from the server, and the output is the information displayed on the user's terminal.

[0640] Step 6:

[0641] Users wear virtual vision devices (such as smart glasses) to experience renovation plans in a three-dimensional space. Through the virtual vision device, users can visually confirm the floor plan in three-dimensional images. The input is the user's wearing information and the virtual vision device's setting data, and the output is a three-dimensional image.

[0642] Step 7:

[0643] The user checks the 3D image provided through the virtual visual device and provides specific feedback, such as "I want to change the color of the wall to red." This feedback is sent from the terminal to the server in the form of a prompt sentence. The input is the user's feedback prompt sentence, and the output is the prompt sentence data sent from the terminal to the server.

[0644] Step 8:

[0645] The server uses a generative AI model based on the received prompt sentence to regenerate and update the renovation plan. The input is the prompt sentence data and the existing renovation plan, and the output is the updated renovation plan.

[0646] Step 9:

[0647] The server renders the updated renovation plan again as a 3D image and provides it to the user via the terminal and virtual viewing device. The input is the updated renovation plan data, and the output is the 3D image displayed to the user.

[0648] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0649] The system of the present invention allows users to create their ideal floor plan or import an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring the floor plan of a property they are planning to purchase or currently living in closer to their ideal floor plan. Furthermore, by combining it with an emotion engine, the system also has the function of recognizing the user's emotional state in real time and adjusting the proposal content based on that.

[0650] Overall system overview

[0651] The system consists of three main components: the user, the device, and the server. The user mainly operates the device, while the server performs data analysis and plan generation in the backend. The emotion engine also analyzes the user's emotional state in real time.

[0652] User-created and imported floor plans

[0653] 1. User: Create your ideal floor plan through the system's UI. The UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. You can also upload an image of an existing floor plan.

[0654] 2. Device: Captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[0655] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[0656] Providing information on similar rental properties

[0657] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[0658] 5. Server: Using the user's emotion engine, search results are prioritized based on the user's preferences. The emotion engine evaluates the user's emotions by analyzing past choices, current facial expressions, and voice.

[0659] 6. Terminal: The user is presented with a list of similar rental property information sent from the server. The user can review this list and view detailed information (e.g., floor plan, rent, address).

[0660] Renovation plan proposal

[0661] 7. User: Upload floor plans of properties you currently live in or are considering purchasing.

[0662] 8. Server: Analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. Based on the analysis results, evaluates the possibility of renovation.

[0663] 9. Server: Compares the user's ideal floor plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[0664] 10. Server: The generated renovation plan is rendered as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[0665] 11. Terminal: Displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[0666] Review and feedback on the proposed plan

[0667] 12. User: Sends feedback on the renovation plan to the server via the terminal. For example, inputs specific requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[0668] 13. Server: The emotion engine analyzes the user's emotional state at the time of feedback and determines whether further adjustments are necessary. Based on the received feedback, the renovation plan is regenerated and updated.

[0669] 14. Device: The updated renovation plan is displayed again to the user, who can then review the 3D image again and make a final decision or provide further feedback.

[0670] Specific examples

[0671] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[0672] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is shown a concrete visual of the interior and furniture layout. The emotion engine analyzes the user's reactions to these suggestions in real time and presents the optimal plan.

[0673] If a user checks the 3D image and then sends feedback requesting a change to the wall color, the emotion engine will analyze the user's emotional state at the time of the feedback and further adjust the suggestions as necessary. For example, it may suggest bolder design ideas to a user who expresses positive emotions, and more conservative ideas to a user who expresses caution.

[0674] By combining emotion engines in this way, the present invention is able to provide optimal rental property information and propose renovation plans that are tailored to the user's emotional state.

[0675] The processing flow will be explained below.

[0676] Step 1:

[0677] Users create their ideal floor plan using the system's UI, which features a drag-and-drop function that allows intuitive configuration of room placement and size. Users can also upload images of existing floor plans.

[0678] Step 2:

[0679] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[0680] Step 3:

[0681] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[0682] Step 4:

[0683] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[0684] Step 5:

[0685] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[0686] Step 6:

[0687] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[0688] Step 7:

[0689] The emotion engine recognizes the user's real-time emotions and assesses their interests and preferences by analyzing their facial expressions and voice.

[0690] Step 8:

[0691] The server receives feedback from the emotion engine and adjusts the prioritization of rental listings to display based on customer preferences, for example, displaying properties that the user has expressed interest in at the top of the list.

[0692] Step 9:

[0693] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[0694] Step 10:

[0695] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[0696] Step 11:

[0697] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[0698] Step 12:

[0699] The server renders the generated renovation plan as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[0700] Step 13:

[0701] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[0702] Step 14:

[0703] The emotion engine analyzes the user's emotional state during feedback in real time and determines whether further updates are needed.

[0704] Step 15:

[0705] The server regenerates and updates the renovation plan based on the feedback it receives, for example re-rendering the plan with a changed wall color.

[0706] Step 16:

[0707] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[0708] This process allows users to efficiently find their ideal rental property and at the same time receive proposals for renovation plans that take into account the user's emotional state.

[0709] Example 2

[0710] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0711] Conventional floor plan creation tools and rental property search systems often do not take into account the user's individual preferences or emotional state, resulting in proposed properties and plans that do not meet the user's expectations. Furthermore, when proposing renovation plans, there was an insufficient mechanism for fully reflecting user feedback. Therefore, in order to improve user satisfaction, flexible proposals that respond to the user's emotional state are required.

[0712] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0713] In this invention, the server includes an emotion engine means for recognizing the user's emotional state in real time and adjusting the proposed content, a means for regenerating and updating renovation plans based on the feedback and the emotional state, and a means for evaluating the user's emotional state using the emotion engine, thereby making it possible to provide rental property information and propose renovation plans appropriate to the user's emotional state.

[0714] A "user" is an individual or organization that operates the system to create desired floor plans, search for rental property information, or check renovation plans.

[0715] A "floor plan" is a drawing that shows the layout and structure of a building or room, and represents the layout of the rooms and the location of equipment.

[0716] The "server" is a computer system that analyzes data provided by users, extracts floor plan information, and generates rental property information and renovation plans.

[0717] An "emotion engine" is a combination of software or hardware that recognizes a user's emotional state in real time and adjusts suggestions based on that information.

[0718] "Feedback" refers to the opinions and reactions users provide to proposed renovation plans and rental property information, and is information used to readjust the system.

[0719] A "renovation plan" is a specific proposal or plan for renovating or rearranging an existing property to bring it closer to the user's ideals.

[0720] "Three-dimensional images" are images that represent renovation plans and floor plans in three dimensions, and are rendered so that users can visually confirm them.

[0721] A "database" is an information system that organizes and stores information on rental properties and floor plans, and manages it so that it can be searched and retrieved as needed.

[0722] "Analysis" is the process in which the server processes the input floor plan data and images and extracts information such as the layout of rooms and equipment.

[0723] The system of the present invention consists of three main components: a user, a terminal, and a server. The following will specifically explain how to implement the system.

[0724] System Overview

[0725] The system allows users to create and load their ideal floor plan, and the server analyzes it to provide information on similar rental properties and propose renovation plans. Furthermore, by combining it with an emotion engine, the system can recognize the user's emotional state in real time and adjust the proposals accordingly.

[0726] Creating and loading floor plans

[0727] 1. Users create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing them to intuitively arrange the living room, kitchen, bedroom, etc. Users can also upload an image of an existing floor plan.

[0728] 2. The device captures the floor plan data created by the user and the floor plan images uploaded by the user and sends them to the server using a secure communication protocol (e.g., HTTPS).

[0729] Providing rental property information

[0730] 3. The server analyzes the received floor plan data using an image analysis algorithm (e.g., OpenCV) to identify rooms and facilities such as the living room, kitchen, and bathroom.

[0731] 4. Based on the analysis results, the server searches the database and extracts rental property information that matches the conditions specified by the user.

[0732] 5. The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preferences. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis.

[0733] 6. The terminal receives the list of similar rental property information sent from the server and displays it to the user.

[0734] Providing renovation plans

[0735] 7. Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are accepted, including image files and PDFs.

[0736] 8. The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions.

[0737] 9. Based on the analysis results, the server compares the user's ideal floor plan and generates multiple realistic renovation plans, taking into account things like removing rooms, adding walls, and changing fixtures.

[0738] 10. The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine).

[0739] 11. The device displays the rendered 3D image to the user, allowing the user to examine it in detail and get a concrete idea of ​​the renovation plan.

[0740] 12. The user sends feedback about the renovation plan to the server via their device. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture."

[0741] Re-adjusting the plan

[0742] 13. The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed: if the engine indicates a positive emotion, it will make bold design suggestions, but if it indicates a cautious emotion, it will make more conservative suggestions.

[0743] 14. The device displays the reworked renovation plan to the user again, who can review the updated 3D image and make a final decision or provide further feedback.

[0744] Specific examples

[0745] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[0746] Prompt Sentence Examples

[0747] If you were to use a generative AI model to prompt the system for this sequence, you could use a prompt like this:

[0748] The system allows users to create and import their ideal floor plan, provides rental property information that matches it, and proposes renovation plans. Please explain the process in detail.

[0749] The above is an embodiment of the present invention. The purpose of the present invention is to improve user satisfaction by providing suggestions and information according to the user's emotional state through the combination of an emotion engine.

[0750] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0751] Step 1:

[0752] Users create their ideal floor plan using the system's UI. This UI allows them to intuitively arrange living rooms, kitchens, bedrooms, etc. using the drag-and-drop function. Users can also upload existing floor plan images. The input here is the floor plan data created by the user or an uploaded image file, and the output is this data ready to be sent to the server.

[0753] Step 2:

[0754] The device captures floor plan data created by the user and floor plan images uploaded by the user and sends them to the server. A secure communication protocol (e.g., HTTPS) is used for data transmission. The input is the user's floor plan data, and the output is the completion of data transmission to the server.

[0755] Step 3:

[0756] The server analyzes the received floor plan data. This analysis uses an image analysis algorithm (e.g., OpenCV) to identify the layout of rooms and facilities such as living rooms, kitchens, and bathrooms. The input is the floor plan data sent from the device, and the output is the layout information of rooms and facilities as a result of the analysis.

[0757] Step 4:

[0758] The server searches the database based on the analysis results and extracts rental property information that matches the user's specified criteria. The input here is the analysis results, and the output is rental property information based on the criteria.

[0759] Step 5:

[0760] The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preference. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis. The input is rental property information and the user's emotional data, and the output is prioritized rental property information that takes emotions into account.

[0761] Step 6:

[0762] The terminal receives the list of similar rental property information sent from the server and displays it to the user. The input is the rental property information from the server, and the output is a list of rental property information that the user can check.

[0763] Step 7:

[0764] Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are allowed, including image files and PDFs. The input is the user's property floor plan data, and the output is this data ready to be sent to the server.

[0765] Step 8:

[0766] The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. The input is the uploaded floor plan data, and the output is the analysis results, including the current room layout and equipment conditions.

[0767] Step 9:

[0768] Based on the analysis results, the server compares them with the user's ideal floor plan and generates multiple realistic renovation plans. This involves removing rooms, adding walls, changing fixtures, etc. The input is the analysis results and the ideal floor plan, and the output is multiple renovation plans.

[0769] Step 10:

[0770] The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine). The input is the renovation plan, and the output is the 3D image.

[0771] Step 11:

[0772] The terminal receives the rendered 3D image and displays it to the user. The input is the 3D image from the server, and the output is the 3D image that the user can visually confirm.

[0773] Step 12:

[0774] Users send feedback about the renovation plan to the server via their devices. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture." The input is the user's feedback, and the output is the feedback data sent to the server.

[0775] Step 13:

[0776] The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed. If the engine indicates a positive emotion, it makes bold design suggestions, and if it indicates a cautious emotion, it makes more conservative suggestions. The input is the feedback and the user's emotional data, and the output is the readjusted renovation plan.

[0777] Step 14:

[0778] The terminal displays the re-adjusted renovation plan to the user again. The input is the re-adjusted renovation plan from the server, and the output is an updated 3D image that the user can view.

