System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a user input; means for transmitting the user input to a server; means for generating an interior coordinate using a generative AI model; means for searching for furnishings that fit a budget; means for applying the found furnishings to the user's interior coordinate; means for displaying the interior coordinate on a user interface; and means for receiving feedback from the user and generating a re-proposal.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] With the increasing number of new graduates and new college students, people changing their living environment due to marriage or job transfers, and people starting small businesses, coordinating the right interior is challenging for those who lack confidence in their sense of style or who want to find the right furniture for their needs on a limited budget. This challenge is related to the high cost of hiring an interior coordinator and specific issues such as how to balance existing furniture with new pieces. Furthermore, it is often difficult to select furniture that matches the interior taste and fits within a budget. To meet this demand, a system that allows for easy and effective interior coordination is needed. [Means for solving the problem]

[0005] This invention is a system that includes a means for accepting user input, a means for transmitting user-entered data to a server, a means for generating an interior coordination using a generative AI model, a means for searching for furniture that fits within a budget, a means for applying the searched furniture to the user's interior coordination, a means for displaying the interior coordination on a user interface, and a means for receiving user feedback and generating re-proposals. This system enables people, such as those entering the workforce or entering university, those changing their living environment due to a job transfer, and small business owners, to effectively realize their ideal interior design within their budget without hiring an interior coordinator. Furthermore, by including a means for searching a furniture database via the Internet and identifying furniture available within the user's budget, the system allows users to easily find furniture that matches the proposed interior. This significantly reduces consumer effort and increases satisfaction.

[0006] "Means for accepting user input" refers to an interface or device that allows the user to input data such as the room layout, interior style, purpose of use of the room, and budget.

[0007] "Means for sending to server" refers to a function or device for sending data entered by a user to a server via the Internet or other communication means.

[0008] A "generative AI model" is an artificial intelligence algorithm or system used to automatically generate interior coordination.

[0009] "Means for generating interior coordination" refers to a function or system that uses a generative AI model to create an interior design plan based on data entered by the user.

[0010] "Means for searching for furniture that fits a budget" refers to a function or system that searches for furniture on the Internet or in a specific database based on the user's budget and selects the most suitable furniture.

[0011] "Means for applying furniture to the user's interior coordination" refers to functions and systems for incorporating the selected furniture into the generated interior coordination plan and proposing it.

[0012] "Means for displaying interior coordination on a user interface" refers to a function or system for visually displaying interior coordination suggestions to a user on a terminal screen.

[0013] "Means for receiving feedback from users and generating new proposals" refers to a function or system that provides an interface where users can input their opinions and changes regarding the proposals, and then generates new interior coordination based on that.

[0014] "Means for searching furniture databases via the Internet" refers to a function or system that queries multiple online furniture databases via the Internet to search for furniture that meets the user's requirements.

[0015] The "means for identifying furniture that can be acquired within the user's budget" refers to a function or system for listing furniture that can be purchased within the user's budget based on the user's budget information and presenting it to the user. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention is a system that allows a user to efficiently coordinate the interior of a room, and the processing of the program will be specifically described below.

[0038] System Operation Overview

[0039] The system allows users to input their room layout, interior taste, purpose of use, and budget, and then uses that information to suggest the optimal interior plan and furniture. The system receives user input and uses a generative AI model to generate an interior coordination and select furniture.

[0040] Accepting user input

[0041] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0042] Sending data

[0043] Terminal: Sends data entered by the user to the server in a standard format such as JSON.

[0044] Data reception and analysis

[0045] Server: The server receives and analyzes the data sent from the device. The analyzed data is then fed into a generative AI model. For example, it might understand that a Scandinavian-inspired interior is desired, or that the room layout is 5 meters long and 4 meters wide.

[0046] Generate interior plans

[0047] Server: The server uses a generative AI model to generate interior coordination based on input data. For a Scandinavian style, the generative AI model suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[0048] Furniture selection

[0049] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[0050] Integration of interior planning and furniture

[0051] Server: Integrates the generated interior plan and selected furniture information into a single proposal. For example, it provides detailed information including a specific furniture layout for a Scandinavian-style living room, the price of each piece of furniture, and a link to purchase it.

[0052] Sending data

[0053] Server: Sends the proposal data to the terminal.

[0054] View Suggestions

[0055] Device: The proposed interior coordination and furniture recommendations are displayed on the user interface. The user can check detailed information (price, purchase link, size) of the recommended furniture.

[0056] Receiving feedback and resubmitting

[0057] Terminal: The user enters feedback on the suggestion (e.g., I would like to change the color of the sofa). The feedback is sent back to the server.

[0058] Server: Receives feedback and generates new interior design proposals, for example, new proposals that include a brightly colored sofa.

[0059] The above steps are repeated until the proposed interior coordination is satisfactory to the user, thereby achieving the optimal interior.

[0060] In this way, users can easily and efficiently coordinate their interiors and create their ideal living environment or work space.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0064] Step 2:

[0065] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[0066] Step 3:

[0067] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[0068] Step 4:

[0069] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[0070] Step 5:

[0071] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[0072] Step 6:

[0073] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0074] Step 7:

[0075] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[0076] Step 8:

[0077] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[0078] Step 9:

[0079] User: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[0080] Step 10:

[0081] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[0082] Step 11:

[0083] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[0084] Step 12:

[0085] Server: Sends new interior design proposals to the device.

[0086] Step 13:

[0087] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[0088] These are the specific processing steps of this system. Through this series of processes, users can efficiently realize their ideal interior.

[0089] Example 1

[0090] 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."

[0091] Currently, there are few efficient ways to coordinate the interior of a room. Users often have to think about the interior design and select and arrange the furniture themselves, which takes time and effort. In addition, there are few systems that can propose interior plans that match the user's image, making it difficult for users to achieve an interior environment that satisfies them. To solve this problem, a system is needed that can automatically propose optimal interior plans and furniture based on user input.

[0092] 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.

[0093] In this invention, the server includes means for transmitting data input by a user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits a budget, means for applying the searched furniture to the user's interior coordination, means for creating and transmitting prompts to the generative AI model, and means for providing an optimal interior plan based on the user's room layout and interior taste, thereby enabling the user to realize their ideal interior coordination without any hassle.

[0094] "User" refers to an individual or corporation that uses the system to coordinate the interior of a room.

[0095] "Server" refers to the computer system that receives data sent by users and generates interior coordination using analytical and generative AI models.

[0096] "Terminal" refers to the device (e.g., smartphone, computer, tablet) that a user uses to access the system and enter data, review suggestions, etc.

[0097] A "generative AI model" refers to an artificial intelligence model that generates optimal interior coordination based on data entered by the user.

[0098] A "prompt" refers to an instruction or question that is input to a generative AI model to generate an interior coordination.

[0099] "Interior coordination" refers to a plan that proposes optimal furniture placement and decoration based on the room layout, interior taste, purpose of use of the room, budget, etc.

[0100] "Furniture" refers to items (e.g., tables, sofas, carpets) that are placed in a room and are necessary for interior coordination.

[0101] A "furniture database" refers to an online database that registers information about various furniture items (e.g., price, size, material, and purchase link).

[0102] "User interface" refers to the screen or operating means through which a user inputs data into a system or checks suggestions.

[0103] "Feedback" refers to opinions and information such as requests for changes or improvements made by users in response to proposals.

[0104] "Re-proposals" refer to new interior coordination ideas generated based on feedback received from users.

[0105] The present invention is a system for enabling a user to efficiently coordinate the interior design of a room. Specific embodiments will be described below.

[0106] The system consists of three main components: a terminal where users input information, a server that receives and processes the input data, and a generative AI model.

[0107] Accepting user input

[0108] Device: Users access the system using a PC, smartphone, or tablet device. On the user interface, they input information such as the room layout, interior style, purpose of use, and budget. For example, a user might input a 5-meter by 4-meter floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0109] Sending data

[0110] Terminal: The data entered by the user is converted to JSON format and sent to the server. For example, the following JSON data is generated:

[0111] json

[0112] {

[0113] "Layout": {"Length": 5, "Width": 4},

[0114] "Taste": "Scandinavian",

[0115] "Purpose of Use": "Living Room",

[0116] "Budget": 50000

[0117] }

[0118] Data reception and analysis

[0119] Server: Analyzes the received data and converts it into a format suitable for the generative AI model. For example, it generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[0120] Generate interior plans

[0121] Server: Input a prompt into the generative AI model and generate interior coordination ideas. For example, use the following prompt:

[0122] "Please coordinate a living room with a Scandinavian feel. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior design that emphasizes simple, light-colored furniture and natural materials."

[0123] Furniture selection

[0124] Server: Based on the generated interior coordination proposal, the server searches the internet for furniture that can be acquired within the budget. For example, it uses an online shop's API to suggest a wooden center table, a Scandinavian-style sofa, and a light-toned carpet.

[0125] Integration of interior planning and furniture

[0126] Server: Integrates the generated interior coordination ideas with the selected furniture information and generates data to present to the user, such as detailed information including a room layout, furniture placement, prices, sizes, and purchase links.

[0127] View Suggestions

[0128] Terminal: The proposed data received from the server is displayed on the user interface. The user can check the proposed interior coordination and detailed furniture information. They can also easily purchase the furniture by clicking the purchase link.

[0129] Receiving feedback and resubmitting

[0130] Terminal: The user inputs feedback on the proposal. For example, they input a request such as "I would like to change the color of the sofa" and request a new proposal.

[0131] Server: Receives feedback and sends new prompts to the generative AI model to generate new interior design suggestions. For example, it sends a new prompt such as, "Generate new coordination ideas for a Scandinavian-style living room, measuring 5 meters long and 4 meters wide, with a bright-colored sofa, within a budget of 50,000 yen."

[0132] This allows users to effortlessly create their ideal interior coordination, and the system can continue to provide a variety of suggestions based on user feedback.

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

[0134] Step 1: Accept user input

[0135] Terminal: The user enters information such as the room layout, interior style, purpose of use, budget, etc. on the interface. The entered information is converted into a JSON format that the system can understand.

[0136] Input: User's room layout (e.g., 5 meters long, 4 meters wide), interior style (e.g., Scandinavian), purpose of room (e.g., living room), budget (e.g., 50,000 yen).

[0137] Output: JSON formatted data.

[0138] Specific operation: The user checks the information entered and clicks the "Submit" button. This action causes the data to be processed.

[0139] Step 2: Sending data

[0140] Terminal: The terminal sends the entered JSON format data to the server.

[0141] Input: User input data in JSON format.

[0142] Output: The HTTP request sent to the server.

[0143] Specific operation: The device makes an HTTP POST request to the server and sends JSON data. If the sending process is successful, a confirmation message will be displayed.

[0144] Step 3: Receiving and analyzing data

[0145] Server: Receives and analyzes JSON data sent from the terminal. Generates a prompt based on the input data.

[0146] Input: JSON data sent from the terminal.

[0147] Output: The generated prompt statement.

[0148] Specific operation: The server analyzes the JSON data and generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[0149] Step 4: Generate an interior plan

[0150] Server: The generated prompt sentence is input into the generative AI model to generate interior coordination suggestions.

[0151] Input: The generated prompt statement.

[0152] Output: Interior coordination suggestions from the generative AI model.

[0153] Specific operation: The server sends the following prompt to the generative AI model: "Please coordinate a living room with a Scandinavian style. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior that emphasizes simple, light-colored furniture and natural materials." The server then receives the coordination suggestions provided by the model.

[0154] Step 5: Furniture selection

[0155] Server: Based on the generated interior design ideas, the server searches the internet for furniture that can be obtained within the budget.

[0156] Input: Generated interior coordination proposal.

[0157] Output: A list of furniture that can be acquired within your budget.

[0158] Specific operation: The server executes a search query using the online shop's API, and obtains information such as "a wooden center table, a Nordic-style sofa, and a light-toned carpet for under 50,000 yen."

[0159] Step 6: Integrating the interior plan and furniture

[0160] Server: Integrates the generated interior plan and furniture information to generate proposal data.

[0161] Input: Interior coordination ideas and furniture list.

[0162] Output: Consolidated proposal data.

[0163] What it does: The server creates a detailed layout diagram including the layout, price, size, and purchase link for each piece of furniture, and provides it to the user as an integrated interior plan.

[0164] Step 7: Viewing Proposals

[0165] Terminal: Displays the proposal data received from the server on the user interface.

[0166] Input: Proposal data received from the server.

[0167] Output: Interior coordination ideas and furniture information displayed on the user interface.

[0168] Specific operation: The device displays a layout diagram, furniture layout, prices, sizes, purchase links, etc. for the user to review.

[0169] Step 8: Receive feedback and resubmit

[0170] Terminal: The user enters feedback on the suggestion.

[0171] Input: User feedback.

[0172] Output: Feedback data sent to the server.

[0173] Specific behavior: The user enters feedback and sends it to the server as a re-proposal request. This action generates a new prompt and a new proposal.

[0174] By clearly separating each processing step and its specific operation for the user, terminal, and server, this system allows users to realize their ideal interior coordination.

[0175] (Application example 1)

[0176] 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."

[0177] Conventional interior coordination systems have limited means for users to visually check furniture placement and design, and lack a real-time interactive experience. Furthermore, because re-suggestions based on user feedback are not made quickly, achieving the optimal coordination often takes time. Furthermore, these systems are difficult to understand for users who do not have a concrete image of the interior plan, making it difficult to achieve a satisfactory feeling when using them.

[0178] 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.

[0179] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits the user's budget, means for applying the searched furniture to the user's interior coordination, means for displaying the interior coordination on a user interface, means for receiving feedback from the user and generating a re-proposal, and means for viewing the interior via a VR device and changing the coordination content in real time. This allows the user to visually and interactively coordinate their interior in real time, enabling them to quickly and efficiently realize an optimal interior plan.

[0180] "Means for accepting user input" refers to technology that provides an interface for collecting data entered by the user.

[0181] "Means for transmitting data entered by the user to the server" refers to a mechanism for transferring data provided by the user to the server via a network.

[0182] "Means for generating interior coordination using a generative AI model" refers to technology that uses a generative AI model (e.g., a machine learning model) to create an interior plan that meets the user's requirements.

[0183] "A means of searching for furniture that fits a user's budget" is a function that searches an online database for furniture that can be purchased within the user's set budget.

[0184] The "means for applying the searched furniture to the user's interior coordination" is a technique for incorporating the searched furniture as part of an interior plan.

[0185] The "means for displaying interior coordination on a user interface" is a display system for visually presenting the generated interior plan to the user.

[0186] "Means for receiving feedback from users and generating new proposals" refers to a mechanism for collecting user opinions and requests and creating new proposals based on them.

[0187] "A means of viewing interiors via a VR device and changing the coordination details in real time" refers to a technology that uses a VR device to check interior plans in a virtual reality space and make changes on the spot as needed.

[0188] The present invention is a system that allows a user to efficiently coordinate the interior of a room, and specific embodiments thereof will be described below.

[0189] System configuration

[0190] The system consists of a user terminal, a server, and a VR device. The user terminal provides the user interface and is responsible for inputting and displaying data. The server processes the data and executes the generative AI model, and the VR device is used by the user to visually check the generated interior plan.

[0191] Hardware and software used

[0192] Hardware:

[0193] User devices: PC, tablet, smartphone

[0194] Server: High-performance computer

[0195] VR devices: smart glasses, head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0196] software:

[0197] User Interface Applications

[0198] Server program (e.g. Python, Flask)

[0199] Generative AI models (e.g., GPT-4)

[0200] Database Interface

[0201] Operation overview

[0202] 1. Accept user input:

[0203] The user uses a user terminal to input information such as the room layout, interior taste, purpose of use of the room, budget, etc. This input is done through a user interface application.

[0204] 2. Sending and Receiving Data:

[0205] The terminal sends the input data in JSON format to the server, which receives it and analyzes the data.

[0206] 3. Generate interior plan:

[0207] The server inputs the analyzed data into a generative AI model to generate an interior coordination based on the user's requests. For example, if a Scandinavian style is desired, furniture made of light colors and natural materials will be selected.

[0208] 4. Furniture selection:

[0209] The server searches a furniture database via the Internet to find furniture that is available within the user's budget, and applies the found furniture to the user's interior plan.

[0210] 5. View and real-time changes on VR devices:

[0211] Users can view the generated interior plan in real time using a VR device. Based on user feedback (e.g., a desire to change the color of the sofa), the server generates new proposals using the generative AI model.

[0212] Specific examples

[0213] User input: "The living room layout is 15 feet by 18 feet. The style is Scandinavian and the budget is $60,000."

[0214] Generative AI prompt: "Given a Scandinavian-style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection."

[0215] This system allows users to visually and interactively coordinate interiors in real time, enabling them to quickly and efficiently create optimal interior plans.

[0216] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0217] Step 1:

[0218] The user inputs interior information from the device. Specifically, the user uses the user interface on the device to input the room layout (e.g., 4 meters long, 5 meters wide), interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 60,000 yen). The input data is organized in JSON format.

[0219] Step 2:

[0220] The terminal sends the input data to the server. The input data (JSON format) is sent to the server via the network, and the server receives this data.

[0221] Step 3:

[0222] The server parses the received data, which is in JSON format, and extracts information such as the room layout, interior design, purpose of use, and budget. This analysis creates prompts for the generative AI model.

[0223] Step 4:

[0224] The server generates an interior coordination using a generative AI model. Specifically, based on the analyzed data, the server inputs the following prompts into the generative AI model (e.g., GPT-4):

[0225] "Given a Scandinavian style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection." Based on this prompt, the model generates an appropriate interior plan.

[0226] Step 5:

[0227] The server searches a furniture database via the Internet based on the generated interior plan. It searches for and collects furniture that is available within the user's budget. Specifically, it uses An API to search the furniture database and obtains information on furniture that matches the user's criteria (e.g., a wooden center table, a Nordic-style sofa, a light-toned carpet).

[0228] Step 6:

[0229] The server applies the furniture it finds to the interior plan. It then integrates the interior plan provided by the generative AI model with the furniture information obtained from the furniture database to create a specific layout plan. This completes the interior plan.

[0230] Step 7:

[0231] The server sends the completed interior plan to the terminal. The data including the generated interior plan and furniture information is sent to the terminal and converted into a format that can be displayed on the user interface.

[0232] Step 8:

[0233] The user checks the interior plan through the terminal and visually views the plan using the VR device. The terminal displays the interior plan and transmits the information to the VR device.

[0234] Step 9:

[0235] Accepts feedback from users. The user uses the VR device and terminal to input feedback about the interior plan (e.g., wanting to change the color of the sofa). This feedback is sent from the terminal to the server.

[0236] Step 10:

[0237] The server generates new interior proposals based on the received feedback. It then uses the generative AI model again to generate a new interior plan that reflects the feedback, and repeats the process from step 5 onwards.

[0238] By following these steps, users can visually and interactively coordinate interiors in real time.

[0239] 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.

[0240] This invention is a system that allows users to efficiently coordinate the interior of a room, and the processing of the program will be explained in detail below, especially the part that combines the emotion engine.

