System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a picture of a room taken by a user; means for analyzing the picture to recognize room features, existing furnishings, colors, and lighting arrangements; means for collecting information about a user's preferred design styles and color palettes; means for generating a personalized interior design suggestion based on the room features and user preferences; and means for 3D modeling and displaying the interior design suggestion to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional interior coordination requires the assistance of an expert, making it difficult for users to find a design that suits their tastes. Furthermore, it requires a great deal of time and effort for users to realize their desired image, creating a significant burden. Furthermore, selecting the optimal product within a budget is cumbersome, making it difficult to find the right one from the many options available. Therefore, the present invention aims to solve these problems and provide a means for users to easily find and realize an interior design that suits their tastes. [Means for solving the problem]

[0005] The present invention provides an interior design proposal system including: means for receiving photos of a room taken by a user; means for analyzing the photos to recognize the room's features, existing furniture, colors, and lighting arrangement; means for collecting information on the user's preferred design style and color palette; means for generating personalized interior design proposals based on the room's features and the user's preferences; and means for converting the interior design proposals into 3D models and displaying them to the user. Furthermore, the system includes means for selecting optimal products within a user-specified budget and means for the user to make changes to the proposed design, thereby enabling the user to easily and effectively realize an interior design that meets their preferences.

[0006] The term "user" refers to a person who uses the system and provides photos and preferred styles of interior design for a room.

[0007] "Room Photo" means an image of a room taken by a user that visually captures the room's layout, existing furniture, decorations, and color scheme.

[0008] "Means for receiving" refers to the function of acquiring photos of rooms uploaded by users to the system and converting them into a form that can be processed within the system.

[0009] "Means for analyzing" refers to the AI ​​models and algorithms used to recognize room features, existing furniture, colors, and lighting arrangements from the received photos.

[0010] "Room features" refers to physical and visual attributes such as the room layout, furniture position, color, and lighting arrangement.

[0011] "Design style" refers to the overall theme or atmosphere of the interior design preferred by the user, such as modern, classic, minimalist, etc.

[0012] A "color palette" refers to a set of color combinations or color schemes that a user prefers, and is used to achieve harmony with the overall color tone of a design.

[0013] "Personalized interior design suggestions" refers to interior design suggestions customized based on the characteristics and preferences of a user's room, including specific layout and decoration ideas.

[0014] "3D modeling" refers to the process of recreating a proposed interior design in a three-dimensional virtual space so that users can visually confirm it.

[0015] "Means for selecting optimal products within a budget" refers to a function that takes into account the budget set by the user and selects the optimal interior products that can be purchased within that range.

[0016] "Means for making changes" refers to the function that allows users to provide feedback on the proposed design and modify or update the furniture placement, color, etc. according to the user's requests. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The interior design proposal system of the present invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[0039] System Overview

[0040] 1. Upload a photo

[0041] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[0042] 2. Receiving and analyzing photos

[0043] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[0044] 3. Collecting user preference information

[0045] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[0046] 4. Generate design proposals

[0047] The server combines the room analysis results with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting options, curtains, etc. It also selects optimal products within the user's budget.

[0048] 5. 3D Model Generation and Display

[0049] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in a virtual space and make any necessary changes.

[0050] Program implementation example

[0051] 1. Upload a photo

[0052] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[0053] Examples:

[0054] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[0055] 2. Receiving and analyzing photos

[0056] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[0057] Examples:

[0058] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[0059] 3. Collecting user preference information

[0060] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[0061] Examples:

[0062] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[0063] 4. Generate design proposals

[0064] The server generates interior design proposals based on the results of photo analysis and the user's preferences, and also selects the best products based on the user's budget.

[0065] Examples:

[0066] The server generates suggestions for user A, such as a modern sofa and an orange accent wall, and selects furniture that can be purchased within the user's budget.

[0067] 5. 3D Model Generation and Display

[0068] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[0069] Examples:

[0070] When User A opens the app, checks the 3D model, and changes the sofa position or wall color, it is updated in real time.

[0071] As described above, the system of the present invention provides a means for users to easily find and realize interior designs that suit their tastes, allowing users to easily coordinate the interior of their home without the help of a professional.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] The user takes a photo of their room. The user uses a smartphone or a digital camera to take a photo of a room such as a living room, bedroom, or kitchen.

[0075] Step 2:

[0076] The device displays the photos that have been taken so that the user can select them. The user selects a photo on the device screen and presses the upload button.

[0077] Step 3:

[0078] The terminal uploads a photo of the selected room to the server, where it is converted into a format that can be processed within the system.

[0079] Step 4:

[0080] The server receives the photos uploaded by the user and verifies that the photos were received correctly.

[0081] Step 5:

[0082] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[0083] Step 6:

[0084] The server generates the analysis results and stores the information in a temporary file or database, thereby recording the room's characteristics as data.