[0779] (Application example 2)

[0780] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0781] Currently, it is difficult to customize the interior layout of an autonomous vehicle based on the preferences and feelings of each individual user. Furthermore, there is a lack of tools to collect vehicle information that closely matches the ideal layout desired by the user or to receive suggestions for renovating existing vehicles. As a result, users face the challenge of finding the optimal interior and layout that suits their preferences.

[0782] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0783] In this invention, the server includes a means for allowing a user to create an ideal spatial layout, a means for loading a layout image close to the ideal, and a means for analyzing the ideal layout or the loaded layout image to extract spatial and equipment conditions, thereby enabling the proposal and customization of a vehicle interior layout based on the user's emotional state. The server also includes a means for acquiring similar property information from a data storage device, a means for displaying the acquired property information to the user, an emotion analysis means for analyzing the user's emotional state in real time, and a means for adjusting the priority of similar property information based on the analysis results. This allows the user to create an ideal vehicle interior layout and receive proposals for optimal property information and renovation plans based on that layout.

[0784] A "user" is a person who operates the system to create an ideal spatial layout or load an existing layout.

[0785] "Spatial layout" refers to drawings or designs that show the arrangement of rooms and facilities.

[0786] A "layout image" is image data that visually represents a spatial layout.

[0787] "Analysis" refers to the process of extracting room and equipment conditions from the input layout image.

[0788] "Space and equipment conditions" refers to layout characteristics such as room arrangement, size, and equipment placement.

[0789] "Property information" refers to detailed data about the spatial layout in which a user is interested.

[0790] A "data storage device" is a device that stores data long-term and allows it to be accessed as needed.

[0791] "Emotional state" refers to a state that indicates the user's state of mind or mood.

[0792] "Emotion analysis means" refers to means for assessing a user's emotional state by analyzing their facial expressions and vocal tone.

[0793] "Means for adjusting priority" refers to means for changing the order and importance of information to be displayed based on the results of sentiment analysis.

[0794] "3D video" refers to digital images that visually recreate objects and environments in three-dimensional space.

[0795] "Visualization" is the process of visually representing data or information.

[0796] "Opinions" are feedback and improvement requests provided by users.

[0797] The system for realizing this invention mainly consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, while the server performs data analysis and plan generation on the backend. In addition, an emotion analysis means analyzes the user's emotional state in real time.

[0798] 1. User-created and loaded spatial layouts

[0799] Users wear a head-mounted display (HMD) and create their ideal spatial layout using an intuitive UI with drag-and-drop functionality. Alternatively, by uploading an image of an existing layout, the system analyzes the image and extracts spatial and facility conditions.

[0800] 2. Layout analysis and provision of similar property information

[0801] The terminal captures the layout created or imported by the user and sends it to the server. The server analyzes the received layout image and performs image analysis processing to identify the conditions of the rooms and facilities. This process uses the OpenCV library. Based on the analysis results, similar property information is searched for in the data storage device and provided to the user. Furthermore, an emotion analysis means evaluates the user's emotional state and adjusts the priority of property information based on the user's preferences.

[0802] 3. Proposal of renovation plan

[0803] When a user uploads an existing property layout, the device sends the layout to the server. The server analyzes the layout to determine the current room arrangement and equipment conditions. Based on the analysis results, a realistic renovation plan is generated by comparing it with the ideal layout. This may include removing walls, adding rooms, or changing equipment. The renovation plan is then rendered as a 3D image using Unity 3D.

[0804] 4. User feedback and plan regeneration

[0805] The user can view the 3D image in detail through the HMD and provide feedback, which is then sent to the server via the device. The server then uses emotion analysis to reassess the user's emotional state and regenerate and update the renovation plan as necessary.

[0806] Hardware and software used

[0807] Head-mounted display (HMD): Use Meta Quest 2, HTC Vive, etc.

[0808] Image Analysis Library: Analyzes layout images using OpenCV.

[0809] 3D video rendering software: Real-time rendering using Unity 3D.

[0810] Sentiment analysis method: Affectiva SDK is used to analyze the user's emotional state in real time.

[0811] Examples and prompts

[0812] As a concrete example, we will show a scenario in which a user creates an interior layout for an autonomous vehicle and receives suggestions for similar properties and renovation plans based on that layout.

[0813] Example prompt sentence:

[0814] "In an interior layout design app for autonomous vehicles, provide a function that allows users to wear an HMD and create, load, and customize their ideal layout. At this time, please add a function that uses emotion analysis means to analyze the user's emotional state in real time and adjust the proposal content based on their emotion."

[0815] This system allows users to create their ideal interior layout and receive optimal property information and renovation plan suggestions based on that.

[0816] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0817] Step 1:

[0818] The user wears a head-mounted display (HMD) and creates an ideal spatial layout using a UI with drag-and-drop functionality. It is also possible to upload an existing layout image. The input is the user's operation data or the uploaded layout image. The output is the generated ideal layout data or the uploaded layout image.

[0819] Step 2:

[0820] The terminal captures layout data created by the user or a layout image loaded by the user and transmits it to the server. The input here is the layout data created or uploaded by the user, and the output is the data transmitted to the server.

[0821] Step 3:

[0822] The server analyzes the received layout image and extracts the spatial and equipment conditions. This process uses the OpenCV library. The input is the received layout image data, and the output is the extracted spatial and equipment condition data. Specifically, the server applies an image analysis algorithm to identify the layout of rooms and equipment.

[0823] Step 4:

[0824] The server searches for similar property information from its data storage device based on the analysis results. The input is the extracted spatial and facility condition data, and the output is similar property information. Specifically, the server executes a query to efficiently search for data that matches the conditions.

[0825] Step 5:

[0826] The server uses emotion analysis to evaluate the user's emotional state in real time and adjust the priority of the retrieved property information. The input is the user's emotional data (facial expression, tone of voice, etc.) and the property information from the search results, and the output is a prioritized property list. Specifically, the server uses an emotion analysis algorithm to dynamically change the display order of properties based on the retrieved data.

[0827] Step 6:

[0828] The information sent from the server is displayed to the user on the terminal. The input is a prioritized property list, and the output is visual information displayed on the HMD. Specifically, the property information is displayed in the user's field of vision using the HMD display.

[0829] Step 7:

[0830] When a user uploads an existing property layout, the terminal sends the layout to the server. The input is the property layout data uploaded by the user, and the output is the data sent to the server.

[0831] Step 8:

[0832] The server analyzes the uploaded layout and determines the current room arrangement and equipment conditions. The input is the layout data sent, and the output is the analysis results data. Specifically, the server again uses the OpenCV library to identify the arrangement of each room in the layout.

[0833] Step 9:

[0834] The server compares the ideal layout with the data and generates a realistic renovation plan. The input is the analysis result data and the ideal layout data, and the output is the renovation plan. Specifically, it uses the generative AI model to create the necessary renovation plan.

[0835] Step 10:

[0836] The server uses Unity 3D to render the generated renovation plan as a 3D image and sends it to the HMD. The input is the renovation plan data, and the output is the 3D image data. Specifically, it uses Unity 3D's rendering function to create a visually detailed 3D image.

[0837] Step 11:

[0838] The user can view the 3D image in detail through the HMD and provide feedback. The input is the 3D image, and the output is the feedback data from the user.

[0839] Step 12:

[0840] The feedback is sent to the server via the device, and the server uses emotion analysis means to reassess the user's emotional state and regenerate and update the renovation plan as necessary. The input is the user's feedback data and emotion data, and the output is a regenerated renovation plan. Specifically, the renovation plan is adjusted and updated using an emotion analysis algorithm and a generative AI model.

[0841] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0842] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0843] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0844] [Third embodiment]

[0845] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0846] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0847] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0848] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0849] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0850] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0851] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0852] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0853] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0854] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0855] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0856] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0857] The system of the present invention allows users to create their ideal floor plan or load an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring a property they are planning to purchase or currently living in closer to their ideal floor plan.

[0858] Overall system overview

[0859] The system consists of three main components: the user, the terminal, and the server. The user mainly operates the terminal, and the server performs data analysis and plan generation in the backend.

[0860] User-created and imported floor plans

[0861] 1. User: Create your ideal floor plan through the system's UI, which features drag-and-drop functionality, allowing you to intuitively manipulate the layout and size of rooms.

[0862] 2. Terminal: Captures the floor plan created by the user and sends it to the server. Users can also upload images of existing floor plans.

[0863] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[0864] Providing information on similar rental properties

[0865] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[0866] 5. Terminal: The user checks the list of similar rental properties sent from the server and displays detailed information (e.g., floor plan, rent, address).

[0867] Renovation plan proposal

[0868] 6. User: Upload floor plans of properties you currently live in or are considering purchasing.

[0869] 7. Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. It then generates a realistic renovation plan, which typically includes specific modifications such as removing walls or adding new rooms.

[0870] 8. Server: The generated renovation plan is rendered as a 3D image, generating a concrete image including the interior and furniture layout.

[0871] Review and feedback on the proposed plan

[0872] 9. Terminal: The user can view a 3D image of the proposed renovation plan, including details such as the interior design, furniture layout, and room color scheme.

[0873] 10. User: Provides feedback and sends specific requests to the server, such as "I want to change the color of the walls" or "Can I rearrange this furniture?"

[0874] 11. Server: Receive feedback, re-render, and update / re-propose the renovation plan.

[0875] 12. Device: Redisplay the updated plan to the user for final confirmation.

[0876] Specific examples

[0877] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[0878] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout.

[0879] If the user checks the 3D image and sends feedback that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again, thus finally providing the user with a satisfactory renovation plan.

[0880] The present invention provides a method that allows users to efficiently realize their ideal floor plan using such a system.

[0881] The processing flow will be explained below.

[0882] Step 1:

[0883] Users can create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing intuitive placement and size of the devices. It is also possible to upload an image of an existing floor plan.

[0884] Step 2:

[0885] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[0886] Step 3:

[0887] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[0888] Step 4:

[0889] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[0890] Step 5:

[0891] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[0892] Step 6:

[0893] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[0894] Step 7:

[0895] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[0896] Step 8:

[0897] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[0898] Step 9:

[0899] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[0900] Step 10:

[0901] The server renders the generated renovation plan as a 3D image, allowing users to visualize the layout of furniture and interior décor in concrete terms.

[0902] Step 11:

[0903] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[0904] Step 12:

[0905] The user sends feedback about the renovation plan to the server via their device, for example, by inputting requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[0906] Step 13:

[0907] Based on the feedback received by the server, the renovation plan is regenerated and updated, for example by re-rendering a plan with a different wall color.

[0908] Step 14:

[0909] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[0910] This process allows users to efficiently find their ideal rental property and also obtain specific renovation plans to bring the layout closer to their ideal one.

[0911] Example 1

[0912] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0913] Conventional floor plan creation and analysis systems have the drawback of requiring a lot of time and effort when users create their ideal floor plan or obtain rental property information and renovation plans based on existing floor plans. Furthermore, when proposing renovation plans, the system lacks the technology to flexibly update plans based on user feedback, resulting in an unsatisfactory user experience.

[0914] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0915] In this invention, the server includes: means for allowing a user to create an ideal floor plan; means for loading an image of a floor plan close to the ideal; means for analyzing the ideal floor plan or the loaded floor plan image to extract room and equipment conditions; means for retrieving similar rental property information from a database based on the conditions; means for displaying the retrieved rental property information to the user; means for receiving feedback from the user; means for updating the proposal based on the feedback; means for generating and displaying a 3D image of the proposed interior and furniture arrangement; means for loading a floor plan of a property to be purchased or currently occupied; means for generating a realistically feasible renovation plan based on the floor plan of the property and the ideal floor plan; means for rendering the generated renovation plan as a 3D image; means for the user to review the 3D image and provide feedback; and means for regenerating and updating the renovation plan based on the feedback. This enables users to intuitively and efficiently create their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[0916] 1. An "ideal floor plan" is a drawing that reflects the user's desired room layout and size.

[0917] 2. "Floor plan image" is an image file showing the layout of rooms in an existing property.

[0918] 3. "Room and facility conditions" refers to information about the layout of rooms and their facilities, such as the living room, kitchen, bedrooms, and bathrooms, that appear on the floor plan.

[0919] 4. "Database" means an information system that stores information on various rental properties.

[0920] 5. "Three-dimensional images" are images that have physical depth and a sense of three-dimensionality and are visually consistent.