[0241] System Operation Overview

[0242] The system will suggest optimal interior plans and furniture based on the user's input of the room layout, interior taste, purpose of use, and budget. It also incorporates an emotion engine that recognizes the user's emotions, enabling it to offer interior suggestions that will further satisfy the user.

[0243] Accepting user input

[0244] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0245] Sending data

[0246] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[0247] Data reception and analysis

[0248] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[0249] Generate interior plans

[0250] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[0251] Furniture selection and proposal integration

[0252] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[0253] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0254] Analysis by emotion engine

[0255] Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfaction, dissatisfaction, excitement, etc.).

[0256] Emotion-based re-suggestion generation

[0257] Server: The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[0258] Data retransmission and display

[0259] Server: After generating new interior proposals, it sends the data to the device again.

[0260] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[0261] Specific examples

[0262] For example, if a user is not satisfied with the "Scandinavian-style living room" suggestion, the emotion engine will detect this and send dissatisfaction feedback to the server. The server will then regenerate a new suggestion incorporating different furniture arrangements and items and present it to the user again. Through this process, the system can provide an interior design that the user is completely satisfied with.

[0263] The above is a concrete example of how to implement the present invention. This system allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving a high level of satisfaction.

[0264] The processing flow will be explained below.

[0265] Step 1:

[0266] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0267] Step 2:

[0268] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[0269] Step 3:

[0270] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[0271] Step 4:

[0272] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[0273] Step 5:

[0274] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[0275] Step 6:

[0276] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0277] Step 7:

[0278] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[0279] Step 8:

[0280] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[0281] Step 9:

[0282] On the device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfied, dissatisfied, excited, etc.). For example, if the user is dissatisfied with the suggestions, the emotion engine will detect this.

[0283] Step 10:

[0284] Terminal: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[0285] Step 11:

[0286] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[0287] Step 12:

[0288] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[0289] Step 13:

[0290] Server: The server also takes into account feedback from the emotion engine to analyze the user's emotional state. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[0291] Step 14:

[0292] Server: After generating new interior proposals, it sends the data to the device again.

[0293] Step 15:

[0294] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[0295] This series of processes allows users to efficiently coordinate their interiors in a way that enhances their emotional satisfaction.

[0296] Example 2

[0297] 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."

[0298] In modern living spaces, many people often struggle with designing their own rooms. It can be particularly difficult to select the optimal interior design, taking into account numerous factors, such as the room's layout, interior taste, intended use, and budget. Furthermore, there are cases where the furniture purchased does not match the overall interior design or exceeds budget. Furthermore, there is no system that can provide interior design suggestions that take into account the user's emotions and reactions, which can lead to a decline in user satisfaction.

[0299] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for transmitting data input by a user to the server, a means for generating an interior coordination using a generative AI model, and a means for searching for furniture that fits the budget. This allows the user to efficiently coordinate the interior of a room.

[0300] The server also includes a means for applying the searched furniture to the user's interior coordination, a means for displaying the interior coordination on a user interface, a means for analyzing the user's emotional state, and a means for generating a re-proposal based on the user's emotional feedback. This enables interior proposals that reflect real-time feedback based on the user's emotions, ultimately achieving high satisfaction.

[0301] "User" refers to an individual or corporation that uses the system to input the data necessary to receive interior coordination proposals and to review the proposed interiors.

[0302] "Means for accepting input" refers to an interface or device that allows the user to input information such as the room layout, interior style, purpose of use of the room, budget, etc.

[0303] "Means for transmitting data to a server" refers to the function of encoding information entered by the user and sending it to a server via a communication means such as the Internet.

[0304] "Generative AI model" refers to an artificial intelligence model trained to automatically generate interior coordination based on specific interior tastes and requirements.

[0305] "Means for generating interior coordination" refers to the function of using a generative AI model to create an interior plan based on user input information.

[0306] "Searching tools" refers to the functionality that uses the internet and databases to find furniture and interior items that are within the user's budget.

[0307] "Means of application" refers to the function of reflecting the searched furniture and interior items in the generated interior coordination.

[0308] "User interface" refers to the screens and operating means through which users can view interior design proposals and provide feedback.

[0309] "Means for displaying" refers to the function of visually presenting the interior coordination generated by the server to the user through the user interface.

[0310] "Means for analyzing emotional state" refers to a function that uses an emotion engine to analyze emotions from the user's facial expressions, voice tone, etc., and determine satisfaction, dissatisfaction, etc.

[0311] "Means for generating re-proposals" refers to the function of re-operating the generative AI model to create new interior proposals based on the user's emotional feedback.

[0312] This invention is a system that allows users to efficiently coordinate the interior of a room. The program processing is specifically explained. This system uses a generative AI model to propose appropriate interior coordination based on user input, and further improves user satisfaction by making further proposals that reflect the user's emotional feedback.

[0313] Hardware and Software

[0314] Terminal: A device through which a user enters information, including computers, smartphones, tablets, etc.

[0315] Server: Analyzes the received data, generates interior coordination using a generative AI model, and makes new suggestions.

[0316] Emotion engine: Software used to analyze a user's facial expressions and tone of voice to determine their emotional state.

[0317] Program processing

[0318] 1. Accepting user input

[0319] Users input their room layout, interior style, purpose of use, and budget through the terminal. The interface is designed to be easy to use, and it is possible to input specific information such as a "floor plan of 5 meters long and 4 meters wide," a "Scandinavian-style living room," and a "budget of 50,000 yen."

[0320] 2. Data transmission

[0321] After checking the input, the user presses the send button, and the device encodes the input data in JSON format and sends it to the server via the Internet.

[0322] 3. Data Receipt and Analysis

[0323] The server receives the data sent from the device and analyzes the information obtained. Based on this analysis, it understands the user's requirements (floor layout, interior taste, purpose of use, budget).

[0324] 4. Generate interior plans

[0325] The server then uses a generative AI model based on the analyzed data to generate interior coordination. This AI model is optimized for a specific interior style (e.g., Scandinavian style) and suggests simple, light-colored furniture and natural materials. It also calculates the optimal furniture placement based on the room layout.

[0326] 5. Furniture selection and proposal integration

[0327] The server searches a furniture database via the Internet and selects items that can be purchased within the customer's budget. For example, it selects a wooden center table or a Scandinavian-style sofa from an online furniture database. This ensures that the data is consistent. Finally, it compiles a furniture layout diagram and detailed information about each piece of furniture (price, purchase link, size) into a single proposal data set.

[0328] 6. Analysis by Emotion Engine

[0329] As the user browses the suggested interiors, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state (satisfied, dissatisfied, excited, etc.).

[0330] 7. Emotion-based re-suggestion generation

[0331] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, it generates new interior design suggestions by re-running the generative AI model.

[0332] 8. Data retransmission and display

[0333] After generating new interior suggestions, the system re-encodes them and sends the data to the device, which receives the new suggestions and displays them again on the user interface. This process can be repeated until the user is satisfied.

[0334] Specific examples

[0335] For example, if a user enters, "I want to create a Scandinavian-style living room in a room that is 5 meters long and 4 meters wide. My budget is 50,000 yen," the system will perform the following actions:

[0336] 1. User: Enter the above information using the terminal.

[0337] 2. Terminal: The input is encoded in JSON format and sent to the server.

[0338] 3. Server: Receives and analyzes the data and generates an interior plan using a generative AI model.

[0339] 4. Server: Searches relevant online furniture databases and selects furniture that can be purchased within your budget.

[0340] 5. Server: Integrates the interior plan and selected furniture to generate detailed data.

[0341] 6. Terminal: The generated interior design proposals are displayed to the user, and the emotion engine analyzes the user's reaction.

[0342] 7. Server: Regenerates if necessary and sends new proposals to the device.

[0343] Example prompts for generative AI models

[0344] Below is an example of an input prompt sentence for the generative AI model.

[0345] "Please suggest a Scandinavian-inspired living room for a 5m x 4m room. My budget is 50,000 yen."

[0346] The above is the specific operation and implementation form of this system, which allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving high levels of satisfaction.

[0347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0348] Step 1:

[0349] Accepting user input

[0350] 1. User: Uses the device to enter information such as the room layout, interior style, purpose of use of the room, budget, etc.

[0351] 2. Input: room layout (5 meters long x 4 meters wide), interior style (Scandinavian), purpose of room (living room), budget (50,000 yen).

[0352] 3. Output: The input data is stored in the device's memory.

[0353] 4. Specific actions: The user enters the necessary information into the input form on the device and presses the "Submit" button.

[0354] Step 2:

[0355] Sending data

[0356] 1. Terminal: The input data is encoded in JSON format and sent to the server for further processing.

[0357] 2. Input: Data entered by the user.

[0358] 3. Output: JSON formatted data is sent to the server.

[0359] 4. Specific operation: The terminal compiles the input content into a single JSON object and sends it to the server via the Internet.

[0360] Step 3:

[0361] Data reception and analysis

[0362] 1. Server: Analyzes the JSON format data received from the device and understands the user's requirements (floor plan, interior style, purpose of use, budget).

[0363] 2. Input: JSON format data sent from the terminal.

[0364] 3. Output: Analyzed data (floor plan, interior design, purpose of use, budget).

[0365] 4. Specific operation: The server decodes the received JSON data, stores it in an internal structure, and analyzes it.

[0366] Step 4:

[0367] Generate interior plans

[0368] 1. Server: Based on the analyzed data, it generates interior coordination using a generative AI model.

[0369] 2. Input: Parsed data.

[0370] 3. Output: Generated interior plan.

[0371] 4. Specific operation: Pass the prompt to the generative AI model and receive an interior plan based on the user's requirements.

[0372] Step 5:

[0373] Furniture selection and proposal integration

[0374] 1. Server: Searches a furniture database via the Internet and selects furniture that can be purchased within the budget.

[0375] 2. Input: Generated interior plan and budget.

[0376] 3. Output: A list of selected furniture.

[0377] 4. Specific Action: Query an online furniture database and filter the results to find furniture within your budget.

[0378] 5. Server: Integrates the furniture list and the generated interior plan, and generates proposal data to present to the end user.

[0379] 6. Input: List of selected furniture.

[0380] 7. Output: Consolidated proposal data.

[0381] 8. Specific actions: Compile furniture layout diagrams, pricing information, product links, etc. into a single proposal document.

[0382] Step 6:

[0383] Analysis by emotion engine

[0384] 1. Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[0385] 2. Input: User's facial expression data, tone of voice.

[0386] 3. Output: The user's emotional state (satisfied, dissatisfied, excited, etc.).

[0387] 4. Specific operation: The emotion engine collects and analyzes data using the camera and microphone installed on the device.

[0388] Step 7:

[0389] Emotion-based re-suggestion generation

[0390] 1. Server: Analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, the generative AI model is reactivated to generate new interior design suggestions.

[0391] 2. Input: User's emotional feedback.

[0392] 3. Output: Re-proposed interior plan.

[0393] 4. Specific actions: Analyze the feedback data and pass new prompts to the generative AI model to regenerate the interior plan.

[0394] Step 8:

[0395] Resend and display data

[0396] 1. Server: Sends new interior proposals to the device.

[0397] 2. Input: Regenerated interior plan.

[0398] 3. Output: The new proposal data sent to the device.

[0399] 4. Specific operation: The proposed data is re-encoded and sent to the terminal via the Internet.

[0400] 5. Terminal: Receives new proposal data and displays it on the user interface.

[0401] 6. Input: Re-proposal data sent from the server.

[0402] 7. Output: Interior proposals displayed on the user interface.

[0403] 8. Specific operation: The terminal decodes the received data and updates the user interface displayed on the screen.

[0404] (Application example 2)

[0405] 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."

[0406] Conventional interior coordination systems simply generate and provide interior plans based on data entered by the user. As a result, they were unable to make dynamic suggestions based on the user's emotions and satisfaction, and multiple trials and manual adjustments were required to obtain optimal interior suggestions. Furthermore, they lacked real-time display and feedback of the interior plans, limiting the user experience. In response, there is a need for a system that can recognize the user's emotional state and automatically generate optimal suggestions while receiving feedback in real time.

[0407] 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.

[0408] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for items that fit the user's budget, means for applying the searched items to the user's interior coordination, means for displaying the interior coordination on a user interface, means for recognizing the user's emotional state, and means for generating re-proposals based on the recognized emotional state. This makes it possible to analyze the user's emotional feedback in real time and quickly automatically generate optimized interior proposals. The user can repeatedly receive proposals until they are satisfied, thereby achieving higher satisfaction.

[0409] The "means for accepting user input" is a device that provides an interface for the user to input data such as the room layout, interior taste, purpose of use of the room, budget, etc.

[0410] A "means for transmitting data entered by a user to a server" is a device that has the function of encoding information entered by a user in a standard format and transmitting it to a server located at a remote location.

[0411] A "means for generating interior coordination using a generative AI model" is a system that uses a generative AI model to automatically generate optimal interior coordination based on user input.

[0412] The "means for searching for items that fit a budget" is a system that has the function of searching an item database via the Internet and identifying items that can be acquired within the user's budget.

[0413] The "means for applying the searched item to the user's interior coordination" refers to a device or system that has the function of arranging the searched item in the generated interior plan.

[0414] The "means for displaying interior coordination on a user interface" refers to a display device or software for visually presenting the generated interior plan to the user.

[0415] "Means for recognizing the user's emotional state" refers to devices or software that analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[0416] The "means for generating new suggestions based on the recognized emotional state" is a system that automatically generates new interior suggestions according to the user's emotions based on feedback from the emotion engine.

[0417] This invention is a system that allows users to efficiently coordinate the interior of a room. Specific embodiments and their configurations are described in detail below. This system uses user input data and proposes interior plans using a generative AI model. It also incorporates an emotion engine to provide optimal proposals in real time based on the user's emotions.

[0418] System configuration

[0419] Hardware

[0420] Smart glasses / tablet: Used as an interface for users to provide input data, such as the room layout, interior taste, purpose of use, and budget.

[0421] Server: Receives, analyzes, and processes data sent by users. Generates interior coordination using generative AI models.

[0422] Emotion recognition device: Analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[0423] software

[0424] Generative AI model: Automatically generates optimal interior coordination based on user input data. This is a model trained to create interior plans that match the user's preferences and room characteristics.

[0425] Emotion engine: Analyzes user emotions in real time and provides feedback on user satisfaction.

[0426] Program Processing Details

[0427] Data collection and input

[0428] First, the user enters data such as the room layout, interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 50,000 yen) into an interface displayed on smart glasses or a tablet.

[0429] Data transmission and analysis

[0430] The data entered by the user is encoded into a standard format (e.g., JSON) and sent to the server. The server receives this data and analyzes it. Specifically, it analyzes information such as the room layout, interior taste, purpose of use, and budget, and generates the optimal interior plan based on that information.

[0431] Generate interior plans

[0432] The server uses the analyzed data to run a generative AI model to generate an interior coordination plan, taking into account the user's specified interior style (e.g., Scandinavian) and the characteristics of the room. It also searches for items that fit the user's budget and selects candidate items.

[0433] Emotion Recognition and Re-Suggestion

[0434] When a user browses an interior plan, an emotion recognition device analyzes the user's facial expressions and tone of voice in real time to determine their emotional state. If the user expresses dissatisfaction, the server recreates a new interior proposal using a generative AI model and presents it to the user again for optimization.

[0435] Specific examples

[0436] For example, if a user requests a "Scandinavian-style living room" and is dissatisfied with the initial proposal, the emotion engine detects the user's dissatisfaction and provides feedback to the server. The server then uses the generative AI model to create a new proposal, perhaps incorporating different furniture arrangements or items. This process is repeated until the user is satisfied.

[0437] Prompt Sentence Examples

[0438] "Room: 5 meters long, 4 meters wide, Use: Living room, Style: Scandinavian, Budget: 50,000 yen. Proposal: Create an interior design with a Scandinavian feel."

[0439] The above is an embodiment of the present invention. This system allows the user to achieve the best interior coordination while receiving real-time feedback based on their emotions.

[0440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0441] Step 1:

[0442] User Input

[0443] Using smart glasses or a tablet, users input the room layout, interior design preferences, purpose of use, and budget, and this input data is captured through the interface.

[0444] Input: Room layout, interior style, purpose of use, budget

[0445] Output: Input data in JSON format

[0446] Step 2:

[0447] Sending data

[0448] The terminal encodes the data entered by the user in a standard format (JSON format) and sends it to the server. Data transmission is triggered when the user presses the send button.

[0449] Input: Input data in JSON format

[0450] Output: Data sent to the server

[0451] Step 3:

[0452] Data reception and analysis

[0453] The server receives the data sent from the device and analyzes it to understand the user's requirements, such as the room layout, interior style, purpose of use, and budget.

[0454] Input: Data from the terminal

[0455] Output: Parsed user request data

[0456] Step 4:

[0457] Generate interior plans

[0458] The server then uses a generative AI model to generate interior coordination based on the analyzed data. For example, it could use a model trained to generate Scandinavian-style interiors to generate a plan. It also optimizes furniture placement based on the room layout.

[0459] Input: Parsed user request data

[0460] Output: Generated interior plan

[0461] Step 5:

[0462] Finding items that fit your budget

[0463] The server searches an online database of items to find items that can be purchased within the budget. For example, it selects items such as a wooden center table, a Scandinavian-style sofa, and a light-toned carpet from the online database.

[0464] Input: Budget and interior plan

[0465] Output: Information on items that can be obtained within the budget

[0466] Step 6:

[0467] Interior plan integration and display

[0468] The server integrates the generated interior coordination and item details based on the selected item information. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0469] Input: Generated interior plan, item information

[0470] Output: Integrated interior proposals

[0471] Step 7:

[0472] Display of interior design proposals

[0473] The terminal receives the interior proposal data sent from the server and displays it on the user interface. The user can then confirm the proposed interior coordination.

[0474] Input: Integrated interior proposals

[0475] Output: Interior design suggestions displayed on the user interface

[0476] Step 8:

[0477] emotion recognition

[0478] As users browse interior design suggestions, the emotion engine analyzes their facial expressions and tone of voice in real time to determine their emotional state (satisfaction, dissatisfaction, excitement, etc.).

[0479] Input: User's facial expressions, tone of voice

[0480] Output: Determined user's emotional state

[0481] Step 9:

[0482] Generate re-proposals

[0483] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[0484] Input: Determined user emotional state

[0485] Output: New interior proposals

[0486] Step 10:

[0487] Submitting and viewing new suggestions

[0488] After generating new interior suggestions, the server sends the data back to the device. The device analyzes the new suggestions and displays them again on the user interface. The user can review the new suggestions and repeat this process until they are satisfied.

[0489] Input: New interior design proposal

[0490] Output: New interior design suggestions displayed on the user interface

[0491] 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.

[0492] 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.

[0493] 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.

[0494] [Second embodiment]

[0495] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0496] 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.

[0497] 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).

[0498] 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.

[0499] 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.

[0500] 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).

[0501] 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.