[0085] Step 7:

[0086] The terminal displays an interface for the user to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[0087] Step 8:

[0088] The user selects a preferred design style and color palette and performs an operation to transmit that information to the system.

[0089] Step 9:

[0090] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[0091] Step 10:

[0092] The server combines the results of photo analysis with user preference information, and generates personalized interior design suggestions based on this information.

[0093] Step 11:

[0094] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed by the user.

[0095] Step 12:

[0096] The server generates a 3D model and sends it to the device, where the user can view the model.

[0097] Step 13:

[0098] The device displays the 3D model to the user and provides an interactive interface, allowing the user to examine the proposed design in detail.

[0099] Step 14:

[0100] Users can make changes to the layout and design while viewing the 3D model, such as changing the sofa position or wall color.

[0101] Step 15:

[0102] The device sends the user's changes to the server, which then reflects the changes in real time and updates the 3D model.

[0103] Step 16:

[0104] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[0105] Step 17:

[0106] The server generates the final design and a list of necessary products and sends them to the terminal, which the user can use to coordinate the interior.

[0107] Through these steps, the system of the present invention proposes an optimal interior design for the user's room and helps the user to easily realize it.

[0108] Example 1

[0109] 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."

[0110] Conventional interior design systems have difficulty efficiently generating design proposals based on a user's individual preferences. Even when a user sets a budget, the system lacks the functionality to select the optimal product within that budget. Furthermore, the system lacks an interface that allows users to make changes to the proposed design, which can lead to reduced user satisfaction.

[0111] 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.

[0112] In this invention, the server includes means for receiving images of a space taken by a user, means for analyzing the images to recognize the layout of the space, existing fixtures, colors, and lighting arrangement, means for collecting information regarding the user's preferred design style and color selection, means for generating a personalized interior design proposal, means for creating a three-dimensional model of the interior design proposal and displaying it to the user, means for selecting optimal products within a user-specified budget, and means for the user to make changes to the proposed design. This allows the server to generate personalized interior design proposals that meet the user's individual preferences, provide optimal products within a user's budget, and enable the user to make changes to the design in real time.

[0113] A "user" is an individual or corporation that uses the system to request an interior design for their space.

[0114] A "space image" is a photograph or image data taken by a user that shows the interior scenery or layout of a room.

[0115] "Means for receiving" refers to the function of importing image data uploaded by users via the Internet into a server.

[0116] The "means of analysis" refers to algorithms or software that process the received image data and recognize the spatial layout, type and placement of fixtures, colors, lighting position, etc.

[0117] "Fixtures" refers to furniture and interior items placed in a room.

[0118] "Color" refers to the various color combinations and color schemes that exist within a space.

[0119] "Lighting arrangement" refers to the location of lighting fixtures within a space and the distribution of light they provide.

[0120] "Design style" is a concept that describes the overall theme or aesthetic of an interior design, and examples include modern, classic, and minimalist.

[0121] "Color selection" refers to the user's preferred color palette or color combination.

[0122] "Individualized interior design proposal" means an interior design plan that is customized based on the user's preferences and the characteristics of the space.

[0123] "3D modeling" refers to the process of digitally representing a design proposal as a three-dimensional visual model.

[0124] "Displaying means" refers to software and hardware functions for displaying the generated three-dimensional model on the user's terminal.

[0125] "Budget" refers to the total amount of money the user can spend on the interior design.

[0126] "Product selection tools" are algorithms and system functions that select the best furniture and interior items within the user's budget.

[0127] "Means for making changes" refers to the interface and functionality that allows a user to make corrections or adjustments to the proposed design.

[0128] The interior design proposal system of the present invention analyzes images of spaces provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as three-dimensional models. Specific technical means and operational examples of the present invention are described below.

[0129] Hardware and Software Configuration

[0130] Users take images of the room using a device such as a smartphone or tablet. A dedicated application is installed on the device, and the user uploads the images to the server through this application. The server receives and stores the image data via the internet. The AI ​​models used include TensorFlow and PyTorch, and Blender and Unity for 3D modeling. These software programs are used within the server to generate design proposals and create 3D models.

[0131] Program processing flow

[0132] When the server receives images uploaded by users, it uses an AI model to analyze them. Specifically, it recognizes the spatial layout, fixture types and placement, colors, and lighting position from the received images. The results of this analysis later become the basis for generating design proposals.

[0133] The device then collects information about the user's preferred design style and color choices through the interface. This information is sent to the server and stored along with the analysis results. For example, if a user selects a modern style and a warm color palette, that information is sent to the server.