[0921] 6. A "renovation plan" is a specific proposal for renovating an existing property to bring it closer to the user's ideals.

[0922] 7. "Feedback" means any opinions or comments regarding suggestions or requested changes provided by a User.

[0923] 8. "Rendering" is the process of generating three-dimensional images using computer graphics.

[0924] MODE FOR CARRYING OUT THE INVENTION

[0925] The system of the present invention consists of three main components: a user, a terminal, and a server. Each component and its function will be explained in detail below.

[0926] User-created and imported floor plans

[0927] 1. User: The user creates their ideal floor plan through the system's UI. This UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. For example, the user can place the living room in the center, the kitchen on the right, and the bedroom on the left.

[0928] 2. Terminal: The terminal captures the floor plan created by the user and sends it to the server as image data. The user can also select and upload an existing floor plan image. The terminal performs the file upload process and sends the floor plan data to the server according to the user's operation.

[0929] 3. Server: The server analyzes the received floor plan image. It uses image processing libraries such as OpenCV and deep learning libraries such as TensorFlow and Keras to classify the room type. For example, it extracts information such as living room, kitchen, bedroom, and bathroom.

[0930] Providing information on similar rental properties

[0931] 1. Server: The server searches the database based on the analysis results and extracts rental property information that matches the conditions of the floor plan created by the user. It uses SQL queries to search the property information in the database and identifies properties that meet the conditions. Conditions include the number of rooms, room layout, and facility layout.

[0932] 2. Terminal: The terminal receives the list of similar rental properties sent from the server and displays it to the user. This list includes information such as floor plans, rent, and address. Front-end technologies such as React and Angular can be used to display the details.

[0933] Renovation plan proposal

[0934] 1. User: A user uploads a floor plan of a property they are currently living in or planning to purchase. For example, they click the "Upload Floor Plan" button on the property information page and select a file.

[0935] 2. Server: The server analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment and generates a realistic renovation plan. For example, it makes specific renovation suggestions, such as demolishing a wall to expand the living room.

[0936] 3. Server: The generated renovation plan is rendered as a 3D image. Blender and Unreal Engine are used for rendering, and the 3D image is generated and provided to the user. The generated 3D image includes the interior and furniture layout.

[0937] Review and feedback on the proposed plan

[0938] 1. Terminal: The terminal allows users to view a 3D image of the proposed renovation plan. Using the 3D viewer, users can freely change the viewpoint.

[0939] 2. User: The user provides feedback and sends a specific request to the server, for example, "I want to change the color of the walls." Feedback is provided through the UI, for example, by text input.

[0940] 3. Server: The server receives feedback from the user and re-renders the renovation plan. The updated plan is then regenerated as a 3D image and provided to the user.

[0941] Specific examples

[0942] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[0943] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it may generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout. If the user reviews the 3D image and then sends feedback indicating that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again.

[0944] Example prompts for generative AI models

[0945] "Analyze the floor plan below to determine the layout of the living room, kitchen, and bedrooms, then search for rental properties that meet similar criteria. Then, display them in a list."

[0946] The system of this invention enables users to efficiently realize their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[0947] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0948] Specific processing flow of the system program

[0949] User-created and imported floor plans

[0950] Step 1:

[0951] User: Accesses the system's UI and creates an ideal floor plan. The user uses the drag-and-drop function to determine the shape, layout, and size of the rooms.

[0952] Input: User actions

[0953] Output: Ideal floor plan

[0954] Step 2:

[0955] Terminal: Captures floor plans created by users and sends them to the server as image data. Users can also select and upload existing floor plan images.

[0956] Input: Ideal floor plan, existing floor plan image

[0957] Output: Floor plan image data

[0958] Step 3:

[0959] Server: Analyzes the received floor plan image. Image processing libraries such as OpenCV are used for image analysis, and deep learning libraries such as TensorFlow and Keras are used to classify room types. The layout and type of rooms (e.g., living room, kitchen, bedroom) are identified, and relevant information is extracted.

[0960] Input: Floor plan image data

[0961] Output: Analysis results (room and equipment conditions)

[0962] Providing information on similar rental properties

[0963] Step 4:

[0964] Server: Searches the database based on the analysis results and extracts rental property information that matches the floor plan created by the user. Searches the database for property information using SQL queries to identify properties that match the criteria.

[0965] Input: Analysis results (room and equipment conditions)

[0966] Output: List of similar rental properties

[0967] Step 5:

[0968] Terminal: The user receives a list of similar rental properties sent from the server and checks them on the UI. The list includes information such as floor plans, rents, and addresses, and includes a link to display more detailed information. The display is done using front-end technologies (e.g., React or Angular).

[0969] Input: List of similar rental properties

[0970] Output: The detailed information screen that the user sees

[0971] Renovation plan proposal

[0972] Step 6:

[0973] Users: Upload floor plans for properties they currently live in or are considering purchasing. Click the "Upload Floor Plan" button on the property information page, select the file, and submit.

[0974] Input: Image data of the property floor plan

[0975] Output: Uploaded data

[0976] Step 7:

[0977] Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment, and generates a realistic renovation plan. It then creates specific renovation proposals (e.g., moving walls, rearranging furniture).

[0978] Input: Image data of the property floor plan, information on the ideal floor plan

[0979] Output: Generated renovation plan

[0980] Step 8:

[0981] Server: The generated renovation plan is rendered as a 3D image. Using Blender and Unreal Engine, a concrete visual image is created and provided as a 3D image including the interior and furniture layout.

[0982] Input: Generated renovation plan

[0983] Output: 3D video

[0984] Review and feedback on the proposed plan

[0985] Step 9:

[0986] Terminal: The user views a 3D image of the proposed renovation plan. Using a 3D viewer displayed on a web browser, the user can freely change the viewpoint to view the interior.

[0987] Input: 3D video

[0988] Output: Confirmation screen

[0989] Step 10:

[0990] User: The user provides feedback and sends a specific change request to the server, for example, "I want to change the wall color." They enter the change request in text form through the UI and press the submit button.

[0991] Input: User feedback

[0992] Output: Feedback data

[0993] Step 11:

[0994] Server: Receives feedback, re-renders, and updates the renovation plan. Generates new 3D images based on the feedback using Blender or similar software, and provides them to the user again.

[0995] Input: Feedback data

[0996] Output: 3D image of the updated renovation plan

[0997] Step 12:

[0998] On the device: The updated plan is displayed again to the user, who can then review the proposed plan again and repeat the process until they are finally satisfied.

[0999] Input: Updated 3D image

[1000] Output: Final confirmation screen

[1001] (Application example 1)

[1002] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1003] Conventional floor plan creation and renovation plan generation systems have limited means for users to specifically check the image of their ideal space, making it difficult to reflect and confirm feedback. Furthermore, the lack of an interface that reflects user feedback in real time and allows intuitive operation has led to low satisfaction with the final plan.

[1004] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1005] In this invention, the server includes means for allowing a user to create an ideal floor plan, means for loading an image of a floor plan close to the ideal, means for analyzing the ideal floor plan or the loaded floor plan image and extracting room and facility conditions, means for retrieving similar real estate property information from a database based on the conditions, means for displaying the retrieved real estate property information to the user, and means for the user to check and operate the renovation plan in three-dimensional space using a virtual visual device, thereby enabling feedback to be reflected in real time and intuitive operation.

[1006] "User" means an individual or organization that uses the System to create floor plans and view and manipulate renovation plans.

[1007] An "ideal floor plan" is a drawing that expresses the layout of the building and the arrangement of rooms that the user desires.

[1008] "Loading" means inputting an existing floor plan image into the system and having it recognized as data.

[1009] "Analysis" refers to the act of extracting information about rooms and facilities from the loaded floor plan image and classifying and recognizing them based on certain conditions.

[1010] "Room and facility conditions" refers to information about the location, size, shape, and facility layout of each room in the floor plan.

[1011] A "database" is a collection of information that stores and makes searchable similar real estate property information based on the user's criteria.

[1012] "Real estate property information" refers to attribute information of actual buildings that are available for rent or purchase, including floor plans, rent, location, etc.

[1013] A "virtual visual device" is a device that allows users to view and manipulate floor plans and renovation plans in three-dimensional space.

[1014] A "three-dimensional image" is a three-dimensional image that has a three-dimensional appearance and can be visually perceived by a user.

[1015] "Feedback" refers to opinions and requests from users, and includes information that includes instructions for adjusting or changing the renovation plan.

[1016] A "generative AI model" is an algorithm that receives user feedback and automatically generates and updates floor plans and renovation plans.

[1017] A "prompt" is text that describes specific instructions or requests that a user inputs to a generative AI model.

[1018] MODE FOR CARRYING OUT THE INVENTION

[1019] Overall structure

[1020] The system of the present invention consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, and the server performs data analysis and plan generation on the back end.

[1021] User-created and imported floor plans

[1022] Users create their ideal floor plan through the system's user interface (UI). The UI features a drag-and-drop function, allowing intuitive manipulation of room layout and size. Users can also upload images of existing floor plans. The device captures the floor plan created by the user and sends it to the server.

[1023] Data analysis by server

[1024] The server analyzes the received floor plan image and extracts the room and facility conditions, for example, identifying the living room, kitchen, bathroom, etc. This analysis uses an image analysis algorithm, such as deep learning technology.

[1025] Providing rental property information

[1026] Based on the analysis results, the server searches the database to extract real estate information that matches the user's specified criteria. These criteria include the number of rooms, room layout, and facility layout. The retrieved real estate information is sent to the terminal, where the user can view it as a list.

[1027] 3D display using virtual visual equipment

[1028] Users can wear virtual vision devices (e.g., smart glasses) and experience the renovation plan in a virtual three-dimensional space. The server then renders the renovation plan as a three-dimensional image, generating a concrete image including the interior and furniture layout.

[1029] Feedback and regeneration processes

[1030] The user views the 3D image through a virtual viewing device and provides specific feedback, such as "I want to change the wall color to red." This feedback is sent to the server in the form of a prompt. The server then uses a generative AI model to regenerate and update the renovation plan based on this feedback.

[1031] Specific examples

[1032] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK real estate properties that meet similar criteria and provides them to the user as a list. Similarly, if a user plans to purchase a 3LDK apartment and uploads a floor plan for that property, the server analyzes the floor plan, understands the current state of the apartment, and generates a renovation plan for renovating it into the ideal 2LDK apartment. For example, it generates a plan to remove a wall to create a larger living space or add new storage space.

[1033] An example of a prompt is "Please change the wall color to FF0000 (red)." Based on this instruction, the server updates the renovation plan. The updated plan is again provided to the user as a 3D image, allowing the user to immediately confirm the changes.

[1034] Hardware and software used

[1035] The system of the present invention uses a server, a user device, and a virtual visual device (such as smart glasses). The software includes THREE.js (for 3D rendering), WebRTC (for real-time rendering and user interaction), and a generative AI model (to generate and update plans based on user feedback).

[1036] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1037] Step 1:

[1038] Users create their ideal floor plan using the device's user interface (UI). The drag-and-drop function allows intuitive manipulation of room layout and size. The input is UI data that the user manipulates, and the output is floor plan data.

[1039] Step 2:

[1040] The device captures the ideal floor plan data created by the user and sends it to the server. This process converts the UI data into images or other formats, and then makes an API call to send it to the server. The input is the floor plan data, and the output is the data sent to the server.

[1041] Step 3:

[1042] The server receives the floor plan data and analyzes it using image analysis algorithms such as deep learning technology, thereby extracting the room and equipment conditions. The input is the floor plan data, and the output is the analysis results including the room and equipment conditions.

[1043] Step 4:

[1044] Based on the analysis results, the server searches the database and extracts real estate property information that matches the user's specified criteria. This process searches for suitable properties in the database using criteria such as the number of rooms, room layout, and facility layout. The input is the analysis result criteria data, and the output is similar real estate property information.

[1045] Step 5:

[1046] The server sends the extracted property information to the terminal, which displays the information in a list format to the user. The user can then check the list and view detailed information (e.g., floor plan, rent, address). The input is property information from the server, and the output is the information displayed on the user's terminal.

[1047] Step 6:

[1048] Users wear virtual vision devices (such as smart glasses) to experience renovation plans in a three-dimensional space. Through the virtual vision device, users can visually confirm the floor plan in three-dimensional images. The input is the user's wearing information and the virtual vision device's setting data, and the output is a three-dimensional image.