[0502] 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.

[0503] 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.

[0504] 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.

[0505] 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.

[0506] 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."

[0507] This invention is a system that allows a user to efficiently coordinate the interior of a room, and the processing of the program will be specifically described below.

[0508] System Operation Overview

[0509] The system allows users to input their room layout, interior taste, purpose of use, and budget, and then uses that information to suggest the optimal interior plan and furniture. The system receives user input and uses a generative AI model to generate an interior coordination and select furniture.

[0510] Accepting user input

[0511] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0512] Sending data

[0513] Terminal: Sends data entered by the user to the server in a standard format such as JSON.

[0514] Data reception and analysis

[0515] Server: The server receives and analyzes the data sent from the device. The analyzed data is then fed into a generative AI model. For example, it might understand that a Scandinavian-inspired interior is desired, or that the room layout is 5 meters long and 4 meters wide.

[0516] Generate interior plans

[0517] Server: The server uses a generative AI model to generate interior coordination based on input data. For a Scandinavian style, the generative AI model suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[0518] Furniture selection

[0519] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[0520] Integration of interior planning and furniture

[0521] Server: Integrates the generated interior plan and selected furniture information into a single proposal. For example, it provides detailed information including a specific furniture layout for a Scandinavian-style living room, the price of each piece of furniture, and a link to purchase it.

[0522] Sending data

[0523] Server: Sends the proposal data to the terminal.

[0524] View Suggestions

[0525] Device: The proposed interior coordination and furniture recommendations are displayed on the user interface. The user can check detailed information (price, purchase link, size) of the recommended furniture.

[0526] Receiving feedback and resubmitting

[0527] Terminal: The user enters feedback on the suggestion (e.g., I would like to change the color of the sofa). The feedback is sent back to the server.

[0528] Server: Receives feedback and generates new interior design proposals, for example, new proposals that include a brightly colored sofa.

[0529] The above steps are repeated until the proposed interior coordination is satisfactory to the user, thereby achieving the optimal interior.

[0530] In this way, users can easily and efficiently coordinate their interiors and create their ideal living environment or work space.

[0531] The processing flow will be explained below.

[0532] Step 1:

[0533] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0534] Step 2:

[0535] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[0536] Step 3:

[0537] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[0538] Step 4:

[0539] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[0540] Step 5:

[0541] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[0542] Step 6:

[0543] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0544] Step 7:

[0545] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[0546] Step 8:

[0547] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[0548] Step 9:

[0549] User: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[0550] Step 10:

[0551] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[0552] Step 11:

[0553] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[0554] Step 12:

[0555] Server: Sends new interior design proposals to the device.

[0556] Step 13:

[0557] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[0558] These are the specific processing steps of this system. Through this series of processes, users can efficiently realize their ideal interior.

[0559] Example 1

[0560] 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."

[0561] Currently, there are few efficient ways to coordinate the interior of a room. Users often have to think about the interior design and select and arrange the furniture themselves, which takes time and effort. In addition, there are few systems that can propose interior plans that match the user's image, making it difficult for users to achieve an interior environment that satisfies them. To solve this problem, a system is needed that can automatically propose optimal interior plans and furniture based on user input.

[0562] 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.

[0563] In this invention, the server includes means for transmitting data input by a user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits a budget, means for applying the searched furniture to the user's interior coordination, means for creating and transmitting prompts to the generative AI model, and means for providing an optimal interior plan based on the user's room layout and interior taste, thereby enabling the user to realize their ideal interior coordination without any hassle.

[0564] "User" refers to an individual or corporation that uses the system to coordinate the interior of a room.

[0565] "Server" refers to the computer system that receives data sent by users and generates interior coordination using analytical and generative AI models.

[0566] "Terminal" refers to the device (e.g., smartphone, computer, tablet) that a user uses to access the system and enter data, review suggestions, etc.

[0567] A "generative AI model" refers to an artificial intelligence model that generates optimal interior coordination based on data entered by the user.

[0568] A "prompt" refers to an instruction or question that is input to a generative AI model to generate an interior coordination.

[0569] "Interior coordination" refers to a plan that proposes optimal furniture placement and decoration based on the room layout, interior taste, purpose of use of the room, budget, etc.

[0570] "Furniture" refers to items (e.g., tables, sofas, carpets) that are placed in a room and are necessary for interior coordination.

[0571] A "furniture database" refers to an online database that registers information about various furniture items (e.g., price, size, material, and purchase link).

[0572] "User interface" refers to the screen or operating means through which a user inputs data into a system or checks suggestions.

[0573] "Feedback" refers to opinions and information such as requests for changes or improvements made by users in response to proposals.

[0574] "Re-proposals" refer to new interior coordination ideas generated based on feedback received from users.

[0575] The present invention is a system for enabling a user to efficiently coordinate the interior design of a room. Specific embodiments will be described below.

[0576] The system consists of three main components: a terminal where users input information, a server that receives and processes the input data, and a generative AI model.

[0577] Accepting user input

[0578] Device: Users access the system using a PC, smartphone, or tablet device. On the user interface, they input information such as the room layout, interior style, purpose of use, and budget. For example, a user might input a 5-meter by 4-meter floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0579] Sending data

[0580] Terminal: The data entered by the user is converted to JSON format and sent to the server. For example, the following JSON data is generated:

[0581] json

[0582] {

[0583] "Layout": {"Length": 5, "Width": 4},

[0584] "Taste": "Scandinavian",

[0585] "Purpose of Use": "Living Room",

[0586] "Budget": 50000

[0587] }

[0588] Data reception and analysis

[0589] Server: Analyzes the received data and converts it into a format suitable for the generative AI model. For example, it generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[0590] Generate interior plans

[0591] Server: Input a prompt into the generative AI model and generate interior coordination ideas. For example, use the following prompt:

[0592] "Please coordinate a living room with a Scandinavian feel. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior design that emphasizes simple, light-colored furniture and natural materials."

[0593] Furniture selection

[0594] Server: Based on the generated interior coordination proposal, the server searches the internet for furniture that can be acquired within the budget. For example, it uses an online shop's API to suggest a wooden center table, a Scandinavian-style sofa, and a light-toned carpet.

[0595] Integration of interior planning and furniture

[0596] Server: Integrates the generated interior coordination ideas with the selected furniture information and generates data to present to the user, such as detailed information including a room layout, furniture placement, prices, sizes, and purchase links.

[0597] View Suggestions

[0598] Terminal: The proposed data received from the server is displayed on the user interface. The user can check the proposed interior coordination and detailed furniture information. They can also easily purchase the furniture by clicking the purchase link.

[0599] Receiving feedback and resubmitting

[0600] Terminal: The user inputs feedback on the proposal. For example, they input a request such as "I would like to change the color of the sofa" and request a new proposal.

[0601] Server: Receives feedback and sends new prompts to the generative AI model to generate new interior design suggestions. For example, it sends a new prompt such as, "Generate new coordination ideas for a Scandinavian-style living room, measuring 5 meters long and 4 meters wide, with a bright-colored sofa, within a budget of 50,000 yen."

[0602] This allows users to effortlessly create their ideal interior coordination, and the system can continue to provide a variety of suggestions based on user feedback.

[0603] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0604] Step 1: Accept user input

[0605] Terminal: The user enters information such as the room layout, interior style, purpose of use, budget, etc. on the interface. The entered information is converted into a JSON format that the system can understand.

[0606] Input: User's room layout (e.g., 5 meters long, 4 meters wide), interior style (e.g., Scandinavian), purpose of room (e.g., living room), budget (e.g., 50,000 yen).

[0607] Output: JSON formatted data.

[0608] Specific operation: The user checks the information entered and clicks the "Submit" button. This action causes the data to be processed.

[0609] Step 2: Sending data

[0610] Terminal: The terminal sends the entered JSON format data to the server.

[0611] Input: User input data in JSON format.

[0612] Output: The HTTP request sent to the server.

[0613] Specific operation: The device makes an HTTP POST request to the server and sends JSON data. If the sending process is successful, a confirmation message will be displayed.

[0614] Step 3: Receiving and analyzing data

[0615] Server: Receives and analyzes JSON data sent from the terminal. Generates a prompt based on the input data.

[0616] Input: JSON data sent from the terminal.

[0617] Output: The generated prompt statement.

[0618] Specific operation: The server analyzes the JSON data and generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[0619] Step 4: Generate an interior plan

[0620] Server: The generated prompt sentence is input into the generative AI model to generate interior coordination suggestions.

[0621] Input: The generated prompt statement.

[0622] Output: Interior coordination suggestions from the generative AI model.

[0623] Specific operation: The server sends the following prompt to the generative AI model: "Please coordinate a living room with a Scandinavian style. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior that emphasizes simple, light-colored furniture and natural materials." The server then receives the coordination suggestions provided by the model.

[0624] Step 5: Furniture selection

[0625] Server: Based on the generated interior design ideas, the server searches the internet for furniture that can be obtained within the budget.

[0626] Input: Generated interior coordination proposal.

[0627] Output: A list of furniture that can be acquired within your budget.

[0628] Specific operation: The server executes a search query using the online shop's API, and obtains information such as "a wooden center table, a Nordic-style sofa, and a light-toned carpet for under 50,000 yen."

[0629] Step 6: Integrating the interior plan and furniture

[0630] Server: Integrates the generated interior plan and furniture information to generate proposal data.

[0631] Input: Interior coordination ideas and furniture list.

[0632] Output: Consolidated proposal data.

[0633] What it does: The server creates a detailed layout diagram including the layout, price, size, and purchase link for each piece of furniture, and provides it to the user as an integrated interior plan.

[0634] Step 7: Viewing Proposals

[0635] Terminal: Displays the proposal data received from the server on the user interface.

[0636] Input: Proposal data received from the server.

[0637] Output: Interior coordination ideas and furniture information displayed on the user interface.

[0638] Specific operation: The device displays a layout diagram, furniture layout, prices, sizes, purchase links, etc. for the user to review.

[0639] Step 8: Receive feedback and resubmit

[0640] Terminal: The user enters feedback on the suggestion.

[0641] Input: User feedback.

[0642] Output: Feedback data sent to the server.

[0643] Specific behavior: The user enters feedback and sends it to the server as a re-proposal request. This action generates a new prompt and a new proposal.

[0644] By clearly separating each processing step and its specific operation for the user, terminal, and server, this system allows users to realize their ideal interior coordination.

[0645] (Application example 1)

[0646] 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."

[0647] Conventional interior coordination systems have limited means for users to visually check furniture placement and design, and lack a real-time interactive experience. Furthermore, because re-suggestions based on user feedback are not made quickly, achieving the optimal coordination often takes time. Furthermore, these systems are difficult to understand for users who do not have a concrete image of the interior plan, making it difficult to achieve a satisfactory feeling when using them.

[0648] 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.

[0649] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits the user's budget, means for applying the searched furniture to the user's interior coordination, means for displaying the interior coordination on a user interface, means for receiving feedback from the user and generating a re-proposal, and means for viewing the interior via a VR device and changing the coordination content in real time. This allows the user to visually and interactively coordinate their interior in real time, enabling them to quickly and efficiently realize an optimal interior plan.

[0650] "Means for accepting user input" refers to technology that provides an interface for collecting data entered by the user.

[0651] "Means for transmitting data entered by the user to the server" refers to a mechanism for transferring data provided by the user to the server via a network.

[0652] "Means for generating interior coordination using a generative AI model" refers to technology that uses a generative AI model (e.g., a machine learning model) to create an interior plan that meets the user's requirements.

[0653] "A means of searching for furniture that fits a user's budget" is a function that searches an online database for furniture that can be purchased within the user's set budget.

[0654] The "means for applying the searched furniture to the user's interior coordination" is a technique for incorporating the searched furniture as part of an interior plan.

[0655] The "means for displaying interior coordination on a user interface" is a display system for visually presenting the generated interior plan to the user.

[0656] "Means for receiving feedback from users and generating new proposals" refers to a mechanism for collecting user opinions and requests and creating new proposals based on them.

[0657] "A means of viewing interiors via a VR device and changing the coordination details in real time" refers to a technology that uses a VR device to check interior plans in a virtual reality space and make changes on the spot as needed.

[0658] The present invention is a system that allows a user to efficiently coordinate the interior of a room, and specific embodiments thereof will be described below.

[0659] System configuration

[0660] The system consists of a user terminal, a server, and a VR device. The user terminal provides the user interface and is responsible for inputting and displaying data. The server processes the data and executes the generative AI model, and the VR device is used by the user to visually check the generated interior plan.

[0661] Hardware and software used

[0662] Hardware:

[0663] User devices: PC, tablet, smartphone

[0664] Server: High-performance computer

[0665] VR devices: smart glasses, head-mounted displays (e.g., Oculus Rift, HTC Vive)

[0666] software:

[0667] User Interface Applications

[0668] Server program (e.g. Python, Flask)

[0669] Generative AI models (e.g., GPT-4)

[0670] Database Interface

[0671] Operation overview

[0672] 1. Accept user input:

[0673] The user uses a user terminal to input information such as the room layout, interior taste, purpose of use of the room, budget, etc. This input is done through a user interface application.

[0674] 2. Sending and Receiving Data:

[0675] The terminal sends the input data in JSON format to the server, which receives it and analyzes the data.

[0676] 3. Generate interior plan:

[0677] The server inputs the analyzed data into a generative AI model to generate an interior coordination based on the user's requests. For example, if a Scandinavian style is desired, furniture made of light colors and natural materials will be selected.

[0678] 4. Furniture selection:

[0679] The server searches a furniture database via the Internet to find furniture that is available within the user's budget, and applies the found furniture to the user's interior plan.

[0680] 5. View and real-time changes on VR devices:

[0681] Users can view the generated interior plan in real time using a VR device. Based on user feedback (e.g., a desire to change the color of the sofa), the server generates new proposals using the generative AI model.

[0682] Specific examples

[0683] User input: "The living room layout is 15 feet by 18 feet. The style is Scandinavian and the budget is $60,000."

[0684] Generative AI prompt: "Given a Scandinavian-style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection."

[0685] This system allows users to visually and interactively coordinate interiors in real time, enabling them to quickly and efficiently create optimal interior plans.

[0686] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0687] Step 1:

[0688] The user inputs interior information from the device. Specifically, the user uses the user interface on the device to input the room layout (e.g., 4 meters long, 5 meters wide), interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 60,000 yen). The input data is organized in JSON format.

[0689] Step 2:

[0690] The terminal sends the input data to the server. The input data (JSON format) is sent to the server via the network, and the server receives this data.

[0691] Step 3:

[0692] The server parses the received data, which is in JSON format, and extracts information such as the room layout, interior design, purpose of use, and budget. This analysis creates prompts for the generative AI model.

[0693] Step 4:

[0694] The server generates an interior coordination using a generative AI model. Specifically, based on the analyzed data, the server inputs the following prompts into the generative AI model (e.g., GPT-4):

[0695] "Given a Scandinavian style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection." Based on this prompt, the model generates an appropriate interior plan.

[0696] Step 5:

[0697] The server searches a furniture database via the Internet based on the generated interior plan. It searches for and collects furniture that is available within the user's budget. Specifically, it uses An API to search the furniture database and obtains information on furniture that matches the user's criteria (e.g., a wooden center table, a Nordic-style sofa, a light-toned carpet).

[0698] Step 6:

[0699] The server applies the furniture it finds to the interior plan. It then integrates the interior plan provided by the generative AI model with the furniture information obtained from the furniture database to create a specific layout plan. This completes the interior plan.

[0700] Step 7:

[0701] The server sends the completed interior plan to the terminal. The data including the generated interior plan and furniture information is sent to the terminal and converted into a format that can be displayed on the user interface.

[0702] Step 8:

[0703] The user checks the interior plan through the terminal and visually views the plan using the VR device. The terminal displays the interior plan and transmits the information to the VR device.

[0704] Step 9:

[0705] Accepts feedback from users. The user uses the VR device and terminal to input feedback about the interior plan (e.g., wanting to change the color of the sofa). This feedback is sent from the terminal to the server.

[0706] Step 10:

[0707] The server generates new interior proposals based on the received feedback. It then uses the generative AI model again to generate a new interior plan that reflects the feedback, and repeats the process from step 5 onwards.

[0708] By following these steps, users can visually and interactively coordinate interiors in real time.

[0709] 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.

[0710] This invention is a system that allows users to efficiently coordinate the interior of a room, and the processing of the program will be explained in detail below, especially the part that combines the emotion engine.

[0711] System Operation Overview

[0712] The system will suggest optimal interior plans and furniture based on the user's input of the room layout, interior taste, purpose of use, and budget. It also incorporates an emotion engine that recognizes the user's emotions, enabling it to offer interior suggestions that will further satisfy the user.

[0713] Accepting user input

[0714] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0715] Sending data

[0716] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[0717] Data reception and analysis

[0718] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[0719] Generate interior plans

[0720] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[0721] Furniture selection and proposal integration

[0722] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[0723] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0724] Analysis by emotion engine

[0725] Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfaction, dissatisfaction, excitement, etc.).

[0726] Emotion-based re-suggestion generation

[0727] Server: The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[0728] Data retransmission and display

[0729] Server: After generating new interior proposals, it sends the data to the device again.

[0730] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[0731] Specific examples

[0732] For example, if a user is not satisfied with the "Scandinavian-style living room" suggestion, the emotion engine will detect this and send dissatisfaction feedback to the server. The server will then regenerate a new suggestion incorporating different furniture arrangements and items and present it to the user again. Through this process, the system can provide an interior design that the user is completely satisfied with.

[0733] The above is a concrete example of how to implement the present invention. This system allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving a high level of satisfaction.

[0734] The processing flow will be explained below.

[0735] Step 1:

[0736] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0737] Step 2:

[0738] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[0739] Step 3:

[0740] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[0741] Step 4:

[0742] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[0743] Step 5:

[0744] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[0745] Step 6:

[0746] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0747] Step 7:

[0748] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[0749] Step 8:

[0750] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[0751] Step 9:

[0752] On the device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfied, dissatisfied, excited, etc.). For example, if the user is dissatisfied with the suggestions, the emotion engine will detect this.

[0753] Step 10:

[0754] Terminal: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[0755] Step 11:

[0756] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[0757] Step 12:

[0758] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[0759] Step 13:

[0760] Server: The server also takes into account feedback from the emotion engine to analyze the user's emotional state. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[0761] Step 14:

[0762] Server: After generating new interior proposals, it sends the data to the device again.

[0763] Step 15:

[0764] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[0765] This series of processes allows users to efficiently coordinate their interiors in a way that enhances their emotional satisfaction.

[0766] Example 2

[0767] 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."

[0768] In modern living spaces, many people often struggle with designing their own rooms. It can be particularly difficult to select the optimal interior design, taking into account numerous factors, such as the room's layout, interior taste, intended use, and budget. Furthermore, there are cases where the furniture purchased does not match the overall interior design or exceeds budget. Furthermore, there is no system that can provide interior design suggestions that take into account the user's emotions and reactions, which can lead to a decline in user satisfaction.