[0134] The server uses a generative AI model (e.g., OpenAI GPT-4) to generate interior design proposals based on the analyzed image data and the user's preferences. These proposals include new fixture placement, wall color, lighting selection, curtains, etc. The server also selects optimal products within the user's budget. These design proposals are then converted into 3D models. For example, the server may generate a proposal for User A, such as a modern sofa and an orange accent wall, and select furniture that can be purchased within the user's budget.

[0135] The generated 3D model is sent from the server to the device, where the user can visually check the design in the virtual space. The dedicated application allows the user to make changes to the displayed 3D model, and the changes are reflected in real time. For example, if User A changes the position of a sofa in the app, the changes are immediately reflected in the 3D model.

[0136] Prompt Sentence Examples

[0137] "Analyze a photo of a living room and suggest a modern interior design. Use a warm color palette and choose the best furniture for the user's budget."

[0138] The above is a concrete example of the technical means and operation of the interior design suggestion system of the present invention. This system allows users to easily find and realize an interior design that suits their tastes.

[0139] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0140] Step 1:

[0141] A user takes a picture of their room with their smartphone and uploads it to the device's application. Specifically, the user selects the image they took from the gallery and presses the "upload" button. This operation causes the image data to be sent to the server by the application.

[0142] Input: A room image taken with a smartphone

[0143] Output: Image data sent to the server

[0144] Step 2:

[0145] The server receives images uploaded by users and saves the received data in a specified folder.

[0146] Input: Uploaded image data

[0147] Output: Saved image file

[0148] Step 3:

[0149] The server inputs the received image data into an AI model (e.g., TensorFlow) for analysis. During the analysis process, image features are extracted and the spatial layout, fixture types and placement, colors, lighting position, etc. are recognized.

[0150] Input: Saved image file

[0151] Output: Analysis results including spatial layout, fixture types and placement, color, and lighting position

[0152] Step 4:

[0153] The device provides a user with an interface to collect information about interior design preferences, where the user inputs design styles (e.g., modern, classic, minimalist) and color preferences (e.g., warm, cool), which are then transmitted to a server in real time.

[0154] Input: User's preferred design style and color selection

[0155] Output: User preference data sent to the server

[0156] Step 5:

[0157] The server combines the received user preference data with the results of the image analysis. It then uses a generative AI model (e.g., OpenAI GPT-4) to generate personalized interior design suggestions. These suggestions include new fixture placement, wall colors, lighting choices, curtains, etc. It also selects the best products within the user's budget.

[0158] Input: User preference data and image analysis results

[0159] Output: personalized interior design suggestions and a list of optimal products

[0160] Step 6:

[0161] The server then creates a 3D model of the interior design proposal and sends it to the device using software such as Blender or Unity.

[0162] Input: personalized interior design proposals

[0163] Output: 3D model and its transmission data

[0164] Step 7:

[0165] The device displays the received 3D model data. The user can then view the 3D model within the application and make changes as needed. For example, if the user changes the position of a sofa or the color of a wall in the virtual space, the changes are reflected in real time.

[0166] Input: 3D model data

[0167] Output: User-visible interface and real-time changes

[0168] By following the above steps, users can easily find and realize an interior design that suits their tastes.

[0169] (Application example 1)

[0170] 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."

[0171] While conventional interior design proposal systems can generate personalized design proposals by analyzing photos taken by users, they lack specific functionality for simulating the interior design of virtual stores. In particular, they lack the functionality to automatically recognize the store layout, existing equipment, product placement, and lighting position, suggest optimal products based on the desired design style and budget, and make adjustments in real time. Therefore, a comprehensive design proposal system for virtual stores is needed.

[0172] 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.

[0173] In this invention, the server includes means for receiving photos of a room taken by a user, means for collecting information on the user's preferred design style and color palette, means for generating personalized interior design proposals based on the room's characteristics and the user's preferences, means for converting the interior design proposals into 3D models and displaying them to the user, means for simulating the interior design of a virtual store, means for analyzing uploaded photos to recognize the store's layout, existing equipment, product placement, and lighting location, means for inputting the desired design style and budget, means for proposing optimal products within the budget, and means for displaying the generated 3D model and allowing the user to make adjustments in real time. This enables advanced interior design proposals to be made in virtual stores without the need for specialized knowledge.

[0174] "User" means an individual or organization that uses the system to receive interior design proposals.

[0175] A "photo" is image data showing an image of the interior of a room or store taken by a user.

[0176] "Receiving" is the process by which the system takes in image data uploaded by the user.

[0177] "Analysis" is the process of using AI models and algorithms to extract characteristics of rooms or stores from image data.

[0178] "Room characteristics" refers to the physical characteristics of a room or store, such as its layout, structure, area, and wall color.

[0179] "Existing Furniture" means furniture and decor items that are already installed and are shown in the photograph.

[0180] "Color" refers to the color combinations used on the walls, floors, furniture, etc. of a room or store.