[1049] Step 7:

[1050] The user checks the 3D image provided through the virtual visual device and provides specific feedback, such as "I want to change the color of the wall to red." This feedback is sent from the terminal to the server in the form of a prompt sentence. The input is the user's feedback prompt sentence, and the output is the prompt sentence data sent from the terminal to the server.

[1051] Step 8:

[1052] The server uses a generative AI model based on the received prompt sentence to regenerate and update the renovation plan. The input is the prompt sentence data and the existing renovation plan, and the output is the updated renovation plan.

[1053] Step 9:

[1054] The server renders the updated renovation plan again as a 3D image and provides it to the user via the terminal and virtual viewing device. The input is the updated renovation plan data, and the output is the 3D image displayed to the user.

[1055] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1056] The system of the present invention allows users to create their ideal floor plan or import an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring the floor plan of a property they are planning to purchase or currently living in closer to their ideal floor plan. Furthermore, by combining it with an emotion engine, the system also has the function of recognizing the user's emotional state in real time and adjusting the proposal content based on that.

[1057] Overall system overview

[1058] The system consists of three main components: the user, the device, and the server. The user mainly operates the device, while the server performs data analysis and plan generation in the backend. The emotion engine also analyzes the user's emotional state in real time.

[1059] User-created and imported floor plans

[1060] 1. User: Create your ideal floor plan through the system's UI. The UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. You can also upload an image of an existing floor plan.

[1061] 2. Device: Captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[1062] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[1063] Providing information on similar rental properties

[1064] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[1065] 5. Server: Using the user's emotion engine, search results are prioritized based on the user's preferences. The emotion engine evaluates the user's emotions by analyzing past choices, current facial expressions, and voice.

[1066] 6. Terminal: The user is presented with a list of similar rental property information sent from the server. The user can review this list and view detailed information (e.g., floor plan, rent, address).

[1067] Renovation plan proposal

[1068] 7. User: Upload floor plans of properties you currently live in or are considering purchasing.

[1069] 8. Server: Analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. Based on the analysis results, evaluates the possibility of renovation.

[1070] 9. Server: Compares the user's ideal floor plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[1071] 10. Server: The generated renovation plan is rendered as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[1072] 11. Terminal: Displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[1073] Review and feedback on the proposed plan

[1074] 12. User: Sends feedback on the renovation plan to the server via the terminal. For example, inputs specific requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[1075] 13. Server: The emotion engine analyzes the user's emotional state at the time of feedback and determines whether further adjustments are necessary. Based on the received feedback, the renovation plan is regenerated and updated.

[1076] 14. Device: The updated renovation plan is displayed again to the user, who can then review the 3D image again and make a final decision or provide further feedback.

[1077] Specific examples

[1078] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[1079] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is shown a concrete visual of the interior and furniture layout. The emotion engine analyzes the user's reactions to these suggestions in real time and presents the optimal plan.

[1080] If a user checks the 3D image and then sends feedback requesting a change to the wall color, the emotion engine will analyze the user's emotional state at the time of the feedback and further adjust the suggestions as necessary. For example, it may suggest bolder design ideas to a user who expresses positive emotions, and more conservative ideas to a user who expresses caution.

[1081] By combining emotion engines in this way, the present invention is able to provide optimal rental property information and propose renovation plans that are tailored to the user's emotional state.

[1082] The processing flow will be explained below.

[1083] Step 1:

[1084] Users create their ideal floor plan using the system's UI, which features a drag-and-drop function that allows intuitive configuration of room placement and size. Users can also upload images of existing floor plans.

[1085] Step 2:

[1086] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[1087] Step 3:

[1088] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[1089] Step 4:

[1090] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[1091] Step 5:

[1092] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[1093] Step 6:

[1094] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[1095] Step 7:

[1096] The emotion engine recognizes the user's real-time emotions and assesses their interests and preferences by analyzing their facial expressions and voice.

[1097] Step 8:

[1098] The server receives feedback from the emotion engine and adjusts the prioritization of rental listings to display based on customer preferences, for example, displaying properties that the user has expressed interest in at the top of the list.

[1099] Step 9:

[1100] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[1101] Step 10:

[1102] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[1103] Step 11:

[1104] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[1105] Step 12:

[1106] The server renders the generated renovation plan as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[1107] Step 13:

[1108] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[1109] Step 14:

[1110] The emotion engine analyzes the user's emotional state during feedback in real time and determines whether further updates are needed.

[1111] Step 15:

[1112] The server regenerates and updates the renovation plan based on the feedback it receives, for example re-rendering the plan with a changed wall color.

[1113] Step 16:

[1114] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[1115] This process allows users to efficiently find their ideal rental property and at the same time receive proposals for renovation plans that take into account the user's emotional state.

[1116] Example 2

[1117] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1118] Conventional floor plan creation tools and rental property search systems often do not take into account the user's individual preferences or emotional state, resulting in proposed properties and plans that do not meet the user's expectations. Furthermore, when proposing renovation plans, there was an insufficient mechanism for fully reflecting user feedback. Therefore, in order to improve user satisfaction, flexible proposals that respond to the user's emotional state are required.

[1119] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1120] In this invention, the server includes an emotion engine means for recognizing the user's emotional state in real time and adjusting the proposed content, a means for regenerating and updating renovation plans based on the feedback and the emotional state, and a means for evaluating the user's emotional state using the emotion engine, thereby making it possible to provide rental property information and propose renovation plans appropriate to the user's emotional state.

[1121] A "user" is an individual or organization that operates the system to create desired floor plans, search for rental property information, or check renovation plans.

[1122] A "floor plan" is a drawing that shows the layout and structure of a building or room, and represents the layout of the rooms and the location of equipment.

[1123] The "server" is a computer system that analyzes data provided by users, extracts floor plan information, and generates rental property information and renovation plans.

[1124] An "emotion engine" is a combination of software or hardware that recognizes a user's emotional state in real time and adjusts suggestions based on that information.

[1125] "Feedback" refers to the opinions and reactions users provide to proposed renovation plans and rental property information, and is information used to readjust the system.

[1126] A "renovation plan" is a specific proposal or plan for renovating or rearranging an existing property to bring it closer to the user's ideals.

[1127] "Three-dimensional images" are images that represent renovation plans and floor plans in three dimensions, and are rendered so that users can visually confirm them.

[1128] A "database" is an information system that organizes and stores information on rental properties and floor plans, and manages it so that it can be searched and retrieved as needed.

[1129] "Analysis" is the process in which the server processes the input floor plan data and images and extracts information such as the layout of rooms and equipment.

[1130] The system of the present invention consists of three main components: a user, a terminal, and a server. The following will specifically explain how to implement the system.

[1131] System Overview

[1132] The system allows users to create and load their ideal floor plan, and the server analyzes it to provide information on similar rental properties and propose renovation plans. Furthermore, by combining it with an emotion engine, the system can recognize the user's emotional state in real time and adjust the proposals accordingly.

[1133] Creating and loading floor plans

[1134] 1. Users create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing them to intuitively arrange the living room, kitchen, bedroom, etc. Users can also upload an image of an existing floor plan.

[1135] 2. The device captures the floor plan data created by the user and the floor plan images uploaded by the user and sends them to the server using a secure communication protocol (e.g., HTTPS).

[1136] Providing rental property information

[1137] 3. The server analyzes the received floor plan data using an image analysis algorithm (e.g., OpenCV) to identify rooms and facilities such as the living room, kitchen, and bathroom.

[1138] 4. Based on the analysis results, the server searches the database and extracts rental property information that matches the conditions specified by the user.

[1139] 5. The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preferences. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis.

[1140] 6. The terminal receives the list of similar rental property information sent from the server and displays it to the user.

[1141] Providing renovation plans

[1142] 7. Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are accepted, including image files and PDFs.

[1143] 8. The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions.

[1144] 9. Based on the analysis results, the server compares the user's ideal floor plan and generates multiple realistic renovation plans, taking into account things like removing rooms, adding walls, and changing fixtures.

[1145] 10. The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine).

[1146] 11. The device displays the rendered 3D image to the user, allowing the user to examine it in detail and get a concrete idea of ​​the renovation plan.

[1147] 12. The user sends feedback about the renovation plan to the server via their device. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture."

[1148] Re-adjusting the plan

[1149] 13. The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed: if the engine indicates a positive emotion, it will make bold design suggestions, but if it indicates a cautious emotion, it will make more conservative suggestions.

[1150] 14. The device displays the reworked renovation plan to the user again, who can review the updated 3D image and make a final decision or provide further feedback.

[1151] Specific examples

[1152] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[1153] Prompt Sentence Examples

[1154] If you were to use a generative AI model to prompt the system for this sequence, you could use a prompt like this:

[1155] The system allows users to create and import their ideal floor plan, provides rental property information that matches it, and proposes renovation plans. Please explain the process in detail.

[1156] The above is an embodiment of the present invention. The purpose of the present invention is to improve user satisfaction by providing suggestions and information according to the user's emotional state through the combination of an emotion engine.

[1157] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1158] Step 1:

[1159] Users create their ideal floor plan using the system's UI. This UI allows them to intuitively arrange living rooms, kitchens, bedrooms, etc. using the drag-and-drop function. Users can also upload existing floor plan images. The input here is the floor plan data created by the user or an uploaded image file, and the output is this data ready to be sent to the server.

[1160] Step 2:

[1161] The device captures floor plan data created by the user and floor plan images uploaded by the user and sends them to the server. A secure communication protocol (e.g., HTTPS) is used for data transmission. The input is the user's floor plan data, and the output is the completion of data transmission to the server.

[1162] Step 3:

[1163] The server analyzes the received floor plan data. This analysis uses an image analysis algorithm (e.g., OpenCV) to identify the layout of rooms and facilities such as living rooms, kitchens, and bathrooms. The input is the floor plan data sent from the device, and the output is the layout information of rooms and facilities as a result of the analysis.

[1164] Step 4:

[1165] The server searches the database based on the analysis results and extracts rental property information that matches the user's specified criteria. The input here is the analysis results, and the output is rental property information based on the criteria.

[1166] Step 5:

[1167] The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preference. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis. The input is rental property information and the user's emotional data, and the output is prioritized rental property information that takes emotions into account.

[1168] Step 6:

[1169] The terminal receives the list of similar rental property information sent from the server and displays it to the user. The input is the rental property information from the server, and the output is a list of rental property information that the user can check.

[1170] Step 7:

[1171] Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are allowed, including image files and PDFs. The input is the user's property floor plan data, and the output is this data ready to be sent to the server.

[1172] Step 8:

[1173] The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. The input is the uploaded floor plan data, and the output is the analysis results, including the current room layout and equipment conditions.

[1174] Step 9:

[1175] Based on the analysis results, the server compares them with the user's ideal floor plan and generates multiple realistic renovation plans. This involves removing rooms, adding walls, changing fixtures, etc. The input is the analysis results and the ideal floor plan, and the output is multiple renovation plans.

[1176] Step 10:

[1177] The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine). The input is the renovation plan, and the output is the 3D image.

[1178] Step 11:

[1179] The terminal receives the rendered 3D image and displays it to the user. The input is the 3D image from the server, and the output is the 3D image that the user can visually confirm.

[1180] Step 12:

[1181] Users send feedback about the renovation plan to the server via their devices. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture." The input is the user's feedback, and the output is the feedback data sent to the server.

[1182] Step 13:

[1183] The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed. If the engine indicates a positive emotion, it makes bold design suggestions, and if it indicates a cautious emotion, it makes more conservative suggestions. The input is the feedback and the user's emotional data, and the output is the readjusted renovation plan.

[1184] Step 14:

[1185] The terminal displays the re-adjusted renovation plan to the user again. The input is the re-adjusted renovation plan from the server, and the output is an updated 3D image that the user can view.

[1186] (Application example 2)

[1187] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1188] Currently, it is difficult to customize the interior layout of an autonomous vehicle based on the preferences and feelings of each individual user. Furthermore, there is a lack of tools to collect vehicle information that closely matches the ideal layout desired by the user or to receive suggestions for renovating existing vehicles. As a result, users face the challenge of finding the optimal interior and layout that suits their preferences.