[0769] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for transmitting data input by a user to the server, a means for generating an interior coordination using a generative AI model, and a means for searching for furniture that fits the budget. This allows the user to efficiently coordinate the interior of a room.

[0770] The server also includes a means for applying the searched furniture to the user's interior coordination, a means for displaying the interior coordination on a user interface, a means for analyzing the user's emotional state, and a means for generating a re-proposal based on the user's emotional feedback. This enables interior proposals that reflect real-time feedback based on the user's emotions, ultimately achieving high satisfaction.

[0771] "User" refers to an individual or corporation that uses the system to input the data necessary to receive interior coordination proposals and to review the proposed interiors.

[0772] "Means for accepting input" refers to an interface or device that allows the user to input information such as the room layout, interior style, purpose of use of the room, budget, etc.

[0773] "Means for transmitting data to a server" refers to the function of encoding information entered by the user and sending it to a server via a communication means such as the Internet.

[0774] "Generative AI model" refers to an artificial intelligence model trained to automatically generate interior coordination based on specific interior tastes and requirements.

[0775] "Means for generating interior coordination" refers to the function of using a generative AI model to create an interior plan based on user input information.

[0776] "Searching tools" refers to the functionality that uses the internet and databases to find furniture and interior items that are within the user's budget.

[0777] "Means of application" refers to the function of reflecting the searched furniture and interior items in the generated interior coordination.

[0778] "User interface" refers to the screens and operating means through which users can view interior design proposals and provide feedback.

[0779] "Means for displaying" refers to the function of visually presenting the interior coordination generated by the server to the user through the user interface.

[0780] "Means for analyzing emotional state" refers to a function that uses an emotion engine to analyze emotions from the user's facial expressions, voice tone, etc., and determine satisfaction, dissatisfaction, etc.

[0781] "Means for generating re-proposals" refers to the function of re-operating the generative AI model to create new interior proposals based on the user's emotional feedback.

[0782] This invention is a system that allows users to efficiently coordinate the interior of a room. The program processing is specifically explained. This system uses a generative AI model to propose appropriate interior coordination based on user input, and further improves user satisfaction by making further proposals that reflect the user's emotional feedback.

[0783] Hardware and Software

[0784] Terminal: A device through which a user enters information, including computers, smartphones, tablets, etc.

[0785] Server: Analyzes the received data, generates interior coordination using a generative AI model, and makes new suggestions.

[0786] Emotion engine: Software used to analyze a user's facial expressions and tone of voice to determine their emotional state.

[0787] Program processing

[0788] 1. Accepting user input

[0789] Users input their room layout, interior style, purpose of use, and budget through the terminal. The interface is designed to be easy to use, and it is possible to input specific information such as a "floor plan of 5 meters long and 4 meters wide," a "Scandinavian-style living room," and a "budget of 50,000 yen."

[0790] 2. Data transmission

[0791] After checking the input, the user presses the send button, and the device encodes the input data in JSON format and sends it to the server via the Internet.

[0792] 3. Data Receipt and Analysis

[0793] The server receives the data sent from the device and analyzes the information obtained. Based on this analysis, it understands the user's requirements (floor layout, interior taste, purpose of use, budget).

[0794] 4. Generate interior plans

[0795] The server then uses a generative AI model based on the analyzed data to generate interior coordination. This AI model is optimized for a specific interior style (e.g., Scandinavian style) and suggests simple, light-colored furniture and natural materials. It also calculates the optimal furniture placement based on the room layout.

[0796] 5. Furniture selection and proposal integration

[0797] The server searches a furniture database via the Internet and selects items that can be purchased within the customer's budget. For example, it selects a wooden center table or a Scandinavian-style sofa from an online furniture database. This ensures that the data is consistent. Finally, it compiles a furniture layout diagram and detailed information about each piece of furniture (price, purchase link, size) into a single proposal data set.

[0798] 6. Analysis by Emotion Engine

[0799] As the user browses the suggested interiors, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state (satisfied, dissatisfied, excited, etc.).

[0800] 7. Emotion-based re-suggestion generation

[0801] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, it generates new interior design suggestions by re-running the generative AI model.

[0802] 8. Data retransmission and display

[0803] After generating new interior suggestions, the system re-encodes them and sends the data to the device, which receives the new suggestions and displays them again on the user interface. This process can be repeated until the user is satisfied.

[0804] Specific examples

[0805] For example, if a user enters, "I want to create a Scandinavian-style living room in a room that is 5 meters long and 4 meters wide. My budget is 50,000 yen," the system will perform the following actions:

[0806] 1. User: Enter the above information using the terminal.

[0807] 2. Terminal: The input is encoded in JSON format and sent to the server.

[0808] 3. Server: Receives and analyzes the data and generates an interior plan using a generative AI model.

[0809] 4. Server: Searches relevant online furniture databases and selects furniture that can be purchased within your budget.

[0810] 5. Server: Integrates the interior plan and selected furniture to generate detailed data.

[0811] 6. Terminal: The generated interior design proposals are displayed to the user, and the emotion engine analyzes the user's reaction.

[0812] 7. Server: Regenerates if necessary and sends new proposals to the device.

[0813] Example prompts for generative AI models

[0814] Below is an example of an input prompt sentence for the generative AI model.

[0815] "Please suggest a Scandinavian-inspired living room for a 5m x 4m room. My budget is 50,000 yen."

[0816] The above is the specific operation and implementation form of this system, which allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving high levels of satisfaction.

[0817] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0818] Step 1:

[0819] Accepting user input

[0820] 1. User: Uses the device to enter information such as the room layout, interior style, purpose of use of the room, budget, etc.

[0821] 2. Input: room layout (5 meters long x 4 meters wide), interior style (Scandinavian), purpose of room (living room), budget (50,000 yen).

[0822] 3. Output: The input data is stored in the device's memory.

[0823] 4. Specific actions: The user enters the necessary information into the input form on the device and presses the "Submit" button.

[0824] Step 2:

[0825] Sending data

[0826] 1. Terminal: The input data is encoded in JSON format and sent to the server for further processing.

[0827] 2. Input: Data entered by the user.

[0828] 3. Output: JSON formatted data is sent to the server.

[0829] 4. Specific operation: The terminal compiles the input content into a single JSON object and sends it to the server via the Internet.

[0830] Step 3:

[0831] Data reception and analysis

[0832] 1. Server: Analyzes the JSON format data received from the device and understands the user's requirements (floor plan, interior style, purpose of use, budget).

[0833] 2. Input: JSON format data sent from the terminal.

[0834] 3. Output: Analyzed data (floor plan, interior design, purpose of use, budget).

[0835] 4. Specific operation: The server decodes the received JSON data, stores it in an internal structure, and analyzes it.

[0836] Step 4:

[0837] Generate interior plans

[0838] 1. Server: Based on the analyzed data, it generates interior coordination using a generative AI model.

[0839] 2. Input: Parsed data.

[0840] 3. Output: Generated interior plan.

[0841] 4. Specific operation: Pass the prompt to the generative AI model and receive an interior plan based on the user's requirements.

[0842] Step 5:

[0843] Furniture selection and proposal integration

[0844] 1. Server: Searches a furniture database via the Internet and selects furniture that can be purchased within the budget.

[0845] 2. Input: Generated interior plan and budget.

[0846] 3. Output: A list of selected furniture.

[0847] 4. Specific Action: Query an online furniture database and filter the results to find furniture within your budget.

[0848] 5. Server: Integrates the furniture list and the generated interior plan, and generates proposal data to present to the end user.

[0849] 6. Input: List of selected furniture.

[0850] 7. Output: Consolidated proposal data.

[0851] 8. Specific actions: Compile furniture layout diagrams, pricing information, product links, etc. into a single proposal document.

[0852] Step 6:

[0853] Analysis by emotion engine

[0854] 1. Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[0855] 2. Input: User's facial expression data, tone of voice.

[0856] 3. Output: The user's emotional state (satisfied, dissatisfied, excited, etc.).

[0857] 4. Specific operation: The emotion engine collects and analyzes data using the camera and microphone installed on the device.

[0858] Step 7:

[0859] Emotion-based re-suggestion generation

[0860] 1. Server: Analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, the generative AI model is reactivated to generate new interior design suggestions.

[0861] 2. Input: User's emotional feedback.

[0862] 3. Output: Re-proposed interior plan.

[0863] 4. Specific actions: Analyze the feedback data and pass new prompts to the generative AI model to regenerate the interior plan.

[0864] Step 8:

[0865] Resend and display data

[0866] 1. Server: Sends new interior proposals to the device.

[0867] 2. Input: Regenerated interior plan.

[0868] 3. Output: The new proposal data sent to the device.

[0869] 4. Specific operation: The proposed data is re-encoded and sent to the terminal via the Internet.

[0870] 5. Terminal: Receives new proposal data and displays it on the user interface.

[0871] 6. Input: Re-proposal data sent from the server.

[0872] 7. Output: Interior proposals displayed on the user interface.

[0873] 8. Specific operation: The terminal decodes the received data and updates the user interface displayed on the screen.

[0874] (Application example 2)

[0875] 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."

[0876] Conventional interior coordination systems simply generate and provide interior plans based on data entered by the user. As a result, they were unable to make dynamic suggestions based on the user's emotions and satisfaction, and multiple trials and manual adjustments were required to obtain optimal interior suggestions. Furthermore, they lacked real-time display and feedback of the interior plans, limiting the user experience. In response, there is a need for a system that can recognize the user's emotional state and automatically generate optimal suggestions while receiving feedback in real time.

[0877] 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.

[0878] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for items that fit the user's budget, means for applying the searched items to the user's interior coordination, means for displaying the interior coordination on a user interface, means for recognizing the user's emotional state, and means for generating re-proposals based on the recognized emotional state. This makes it possible to analyze the user's emotional feedback in real time and quickly automatically generate optimized interior proposals. The user can repeatedly receive proposals until they are satisfied, thereby achieving higher satisfaction.

[0879] The "means for accepting user input" is a device that provides an interface for the user to input data such as the room layout, interior taste, purpose of use of the room, budget, etc.

[0880] A "means for transmitting data entered by a user to a server" is a device that has the function of encoding information entered by a user in a standard format and transmitting it to a server located at a remote location.

[0881] A "means for generating interior coordination using a generative AI model" is a system that uses a generative AI model to automatically generate optimal interior coordination based on user input.

[0882] The "means for searching for items that fit a budget" is a system that has the function of searching an item database via the Internet and identifying items that can be acquired within the user's budget.

[0883] The "means for applying the searched item to the user's interior coordination" refers to a device or system that has the function of arranging the searched item in the generated interior plan.

[0884] The "means for displaying interior coordination on a user interface" refers to a display device or software for visually presenting the generated interior plan to the user.

[0885] "Means for recognizing the user's emotional state" refers to devices or software that analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[0886] The "means for generating new suggestions based on the recognized emotional state" is a system that automatically generates new interior suggestions according to the user's emotions based on feedback from the emotion engine.

[0887] This invention is a system that allows users to efficiently coordinate the interior of a room. Specific embodiments and their configurations are described in detail below. This system uses user input data and proposes interior plans using a generative AI model. It also incorporates an emotion engine to provide optimal proposals in real time based on the user's emotions.

[0888] System configuration

[0889] Hardware

[0890] Smart glasses / tablet: Used as an interface for users to provide input data, such as the room layout, interior taste, purpose of use, and budget.

[0891] Server: Receives, analyzes, and processes data sent by users. Generates interior coordination using generative AI models.

[0892] Emotion recognition device: Analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[0893] software

[0894] Generative AI model: Automatically generates optimal interior coordination based on user input data. This is a model trained to create interior plans that match the user's preferences and room characteristics.

[0895] Emotion engine: Analyzes user emotions in real time and provides feedback on user satisfaction.

[0896] Program Processing Details

[0897] Data collection and input

[0898] First, the user enters data such as the room layout, interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 50,000 yen) into an interface displayed on smart glasses or a tablet.

[0899] Data transmission and analysis

[0900] The data entered by the user is encoded into a standard format (e.g., JSON) and sent to the server. The server receives this data and analyzes it. Specifically, it analyzes information such as the room layout, interior taste, purpose of use, and budget, and generates the optimal interior plan based on that information.

[0901] Generate interior plans

[0902] The server uses the analyzed data to run a generative AI model to generate an interior coordination plan, taking into account the user's specified interior style (e.g., Scandinavian) and the characteristics of the room. It also searches for items that fit the user's budget and selects candidate items.

[0903] Emotion Recognition and Re-Suggestion

[0904] When a user browses an interior plan, an emotion recognition device analyzes the user's facial expressions and tone of voice in real time to determine their emotional state. If the user expresses dissatisfaction, the server recreates a new interior proposal using a generative AI model and presents it to the user again for optimization.

[0905] Specific examples

[0906] For example, if a user requests a "Scandinavian-style living room" and is dissatisfied with the initial proposal, the emotion engine detects the user's dissatisfaction and provides feedback to the server. The server then uses the generative AI model to create a new proposal, perhaps incorporating different furniture arrangements or items. This process is repeated until the user is satisfied.

[0907] Prompt Sentence Examples

[0908] "Room: 5 meters long, 4 meters wide, Use: Living room, Style: Scandinavian, Budget: 50,000 yen. Proposal: Create an interior design with a Scandinavian feel."

[0909] The above is an embodiment of the present invention. This system allows the user to achieve the best interior coordination while receiving real-time feedback based on their emotions.

[0910] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0911] Step 1:

[0912] User Input

[0913] Using smart glasses or a tablet, users input the room layout, interior design preferences, purpose of use, and budget, and this input data is captured through the interface.

[0914] Input: Room layout, interior style, purpose of use, budget

[0915] Output: Input data in JSON format

[0916] Step 2:

[0917] Sending data

[0918] The terminal encodes the data entered by the user in a standard format (JSON format) and sends it to the server. Data transmission is triggered when the user presses the send button.

[0919] Input: Input data in JSON format

[0920] Output: Data sent to the server

[0921] Step 3:

[0922] Data reception and analysis

[0923] The server receives the data sent from the device and analyzes it to understand the user's requirements, such as the room layout, interior style, purpose of use, and budget.

[0924] Input: Data from the terminal

[0925] Output: Parsed user request data

[0926] Step 4:

[0927] Generate interior plans

[0928] The server then uses a generative AI model to generate interior coordination based on the analyzed data. For example, it could use a model trained to generate Scandinavian-style interiors to generate a plan. It also optimizes furniture placement based on the room layout.

[0929] Input: Parsed user request data

[0930] Output: Generated interior plan

[0931] Step 5:

[0932] Finding items that fit your budget

[0933] The server searches an online database of items to find items that can be purchased within the budget. For example, it selects items such as a wooden center table, a Scandinavian-style sofa, and a light-toned carpet from the online database.

[0934] Input: Budget and interior plan

[0935] Output: Information on items that can be obtained within the budget

[0936] Step 6:

[0937] Interior plan integration and display

[0938] The server integrates the generated interior coordination and item details based on the selected item information. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[0939] Input: Generated interior plan, item information

[0940] Output: Integrated interior proposals

[0941] Step 7:

[0942] Display of interior design proposals

[0943] The terminal receives the interior proposal data sent from the server and displays it on the user interface. The user can then confirm the proposed interior coordination.

[0944] Input: Integrated interior proposals

[0945] Output: Interior design suggestions displayed on the user interface

[0946] Step 8:

[0947] emotion recognition

[0948] As users browse interior design suggestions, the emotion engine analyzes their facial expressions and tone of voice in real time to determine their emotional state (satisfaction, dissatisfaction, excitement, etc.).

[0949] Input: User's facial expressions, tone of voice

[0950] Output: Determined user's emotional state

[0951] Step 9:

[0952] Generate re-proposals

[0953] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[0954] Input: Determined user emotional state

[0955] Output: New interior proposals

[0956] Step 10:

[0957] Submitting and viewing new suggestions

[0958] After generating new interior suggestions, the server sends the data back to the device. The device analyzes the new suggestions and displays them again on the user interface. The user can review the new suggestions and repeat this process until they are satisfied.

[0959] Input: New interior design proposal

[0960] Output: New interior design suggestions displayed on the user interface

[0961] 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.

[0962] 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.

[0963] 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.

[0964] [Third embodiment]

[0965] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0966] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0967] 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).

[0968] 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.

[0969] 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.

[0970] 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).

[0971] 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.

[0972] 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.

[0973] 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.

[0974] 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.

[0975] 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.

[0976] 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."

[0977] This invention is a system that allows a user to efficiently coordinate the interior of a room, and the processing of the program will be specifically described below.

[0978] System Operation Overview

[0979] The system allows users to input their room layout, interior taste, purpose of use, and budget, and then uses that information to suggest the optimal interior plan and furniture. The system receives user input and uses a generative AI model to generate an interior coordination and select furniture.

[0980] Accepting user input

[0981] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[0982] Sending data

[0983] Terminal: Sends data entered by the user to the server in a standard format such as JSON.

[0984] Data reception and analysis

[0985] Server: The server receives and analyzes the data sent from the device. The analyzed data is then fed into a generative AI model. For example, it might understand that a Scandinavian-inspired interior is desired, or that the room layout is 5 meters long and 4 meters wide.

[0986] Generate interior plans

[0987] Server: The server uses a generative AI model to generate interior coordination based on input data. For a Scandinavian style, the generative AI model suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[0988] Furniture selection

[0989] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[0990] Integration of interior planning and furniture

[0991] Server: Integrates the generated interior plan and selected furniture information into a single proposal. For example, it provides detailed information including a specific furniture layout for a Scandinavian-style living room, the price of each piece of furniture, and a link to purchase it.

[0992] Sending data

[0993] Server: Sends the proposal data to the terminal.

[0994] View Suggestions

[0995] Device: The proposed interior coordination and furniture recommendations are displayed on the user interface. The user can check detailed information (price, purchase link, size) of the recommended furniture.

[0996] Receiving feedback and resubmitting

[0997] Terminal: The user enters feedback on the suggestion (e.g., I would like to change the color of the sofa). The feedback is sent back to the server.

[0998] Server: Receives feedback and generates new interior design proposals, for example, new proposals that include a brightly colored sofa.

[0999] The above steps are repeated until the proposed interior coordination is satisfactory to the user, thereby achieving the optimal interior.

[1000] In this way, users can easily and efficiently coordinate their interiors and create their ideal living environment or work space.

[1001] The processing flow will be explained below.

[1002] Step 1:

[1003] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1004] Step 2:

[1005] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[1006] Step 3:

[1007] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[1008] Step 4:

[1009] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[1010] Step 5:

[1011] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[1012] Step 6:

[1013] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1014] Step 7:

[1015] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[1016] Step 8:

[1017] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[1018] Step 9:

[1019] User: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[1020] Step 10:

[1021] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[1022] Step 11:

[1023] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[1024] Step 12:

[1025] Server: Sends new interior design proposals to the device.

[1026] Step 13:

[1027] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[1028] These are the specific processing steps of this system. Through this series of processes, users can efficiently realize their ideal interior.