[1189] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1190] In this invention, the server includes a means for allowing a user to create an ideal spatial layout, a means for loading a layout image close to the ideal, and a means for analyzing the ideal layout or the loaded layout image to extract spatial and equipment conditions, thereby enabling the proposal and customization of a vehicle interior layout based on the user's emotional state. The server also includes a means for acquiring similar property information from a data storage device, a means for displaying the acquired property information to the user, an emotion analysis means for analyzing the user's emotional state in real time, and a means for adjusting the priority of similar property information based on the analysis results. This allows the user to create an ideal vehicle interior layout and receive proposals for optimal property information and renovation plans based on that layout.

[1191] A "user" is a person who operates the system to create an ideal spatial layout or load an existing layout.

[1192] "Spatial layout" refers to drawings or designs that show the arrangement of rooms and facilities.

[1193] A "layout image" is image data that visually represents a spatial layout.

[1194] "Analysis" refers to the process of extracting room and equipment conditions from the input layout image.

[1195] "Space and equipment conditions" refers to layout characteristics such as room arrangement, size, and equipment placement.

[1196] "Property information" refers to detailed data about the spatial layout in which a user is interested.

[1197] A "data storage device" is a device that stores data long-term and allows it to be accessed as needed.

[1198] "Emotional state" refers to a state that indicates the user's state of mind or mood.

[1199] "Emotion analysis means" refers to means for assessing a user's emotional state by analyzing their facial expressions and vocal tone.

[1200] "Means for adjusting priority" refers to means for changing the order and importance of information to be displayed based on the results of sentiment analysis.

[1201] "3D video" refers to digital images that visually recreate objects and environments in three-dimensional space.

[1202] "Visualization" is the process of visually representing data or information.

[1203] "Opinions" are feedback and improvement requests provided by users.

[1204] The system for realizing this invention mainly consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, while the server performs data analysis and plan generation on the backend. In addition, an emotion analysis means analyzes the user's emotional state in real time.

[1205] 1. User-created and loaded spatial layouts

[1206] Users wear a head-mounted display (HMD) and create their ideal spatial layout using an intuitive UI with drag-and-drop functionality. Alternatively, by uploading an image of an existing layout, the system analyzes the image and extracts spatial and facility conditions.

[1207] 2. Layout analysis and provision of similar property information

[1208] The terminal captures the layout created or imported by the user and sends it to the server. The server analyzes the received layout image and performs image analysis processing to identify the conditions of the rooms and facilities. This process uses the OpenCV library. Based on the analysis results, similar property information is searched for in the data storage device and provided to the user. Furthermore, an emotion analysis means evaluates the user's emotional state and adjusts the priority of property information based on the user's preferences.

[1209] 3. Proposal of renovation plan

[1210] When a user uploads an existing property layout, the device sends the layout to the server. The server analyzes the layout to determine the current room arrangement and equipment conditions. Based on the analysis results, a realistic renovation plan is generated by comparing it with the ideal layout. This may include removing walls, adding rooms, or changing equipment. The renovation plan is then rendered as a 3D image using Unity 3D.

[1211] 4. User feedback and plan regeneration

[1212] The user can view the 3D image in detail through the HMD and provide feedback, which is then sent to the server via the device. The server then uses emotion analysis to reassess the user's emotional state and regenerate and update the renovation plan as necessary.

[1213] Hardware and software used

[1214] Head-mounted display (HMD): Use Meta Quest 2, HTC Vive, etc.

[1215] Image Analysis Library: Analyzes layout images using OpenCV.

[1216] 3D video rendering software: Real-time rendering using Unity 3D.

[1217] Sentiment analysis method: Affectiva SDK is used to analyze the user's emotional state in real time.

[1218] Examples and prompts

[1219] As a concrete example, we will show a scenario in which a user creates an interior layout for an autonomous vehicle and receives suggestions for similar properties and renovation plans based on that layout.

[1220] Example prompt sentence:

[1221] "In an interior layout design app for autonomous vehicles, provide a function that allows users to wear an HMD and create, load, and customize their ideal layout. At this time, please add a function that uses emotion analysis means to analyze the user's emotional state in real time and adjust the proposal content based on their emotion."

[1222] This system allows users to create their ideal interior layout and receive optimal property information and renovation plan suggestions based on that.

[1223] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1224] Step 1:

[1225] The user wears a head-mounted display (HMD) and creates an ideal spatial layout using a UI with drag-and-drop functionality. It is also possible to upload an existing layout image. The input is the user's operation data or the uploaded layout image. The output is the generated ideal layout data or the uploaded layout image.

[1226] Step 2:

[1227] The terminal captures layout data created by the user or a layout image loaded by the user and transmits it to the server. The input here is the layout data created or uploaded by the user, and the output is the data transmitted to the server.

[1228] Step 3:

[1229] The server analyzes the received layout image and extracts the spatial and equipment conditions. This process uses the OpenCV library. The input is the received layout image data, and the output is the extracted spatial and equipment condition data. Specifically, the server applies an image analysis algorithm to identify the layout of rooms and equipment.

[1230] Step 4:

[1231] The server searches for similar property information from its data storage device based on the analysis results. The input is the extracted spatial and facility condition data, and the output is similar property information. Specifically, the server executes a query to efficiently search for data that matches the conditions.

[1232] Step 5:

[1233] The server uses emotion analysis to evaluate the user's emotional state in real time and adjust the priority of the retrieved property information. The input is the user's emotional data (facial expression, tone of voice, etc.) and the property information from the search results, and the output is a prioritized property list. Specifically, the server uses an emotion analysis algorithm to dynamically change the display order of properties based on the retrieved data.

[1234] Step 6:

[1235] The information sent from the server is displayed to the user on the terminal. The input is a prioritized property list, and the output is visual information displayed on the HMD. Specifically, the property information is displayed in the user's field of vision using the HMD display.

[1236] Step 7:

[1237] When a user uploads an existing property layout, the terminal sends the layout to the server. The input is the property layout data uploaded by the user, and the output is the data sent to the server.

[1238] Step 8:

[1239] The server analyzes the uploaded layout and determines the current room arrangement and equipment conditions. The input is the layout data sent, and the output is the analysis results data. Specifically, the server again uses the OpenCV library to identify the arrangement of each room in the layout.

[1240] Step 9:

[1241] The server compares the ideal layout with the data and generates a realistic renovation plan. The input is the analysis result data and the ideal layout data, and the output is the renovation plan. Specifically, it uses the generative AI model to create the necessary renovation plan.

[1242] Step 10:

[1243] The server uses Unity 3D to render the generated renovation plan as a 3D image and sends it to the HMD. The input is the renovation plan data, and the output is the 3D image data. Specifically, it uses Unity 3D's rendering function to create a visually detailed 3D image.

[1244] Step 11:

[1245] The user can view the 3D image in detail through the HMD and provide feedback. The input is the 3D image, and the output is the feedback data from the user.

[1246] Step 12:

[1247] The feedback is sent to the server via the device, and the server uses emotion analysis means to reassess the user's emotional state and regenerate and update the renovation plan as necessary. The input is the user's feedback data and emotion data, and the output is a regenerated renovation plan. Specifically, the renovation plan is adjusted and updated using an emotion analysis algorithm and a generative AI model.

[1248] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1249] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1250] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1251] [Fourth embodiment]

[1252] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1253] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1254] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1255] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1256] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1257] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1258] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1259] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1260] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1261] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1262] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1263] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1264] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1265] The system of the present invention allows users to create their ideal floor plan or load an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring a property they are planning to purchase or currently living in closer to their ideal floor plan.

[1266] Overall system overview

[1267] The system consists of three main components: the user, the terminal, and the server. The user mainly operates the terminal, and the server performs data analysis and plan generation in the backend.

[1268] User-created and imported floor plans

[1269] 1. User: Create your ideal floor plan through the system's UI, which features drag-and-drop functionality, allowing you to intuitively manipulate the layout and size of rooms.

[1270] 2. Terminal: Captures the floor plan created by the user and sends it to the server. Users can also upload images of existing floor plans.

[1271] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[1272] Providing information on similar rental properties

[1273] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[1274] 5. Terminal: The user checks the list of similar rental properties sent from the server and displays detailed information (e.g., floor plan, rent, address).

[1275] Renovation plan proposal

[1276] 6. User: Upload floor plans of properties you currently live in or are considering purchasing.

[1277] 7. Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. It then generates a realistic renovation plan, which typically includes specific modifications such as removing walls or adding new rooms.

[1278] 8. Server: The generated renovation plan is rendered as a 3D image, generating a concrete image including the interior and furniture layout.

[1279] Review and feedback on the proposed plan

[1280] 9. Terminal: The user can view a 3D image of the proposed renovation plan, including details such as the interior design, furniture layout, and room color scheme.

[1281] 10. User: Provides feedback and sends specific requests to the server, such as "I want to change the color of the walls" or "Can I rearrange this furniture?"

[1282] 11. Server: Receive feedback, re-render, and update / re-propose the renovation plan.

[1283] 12. Device: Redisplay the updated plan to the user for final confirmation.

[1284] Specific examples

[1285] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[1286] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout.

[1287] If the user checks the 3D image and sends feedback that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again, thus finally providing the user with a satisfactory renovation plan.

[1288] The present invention provides a method that allows users to efficiently realize their ideal floor plan using such a system.

[1289] The processing flow will be explained below.

[1290] Step 1:

[1291] Users can create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing intuitive placement and size of the devices. It is also possible to upload an image of an existing floor plan.

[1292] Step 2:

[1293] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[1294] Step 3:

[1295] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[1296] Step 4:

[1297] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[1298] Step 5:

[1299] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[1300] Step 6:

[1301] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[1302] Step 7:

[1303] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[1304] Step 8:

[1305] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[1306] Step 9:

[1307] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[1308] Step 10:

[1309] The server renders the generated renovation plan as a 3D image, allowing users to visualize the layout of furniture and interior décor in concrete terms.

[1310] Step 11:

[1311] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[1312] Step 12:

[1313] The user sends feedback about the renovation plan to the server via their device, for example, by inputting requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[1314] Step 13:

[1315] Based on the feedback received by the server, the renovation plan is regenerated and updated, for example by re-rendering a plan with a different wall color.

[1316] Step 14:

[1317] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[1318] This process allows users to efficiently find their ideal rental property and also obtain specific renovation plans to bring the layout closer to their ideal one.

[1319] Example 1

[1320] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1321] Conventional floor plan creation and analysis systems have the drawback of requiring a lot of time and effort when users create their ideal floor plan or obtain rental property information and renovation plans based on existing floor plans. Furthermore, when proposing renovation plans, the system lacks the technology to flexibly update plans based on user feedback, resulting in an unsatisfactory user experience.

[1322] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1323] In this invention, the server includes: means for allowing a user to create an ideal floor plan; means for loading an image of a floor plan close to the ideal; means for analyzing the ideal floor plan or the loaded floor plan image to extract room and equipment conditions; means for retrieving similar rental property information from a database based on the conditions; means for displaying the retrieved rental property information to the user; means for receiving feedback from the user; means for updating the proposal based on the feedback; means for generating and displaying a 3D image of the proposed interior and furniture arrangement; means for loading a floor plan of a property to be purchased or currently occupied; means for generating a realistically feasible renovation plan based on the floor plan of the property and the ideal floor plan; means for rendering the generated renovation plan as a 3D image; means for the user to review the 3D image and provide feedback; and means for regenerating and updating the renovation plan based on the feedback. This enables users to intuitively and efficiently create their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[1324] 1. An "ideal floor plan" is a drawing that reflects the user's desired room layout and size.

[1325] 2. "Floor plan image" is an image file showing the layout of rooms in an existing property.

[1326] 3. "Room and facility conditions" refers to information about the layout of rooms and their facilities, such as the living room, kitchen, bedrooms, and bathrooms, that appear on the floor plan.

[1327] 4. "Database" means an information system that stores information on various rental properties.

[1328] 5. "Three-dimensional images" are images that have physical depth and a sense of three-dimensionality and are visually consistent.

[1329] 6. A "renovation plan" is a specific proposal for renovating an existing property to bring it closer to the user's ideals.

[1330] 7. "Feedback" means any opinions or comments regarding suggestions or requested changes provided by a User.

[1331] 8. "Rendering" is the process of generating three-dimensional images using computer graphics.

[1332] MODE FOR CARRYING OUT THE INVENTION

[1333] The system of the present invention consists of three main components: a user, a terminal, and a server. Each component and its function will be explained in detail below.

[1334] User-created and imported floor plans

[1335] 1. User: The user creates their ideal floor plan through the system's UI. This UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. For example, the user can place the living room in the center, the kitchen on the right, and the bedroom on the left.

[1336] 2. Terminal: The terminal captures the floor plan created by the user and sends it to the server as image data. The user can also select and upload an existing floor plan image. The terminal performs the file upload process and sends the floor plan data to the server according to the user's operation.

[1337] 3. Server: The server analyzes the received floor plan image. It uses image processing libraries such as OpenCV and deep learning libraries such as TensorFlow and Keras to classify the room type. For example, it extracts information such as living room, kitchen, bedroom, and bathroom.

[1338] Providing information on similar rental properties

[1339] 1. Server: The server searches the database based on the analysis results and extracts rental property information that matches the conditions of the floor plan created by the user. It uses SQL queries to search the property information in the database and identifies properties that meet the conditions. Conditions include the number of rooms, room layout, and facility layout.

[1340] 2. Terminal: The terminal receives the list of similar rental properties sent from the server and displays it to the user. This list includes information such as floor plans, rent, and address. Front-end technologies such as React and Angular can be used to display the details.

[1341] Renovation plan proposal

[1342] 1. User: A user uploads a floor plan of a property they are currently living in or planning to purchase. For example, they click the "Upload Floor Plan" button on the property information page and select a file.

[1343] 2. Server: The server analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment and generates a realistic renovation plan. For example, it makes specific renovation suggestions, such as demolishing a wall to expand the living room.

[1344] 3. Server: The generated renovation plan is rendered as a 3D image. Blender and Unreal Engine are used for rendering, and the 3D image is generated and provided to the user. The generated 3D image includes the interior and furniture layout.

[1345] Review and feedback on the proposed plan

[1346] 1. Terminal: The terminal allows users to view a 3D image of the proposed renovation plan. Using the 3D viewer, users can freely change the viewpoint.

[1347] 2. User: The user provides feedback and sends a specific request to the server, for example, "I want to change the color of the walls." Feedback is provided through the UI, for example, by text input.

[1348] 3. Server: The server receives feedback from the user and re-renders the renovation plan. The updated plan is then regenerated as a 3D image and provided to the user.

[1349] Specific examples

[1350] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms.The server then searches the database for multiple 2LDK rental properties that meet the same criteria and provides them to the user as a list.The user can then review the details of this list and select the property they like.

[1351] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it may generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is presented with a concrete visual of the interior and furniture layout. If the user reviews the 3D image and then sends feedback indicating that they would like to change the wall color, the server will change the wall color based on that feedback and provide the updated plan again.

[1352] Example prompts for generative AI models

[1353] "Analyze the floor plan below to determine the layout of the living room, kitchen, and bedrooms, then search for rental properties that meet similar criteria. Then, display them in a list."

[1354] The system of this invention enables users to efficiently realize their ideal floor plan and flexibly propose and update renovation plans based on existing property information.

[1355] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1356] Specific processing flow of the system program

[1357] User-created and imported floor plans

[1358] Step 1:

[1359] User: Accesses the system's UI and creates an ideal floor plan. The user uses the drag-and-drop function to determine the shape, layout, and size of the rooms.

[1360] Input: User actions

[1361] Output: Ideal floor plan

[1362] Step 2:

[1363] Terminal: Captures floor plans created by users and sends them to the server as image data. Users can also select and upload existing floor plan images.

[1364] Input: Ideal floor plan, existing floor plan image

[1365] Output: Floor plan image data

[1366] Step 3:

[1367] Server: Analyzes the received floor plan image. Image processing libraries such as OpenCV are used for image analysis, and deep learning libraries such as TensorFlow and Keras are used to classify room types. The layout and type of rooms (e.g., living room, kitchen, bedroom) are identified, and relevant information is extracted.

[1368] Input: Floor plan image data

[1369] Output: Analysis results (room and equipment conditions)

[1370] Providing information on similar rental properties

[1371] Step 4:

[1372] Server: Searches the database based on the analysis results and extracts rental property information that matches the floor plan created by the user. Searches the database for property information using SQL queries to identify properties that match the criteria.

[1373] Input: Analysis results (room and equipment conditions)

[1374] Output: List of similar rental properties

[1375] Step 5:

[1376] Terminal: The user receives a list of similar rental properties sent from the server and checks them on the UI. The list includes information such as floor plans, rents, and addresses, and includes a link to display more detailed information. The display is done using front-end technologies (e.g., React or Angular).

[1377] Input: List of similar rental properties

[1378] Output: The detailed information screen that the user sees

[1379] Renovation plan proposal

[1380] Step 6:

[1381] Users: Upload floor plans for properties they currently live in or are considering purchasing. Click the "Upload Floor Plan" button on the property information page, select the file, and submit.

[1382] Input: Image data of the property floor plan

[1383] Output: Uploaded data

[1384] Step 7:

[1385] Server: Analyzes the uploaded floor plan and compares it with the ideal floor plan. Using a deep learning model, it calculates the compatibility of room layout and equipment, and generates a realistic renovation plan. It then creates specific renovation proposals (e.g., moving walls, rearranging furniture).

[1386] Input: Image data of the property floor plan, information on the ideal floor plan

[1387] Output: Generated renovation plan

[1388] Step 8:

[1389] Server: The generated renovation plan is rendered as a 3D image. Using Blender and Unreal Engine, a concrete visual image is created and provided as a 3D image including the interior and furniture layout.

[1390] Input: Generated renovation plan

[1391] Output: 3D video

[1392] Review and feedback on the proposed plan

[1393] Step 9:

[1394] Terminal: The user views a 3D image of the proposed renovation plan. Using a 3D viewer displayed on a web browser, the user can freely change the viewpoint to view the interior.

[1395] Input: 3D video

[1396] Output: Confirmation screen

[1397] Step 10:

[1398] User: The user provides feedback and sends a specific change request to the server, for example, "I want to change the wall color." They enter the change request in text form through the UI and press the submit button.

[1399] Input: User feedback

[1400] Output: Feedback data

[1401] Step 11:

[1402] Server: Receives feedback, re-renders, and updates the renovation plan. Generates new 3D images based on the feedback using Blender or similar software, and provides them to the user again.

[1403] Input: Feedback data

[1404] Output: 3D image of the updated renovation plan

[1405] Step 12:

[1406] On the device: The updated plan is displayed again to the user, who can then review the proposed plan again and repeat the process until they are finally satisfied.

[1407] Input: Updated 3D image

[1408] Output: Final confirmation screen

[1409] (Application example 1)

[1410] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1411] Conventional floor plan creation and renovation plan generation systems have limited means for users to specifically check the image of their ideal space, making it difficult to reflect and confirm feedback. Furthermore, the lack of an interface that reflects user feedback in real time and allows intuitive operation has led to low satisfaction with the final plan.

[1412] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1413] In this invention, the server includes means for allowing a user to create an ideal floor plan, means for loading an image of a floor plan close to the ideal, means for analyzing the ideal floor plan or the loaded floor plan image and extracting room and facility conditions, means for retrieving similar real estate property information from a database based on the conditions, means for displaying the retrieved real estate property information to the user, and means for the user to check and operate the renovation plan in three-dimensional space using a virtual visual device, thereby enabling feedback to be reflected in real time and intuitive operation.

[1414] "User" means an individual or organization that uses the System to create floor plans and view and manipulate renovation plans.

[1415] An "ideal floor plan" is a drawing that expresses the layout of the building and the arrangement of rooms that the user desires.

[1416] "Loading" means inputting an existing floor plan image into the system and having it recognized as data.

[1417] "Analysis" refers to the act of extracting information about rooms and facilities from the loaded floor plan image and classifying and recognizing them based on certain conditions.

[1418] "Room and facility conditions" refers to information about the location, size, shape, and facility layout of each room in the floor plan.

[1419] A "database" is a collection of information that stores and makes searchable similar real estate property information based on the user's criteria.

[1420] "Real estate property information" refers to attribute information of actual buildings that are available for rent or purchase, including floor plans, rent, location, etc.

[1421] A "virtual visual device" is a device that allows users to view and manipulate floor plans and renovation plans in three-dimensional space.

[1422] A "three-dimensional image" is a three-dimensional image that has a three-dimensional appearance and can be visually perceived by a user.

[1423] "Feedback" refers to opinions and requests from users, and includes information that includes instructions for adjusting or changing the renovation plan.

[1424] A "generative AI model" is an algorithm that receives user feedback and automatically generates and updates floor plans and renovation plans.

[1425] A "prompt" is text that describes specific instructions or requests that a user inputs to a generative AI model.

[1426] MODE FOR CARRYING OUT THE INVENTION

[1427] Overall structure

[1428] The system of the present invention consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, and the server performs data analysis and plan generation on the back end.

[1429] User-created and imported floor plans

[1430] Users create their ideal floor plan through the system's user interface (UI). The UI features a drag-and-drop function, allowing intuitive manipulation of room layout and size. Users can also upload images of existing floor plans. The device captures the floor plan created by the user and sends it to the server.

[1431] Data analysis by server

[1432] The server analyzes the received floor plan image and extracts the room and facility conditions, for example, identifying the living room, kitchen, bathroom, etc. This analysis uses an image analysis algorithm, such as deep learning technology.

[1433] Providing rental property information

[1434] Based on the analysis results, the server searches the database to extract real estate information that matches the user's specified criteria. These criteria include the number of rooms, room layout, and facility layout. The retrieved real estate information is sent to the terminal, where the user can view it as a list.

[1435] 3D display using virtual visual equipment

[1436] Users can wear virtual vision devices (e.g., smart glasses) and experience the renovation plan in a virtual three-dimensional space. The server then renders the renovation plan as a three-dimensional image, generating a concrete image including the interior and furniture layout.

[1437] Feedback and regeneration processes

[1438] The user views the 3D image through a virtual viewing device and provides specific feedback, such as "I want to change the wall color to red." This feedback is sent to the server in the form of a prompt. The server then uses a generative AI model to regenerate and update the renovation plan based on this feedback.

[1439] Specific examples

[1440] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK real estate properties that meet similar criteria and provides them to the user as a list. Similarly, if a user plans to purchase a 3LDK apartment and uploads a floor plan for that property, the server analyzes the floor plan, understands the current state of the apartment, and generates a renovation plan for renovating it into the ideal 2LDK apartment. For example, it generates a plan to remove a wall to create a larger living space or add new storage space.

[1441] An example of a prompt is "Please change the wall color to FF0000 (red)." Based on this instruction, the server updates the renovation plan. The updated plan is again provided to the user as a 3D image, allowing the user to immediately confirm the changes.

[1442] Hardware and software used

[1443] The system of the present invention uses a server, a user device, and a virtual visual device (such as smart glasses). The software includes THREE.js (for 3D rendering), WebRTC (for real-time rendering and user interaction), and a generative AI model (to generate and update plans based on user feedback).

[1444] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1445] Step 1:

[1446] Users create their ideal floor plan using the device's user interface (UI). The drag-and-drop function allows intuitive manipulation of room layout and size. The input is UI data that the user manipulates, and the output is floor plan data.

[1447] Step 2:

[1448] The device captures the ideal floor plan data created by the user and sends it to the server. This process converts the UI data into images or other formats, and then makes an API call to send it to the server. The input is the floor plan data, and the output is the data sent to the server.

[1449] Step 3:

[1450] The server receives the floor plan data and analyzes it using image analysis algorithms such as deep learning technology, thereby extracting the room and equipment conditions. The input is the floor plan data, and the output is the analysis results including the room and equipment conditions.

[1451] Step 4:

[1452] Based on the analysis results, the server searches the database and extracts real estate property information that matches the user's specified criteria. This process searches for suitable properties in the database using criteria such as the number of rooms, room layout, and facility layout. The input is the analysis result criteria data, and the output is similar real estate property information.

[1453] Step 5:

[1454] The server sends the extracted property information to the terminal, which displays the information in a list format to the user. The user can then check the list and view detailed information (e.g., floor plan, rent, address). The input is property information from the server, and the output is the information displayed on the user's terminal.