[1029] Example 1

[1030] 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."

[1031] Currently, there are few efficient ways to coordinate the interior of a room. Users often have to think about the interior design and select and arrange the furniture themselves, which takes time and effort. In addition, there are few systems that can propose interior plans that match the user's image, making it difficult for users to achieve an interior environment that satisfies them. To solve this problem, a system is needed that can automatically propose optimal interior plans and furniture based on user input.

[1032] 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.

[1033] In this invention, the server includes means for transmitting data input by a user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits a budget, means for applying the searched furniture to the user's interior coordination, means for creating and transmitting prompts to the generative AI model, and means for providing an optimal interior plan based on the user's room layout and interior taste, thereby enabling the user to realize their ideal interior coordination without any hassle.

[1034] "User" refers to an individual or corporation that uses the system to coordinate the interior of a room.

[1035] "Server" refers to the computer system that receives data sent by users and generates interior coordination using analytical and generative AI models.

[1036] "Terminal" refers to the device (e.g., smartphone, computer, tablet) that a user uses to access the system and enter data, review suggestions, etc.

[1037] A "generative AI model" refers to an artificial intelligence model that generates optimal interior coordination based on data entered by the user.

[1038] A "prompt" refers to an instruction or question that is input to a generative AI model to generate an interior coordination.

[1039] "Interior coordination" refers to a plan that proposes optimal furniture placement and decoration based on the room layout, interior taste, purpose of use of the room, budget, etc.

[1040] "Furniture" refers to items (e.g., tables, sofas, carpets) that are placed in a room and are necessary for interior coordination.

[1041] A "furniture database" refers to an online database that registers information about various furniture items (e.g., price, size, material, and purchase link).

[1042] "User interface" refers to the screen or operating means through which a user inputs data into a system or checks suggestions.

[1043] "Feedback" refers to opinions and information such as requests for changes or improvements made by users in response to proposals.

[1044] "Re-proposals" refer to new interior coordination ideas generated based on feedback received from users.

[1045] The present invention is a system for enabling a user to efficiently coordinate the interior design of a room. Specific embodiments will be described below.

[1046] The system consists of three main components: a terminal where users input information, a server that receives and processes the input data, and a generative AI model.

[1047] Accepting user input

[1048] Device: Users access the system using a PC, smartphone, or tablet device. On the user interface, they input information such as the room layout, interior style, purpose of use, and budget. For example, a user might input a 5-meter by 4-meter floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1049] Sending data

[1050] Terminal: The data entered by the user is converted to JSON format and sent to the server. For example, the following JSON data is generated:

[1051] json

[1052] {

[1053] "Layout": {"Length": 5, "Width": 4},

[1054] "Taste": "Scandinavian",

[1055] "Purpose of Use": "Living Room",

[1056] "Budget": 50000

[1057] }

[1058] Data reception and analysis

[1059] Server: Analyzes the received data and converts it into a format suitable for the generative AI model. For example, it generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[1060] Generate interior plans

[1061] Server: Input a prompt into the generative AI model and generate interior coordination ideas. For example, use the following prompt:

[1062] "Please coordinate a living room with a Scandinavian feel. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior design that emphasizes simple, light-colored furniture and natural materials."

[1063] Furniture selection

[1064] Server: Based on the generated interior coordination proposal, the server searches the internet for furniture that can be acquired within the budget. For example, it uses an online shop's API to suggest a wooden center table, a Scandinavian-style sofa, and a light-toned carpet.

[1065] Integration of interior planning and furniture

[1066] Server: Integrates the generated interior coordination ideas with the selected furniture information and generates data to present to the user, such as detailed information including a room layout, furniture placement, prices, sizes, and purchase links.

[1067] View Suggestions

[1068] Terminal: The proposed data received from the server is displayed on the user interface. The user can check the proposed interior coordination and detailed furniture information. They can also easily purchase the furniture by clicking the purchase link.

[1069] Receiving feedback and resubmitting

[1070] Terminal: The user inputs feedback on the proposal. For example, they input a request such as "I would like to change the color of the sofa" and request a new proposal.

[1071] Server: Receives feedback and sends new prompts to the generative AI model to generate new interior design suggestions. For example, it sends a new prompt such as, "Generate new coordination ideas for a Scandinavian-style living room, measuring 5 meters long and 4 meters wide, with a bright-colored sofa, within a budget of 50,000 yen."

[1072] This allows users to effortlessly create their ideal interior coordination, and the system can continue to provide a variety of suggestions based on user feedback.

[1073] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1074] Step 1: Accept user input

[1075] Terminal: The user enters information such as the room layout, interior style, purpose of use, budget, etc. on the interface. The entered information is converted into a JSON format that the system can understand.

[1076] Input: User's room layout (e.g., 5 meters long, 4 meters wide), interior style (e.g., Scandinavian), purpose of room (e.g., living room), budget (e.g., 50,000 yen).

[1077] Output: JSON formatted data.

[1078] Specific operation: The user checks the information entered and clicks the "Submit" button. This action causes the data to be processed.

[1079] Step 2: Sending data

[1080] Terminal: The terminal sends the entered JSON format data to the server.

[1081] Input: User input data in JSON format.

[1082] Output: The HTTP request sent to the server.

[1083] Specific operation: The device makes an HTTP POST request to the server and sends JSON data. If the sending process is successful, a confirmation message will be displayed.

[1084] Step 3: Receiving and analyzing data

[1085] Server: Receives and analyzes JSON data sent from the terminal. Generates a prompt based on the input data.

[1086] Input: JSON data sent from the terminal.

[1087] Output: The generated prompt statement.

[1088] Specific operation: The server analyzes the JSON data and generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[1089] Step 4: Generate an interior plan

[1090] Server: The generated prompt sentence is input into the generative AI model to generate interior coordination suggestions.

[1091] Input: The generated prompt statement.

[1092] Output: Interior coordination suggestions from the generative AI model.

[1093] Specific operation: The server sends the following prompt to the generative AI model: "Please coordinate a living room with a Scandinavian style. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior that emphasizes simple, light-colored furniture and natural materials." The server then receives the coordination suggestions provided by the model.

[1094] Step 5: Furniture selection

[1095] Server: Based on the generated interior design ideas, the server searches the internet for furniture that can be obtained within the budget.

[1096] Input: Generated interior coordination proposal.

[1097] Output: A list of furniture that can be acquired within your budget.

[1098] Specific operation: The server executes a search query using the online shop's API, and obtains information such as "a wooden center table, a Nordic-style sofa, and a light-toned carpet for under 50,000 yen."

[1099] Step 6: Integrating the interior plan and furniture

[1100] Server: Integrates the generated interior plan and furniture information to generate proposal data.

[1101] Input: Interior coordination ideas and furniture list.

[1102] Output: Consolidated proposal data.

[1103] What it does: The server creates a detailed layout diagram including the layout, price, size, and purchase link for each piece of furniture, and provides it to the user as an integrated interior plan.

[1104] Step 7: Viewing Proposals

[1105] Terminal: Displays the proposal data received from the server on the user interface.

[1106] Input: Proposal data received from the server.

[1107] Output: Interior coordination ideas and furniture information displayed on the user interface.

[1108] Specific operation: The device displays a layout diagram, furniture layout, prices, sizes, purchase links, etc. for the user to review.

[1109] Step 8: Receive feedback and resubmit

[1110] Terminal: The user enters feedback on the suggestion.

[1111] Input: User feedback.

[1112] Output: Feedback data sent to the server.

[1113] Specific behavior: The user enters feedback and sends it to the server as a re-proposal request. This action generates a new prompt and a new proposal.

[1114] By clearly separating each processing step and its specific operation for the user, terminal, and server, this system allows users to realize their ideal interior coordination.

[1115] (Application example 1)

[1116] 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."

[1117] Conventional interior coordination systems have limited means for users to visually check furniture placement and design, and lack a real-time interactive experience. Furthermore, because re-suggestions based on user feedback are not made quickly, achieving the optimal coordination often takes time. Furthermore, these systems are difficult to understand for users who do not have a concrete image of the interior plan, making it difficult to achieve a satisfactory feeling when using them.

[1118] 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.

[1119] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits the user's budget, means for applying the searched furniture to the user's interior coordination, means for displaying the interior coordination on a user interface, means for receiving feedback from the user and generating a re-proposal, and means for viewing the interior via a VR device and changing the coordination content in real time. This allows the user to visually and interactively coordinate their interior in real time, enabling them to quickly and efficiently realize an optimal interior plan.

[1120] "Means for accepting user input" refers to technology that provides an interface for collecting data entered by the user.

[1121] "Means for transmitting data entered by the user to the server" refers to a mechanism for transferring data provided by the user to the server via a network.

[1122] "Means for generating interior coordination using a generative AI model" refers to technology that uses a generative AI model (e.g., a machine learning model) to create an interior plan that meets the user's requirements.

[1123] "A means of searching for furniture that fits a user's budget" is a function that searches an online database for furniture that can be purchased within the user's set budget.

[1124] The "means for applying the searched furniture to the user's interior coordination" is a technique for incorporating the searched furniture as part of an interior plan.

[1125] The "means for displaying interior coordination on a user interface" is a display system for visually presenting the generated interior plan to the user.

[1126] "Means for receiving feedback from users and generating new proposals" refers to a mechanism for collecting user opinions and requests and creating new proposals based on them.

[1127] "A means of viewing interiors via a VR device and changing the coordination details in real time" refers to a technology that uses a VR device to check interior plans in a virtual reality space and make changes on the spot as needed.

[1128] The present invention is a system that allows a user to efficiently coordinate the interior of a room, and specific embodiments thereof will be described below.

[1129] System configuration

[1130] The system consists of a user terminal, a server, and a VR device. The user terminal provides the user interface and is responsible for inputting and displaying data. The server processes the data and executes the generative AI model, and the VR device is used by the user to visually check the generated interior plan.

[1131] Hardware and software used

[1132] Hardware:

[1133] User devices: PC, tablet, smartphone

[1134] Server: High-performance computer

[1135] VR devices: smart glasses, head-mounted displays (e.g., Oculus Rift, HTC Vive)

[1136] software:

[1137] User Interface Applications

[1138] Server program (e.g. Python, Flask)

[1139] Generative AI models (e.g., GPT-4)

[1140] Database Interface

[1141] Operation overview

[1142] 1. Accept user input:

[1143] The user uses a user terminal to input information such as the room layout, interior taste, purpose of use of the room, budget, etc. This input is done through a user interface application.

[1144] 2. Sending and Receiving Data:

[1145] The terminal sends the input data in JSON format to the server, which receives it and analyzes the data.

[1146] 3. Generate interior plan:

[1147] The server inputs the analyzed data into a generative AI model to generate an interior coordination based on the user's requests. For example, if a Scandinavian style is desired, furniture made of light colors and natural materials will be selected.

[1148] 4. Furniture selection:

[1149] The server searches a furniture database via the Internet to find furniture that is available within the user's budget, and applies the found furniture to the user's interior plan.

[1150] 5. View and real-time changes on VR devices:

[1151] Users can view the generated interior plan in real time using a VR device. Based on user feedback (e.g., a desire to change the color of the sofa), the server generates new proposals using the generative AI model.

[1152] Specific examples

[1153] User input: "The living room layout is 15 feet by 18 feet. The style is Scandinavian and the budget is $60,000."

[1154] Generative AI prompt: "Given a Scandinavian-style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection."

[1155] This system allows users to visually and interactively coordinate interiors in real time, enabling them to quickly and efficiently create optimal interior plans.

[1156] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1157] Step 1:

[1158] The user inputs interior information from the device. Specifically, the user uses the user interface on the device to input the room layout (e.g., 4 meters long, 5 meters wide), interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 60,000 yen). The input data is organized in JSON format.

[1159] Step 2:

[1160] The terminal sends the input data to the server. The input data (JSON format) is sent to the server via the network, and the server receives this data.

[1161] Step 3:

[1162] The server parses the received data, which is in JSON format, and extracts information such as the room layout, interior design, purpose of use, and budget. This analysis creates prompts for the generative AI model.

[1163] Step 4:

[1164] The server generates an interior coordination using a generative AI model. Specifically, based on the analyzed data, the server inputs the following prompts into the generative AI model (e.g., GPT-4):

[1165] "Given a Scandinavian style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection." Based on this prompt, the model generates an appropriate interior plan.

[1166] Step 5:

[1167] The server searches a furniture database via the Internet based on the generated interior plan. It searches for and collects furniture that is available within the user's budget. Specifically, it uses An API to search the furniture database and obtains information on furniture that matches the user's criteria (e.g., a wooden center table, a Nordic-style sofa, a light-toned carpet).

[1168] Step 6:

[1169] The server applies the furniture it finds to the interior plan. It then integrates the interior plan provided by the generative AI model with the furniture information obtained from the furniture database to create a specific layout plan. This completes the interior plan.

[1170] Step 7:

[1171] The server sends the completed interior plan to the terminal. The data including the generated interior plan and furniture information is sent to the terminal and converted into a format that can be displayed on the user interface.

[1172] Step 8:

[1173] The user checks the interior plan through the terminal and visually views the plan using the VR device. The terminal displays the interior plan and transmits the information to the VR device.

[1174] Step 9:

[1175] Accepts feedback from users. The user uses the VR device and terminal to input feedback about the interior plan (e.g., wanting to change the color of the sofa). This feedback is sent from the terminal to the server.

[1176] Step 10:

[1177] The server generates new interior proposals based on the received feedback. It then uses the generative AI model again to generate a new interior plan that reflects the feedback, and repeats the process from step 5 onwards.

[1178] By following these steps, users can visually and interactively coordinate interiors in real time.

[1179] 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.

[1180] This invention is a system that allows users to efficiently coordinate the interior of a room, and the processing of the program will be explained in detail below, especially the part that combines the emotion engine.

[1181] System Operation Overview

[1182] The system will suggest optimal interior plans and furniture based on the user's input of the room layout, interior taste, purpose of use, and budget. It also incorporates an emotion engine that recognizes the user's emotions, enabling it to offer interior suggestions that will further satisfy the user.

[1183] Accepting user input

[1184] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1185] Sending data

[1186] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[1187] Data reception and analysis

[1188] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[1189] Generate interior plans

[1190] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[1191] Furniture selection and proposal integration

[1192] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[1193] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1194] Analysis by emotion engine

[1195] Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfaction, dissatisfaction, excitement, etc.).

[1196] Emotion-based re-suggestion generation

[1197] Server: The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[1198] Data retransmission and display

[1199] Server: After generating new interior proposals, it sends the data to the device again.

[1200] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[1201] Specific examples

[1202] For example, if a user is not satisfied with the "Scandinavian-style living room" suggestion, the emotion engine will detect this and send dissatisfaction feedback to the server. The server will then regenerate a new suggestion incorporating different furniture arrangements and items and present it to the user again. Through this process, the system can provide an interior design that the user is completely satisfied with.

[1203] The above is a concrete example of how to implement the present invention. This system allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving a high level of satisfaction.

[1204] The processing flow will be explained below.

[1205] Step 1:

[1206] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1207] Step 2:

[1208] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[1209] Step 3:

[1210] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[1211] Step 4:

[1212] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[1213] Step 5:

[1214] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[1215] Step 6:

[1216] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1217] Step 7:

[1218] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[1219] Step 8:

[1220] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[1221] Step 9:

[1222] On the device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfied, dissatisfied, excited, etc.). For example, if the user is dissatisfied with the suggestions, the emotion engine will detect this.

[1223] Step 10:

[1224] Terminal: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[1225] Step 11:

[1226] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[1227] Step 12:

[1228] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[1229] Step 13:

[1230] Server: The server also takes into account feedback from the emotion engine to analyze the user's emotional state. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[1231] Step 14:

[1232] Server: After generating new interior proposals, it sends the data to the device again.

[1233] Step 15:

[1234] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[1235] This series of processes allows users to efficiently coordinate their interiors in a way that enhances their emotional satisfaction.

[1236] Example 2

[1237] 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."

[1238] In modern living spaces, many people often struggle with designing their own rooms. It can be particularly difficult to select the optimal interior design, taking into account numerous factors, such as the room's layout, interior taste, intended use, and budget. Furthermore, there are cases where the furniture purchased does not match the overall interior design or exceeds budget. Furthermore, there is no system that can provide interior design suggestions that take into account the user's emotions and reactions, which can lead to a decline in user satisfaction.

[1239] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for transmitting data input by a user to the server, a means for generating an interior coordination using a generative AI model, and a means for searching for furniture that fits the budget. This allows the user to efficiently coordinate the interior of a room.

[1240] The server also includes a means for applying the searched furniture to the user's interior coordination, a means for displaying the interior coordination on a user interface, a means for analyzing the user's emotional state, and a means for generating a re-proposal based on the user's emotional feedback. This enables interior proposals that reflect real-time feedback based on the user's emotions, ultimately achieving high satisfaction.

[1241] "User" refers to an individual or corporation that uses the system to input the data necessary to receive interior coordination proposals and to review the proposed interiors.

[1242] "Means for accepting input" refers to an interface or device that allows the user to input information such as the room layout, interior style, purpose of use of the room, budget, etc.

[1243] "Means for transmitting data to a server" refers to the function of encoding information entered by the user and sending it to a server via a communication means such as the Internet.

[1244] "Generative AI model" refers to an artificial intelligence model trained to automatically generate interior coordination based on specific interior tastes and requirements.

[1245] "Means for generating interior coordination" refers to the function of using a generative AI model to create an interior plan based on user input information.

[1246] "Searching tools" refers to the functionality that uses the internet and databases to find furniture and interior items that are within the user's budget.

[1247] "Means of application" refers to the function of reflecting the searched furniture and interior items in the generated interior coordination.

[1248] "User interface" refers to the screens and operating means through which users can view interior design proposals and provide feedback.

[1249] "Means for displaying" refers to the function of visually presenting the interior coordination generated by the server to the user through the user interface.

[1250] "Means for analyzing emotional state" refers to a function that uses an emotion engine to analyze emotions from the user's facial expressions, voice tone, etc., and determine satisfaction, dissatisfaction, etc.

[1251] "Means for generating re-proposals" refers to the function of re-operating the generative AI model to create new interior proposals based on the user's emotional feedback.

[1252] This invention is a system that allows users to efficiently coordinate the interior of a room. The program processing is specifically explained. This system uses a generative AI model to propose appropriate interior coordination based on user input, and further improves user satisfaction by making further proposals that reflect the user's emotional feedback.

[1253] Hardware and Software

[1254] Terminal: A device through which a user enters information, including computers, smartphones, tablets, etc.

[1255] Server: Analyzes the received data, generates interior coordination using a generative AI model, and makes new suggestions.

[1256] Emotion engine: Software used to analyze a user's facial expressions and tone of voice to determine their emotional state.

[1257] Program processing

[1258] 1. Accepting user input

[1259] Users input their room layout, interior style, purpose of use, and budget through the terminal. The interface is designed to be easy to use, and it is possible to input specific information such as a "floor plan of 5 meters long and 4 meters wide," a "Scandinavian-style living room," and a "budget of 50,000 yen."