[1455] Step 6:

[1456] Users wear virtual vision devices (such as smart glasses) to experience renovation plans in a three-dimensional space. Through the virtual vision device, users can visually confirm the floor plan in three-dimensional images. The input is the user's wearing information and the virtual vision device's setting data, and the output is a three-dimensional image.

[1457] Step 7:

[1458] The user checks the 3D image provided through the virtual visual device and provides specific feedback, such as "I want to change the color of the wall to red." This feedback is sent from the terminal to the server in the form of a prompt sentence. The input is the user's feedback prompt sentence, and the output is the prompt sentence data sent from the terminal to the server.

[1459] Step 8:

[1460] The server uses a generative AI model based on the received prompt sentence to regenerate and update the renovation plan. The input is the prompt sentence data and the existing renovation plan, and the output is the updated renovation plan.

[1461] Step 9:

[1462] The server renders the updated renovation plan again as a 3D image and provides it to the user via the terminal and virtual viewing device. The input is the updated renovation plan data, and the output is the 3D image displayed to the user.

[1463] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1464] The system of the present invention allows users to create their ideal floor plan or import an image of an existing floor plan to obtain information on similar rental properties, and also has the function of proposing renovation plans to bring the floor plan of a property they are planning to purchase or currently living in closer to their ideal floor plan. Furthermore, by combining it with an emotion engine, the system also has the function of recognizing the user's emotional state in real time and adjusting the proposal content based on that.

[1465] Overall system overview

[1466] The system consists of three main components: the user, the device, and the server. The user mainly operates the device, while the server performs data analysis and plan generation in the backend. The emotion engine also analyzes the user's emotional state in real time.

[1467] User-created and imported floor plans

[1468] 1. User: Create your ideal floor plan through the system's UI. The UI features a drag-and-drop function, allowing intuitive manipulation of room placement and size. You can also upload an image of an existing floor plan.

[1469] 2. Device: Captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[1470] 3. Server: Analyzes the received floor plan image and performs image analysis processing to extract the room and facility conditions. For example, it identifies the living room, kitchen, bathroom, etc.

[1471] Providing information on similar rental properties

[1472] 4. Server: Based on the analysis results, the database is searched to extract rental property information that matches the user's specified criteria, including the number of rooms, room layout, and facility layout.

[1473] 5. Server: Using the user's emotion engine, search results are prioritized based on the user's preferences. The emotion engine evaluates the user's emotions by analyzing past choices, current facial expressions, and voice.

[1474] 6. Terminal: The user is presented with a list of similar rental property information sent from the server. The user can review this list and view detailed information (e.g., floor plan, rent, address).

[1475] Renovation plan proposal

[1476] 7. User: Upload floor plans of properties you currently live in or are considering purchasing.

[1477] 8. Server: Analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. Based on the analysis results, evaluates the possibility of renovation.

[1478] 9. Server: Compares the user's ideal floor plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[1479] 10. Server: The generated renovation plan is rendered as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[1480] 11. Terminal: Displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[1481] Review and feedback on the proposed plan

[1482] 12. User: Sends feedback on the renovation plan to the server via the terminal. For example, inputs specific requests such as "I want to change the wall color" or "Can I change this furniture arrangement?"

[1483] 13. Server: The emotion engine analyzes the user's emotional state at the time of feedback and determines whether further adjustments are necessary. Based on the received feedback, the renovation plan is regenerated and updated.

[1484] 14. Device: The updated renovation plan is displayed again to the user, who can then review the 3D image again and make a final decision or provide further feedback.

[1485] Specific examples

[1486] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[1487] Next, if a user plans to purchase a 3LDK property and uploads the property's floor plan, the server analyzes the floor plan to understand the current situation and generates a renovation plan to convert it into the ideal 2LDK. For example, it could generate a plan to remove a wall to create a larger living space or add new storage space. These plans are rendered as 3D images, and the user is shown a concrete visual of the interior and furniture layout. The emotion engine analyzes the user's reactions to these suggestions in real time and presents the optimal plan.

[1488] If a user checks the 3D image and then sends feedback requesting a change to the wall color, the emotion engine will analyze the user's emotional state at the time of the feedback and further adjust the suggestions as necessary. For example, it may suggest bolder design ideas to a user who expresses positive emotions, and more conservative ideas to a user who expresses caution.

[1489] By combining emotion engines in this way, the present invention is able to provide optimal rental property information and propose renovation plans that are tailored to the user's emotional state.

[1490] The processing flow will be explained below.

[1491] Step 1:

[1492] Users create their ideal floor plan using the system's UI, which features a drag-and-drop function that allows intuitive configuration of room placement and size. Users can also upload images of existing floor plans.

[1493] Step 2:

[1494] The device captures the floor plan created by the user and sends it to the server. If an existing floor plan image is uploaded, the device sends that image to the server.

[1495] Step 3:

[1496] The server analyzes the received floor plan image and extracts the room and facility conditions. Image recognition technology is used to identify the location and type of rooms and facilities, such as the living room, kitchen, and bathroom.

[1497] Step 4:

[1498] The server searches for rental property information in the database based on the extracted room and facility conditions, for example, to find rental properties with similar room layouts and facility conditions.

[1499] Step 5:

[1500] The server extracts similar rental properties from the search results and creates a list, which includes details such as floor plans, rent, and location.

[1501] Step 6:

[1502] The terminal displays a list of similar rental property information sent from the server to the user, who can then review the list, check details, and select properties that interest them.

[1503] Step 7:

[1504] The emotion engine recognizes the user's real-time emotions and assesses their interests and preferences by analyzing their facial expressions and voice.

[1505] Step 8:

[1506] The server receives feedback from the emotion engine and adjusts the prioritization of rental listings to display based on customer preferences, for example, displaying properties that the user has expressed interest in at the top of the list.

[1507] Step 9:

[1508] The user uploads a floor plan of a property they are currently living in or planning to purchase. The device sends the uploaded floor plan image to the server.

[1509] Step 10:

[1510] The server analyzes the uploaded floor plan to identify the current room layout and equipment conditions, and evaluates the possibility of renovation based on the analysis results.

[1511] Step 11:

[1512] The server compares the user's ideal floor plan with the plan and generates multiple realistic renovation plans, including removing walls, adding rooms, and changing fixtures.

[1513] Step 12:

[1514] The server renders the generated renovation plan as a 3D image, allowing the user to visualize the layout of furniture and interior décor. The emotion engine evaluates the user's emotional state and fine-tunes the specifications of the proposed plan.

[1515] Step 13:

[1516] The device displays a 3D image to the user, who can then review the displayed renovation plan in detail and provide specific feedback.

[1517] Step 14:

[1518] The emotion engine analyzes the user's emotional state during feedback in real time and determines whether further updates are needed.

[1519] Step 15:

[1520] The server regenerates and updates the renovation plan based on the feedback it receives, for example re-rendering the plan with a changed wall color.

[1521] Step 16:

[1522] The device then displays the updated renovation plan to the user again, who can review the 3D image again and make a final decision or provide further feedback.

[1523] This process allows users to efficiently find their ideal rental property and at the same time receive proposals for renovation plans that take into account the user's emotional state.

[1524] Example 2

[1525] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1526] Conventional floor plan creation tools and rental property search systems often do not take into account the user's individual preferences or emotional state, resulting in proposed properties and plans that do not meet the user's expectations. Furthermore, when proposing renovation plans, there was an insufficient mechanism for fully reflecting user feedback. Therefore, in order to improve user satisfaction, flexible proposals that respond to the user's emotional state are required.

[1527] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1528] In this invention, the server includes an emotion engine means for recognizing the user's emotional state in real time and adjusting the proposed content, a means for regenerating and updating renovation plans based on the feedback and the emotional state, and a means for evaluating the user's emotional state using the emotion engine, thereby making it possible to provide rental property information and propose renovation plans appropriate to the user's emotional state.

[1529] A "user" is an individual or organization that operates the system to create desired floor plans, search for rental property information, or check renovation plans.

[1530] A "floor plan" is a drawing that shows the layout and structure of a building or room, and represents the layout of the rooms and the location of equipment.

[1531] The "server" is a computer system that analyzes data provided by users, extracts floor plan information, and generates rental property information and renovation plans.

[1532] An "emotion engine" is a combination of software or hardware that recognizes a user's emotional state in real time and adjusts suggestions based on that information.

[1533] "Feedback" refers to the opinions and reactions users provide to proposed renovation plans and rental property information, and is information used to readjust the system.

[1534] A "renovation plan" is a specific proposal or plan for renovating or rearranging an existing property to bring it closer to the user's ideals.

[1535] "Three-dimensional images" are images that represent renovation plans and floor plans in three dimensions, and are rendered so that users can visually confirm them.

[1536] A "database" is an information system that organizes and stores information on rental properties and floor plans, and manages it so that it can be searched and retrieved as needed.

[1537] "Analysis" is the process in which the server processes the input floor plan data and images and extracts information such as the layout of rooms and equipment.

[1538] The system of the present invention consists of three main components: a user, a terminal, and a server. The following will specifically explain how to implement the system.

[1539] System Overview

[1540] The system allows users to create and load their ideal floor plan, and the server analyzes it to provide information on similar rental properties and propose renovation plans. Furthermore, by combining it with an emotion engine, the system can recognize the user's emotional state in real time and adjust the proposals accordingly.

[1541] Creating and loading floor plans

[1542] 1. Users create their ideal floor plan using the system's UI. The UI features a drag-and-drop function, allowing them to intuitively arrange the living room, kitchen, bedroom, etc. Users can also upload an image of an existing floor plan.

[1543] 2. The device captures the floor plan data created by the user and the floor plan images uploaded by the user and sends them to the server using a secure communication protocol (e.g., HTTPS).

[1544] Providing rental property information

[1545] 3. The server analyzes the received floor plan data using an image analysis algorithm (e.g., OpenCV) to identify rooms and facilities such as the living room, kitchen, and bathroom.

[1546] 4. Based on the analysis results, the server searches the database and extracts rental property information that matches the conditions specified by the user.

[1547] 5. The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preferences. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis.

[1548] 6. The terminal receives the list of similar rental property information sent from the server and displays it to the user.

[1549] Providing renovation plans

[1550] 7. Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are accepted, including image files and PDFs.

[1551] 8. The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions.

[1552] 9. Based on the analysis results, the server compares the user's ideal floor plan and generates multiple realistic renovation plans, taking into account things like removing rooms, adding walls, and changing fixtures.

[1553] 10. The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine).

[1554] 11. The device displays the rendered 3D image to the user, allowing the user to examine it in detail and get a concrete idea of ​​the renovation plan.

[1555] 12. The user sends feedback about the renovation plan to the server via their device. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture."

[1556] Re-adjusting the plan

[1557] 13. The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed: if the engine indicates a positive emotion, it will make bold design suggestions, but if it indicates a cautious emotion, it will make more conservative suggestions.

[1558] 14. The device displays the reworked renovation plan to the user again, who can review the updated 3D image and make a final decision or provide further feedback.

[1559] Specific examples

[1560] For example, if a user creates a floor plan for a 2LDK apartment, the server analyzes the plan and identifies the living room, kitchen, and two bedrooms. It then searches the database for multiple 2LDK rental properties that meet similar criteria and provides them to the user as a list. The emotion engine analyzes the user's facial expressions and tone of voice to assess whether the user is interested in a particular property. Based on this, the server adjusts the priority of the properties to display.

[1561] Prompt Sentence Examples

[1562] If you were to use a generative AI model to prompt the system for this sequence, you could use a prompt like this:

[1563] The system allows users to create and import their ideal floor plan, provides rental property information that matches it, and proposes renovation plans. Please explain the process in detail.

[1564] The above is an embodiment of the present invention. The purpose of the present invention is to improve user satisfaction by providing suggestions and information according to the user's emotional state through the combination of an emotion engine.

[1565] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1566] Step 1:

[1567] Users create their ideal floor plan using the system's UI. This UI allows them to intuitively arrange living rooms, kitchens, bedrooms, etc. using the drag-and-drop function. Users can also upload existing floor plan images. The input here is the floor plan data created by the user or an uploaded image file, and the output is this data ready to be sent to the server.

[1568] Step 2:

[1569] The device captures floor plan data created by the user and floor plan images uploaded by the user and sends them to the server. A secure communication protocol (e.g., HTTPS) is used for data transmission. The input is the user's floor plan data, and the output is the completion of data transmission to the server.