[1260] 2. Data transmission

[1261] After checking the input, the user presses the send button, and the device encodes the input data in JSON format and sends it to the server via the Internet.

[1262] 3. Data Receipt and Analysis

[1263] The server receives the data sent from the device and analyzes the information obtained. Based on this analysis, it understands the user's requirements (floor layout, interior taste, purpose of use, budget).

[1264] 4. Generate interior plans

[1265] The server then uses a generative AI model based on the analyzed data to generate interior coordination. This AI model is optimized for a specific interior style (e.g., Scandinavian style) and suggests simple, light-colored furniture and natural materials. It also calculates the optimal furniture placement based on the room layout.

[1266] 5. Furniture selection and proposal integration

[1267] The server searches a furniture database via the Internet and selects items that can be purchased within the customer's budget. For example, it selects a wooden center table or a Scandinavian-style sofa from an online furniture database. This ensures that the data is consistent. Finally, it compiles a furniture layout diagram and detailed information about each piece of furniture (price, purchase link, size) into a single proposal data set.

[1268] 6. Analysis by Emotion Engine

[1269] As the user browses the suggested interiors, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state (satisfied, dissatisfied, excited, etc.).

[1270] 7. Emotion-based re-suggestion generation

[1271] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, it generates new interior design suggestions by re-running the generative AI model.

[1272] 8. Data retransmission and display

[1273] After generating new interior suggestions, the system re-encodes them and sends the data to the device, which receives the new suggestions and displays them again on the user interface. This process can be repeated until the user is satisfied.

[1274] Specific examples

[1275] For example, if a user enters, "I want to create a Scandinavian-style living room in a room that is 5 meters long and 4 meters wide. My budget is 50,000 yen," the system will perform the following actions:

[1276] 1. User: Enter the above information using the terminal.

[1277] 2. Terminal: The input is encoded in JSON format and sent to the server.

[1278] 3. Server: Receives and analyzes the data and generates an interior plan using a generative AI model.

[1279] 4. Server: Searches relevant online furniture databases and selects furniture that can be purchased within your budget.

[1280] 5. Server: Integrates the interior plan and selected furniture to generate detailed data.

[1281] 6. Terminal: The generated interior design proposals are displayed to the user, and the emotion engine analyzes the user's reaction.

[1282] 7. Server: Regenerates if necessary and sends new proposals to the device.

[1283] Example prompts for generative AI models

[1284] Below is an example of an input prompt sentence for the generative AI model.

[1285] "Please suggest a Scandinavian-inspired living room for a 5m x 4m room. My budget is 50,000 yen."

[1286] The above is the specific operation and implementation form of this system, which allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving high levels of satisfaction.

[1287] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1288] Step 1:

[1289] Accepting user input

[1290] 1. User: Uses the device to enter information such as the room layout, interior style, purpose of use of the room, budget, etc.

[1291] 2. Input: room layout (5 meters long x 4 meters wide), interior style (Scandinavian), purpose of room (living room), budget (50,000 yen).

[1292] 3. Output: The input data is stored in the device's memory.

[1293] 4. Specific actions: The user enters the necessary information into the input form on the device and presses the "Submit" button.

[1294] Step 2:

[1295] Sending data

[1296] 1. Terminal: The input data is encoded in JSON format and sent to the server for further processing.

[1297] 2. Input: Data entered by the user.

[1298] 3. Output: JSON formatted data is sent to the server.

[1299] 4. Specific operation: The terminal compiles the input content into a single JSON object and sends it to the server via the Internet.

[1300] Step 3:

[1301] Data reception and analysis

[1302] 1. Server: Analyzes the JSON format data received from the device and understands the user's requirements (floor plan, interior style, purpose of use, budget).

[1303] 2. Input: JSON format data sent from the terminal.

[1304] 3. Output: Analyzed data (floor plan, interior design, purpose of use, budget).

[1305] 4. Specific operation: The server decodes the received JSON data, stores it in an internal structure, and analyzes it.

[1306] Step 4:

[1307] Generate interior plans

[1308] 1. Server: Based on the analyzed data, it generates interior coordination using a generative AI model.

[1309] 2. Input: Parsed data.

[1310] 3. Output: Generated interior plan.

[1311] 4. Specific operation: Pass the prompt to the generative AI model and receive an interior plan based on the user's requirements.

[1312] Step 5:

[1313] Furniture selection and proposal integration

[1314] 1. Server: Searches a furniture database via the Internet and selects furniture that can be purchased within the budget.

[1315] 2. Input: Generated interior plan and budget.

[1316] 3. Output: A list of selected furniture.

[1317] 4. Specific Action: Query an online furniture database and filter the results to find furniture within your budget.

[1318] 5. Server: Integrates the furniture list and the generated interior plan, and generates proposal data to present to the end user.

[1319] 6. Input: List of selected furniture.

[1320] 7. Output: Consolidated proposal data.

[1321] 8. Specific actions: Compile furniture layout diagrams, pricing information, product links, etc. into a single proposal document.

[1322] Step 6:

[1323] Analysis by emotion engine

[1324] 1. Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[1325] 2. Input: User's facial expression data, tone of voice.

[1326] 3. Output: The user's emotional state (satisfied, dissatisfied, excited, etc.).

[1327] 4. Specific operation: The emotion engine collects and analyzes data using the camera and microphone installed on the device.

[1328] Step 7:

[1329] Emotion-based re-suggestion generation

[1330] 1. Server: Analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, the generative AI model is reactivated to generate new interior design suggestions.

[1331] 2. Input: User's emotional feedback.

[1332] 3. Output: Re-proposed interior plan.

[1333] 4. Specific actions: Analyze the feedback data and pass new prompts to the generative AI model to regenerate the interior plan.

[1334] Step 8:

[1335] Resend and display data

[1336] 1. Server: Sends new interior proposals to the device.

[1337] 2. Input: Regenerated interior plan.

[1338] 3. Output: The new proposal data sent to the device.

[1339] 4. Specific operation: The proposed data is re-encoded and sent to the terminal via the Internet.

[1340] 5. Terminal: Receives new proposal data and displays it on the user interface.

[1341] 6. Input: Re-proposal data sent from the server.

[1342] 7. Output: Interior proposals displayed on the user interface.

[1343] 8. Specific operation: The terminal decodes the received data and updates the user interface displayed on the screen.

[1344] (Application example 2)

[1345] 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."

[1346] Conventional interior coordination systems simply generate and provide interior plans based on data entered by the user. As a result, they were unable to make dynamic suggestions based on the user's emotions and satisfaction, and multiple trials and manual adjustments were required to obtain optimal interior suggestions. Furthermore, they lacked real-time display and feedback of the interior plans, limiting the user experience. In response, there is a need for a system that can recognize the user's emotional state and automatically generate optimal suggestions while receiving feedback in real time.

[1347] 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.

[1348] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for items that fit the user's budget, means for applying the searched items to the user's interior coordination, means for displaying the interior coordination on a user interface, means for recognizing the user's emotional state, and means for generating re-proposals based on the recognized emotional state. This makes it possible to analyze the user's emotional feedback in real time and quickly automatically generate optimized interior proposals. The user can repeatedly receive proposals until they are satisfied, thereby achieving higher satisfaction.

[1349] The "means for accepting user input" is a device that provides an interface for the user to input data such as the room layout, interior taste, purpose of use of the room, budget, etc.

[1350] A "means for transmitting data entered by a user to a server" is a device that has the function of encoding information entered by a user in a standard format and transmitting it to a server located at a remote location.

[1351] A "means for generating interior coordination using a generative AI model" is a system that uses a generative AI model to automatically generate optimal interior coordination based on user input.

[1352] The "means for searching for items that fit a budget" is a system that has the function of searching an item database via the Internet and identifying items that can be acquired within the user's budget.

[1353] The "means for applying the searched item to the user's interior coordination" refers to a device or system that has the function of arranging the searched item in the generated interior plan.

[1354] The "means for displaying interior coordination on a user interface" refers to a display device or software for visually presenting the generated interior plan to the user.

[1355] "Means for recognizing the user's emotional state" refers to devices or software that analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[1356] The "means for generating new suggestions based on the recognized emotional state" is a system that automatically generates new interior suggestions according to the user's emotions based on feedback from the emotion engine.

[1357] This invention is a system that allows users to efficiently coordinate the interior of a room. Specific embodiments and their configurations are described in detail below. This system uses user input data and proposes interior plans using a generative AI model. It also incorporates an emotion engine to provide optimal proposals in real time based on the user's emotions.

[1358] System configuration

[1359] Hardware

[1360] Smart glasses / tablet: Used as an interface for users to provide input data, such as the room layout, interior taste, purpose of use, and budget.

[1361] Server: Receives, analyzes, and processes data sent by users. Generates interior coordination using generative AI models.

[1362] Emotion recognition device: Analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[1363] software

[1364] Generative AI model: Automatically generates optimal interior coordination based on user input data. This is a model trained to create interior plans that match the user's preferences and room characteristics.

[1365] Emotion engine: Analyzes user emotions in real time and provides feedback on user satisfaction.

[1366] Program Processing Details

[1367] Data collection and input

[1368] First, the user enters data such as the room layout, interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 50,000 yen) into an interface displayed on smart glasses or a tablet.

[1369] Data transmission and analysis

[1370] The data entered by the user is encoded into a standard format (e.g., JSON) and sent to the server. The server receives this data and analyzes it. Specifically, it analyzes information such as the room layout, interior taste, purpose of use, and budget, and generates the optimal interior plan based on that information.

[1371] Generate interior plans

[1372] The server uses the analyzed data to run a generative AI model to generate an interior coordination plan, taking into account the user's specified interior style (e.g., Scandinavian) and the characteristics of the room. It also searches for items that fit the user's budget and selects candidate items.

[1373] Emotion Recognition and Re-Suggestion

[1374] When a user browses an interior plan, an emotion recognition device analyzes the user's facial expressions and tone of voice in real time to determine their emotional state. If the user expresses dissatisfaction, the server recreates a new interior proposal using a generative AI model and presents it to the user again for optimization.

[1375] Specific examples

[1376] For example, if a user requests a "Scandinavian-style living room" and is dissatisfied with the initial proposal, the emotion engine detects the user's dissatisfaction and provides feedback to the server. The server then uses the generative AI model to create a new proposal, perhaps incorporating different furniture arrangements or items. This process is repeated until the user is satisfied.

[1377] Prompt Sentence Examples

[1378] "Room: 5 meters long, 4 meters wide, Use: Living room, Style: Scandinavian, Budget: 50,000 yen. Proposal: Create an interior design with a Scandinavian feel."

[1379] The above is an embodiment of the present invention. This system allows the user to achieve the best interior coordination while receiving real-time feedback based on their emotions.

[1380] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1381] Step 1:

[1382] User Input

[1383] Using smart glasses or a tablet, users input the room layout, interior design preferences, purpose of use, and budget, and this input data is captured through the interface.

[1384] Input: Room layout, interior style, purpose of use, budget

[1385] Output: Input data in JSON format

[1386] Step 2:

[1387] Sending data

[1388] The terminal encodes the data entered by the user in a standard format (JSON format) and sends it to the server. Data transmission is triggered when the user presses the send button.

[1389] Input: Input data in JSON format

[1390] Output: Data sent to the server

[1391] Step 3:

[1392] Data reception and analysis

[1393] The server receives the data sent from the device and analyzes it to understand the user's requirements, such as the room layout, interior style, purpose of use, and budget.

[1394] Input: Data from the terminal

[1395] Output: Parsed user request data

[1396] Step 4:

[1397] Generate interior plans

[1398] The server then uses a generative AI model to generate interior coordination based on the analyzed data. For example, it could use a model trained to generate Scandinavian-style interiors to generate a plan. It also optimizes furniture placement based on the room layout.

[1399] Input: Parsed user request data

[1400] Output: Generated interior plan

[1401] Step 5:

[1402] Finding items that fit your budget

[1403] The server searches an online database of items to find items that can be purchased within the budget. For example, it selects items such as a wooden center table, a Scandinavian-style sofa, and a light-toned carpet from the online database.

[1404] Input: Budget and interior plan

[1405] Output: Information on items that can be obtained within the budget

[1406] Step 6:

[1407] Interior plan integration and display

[1408] The server integrates the generated interior coordination and item details based on the selected item information. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1409] Input: Generated interior plan, item information

[1410] Output: Integrated interior proposals

[1411] Step 7:

[1412] Display of interior design proposals

[1413] The terminal receives the interior proposal data sent from the server and displays it on the user interface. The user can then confirm the proposed interior coordination.

[1414] Input: Integrated interior proposals

[1415] Output: Interior design suggestions displayed on the user interface

[1416] Step 8:

[1417] emotion recognition

[1418] As users browse interior design suggestions, the emotion engine analyzes their facial expressions and tone of voice in real time to determine their emotional state (satisfaction, dissatisfaction, excitement, etc.).

[1419] Input: User's facial expressions, tone of voice

[1420] Output: Determined user's emotional state

[1421] Step 9:

[1422] Generate re-proposals

[1423] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[1424] Input: Determined user emotional state

[1425] Output: New interior proposals

[1426] Step 10:

[1427] Submitting and viewing new suggestions

[1428] After generating new interior suggestions, the server sends the data back to the device. The device analyzes the new suggestions and displays them again on the user interface. The user can review the new suggestions and repeat this process until they are satisfied.

[1429] Input: New interior design proposal

[1430] Output: New interior design suggestions displayed on the user interface

[1431] 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.

[1432] 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.

[1433] 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.

[1434] [Fourth embodiment]

[1435] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1436] 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.

[1437] 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).

[1438] 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.

[1439] 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.

[1440] 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).

[1441] 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.

[1442] 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.

[1443] 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.

[1444] 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.

[1445] 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.

[1446] 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.

[1447] 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."

[1448] This invention is a system that allows a user to efficiently coordinate the interior of a room, and the processing of the program will be specifically described below.

[1449] System Operation Overview

[1450] The system allows users to input their room layout, interior taste, purpose of use, and budget, and then uses that information to suggest the optimal interior plan and furniture. The system receives user input and uses a generative AI model to generate an interior coordination and select furniture.

[1451] Accepting user input

[1452] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1453] Sending data

[1454] Terminal: Sends data entered by the user to the server in a standard format such as JSON.

[1455] Data reception and analysis

[1456] Server: The server receives and analyzes the data sent from the device. The analyzed data is then fed into a generative AI model. For example, it might understand that a Scandinavian-inspired interior is desired, or that the room layout is 5 meters long and 4 meters wide.

[1457] Generate interior plans

[1458] Server: The server uses a generative AI model to generate interior coordination based on input data. For a Scandinavian style, the generative AI model suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[1459] Furniture selection

[1460] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[1461] Integration of interior planning and furniture

[1462] Server: Integrates the generated interior plan and selected furniture information into a single proposal. For example, it provides detailed information including a specific furniture layout for a Scandinavian-style living room, the price of each piece of furniture, and a link to purchase it.

[1463] Sending data

[1464] Server: Sends the proposal data to the terminal.

[1465] View Suggestions

[1466] Device: The proposed interior coordination and furniture recommendations are displayed on the user interface. The user can check detailed information (price, purchase link, size) of the recommended furniture.

[1467] Receiving feedback and resubmitting

[1468] Terminal: The user enters feedback on the suggestion (e.g., I would like to change the color of the sofa). The feedback is sent back to the server.

[1469] Server: Receives feedback and generates new interior design proposals, for example, new proposals that include a brightly colored sofa.

[1470] The above steps are repeated until the proposed interior coordination is satisfactory to the user, thereby achieving the optimal interior.

[1471] In this way, users can easily and efficiently coordinate their interiors and create their ideal living environment or work space.

[1472] The processing flow will be explained below.

[1473] Step 1:

[1474] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1475] Step 2:

[1476] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[1477] Step 3:

[1478] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[1479] Step 4:

[1480] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[1481] Step 5:

[1482] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[1483] Step 6:

[1484] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1485] Step 7:

[1486] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[1487] Step 8:

[1488] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[1489] Step 9:

[1490] User: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[1491] Step 10:

[1492] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[1493] Step 11:

[1494] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[1495] Step 12:

[1496] Server: Sends new interior design proposals to the device.

[1497] Step 13:

[1498] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[1499] These are the specific processing steps of this system. Through this series of processes, users can efficiently realize their ideal interior.

[1500] Example 1

[1501] 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."

[1502] Currently, there are few efficient ways to coordinate the interior of a room. Users often have to think about the interior design and select and arrange the furniture themselves, which takes time and effort. In addition, there are few systems that can propose interior plans that match the user's image, making it difficult for users to achieve an interior environment that satisfies them. To solve this problem, a system is needed that can automatically propose optimal interior plans and furniture based on user input.

[1503] 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.

[1504] In this invention, the server includes means for transmitting data input by a user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits a budget, means for applying the searched furniture to the user's interior coordination, means for creating and transmitting prompts to the generative AI model, and means for providing an optimal interior plan based on the user's room layout and interior taste, thereby enabling the user to realize their ideal interior coordination without any hassle.

[1505] "User" refers to an individual or corporation that uses the system to coordinate the interior of a room.

[1506] "Server" refers to the computer system that receives data sent by users and generates interior coordination using analytical and generative AI models.

[1507] "Terminal" refers to the device (e.g., smartphone, computer, tablet) that a user uses to access the system and enter data, review suggestions, etc.

[1508] A "generative AI model" refers to an artificial intelligence model that generates optimal interior coordination based on data entered by the user.

[1509] A "prompt" refers to an instruction or question that is input to a generative AI model to generate an interior coordination.

[1510] "Interior coordination" refers to a plan that proposes optimal furniture placement and decoration based on the room layout, interior taste, purpose of use of the room, budget, etc.

[1511] "Furniture" refers to items (e.g., tables, sofas, carpets) that are placed in a room and are necessary for interior coordination.

[1512] A "furniture database" refers to an online database that registers information about various furniture items (e.g., price, size, material, and purchase link).

[1513] "User interface" refers to the screen or operating means through which a user inputs data into a system or checks suggestions.

[1514] "Feedback" refers to opinions and information such as requests for changes or improvements made by users in response to proposals.

[1515] "Re-proposals" refer to new interior coordination ideas generated based on feedback received from users.

[1516] The present invention is a system for enabling a user to efficiently coordinate the interior design of a room. Specific embodiments will be described below.

[1517] The system consists of three main components: a terminal where users input information, a server that receives and processes the input data, and a generative AI model.