[1570] Step 3:

[1571] The server analyzes the received floor plan data. This analysis uses an image analysis algorithm (e.g., OpenCV) to identify the layout of rooms and facilities such as living rooms, kitchens, and bathrooms. The input is the floor plan data sent from the device, and the output is the layout information of rooms and facilities as a result of the analysis.

[1572] Step 4:

[1573] The server searches the database based on the analysis results and extracts rental property information that matches the user's specified criteria. The input here is the analysis results, and the output is rental property information based on the criteria.

[1574] Step 5:

[1575] The server uses an emotion engine to analyze the user's emotional state and prioritize the search results in order of the user's preference. The emotion engine uses facial expression recognition technology (e.g., facial recognition API) and voice analysis. The input is rental property information and the user's emotional data, and the output is prioritized rental property information that takes emotions into account.

[1576] Step 6:

[1577] The terminal receives the list of similar rental property information sent from the server and displays it to the user. The input is the rental property information from the server, and the output is a list of rental property information that the user can check.

[1578] Step 7:

[1579] Users upload floor plans of properties they currently live in or plan to purchase to the system. Multiple file formats are allowed, including image files and PDFs. The input is the user's property floor plan data, and the output is this data ready to be sent to the server.

[1580] Step 8:

[1581] The server analyzes the uploaded floor plan and identifies the current room layout and equipment conditions. The input is the uploaded floor plan data, and the output is the analysis results, including the current room layout and equipment conditions.

[1582] Step 9:

[1583] Based on the analysis results, the server compares them with the user's ideal floor plan and generates multiple realistic renovation plans. This involves removing rooms, adding walls, changing fixtures, etc. The input is the analysis results and the ideal floor plan, and the output is multiple renovation plans.

[1584] Step 10:

[1585] The server renders the generated renovation plan as a 3D image using a 3D graphics engine (e.g., Unity or Unreal Engine). The input is the renovation plan, and the output is the 3D image.

[1586] Step 11:

[1587] The terminal receives the rendered 3D image and displays it to the user. The input is the 3D image from the server, and the output is the 3D image that the user can visually confirm.

[1588] Step 12:

[1589] Users send feedback about the renovation plan to the server via their devices. For example, they can enter specific requests such as "I want to change the wall color" or "I want to rearrange the furniture." The input is the user's feedback, and the output is the feedback data sent to the server.

[1590] Step 13:

[1591] The server uses an emotion engine to analyze the user's emotional state at the time of feedback and readjusts the renovation plan as needed. If the engine indicates a positive emotion, it makes bold design suggestions, and if it indicates a cautious emotion, it makes more conservative suggestions. The input is the feedback and the user's emotional data, and the output is the readjusted renovation plan.

[1592] Step 14:

[1593] The terminal displays the re-adjusted renovation plan to the user again. The input is the re-adjusted renovation plan from the server, and the output is an updated 3D image that the user can view.

[1594] (Application example 2)

[1595] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1596] Currently, it is difficult to customize the interior layout of an autonomous vehicle based on the preferences and feelings of each individual user. Furthermore, there is a lack of tools to collect vehicle information that closely matches the ideal layout desired by the user or to receive suggestions for renovating existing vehicles. As a result, users face the challenge of finding the optimal interior and layout that suits their preferences.

[1597] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1598] In this invention, the server includes a means for allowing a user to create an ideal spatial layout, a means for loading a layout image close to the ideal, and a means for analyzing the ideal layout or the loaded layout image to extract spatial and equipment conditions, thereby enabling the proposal and customization of a vehicle interior layout based on the user's emotional state. The server also includes a means for acquiring similar property information from a data storage device, a means for displaying the acquired property information to the user, an emotion analysis means for analyzing the user's emotional state in real time, and a means for adjusting the priority of similar property information based on the analysis results. This allows the user to create an ideal vehicle interior layout and receive proposals for optimal property information and renovation plans based on that layout.

[1599] A "user" is a person who operates the system to create an ideal spatial layout or load an existing layout.

[1600] "Spatial layout" refers to drawings or designs that show the arrangement of rooms and facilities.

[1601] A "layout image" is image data that visually represents a spatial layout.

[1602] "Analysis" refers to the process of extracting room and equipment conditions from the input layout image.

[1603] "Space and equipment conditions" refers to layout characteristics such as room arrangement, size, and equipment placement.

[1604] "Property information" refers to detailed data about the spatial layout in which a user is interested.

[1605] A "data storage device" is a device that stores data long-term and allows it to be accessed as needed.

[1606] "Emotional state" refers to a state that indicates the user's state of mind or mood.

[1607] "Emotion analysis means" refers to means for assessing a user's emotional state by analyzing their facial expressions and vocal tone.

[1608] "Means for adjusting priority" refers to means for changing the order and importance of information to be displayed based on the results of sentiment analysis.

[1609] "3D video" refers to digital images that visually recreate objects and environments in three-dimensional space.

[1610] "Visualization" is the process of visually representing data or information.

[1611] "Opinions" are feedback and improvement requests provided by users.

[1612] The system for realizing this invention mainly consists of three main components: a user, a terminal, and a server. The user mainly operates the terminal, while the server performs data analysis and plan generation on the backend. In addition, an emotion analysis means analyzes the user's emotional state in real time.

[1613] 1. User-created and loaded spatial layouts

[1614] Users wear a head-mounted display (HMD) and create their ideal spatial layout using an intuitive UI with drag-and-drop functionality. Alternatively, by uploading an image of an existing layout, the system analyzes the image and extracts spatial and facility conditions.

[1615] 2. Layout analysis and provision of similar property information

[1616] The terminal captures the layout created or imported by the user and sends it to the server. The server analyzes the received layout image and performs image analysis processing to identify the conditions of the rooms and facilities. This process uses the OpenCV library. Based on the analysis results, similar property information is searched for in the data storage device and provided to the user. Furthermore, an emotion analysis means evaluates the user's emotional state and adjusts the priority of property information based on the user's preferences.

[1617] 3. Proposal of renovation plan

[1618] When a user uploads an existing property layout, the device sends the layout to the server. The server analyzes the layout to determine the current room arrangement and equipment conditions. Based on the analysis results, a realistic renovation plan is generated by comparing it with the ideal layout. This may include removing walls, adding rooms, or changing equipment. The renovation plan is then rendered as a 3D image using Unity 3D.

[1619] 4. User feedback and plan regeneration

[1620] The user can view the 3D image in detail through the HMD and provide feedback, which is then sent to the server via the device. The server then uses emotion analysis to reassess the user's emotional state and regenerate and update the renovation plan as necessary.

[1621] Hardware and software used

[1622] Head-mounted display (HMD): Use Meta Quest 2, HTC Vive, etc.

[1623] Image Analysis Library: Analyzes layout images using OpenCV.

[1624] 3D video rendering software: Real-time rendering using Unity 3D.

[1625] Sentiment analysis method: Affectiva SDK is used to analyze the user's emotional state in real time.

[1626] Examples and prompts

[1627] As a concrete example, we will show a scenario in which a user creates an interior layout for an autonomous vehicle and receives suggestions for similar properties and renovation plans based on that layout.

[1628] Example prompt sentence:

[1629] "In an interior layout design app for autonomous vehicles, provide a function that allows users to wear an HMD and create, load, and customize their ideal layout. At this time, please add a function that uses emotion analysis means to analyze the user's emotional state in real time and adjust the proposal content based on their emotion."

[1630] This system allows users to create their ideal interior layout and receive optimal property information and renovation plan suggestions based on that.

[1631] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1632] Step 1:

[1633] The user wears a head-mounted display (HMD) and creates an ideal spatial layout using a UI with drag-and-drop functionality. It is also possible to upload an existing layout image. The input is the user's operation data or the uploaded layout image. The output is the generated ideal layout data or the uploaded layout image.

[1634] Step 2:

[1635] The terminal captures layout data created by the user or a layout image loaded by the user and transmits it to the server. The input here is the layout data created or uploaded by the user, and the output is the data transmitted to the server.

[1636] Step 3:

[1637] The server analyzes the received layout image and extracts the spatial and equipment conditions. This process uses the OpenCV library. The input is the received layout image data, and the output is the extracted spatial and equipment condition data. Specifically, the server applies an image analysis algorithm to identify the layout of rooms and equipment.

[1638] Step 4:

[1639] The server searches for similar property information from its data storage device based on the analysis results. The input is the extracted spatial and facility condition data, and the output is similar property information. Specifically, the server executes a query to efficiently search for data that matches the conditions.

[1640] Step 5:

[1641] The server uses emotion analysis to evaluate the user's emotional state in real time and adjust the priority of the retrieved property information. The input is the user's emotional data (facial expression, tone of voice, etc.) and the property information from the search results, and the output is a prioritized property list. Specifically, the server uses an emotion analysis algorithm to dynamically change the display order of properties based on the retrieved data.

[1642] Step 6:

[1643] The information sent from the server is displayed to the user on the terminal. The input is a prioritized property list, and the output is visual information displayed on the HMD. Specifically, the property information is displayed in the user's field of vision using the HMD display.

[1644] Step 7:

[1645] When a user uploads an existing property layout, the terminal sends the layout to the server. The input is the property layout data uploaded by the user, and the output is the data sent to the server.

[1646] Step 8:

[1647] The server analyzes the uploaded layout and determines the current room arrangement and equipment conditions. The input is the layout data sent, and the output is the analysis results data. Specifically, the server again uses the OpenCV library to identify the arrangement of each room in the layout.

[1648] Step 9:

[1649] The server compares the ideal layout with the data and generates a realistic renovation plan. The input is the analysis result data and the ideal layout data, and the output is the renovation plan. Specifically, it uses the generative AI model to create the necessary renovation plan.

[1650] Step 10:

[1651] The server uses Unity 3D to render the generated renovation plan as a 3D image and sends it to the HMD. The input is the renovation plan data, and the output is the 3D image data. Specifically, it uses Unity 3D's rendering function to create a visually detailed 3D image.

[1652] Step 11:

[1653] The user can view the 3D image in detail through the HMD and provide feedback. The input is the 3D image, and the output is the feedback data from the user.

[1654] Step 12:

[1655] The feedback is sent to the server via the device, and the server uses emotion analysis means to reassess the user's emotional state and regenerate and update the renovation plan as necessary. The input is the user's feedback data and emotion data, and the output is a regenerated renovation plan. Specifically, the renovation plan is adjusted and updated using an emotion analysis algorithm and a generative AI model.

[1656] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1657] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1658] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1659] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1660] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1661] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1662] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1663] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1664] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1665] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1666] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1667] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1668] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1669] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1670] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1671] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1672] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1673] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1674] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1675] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1676] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1677] The following is further disclosed regarding the above embodiment.

[1678] (Claim 1)

[1679] a means for users to create their ideal floor plan;

[1680] A means to load an image of the floor plan that is close to your ideal,

[1681] A means for analyzing the ideal floor plan or the loaded floor plan image to extract room and facility conditions;

[1682] A means for acquiring similar rental property information from a database based on the conditions;

[1683] means for displaying the acquired rental property information to a user;

[1684] A system including:

[1685] (Claim 2)

[1686] A means to load floor plans for properties you are planning to purchase or currently occupy;

[1687] A means for generating a realistic renovation plan based on the floor plan of the property and an ideal floor plan;

[1688] A means to render the generated renovation plan as a 3D image,

[1689] a means for the user to view the 3D image and p...

Claims

1. a means for users to create their ideal floor plan; A means to load an image of the floor plan that is close to your ideal, A means for analyzing the ideal floor plan or the loaded floor plan image to extract room and facility conditions; A means for acquiring similar rental property information from a database based on the conditions; means for displaying the acquired rental property information to a user; A system including:

2. A means to load floor plans for properties you are planning to purchase or currently occupy; A means for generating a realistic renovation plan based on the floor plan of the property and an ideal floor plan; A means to render the generated renovation plan as a 3D image, a means for the user to view the 3D image and provide feedback; A means to regenerate and update renovation plans based on feedback, and The system of claim 1 , comprising:

3. The system according to claim 1, further comprising means for generating and displaying an image of the interior and furniture arrangement in the ideal floor plan or the renovation plan as a three-dimensional image.

Images