[1518] Accepting user input

[1519] Device: Users access the system using a PC, smartphone, or tablet device. On the user interface, they input information such as the room layout, interior style, purpose of use, and budget. For example, a user might input a 5-meter by 4-meter floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1520] Sending data

[1521] Terminal: The data entered by the user is converted to JSON format and sent to the server. For example, the following JSON data is generated:

[1522] json

[1523] {

[1524] "Layout": {"Length": 5, "Width": 4},

[1525] "Taste": "Scandinavian",

[1526] "Purpose of Use": "Living Room",

[1527] "Budget": 50000

[1528] }

[1529] Data reception and analysis

[1530] Server: Analyzes the received data and converts it into a format suitable for the generative AI model. For example, it generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[1531] Generate interior plans

[1532] Server: Input a prompt into the generative AI model and generate interior coordination ideas. For example, use the following prompt:

[1533] "Please coordinate a living room with a Scandinavian feel. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior design that emphasizes simple, light-colored furniture and natural materials."

[1534] Furniture selection

[1535] Server: Based on the generated interior coordination proposal, the server searches the internet for furniture that can be acquired within the budget. For example, it uses an online shop's API to suggest a wooden center table, a Scandinavian-style sofa, and a light-toned carpet.

[1536] Integration of interior planning and furniture

[1537] Server: Integrates the generated interior coordination ideas with the selected furniture information and generates data to present to the user, such as detailed information including a room layout, furniture placement, prices, sizes, and purchase links.

[1538] View Suggestions

[1539] Terminal: The proposed data received from the server is displayed on the user interface. The user can check the proposed interior coordination and detailed furniture information. They can also easily purchase the furniture by clicking the purchase link.

[1540] Receiving feedback and resubmitting

[1541] Terminal: The user inputs feedback on the proposal. For example, they input a request such as "I would like to change the color of the sofa" and request a new proposal.

[1542] Server: Receives feedback and sends new prompts to the generative AI model to generate new interior design suggestions. For example, it sends a new prompt such as, "Generate new coordination ideas for a Scandinavian-style living room, measuring 5 meters long and 4 meters wide, with a bright-colored sofa, within a budget of 50,000 yen."

[1543] This allows users to effortlessly create their ideal interior coordination, and the system can continue to provide a variety of suggestions based on user feedback.

[1544] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1545] Step 1: Accept user input

[1546] Terminal: The user enters information such as the room layout, interior style, purpose of use, budget, etc. on the interface. The entered information is converted into a JSON format that the system can understand.

[1547] Input: User's room layout (e.g., 5 meters long, 4 meters wide), interior style (e.g., Scandinavian), purpose of room (e.g., living room), budget (e.g., 50,000 yen).

[1548] Output: JSON formatted data.

[1549] Specific operation: The user checks the information entered and clicks the "Submit" button. This action causes the data to be processed.

[1550] Step 2: Sending data

[1551] Terminal: The terminal sends the entered JSON format data to the server.

[1552] Input: User input data in JSON format.

[1553] Output: The HTTP request sent to the server.

[1554] Specific operation: The device makes an HTTP POST request to the server and sends JSON data. If the sending process is successful, a confirmation message will be displayed.

[1555] Step 3: Receiving and analyzing data

[1556] Server: Receives and analyzes JSON data sent from the terminal. Generates a prompt based on the input data.

[1557] Input: JSON data sent from the terminal.

[1558] Output: The generated prompt statement.

[1559] Specific operation: The server analyzes the JSON data and generates a prompt such as, "The room layout is 5 meters long and 4 meters wide, the style is Scandinavian, the purpose is a living room, and the budget is 50,000 yen."

[1560] Step 4: Generate an interior plan

[1561] Server: The generated prompt sentence is input into the generative AI model to generate interior coordination suggestions.

[1562] Input: The generated prompt statement.

[1563] Output: Interior coordination suggestions from the generative AI model.

[1564] Specific operation: The server sends the following prompt to the generative AI model: "Please coordinate a living room with a Scandinavian style. The room size is 5 meters long and 4 meters wide, and the budget is 50,000 yen. Please suggest an interior that emphasizes simple, light-colored furniture and natural materials." The server then receives the coordination suggestions provided by the model.

[1565] Step 5: Furniture selection

[1566] Server: Based on the generated interior design ideas, the server searches the internet for furniture that can be obtained within the budget.

[1567] Input: Generated interior coordination proposal.

[1568] Output: A list of furniture that can be acquired within your budget.

[1569] Specific operation: The server executes a search query using the online shop's API, and obtains information such as "a wooden center table, a Nordic-style sofa, and a light-toned carpet for under 50,000 yen."

[1570] Step 6: Integrating the interior plan and furniture

[1571] Server: Integrates the generated interior plan and furniture information to generate proposal data.

[1572] Input: Interior coordination ideas and furniture list.

[1573] Output: Consolidated proposal data.

[1574] What it does: The server creates a detailed layout diagram including the layout, price, size, and purchase link for each piece of furniture, and provides it to the user as an integrated interior plan.

[1575] Step 7: Viewing Proposals

[1576] Terminal: Displays the proposal data received from the server on the user interface.

[1577] Input: Proposal data received from the server.

[1578] Output: Interior coordination ideas and furniture information displayed on the user interface.

[1579] Specific operation: The device displays a layout diagram, furniture layout, prices, sizes, purchase links, etc. for the user to review.

[1580] Step 8: Receive feedback and resubmit

[1581] Terminal: The user enters feedback on the suggestion.

[1582] Input: User feedback.

[1583] Output: Feedback data sent to the server.

[1584] Specific behavior: The user enters feedback and sends it to the server as a re-proposal request. This action generates a new prompt and a new proposal.

[1585] By clearly separating each processing step and its specific operation for the user, terminal, and server, this system allows users to realize their ideal interior coordination.

[1586] (Application example 1)

[1587] 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."

[1588] Conventional interior coordination systems have limited means for users to visually check furniture placement and design, and lack a real-time interactive experience. Furthermore, because re-suggestions based on user feedback are not made quickly, achieving the optimal coordination often takes time. Furthermore, these systems are difficult to understand for users who do not have a concrete image of the interior plan, making it difficult to achieve a satisfactory feeling when using them.

[1589] 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.

[1590] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for furniture that fits the user's budget, means for applying the searched furniture to the user's interior coordination, means for displaying the interior coordination on a user interface, means for receiving feedback from the user and generating a re-proposal, and means for viewing the interior via a VR device and changing the coordination content in real time. This allows the user to visually and interactively coordinate their interior in real time, enabling them to quickly and efficiently realize an optimal interior plan.

[1591] "Means for accepting user input" refers to technology that provides an interface for collecting data entered by the user.

[1592] "Means for transmitting data entered by the user to the server" refers to a mechanism for transferring data provided by the user to the server via a network.

[1593] "Means for generating interior coordination using a generative AI model" refers to technology that uses a generative AI model (e.g., a machine learning model) to create an interior plan that meets the user's requirements.

[1594] "A means of searching for furniture that fits a user's budget" is a function that searches an online database for furniture that can be purchased within the user's set budget.

[1595] The "means for applying the searched furniture to the user's interior coordination" is a technique for incorporating the searched furniture as part of an interior plan.

[1596] The "means for displaying interior coordination on a user interface" is a display system for visually presenting the generated interior plan to the user.

[1597] "Means for receiving feedback from users and generating new proposals" refers to a mechanism for collecting user opinions and requests and creating new proposals based on them.

[1598] "A means of viewing interiors via a VR device and changing the coordination details in real time" refers to a technology that uses a VR device to check interior plans in a virtual reality space and make changes on the spot as needed.

[1599] The present invention is a system that allows a user to efficiently coordinate the interior of a room, and specific embodiments thereof will be described below.

[1600] System configuration

[1601] The system consists of a user terminal, a server, and a VR device. The user terminal provides the user interface and is responsible for inputting and displaying data. The server processes the data and executes the generative AI model, and the VR device is used by the user to visually check the generated interior plan.

[1602] Hardware and software used

[1603] Hardware:

[1604] User devices: PC, tablet, smartphone

[1605] Server: High-performance computer

[1606] VR devices: smart glasses, head-mounted displays (e.g., Oculus Rift, HTC Vive)

[1607] software:

[1608] User Interface Applications

[1609] Server program (e.g. Python, Flask)

[1610] Generative AI models (e.g., GPT-4)

[1611] Database Interface

[1612] Operation overview

[1613] 1. Accept user input:

[1614] The user uses a user terminal to input information such as the room layout, interior taste, purpose of use of the room, budget, etc. This input is done through a user interface application.

[1615] 2. Sending and Receiving Data:

[1616] The terminal sends the input data in JSON format to the server, which receives it and analyzes the data.

[1617] 3. Generate interior plan:

[1618] The server inputs the analyzed data into a generative AI model to generate an interior coordination based on the user's requests. For example, if a Scandinavian style is desired, furniture made of light colors and natural materials will be selected.

[1619] 4. Furniture selection:

[1620] The server searches a furniture database via the Internet to find furniture that is available within the user's budget, and applies the found furniture to the user's interior plan.

[1621] 5. View and real-time changes on VR devices:

[1622] Users can view the generated interior plan in real time using a VR device. Based on user feedback (e.g., a desire to change the color of the sofa), the server generates new proposals using the generative AI model.

[1623] Specific examples

[1624] User input: "The living room layout is 15 feet by 18 feet. The style is Scandinavian and the budget is $60,000."

[1625] Generative AI prompt: "Given a Scandinavian-style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection."

[1626] This system allows users to visually and interactively coordinate interiors in real time, enabling them to quickly and efficiently create optimal interior plans.

[1627] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1628] Step 1:

[1629] The user inputs interior information from the device. Specifically, the user uses the user interface on the device to input the room layout (e.g., 4 meters long, 5 meters wide), interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 60,000 yen). The input data is organized in JSON format.

[1630] Step 2:

[1631] The terminal sends the input data to the server. The input data (JSON format) is sent to the server via the network, and the server receives this data.

[1632] Step 3:

[1633] The server parses the received data, which is in JSON format, and extracts information such as the room layout, interior design, purpose of use, and budget. This analysis creates prompts for the generative AI model.

[1634] Step 4:

[1635] The server generates an interior coordination using a generative AI model. Specifically, based on the analyzed data, the server inputs the following prompts into the generative AI model (e.g., GPT-4):

[1636] "Given a Scandinavian style living room with a layout of 4m by 5m and a budget of 60,000 yen, generate an appropriate interior design plan including furniture placement and selection." Based on this prompt, the model generates an appropriate interior plan.

[1637] Step 5:

[1638] The server searches a furniture database via the Internet based on the generated interior plan. It searches for and collects furniture that is available within the user's budget. Specifically, it uses An API to search the furniture database and obtains information on furniture that matches the user's criteria (e.g., a wooden center table, a Nordic-style sofa, a light-toned carpet).

[1639] Step 6:

[1640] The server applies the furniture it finds to the interior plan. It then integrates the interior plan provided by the generative AI model with the furniture information obtained from the furniture database to create a specific layout plan. This completes the interior plan.

[1641] Step 7:

[1642] The server sends the completed interior plan to the terminal. The data including the generated interior plan and furniture information is sent to the terminal and converted into a format that can be displayed on the user interface.

[1643] Step 8:

[1644] The user checks the interior plan through the terminal and visually views the plan using the VR device. The terminal displays the interior plan and transmits the information to the VR device.

[1645] Step 9:

[1646] Accepts feedback from users. The user uses the VR device and terminal to input feedback about the interior plan (e.g., wanting to change the color of the sofa). This feedback is sent from the terminal to the server.

[1647] Step 10:

[1648] The server generates new interior proposals based on the received feedback. It then uses the generative AI model again to generate a new interior plan that reflects the feedback, and repeats the process from step 5 onwards.

[1649] By following these steps, users can visually and interactively coordinate interiors in real time.

[1650] 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.

[1651] This invention is a system that allows users to efficiently coordinate the interior of a room, and the processing of the program will be explained in detail below, especially the part that combines the emotion engine.

[1652] System Operation Overview

[1653] The system will suggest optimal interior plans and furniture based on the user's input of the room layout, interior taste, purpose of use, and budget. It also incorporates an emotion engine that recognizes the user's emotions, enabling it to offer interior suggestions that will further satisfy the user.

[1654] Accepting user input

[1655] Terminal: Provides an interface for users to input the room layout, interior style, purpose of use, and budget. For example, a user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1656] Sending data

[1657] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[1658] Data reception and analysis

[1659] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[1660] Generate interior plans

[1661] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials. It also optimizes furniture placement by taking into account the room layout.

[1662] Furniture selection and proposal integration

[1663] Server: The server searches furniture databases via the Internet to find furniture that can be acquired within the budget. For example, the server selects a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc. from online databases such as Yahoo Shopping.

[1664] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1665] Analysis by emotion engine

[1666] Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfaction, dissatisfaction, excitement, etc.).

[1667] Emotion-based re-suggestion generation

[1668] Server: The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[1669] Data retransmission and display

[1670] Server: After generating new interior proposals, it sends the data to the device again.

[1671] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[1672] Specific examples

[1673] For example, if a user is not satisfied with the "Scandinavian-style living room" suggestion, the emotion engine will detect this and send dissatisfaction feedback to the server. The server will then regenerate a new suggestion incorporating different furniture arrangements and items and present it to the user again. Through this process, the system can provide an interior design that the user is completely satisfied with.

[1674] The above is a concrete example of how to implement the present invention. This system allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving a high level of satisfaction.

[1675] The processing flow will be explained below.

[1676] Step 1:

[1677] Terminal: The user accesses an interface where they can input the room layout, interior style, purpose of use, and budget. For example, the user can input data such as a 5m x 4m floor plan, Scandinavian style, living room, and a budget of 50,000 yen.

[1678] Step 2:

[1679] Terminal: When the user checks the input and presses the send button, the terminal encodes the input data in a standard format such as JSON and sends the data to the server.

[1680] Step 3:

[1681] Server: The server receives the data sent from the device. The received data is analyzed to understand the user's requirements (floor layout, interior taste, purpose of use, budget).

[1682] Step 4:

[1683] Server: The server uses a generative AI model to generate interior coordination based on the analyzed data. This AI model is trained to generate Scandinavian-style interiors, for example, and suggests simple, light-colored furniture and natural materials.

[1684] Step 5:

[1685] Server: Based on the generated interior coordination, the server searches the internet for furniture that fits the user's budget. For example, it queries a furniture database (online shopping site) to find a wooden center table, a Scandinavian-style sofa, a light-toned carpet, etc.

[1686] Step 6:

[1687] Server: Based on the selected furniture information, the server integrates the generated interior coordination and furniture details. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1688] Step 7:

[1689] Server: Sends the consolidated proposal data to the device, also encoded in a standard format such as JSON.

[1690] Step 8:

[1691] Terminal: The terminal analyzes the received proposal data and displays it on the user interface. The user can visually check the interior coordination proposal and check detailed information (price, purchase link, size) of the recommended furniture.

[1692] Step 9:

[1693] On the device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine the user's emotional state (satisfied, dissatisfied, excited, etc.). For example, if the user is dissatisfied with the suggestions, the emotion engine will detect this.

[1694] Step 10:

[1695] Terminal: The user enters feedback on the proposal (e.g., I would like to change the color of the sofa to a lighter color). The user enters the feedback into the terminal and presses the send button.

[1696] Step 11:

[1697] Device: Sends user feedback to the server, also encoded in a standard format such as JSON.

[1698] Step 12:

[1699] Server: The server analyzes the received feedback and uses the generative AI model again based on the user's instructions to generate new interior suggestions, such as changing the sofa color to a brighter one.

[1700] Step 13:

[1701] Server: The server also takes into account feedback from the emotion engine to analyze the user's emotional state. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[1702] Step 14:

[1703] Server: After generating new interior proposals, it sends the data to the device again.

[1704] Step 15:

[1705] Terminal: The terminal analyzes the new proposal data and displays it again on the user interface. The user can review the proposed interior coordination and repeat the process until satisfied.

[1706] This series of processes allows users to efficiently coordinate their interiors in a way that enhances their emotional satisfaction.

[1707] Example 2

[1708] 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."

[1709] In modern living spaces, many people often struggle with designing their own rooms. It can be particularly difficult to select the optimal interior design, taking into account numerous factors, such as the room's layout, interior taste, intended use, and budget. Furthermore, there are cases where the furniture purchased does not match the overall interior design or exceeds budget. Furthermore, there is no system that can provide interior design suggestions that take into account the user's emotions and reactions, which can lead to a decline in user satisfaction.

[1710] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for transmitting data input by a user to the server, a means for generating an interior coordination using a generative AI model, and a means for searching for furniture that fits the budget. This allows the user to efficiently coordinate the interior of a room.

[1711] The server also includes a means for applying the searched furniture to the user's interior coordination, a means for displaying the interior coordination on a user interface, a means for analyzing the user's emotional state, and a means for generating a re-proposal based on the user's emotional feedback. This enables interior proposals that reflect real-time feedback based on the user's emotions, ultimately achieving high satisfaction.

[1712] "User" refers to an individual or corporation that uses the system to input the data necessary to receive interior coordination proposals and to review the proposed interiors.

[1713] "Means for accepting input" refers to an interface or device that allows the user to input information such as the room layout, interior style, purpose of use of the room, budget, etc.

[1714] "Means for transmitting data to a server" refers to the function of encoding information entered by the user and sending it to a server via a communication means such as the Internet.

[1715] "Generative AI model" refers to an artificial intelligence model trained to automatically generate interior coordination based on specific interior tastes and requirements.

[1716] "Means for generating interior coordination" refers to the function of using a generative AI model to create an interior plan based on user input information.

[1717] "Searching tools" refers to the functionality that uses the internet and databases to find furniture and interior items that are within the user's budget.

[1718] "Means of application" refers to the function of reflecting the searched furniture and interior items in the generated interior coordination.

[1719] "User interface" refers to the screens and operating means through which users can view interior design proposals and provide feedback.

[1720] "Means for displaying" refers to the function of visually presenting the interior coordination generated by the server to the user through the user interface.

[1721] "Means for analyzing emotional state" refers to a function that uses an emotion engine to analyze emotions from the user's facial expressions, voice tone, etc., and determine satisfaction, dissatisfaction, etc.

[1722] "Means for generating re-proposals" refers to the function of re-operating the generative AI model to create new interior proposals based on the user's emotional feedback.

[1723] This invention is a system that allows users to efficiently coordinate the interior of a room. The program processing is specifically explained. This system uses a generative AI model to propose appropriate interior coordination based on user input, and further improves user satisfaction by making further proposals that reflect the user's emotional feedback.

[1724] Hardware and Software

[1725] Terminal: A device through which a user enters information, including computers, smartphones, tablets, etc.

[1726] Server: Analyzes the received data, generates interior coordination using a generative AI model, and makes new suggestions.

[1727] Emotion engine: Software used to analyze a user's facial expressions and tone of voice to determine their emotional state.

[1728] Program processing

[1729] 1. Accepting user input

[1730] Users input their room layout, interior style, purpose of use, and budget through the terminal. The interface is designed to be easy to use, and it is possible to input specific information such as a "floor plan of 5 meters long and 4 meters wide," a "Scandinavian-style living room," and a "budget of 50,000 yen."

[1731] 2. Data transmission

[1732] After checking the input, the user presses the send button, and the device encodes the input data in JSON format and sends it to the server via the Internet.

[1733] 3. Data Receipt and Analysis

[1734] The server receives the data sent from the device and analyzes the information obtained. Based on this analysis, it understands the user's requirements (floor layout, interior taste, purpose of use, budget).

[1735] 4. Generate interior plans

[1736] The server then uses a generative AI model based on the analyzed data to generate interior coordination. This AI model is optimized for a specific interior style (e.g., Scandinavian style) and suggests simple, light-colored furniture and natural materials. It also calculates the optimal furniture placement based on the room layout.

[1737] 5. Furniture selection and proposal integration

[1738] The server searches a furniture database via the Internet and selects items that can be purchased within the customer's budget. For example, it selects a wooden center table or a Scandinavian-style sofa from an online furniture database. This ensures that the data is consistent. Finally, it compiles a furniture layout diagram and detailed information about each piece of furniture (price, purchase link, size) into a single proposal data set.

[1739] 6. Analysis by Emotion Engine

[1740] As the user browses the suggested interiors, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state (satisfied, dissatisfied, excited, etc.).

[1741] 7. Emotion-based re-suggestion generation

[1742] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, it generates new interior design suggestions by re-running the generative AI model.

[1743] 8. Data retransmission and display

[1744] After generating new interior suggestions, the system re-encodes them and sends the data to the device, which receives the new suggestions and displays them again on the user interface. This process can be repeated until the user is satisfied.

[1745] Specific examples

[1746] For example, if a user enters, "I want to create a Scandinavian-style living room in a room that is 5 meters long and 4 meters wide. My budget is 50,000 yen," the system will perform the following actions:

[1747] 1. User: Enter the above information using the terminal.

[1748] 2. Terminal: The input is encoded in JSON format and sent to the server.

[1749] 3. Server: Receives and analyzes the data and generates an interior plan using a generative AI model.

[1750] 4. Server: Searches relevant online furniture databases and selects furniture that can be purchased within your budget.

[1751] 5. Server: Integrates the interior plan and selected furniture to generate detailed data.

[1752] 6. Terminal: The generated interior design proposals are displayed to the user, and the emotion engine analyzes the user's reaction.

[1753] 7. Server: Regenerates if necessary and sends new proposals to the device.

[1754] Example prompts for generative AI models

[1755] Below is an example of an input prompt sentence for the generative AI model.

[1756] "Please suggest a Scandinavian-inspired living room for a 5m x 4m room. My budget is 50,000 yen."

[1757] The above is the specific operation and implementation form of this system, which allows users to select the optimal interior design while receiving real-time feedback based on their emotions, ultimately achieving high levels of satisfaction.

[1758] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1759] Step 1:

[1760] Accepting user input

[1761] 1. User: Uses the device to enter information such as the room layout, interior style, purpose of use of the room, budget, etc.

[1762] 2. Input: room layout (5 meters long x 4 meters wide), interior style (Scandinavian), purpose of room (living room), budget (50,000 yen).

[1763] 3. Output: The input data is stored in the device's memory.

[1764] 4. Specific actions: The user enters the necessary information into the input form on the device and presses the "Submit" button.

[1765] Step 2:

[1766] Sending data

[1767] 1. Terminal: The input data is encoded in JSON format and sent to the server for further processing.

[1768] 2. Input: Data entered by the user.

[1769] 3. Output: JSON formatted data is sent to the server.

[1770] 4. Specific operation: The terminal compiles the input content into a single JSON object and sends it to the server via the Internet.

[1771] Step 3:

[1772] Data reception and analysis

[1773] 1. Server: Analyzes the JSON format data received from the device and understands the user's requirements (floor plan, interior style, purpose of use, budget).

[1774] 2. Input: JSON format data sent from the terminal.

[1775] 3. Output: Analyzed data (floor plan, interior design, purpose of use, budget).

[1776] 4. Specific operation: The server decodes the received JSON data, stores it in an internal structure, and analyzes it.

[1777] Step 4:

[1778] Generate interior plans

[1779] 1. Server: Based on the analyzed data, it generates interior coordination using a generative AI model.

[1780] 2. Input: Parsed data.

[1781] 3. Output: Generated interior plan.

[1782] 4. Specific operation: Pass the prompt to the generative AI model and receive an interior plan based on the user's requirements.

[1783] Step 5:

[1784] Furniture selection and proposal integration

[1785] 1. Server: Searches a furniture database via the Internet and selects furniture that can be purchased within the budget.

[1786] 2. Input: Generated interior plan and budget.

[1787] 3. Output: A list of selected furniture.

[1788] 4. Specific Action: Query an online furniture database and filter the results to find furniture within your budget.

[1789] 5. Server: Integrates the furniture list and the generated interior plan, and generates proposal data to present to the end user.

[1790] 6. Input: List of selected furniture.

[1791] 7. Output: Consolidated proposal data.

[1792] 8. Specific actions: Compile furniture layout diagrams, pricing information, product links, etc. into a single proposal document.

[1793] Step 6:

[1794] Analysis by emotion engine

[1795] 1. Device: While the user is browsing interior design suggestions, the emotion engine analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[1796] 2. Input: User's facial expression data, tone of voice.

[1797] 3. Output: The user's emotional state (satisfied, dissatisfied, excited, etc.).

[1798] 4. Specific operation: The emotion engine collects and analyzes data using the camera and microphone installed on the device.

[1799] Step 7:

[1800] Emotion-based re-suggestion generation

[1801] 1. Server: Analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied, the generative AI model is reactivated to generate new interior design suggestions.

[1802] 2. Input: User's emotional feedback.

[1803] 3. Output: Re-proposed interior plan.

[1804] 4. Specific actions: Analyze the feedback data and pass new prompts to the generative AI model to regenerate the interior plan.

[1805] Step 8:

[1806] Resend and display data

[1807] 1. Server: Sends new interior proposals to the device.

[1808] 2. Input: Regenerated interior plan.

[1809] 3. Output: The new proposal data sent to the device.

[1810] 4. Specific operation: The proposed data is re-encoded and sent to the terminal via the Internet.

[1811] 5. Terminal: Receives new proposal data and displays it on the user interface.

[1812] 6. Input: Re-proposal data sent from the server.

[1813] 7. Output: Interior proposals displayed on the user interface.

[1814] 8. Specific operation: The terminal decodes the received data and updates the user interface displayed on the screen.

[1815] (Application example 2)

[1816] 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."

[1817] Conventional interior coordination systems simply generate and provide interior plans based on data entered by the user. As a result, they were unable to make dynamic suggestions based on the user's emotions and satisfaction, and multiple trials and manual adjustments were required to obtain optimal interior suggestions. Furthermore, they lacked real-time display and feedback of the interior plans, limiting the user experience. In response, there is a need for a system that can recognize the user's emotional state and automatically generate optimal suggestions while receiving feedback in real time.

[1818] 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.

[1819] In this invention, the server includes means for accepting user input, means for transmitting data input by the user to the server, means for generating an interior coordination using a generative AI model, means for searching for items that fit the user's budget, means for applying the searched items to the user's interior coordination, means for displaying the interior coordination on a user interface, means for recognizing the user's emotional state, and means for generating re-proposals based on the recognized emotional state. This makes it possible to analyze the user's emotional feedback in real time and quickly automatically generate optimized interior proposals. The user can repeatedly receive proposals until they are satisfied, thereby achieving higher satisfaction.

[1820] The "means for accepting user input" is a device that provides an interface for the user to input data such as the room layout, interior taste, purpose of use of the room, budget, etc.

[1821] A "means for transmitting data entered by a user to a server" is a device that has the function of encoding information entered by a user in a standard format and transmitting it to a server located at a remote location.

[1822] A "means for generating interior coordination using a generative AI model" is a system that uses a generative AI model to automatically generate optimal interior coordination based on user input.

[1823] The "means for searching for items that fit a budget" is a system that has the function of searching an item database via the Internet and identifying items that can be acquired within the user's budget.

[1824] The "means for applying the searched item to the user's interior coordination" refers to a device or system that has the function of arranging the searched item in the generated interior plan.

[1825] The "means for displaying interior coordination on a user interface" refers to a display device or software for visually presenting the generated interior plan to the user.

[1826] "Means for recognizing the user's emotional state" refers to devices or software that analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[1827] The "means for generating new suggestions based on the recognized emotional state" is a system that automatically generates new interior suggestions according to the user's emotions based on feedback from the emotion engine.

[1828] This invention is a system that allows users to efficiently coordinate the interior of a room. Specific embodiments and their configurations are described in detail below. This system uses user input data and proposes interior plans using a generative AI model. It also incorporates an emotion engine to provide optimal proposals in real time based on the user's emotions.

[1829] System configuration

[1830] Hardware

[1831] Smart glasses / tablet: Used as an interface for users to provide input data, such as the room layout, interior taste, purpose of use, and budget.

[1832] Server: Receives, analyzes, and processes data sent by users. Generates interior coordination using generative AI models.

[1833] Emotion recognition device: Analyzes the user's facial expressions and tone of voice in real time to determine their emotional state.

[1834] software

[1835] Generative AI model: Automatically generates optimal interior coordination based on user input data. This is a model trained to create interior plans that match the user's preferences and room characteristics.

[1836] Emotion engine: Analyzes user emotions in real time and provides feedback on user satisfaction.

[1837] Program Processing Details

[1838] Data collection and input

[1839] First, the user enters data such as the room layout, interior style (e.g., Scandinavian), purpose of the room (e.g., living room), and budget (e.g., 50,000 yen) into an interface displayed on smart glasses or a tablet.

[1840] Data transmission and analysis

[1841] The data entered by the user is encoded into a standard format (e.g., JSON) and sent to the server. The server receives this data and analyzes it. Specifically, it analyzes information such as the room layout, interior taste, purpose of use, and budget, and generates the optimal interior plan based on that information.

[1842] Generate interior plans

[1843] The server uses the analyzed data to run a generative AI model to generate an interior coordination plan, taking into account the user's specified interior style (e.g., Scandinavian) and the characteristics of the room. It also searches for items that fit the user's budget and selects candidate items.

[1844] Emotion Recognition and Re-Suggestion

[1845] When a user browses an interior plan, an emotion recognition device analyzes the user's facial expressions and tone of voice in real time to determine their emotional state. If the user expresses dissatisfaction, the server recreates a new interior proposal using a generative AI model and presents it to the user again for optimization.

[1846] Specific examples

[1847] For example, if a user requests a "Scandinavian-style living room" and is dissatisfied with the initial proposal, the emotion engine detects the user's dissatisfaction and provides feedback to the server. The server then uses the generative AI model to create a new proposal, perhaps incorporating different furniture arrangements or items. This process is repeated until the user is satisfied.

[1848] Prompt Sentence Examples

[1849] "Room: 5 meters long, 4 meters wide, Use: Living room, Style: Scandinavian, Budget: 50,000 yen. Proposal: Create an interior design with a Scandinavian feel."

[1850] The above is an embodiment of the present invention. This system allows the user to achieve the best interior coordination while receiving real-time feedback based on their emotions.

[1851] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1852] Step 1:

[1853] User Input

[1854] Using smart glasses or a tablet, users input the room layout, interior design preferences, purpose of use, and budget, and this input data is captured through the interface.

[1855] Input: Room layout, interior style, purpose of use, budget

[1856] Output: Input data in JSON format

[1857] Step 2:

[1858] Sending data

[1859] The terminal encodes the data entered by the user in a standard format (JSON format) and sends it to the server. Data transmission is triggered when the user presses the send button.

[1860] Input: Input data in JSON format

[1861] Output: Data sent to the server

[1862] Step 3:

[1863] Data reception and analysis

[1864] The server receives the data sent from the device and analyzes it to understand the user's requirements, such as the room layout, interior style, purpose of use, and budget.

[1865] Input: Data from the terminal

[1866] Output: Parsed user request data

[1867] Step 4:

[1868] Generate interior plans

[1869] The server then uses a generative AI model to generate interior coordination based on the analyzed data. For example, it could use a model trained to generate Scandinavian-style interiors to generate a plan. It also optimizes furniture placement based on the room layout.

[1870] Input: Parsed user request data

[1871] Output: Generated interior plan

[1872] Step 5:

[1873] Finding items that fit your budget

[1874] The server searches an online database of items to find items that can be purchased within the budget. For example, it selects items such as a wooden center table, a Scandinavian-style sofa, and a light-toned carpet from the online database.

[1875] Input: Budget and interior plan

[1876] Output: Information on items that can be obtained within the budget

[1877] Step 6:

[1878] Interior plan integration and display

[1879] The server integrates the generated interior coordination and item details based on the selected item information. Specifically, it compiles the furniture layout plan and detailed information for each piece of furniture (price, purchase link, size) into a single proposal data.

[1880] Input: Generated interior plan, item information

[1881] Output: Integrated interior proposals

[1882] Step 7:

[1883] Display of interior design proposals

[1884] The terminal receives the interior proposal data sent from the server and displays it on the user interface. The user can then confirm the proposed interior coordination.

[1885] Input: Integrated interior proposals

[1886] Output: Interior design suggestions displayed on the user interface

[1887] Step 8:

[1888] emotion recognition

[1889] As users browse interior design suggestions, the emotion engine analyzes their facial expressions and tone of voice in real time to determine their emotional state (satisfaction, dissatisfaction, excitement, etc.).

[1890] Input: User's facial expressions, tone of voice

[1891] Output: Determined user's emotional state

[1892] Step 9:

[1893] Generate re-proposals

[1894] The server analyzes the user's emotional state based on feedback from the emotion engine. If the user is dissatisfied with the current interior design proposal, the server re-runs the generative AI model to generate new interior design proposals.

[1895] Input: Determined user emotional state

[1896] Output: New interior proposals

[1897] Step 10:

[1898] Submitting and viewing new suggestions

[1899] After generating new interior suggestions, the server sends the data back to the device. The device analyzes the new suggestions and displays them again on the user interface. The user can review the new suggestions and repeat this process until they are satisfied.

[1900] Input: New interior design proposal

[1901] Output: New interior design suggestions displayed on the user interface

[1902] 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.

[1903] 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.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] 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.

[1908] 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).

[1909] 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.

[1910] 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."

[1911] 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.

[1912] 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).

[1913] 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.

[1914] 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.

[1915] 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.

[1916] 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.

[1917] 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.

[1918] 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.

[1919] 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.

[1920] 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.

[1921] 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.

[1922] 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.

[1923] The following is further disclosed regarding the above embodiment.

[1924] (Claim 1)

[1925] a means for accepting user input;

[1926] means for transmitting user-entered data to a server;

[1927] A means for generating interior coordination using a generative AI model;

[1928] A way to find furniture that fits your budget,

[1929] A means for applying the searched furniture to the user's interior coordination;

[1930] A means for displaying interior coordination on a user interface;

[1931] a means for receiving feedback from users and generating re-suggestions;

[1932] A system including:

[1933] (Claim 2)

[1934] The system according to claim 1, further comprising means for optimizing the interior plan based on a user's interior taste and the intended use of the room.

[1935] (Claim 3)

[1936] 10. The system of claim 1, further comprising means for searching a furniture database via the Internet to identify furniture available within the user's budget.

[1937] "Example 1"

[1938] (Claim 1)

[1939] a means for accepting user input;

[1940] means for transmitting user-entered data to a server;

[1941] A means for generating interior coordination using a generative AI model;

[1942] A way to find furniture that fits your budget,

[1943] A means for applying the searched furniture to the user's interior coordination;

[1944] A means for displaying interior coordination on a user interface;

[1945] a means for receiving feedback from users and generating re-suggestions;

[1946] a means for creating and sending prompts to the generative AI model;

[1947] A means for providing an optimal interior plan based on the layout and interior taste of the user's room;

[1948] A system including:

[1949] (Claim 2)

[1950] The system according to claim 1, further comprising means for optimizing the interior plan based on a user's interior taste and the intended use of the room.

[1951] (Claim 3)

[1952] 10. The system of claim 1, further comprising means for searching a furniture database via the Internet to identify furniture available within the user's budget.

[1953] "Application Example 1"

[1954] (Claim 1)

[1955] a means for accepting user input;

[1956] means for transmitting user-entered data to a server;

[1957] A means for generating interior coordination using a generative AI model;

[1958] A way to find furniture that fits your budget,

[1959] A means for applying the searched furniture to the user's interior coordination;

[1960] A means for displaying interior coordination on a user interface;

[1961] a means for receiving feedback from users and generating re-suggestions;

[1962] A way to view interiors via a VR device and change the coordination details in real time.

[1963] A system including:

[1964] (Claim 2)

[1965] The system according to claim 1, further comprising means for optimizing the interior plan based on a user's interior taste and the intended use of the room.

[1966] (Claim 3)

[1967] 10. The system of claim 1, further comprising means for searching a furniture database via the Internet to identify furniture available within the user's budget.

[1968] "Example 2: Combining Emotion Engines"

[1969] (Claim 1)

[1970] a means for accepting user input;

[1971] means for transmitting user-entered data to a server;

[1972] A means for generating interior coordination using a generative AI model;

[1973] A way to find furniture that fits your budget,

[1974] A means for applying the searched furniture to the user's interior coordination;

[1975] A means for displaying interior coordination on a user interface;

[1976] a means for analyzing the emotional state of a user;

[1977] a means for generating re-suggestions based on the user's emotional feedback;

[1978] A system including:

[1979] (Claim 2)

[1980] The system according to claim 1, further comprising means for optimizing the interior plan based on a user's interior taste and the intended use of the room.

[1981] (Claim 3)

[1982] 10. The system of claim 1, further comprising means for searching a furniture database via the Internet to identify furniture available within the user's budget.

[1983] "Application example 2 when combining emotion engines"

[1984] (Claim 1)

[1985] a means for accepting user input;

[1986] means for transmitting user-entered data to a server;

[1987] A means for generating interior coordination using a generative AI model;

[1988] A way to find items that fit your budget,

[1989] A means for applying the searched item to the user's interior coordination;

[1990] A means for displaying interior coordination on a user interface;

[1991] a means for recognizing the emotional state of a user;

[1992] means for generating re-suggestions based on the recognized emotional state;

[1993] A system including:

[1994] (Claim 2)

[1995] The system according to claim 1, further comprising means for optimizing the interior plan based on a user's interior taste and the intended use of the room.

[1996] (Claim 3)

[1997] 10. The system of claim 1, further comprising means for searching a database of items via the Internet to identify items that are available within the user's budget. [Explanation of symbols]

[1998] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for accepting user input; means for transmitting user-entered data to a server; A means for generating interior coordination using a generative AI model; A way to find furniture that fits your budget, A means for applying the searched furniture to the user's interior coordination; A means for displaying interior coordination on a user interface; a means for receiving feedback from users and generating re-suggestions; A system including:

2. 2. The system according to claim 1, further comprising means for optimizing an interior plan based on a user's interior taste and a room's intended use.

3. 10. The system of claim 1, further comprising means for searching a furniture database via the Internet to identify furniture that is available within the user's budget.

Images