[0181] "Lighting arrangement" refers to the location and type of lighting fixtures in a room or store, and their placement.

[0182] "Design style" refers to the overall interior theme or aesthetic preferred by a user, including modern, classic, minimalist, etc.

[0183] A "color palette" refers to a particular combination of colors that a user prefers.

[0184] "Personalization" is the process of applying a specific design based on a user's individual preferences and requirements.

[0185] "Interior design proposal" refers to a new design plan that reflects the analysis results and the user's preferences.

[0186] A "3D model" is data that represents an interior design proposal in three dimensions.

[0187] A "virtual store" refers to a store model built in a digital space.

[0188] "Simulation" is the process of replicating a real-world design in a virtual environment.

[0189] "Layout" refers to the physical arrangement and structure of the interior of a store or room.

[0190] "Existing Installations" means pre-installed lighting fixtures and fixtures.

[0191] "Product placement" refers to the location of products and displays within a store.

[0192] "Budget" is the amount of money the user prepares for interior design.

[0193] "Optimal products" are the best furniture and interior items selected based on the user's preferences and budget.

[0194] "Real-time" means immediate response and changes are implemented without any time delay.

[0195] The interior design proposal system of this invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. This system can also be applied to virtual stores.

[0196] System configuration and operation method

[0197] 1. Upload a photo

[0198] Users use their smartphones to take photos of their rooms or stores and then upload them to the system through the application, which uses a simple interface.

[0199] 2. Receiving and analyzing photos

[0200] The server receives photos uploaded by users, which are then analyzed using an AI model (such as ImageAI's ResNet). This analysis process recognizes the room layout, existing furniture, color scheme, and lighting arrangement.

[0201] 3. Collecting user preference information

[0202] The terminal provides the user with an interface where they can input information such as their desired design style, preferred color palette, budget, etc. This information is then sent to the server.

[0203] 4. Generate design proposals

[0204] The server combines the results of photo analysis with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting choices, curtain designs, etc. It also selects optimal products within the user's budget.

[0205] 5. 3D Model Generation and Display

[0206] The server then converts the generated interior design proposal into a 3D model and sends it to the user's device for display, allowing the user to visually check the design in a virtual space and make changes as needed.

[0207] Hardware and software used

[0208] Hardware:

[0209] Smartphone (for taking photos and operating applications)

[0210] Server (for photo analysis and design proposal generation)

[0211] software:

[0212] AI models (such as ImageAI's ResNet)

[0213] OpenCV (for image analysis)

[0214] Trimesh and OpenGL (for 3D model generation and display)

[0215] Specific examples

[0216] Consider a scenario in which a user wants to update the design of a virtual store. The user takes a photo of the interior using the camera on their smartphone. They then open the application and upload the photo. Next, the user selects "modern" as the desired design style, "warm" as the color palette, and enters a budget of ¥200,000. The server analyzes the uploaded photo and generates a new interior design based on it. The generated design is displayed as a 3D model, which the user can view in real time and make further adjustments. Finally, the user can review the details of the new design and purchase appropriate products within their budget.

[0217] Example prompt:

[0218] markdown

[0219] To propose an interior design for a room, upload a photo of your store and propose a new design using a modern style and warm color palette. Your budget is ¥200,000.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Step 1:

[0222] A user takes a photo of a room or store using a smartphone and uploads the photo to the system via the application. The input data is the photo taken with the smartphone, and this photo is sent to the system.

[0223] Step 2:

[0224] The server receives photos uploaded by users. It uses OpenCV to preprocess (resize, filter, etc.) the received photo data and prepares it for analysis. The output is image data converted into an analyzable format.

[0225] Step 3:

[0226] The server uses an AI model (e.g., ImageAI's ResNet) to analyze the preprocessed image data. This analysis extracts the room or store layout, existing furniture, color, and lighting arrangement. The input data is the preprocessed image, and the output data is metadata describing the physical characteristics.

[0227] Step 4:

[0228] Through a smartphone application, users input their preferred design style (e.g., modern, classic, minimal, etc.), color palette, budget, etc. The input data is the user's preference information and is sent to the server.

[0229] Step 5:

[0230] The server combines the received user preference information with the analyzed physical feature data. Using AI algorithms, it generates personalized interior design proposals based on this data, including furniture placement, wall color, lighting selection, and curtains. The output data is a design proposal based on the user's preferences and the room's features.

[0231] Step 6:

[0232] The server creates a 3D model of the generated design proposal. It uses Trimesh and OpenGL to represent the design proposal in three dimensions. The input data is the design proposal, and the output data is the 3D model.

[0233] Step 7:

[0234] The server sends the generated 3D model to the user's device and displays it within the application. The user can visually check this 3D model and make changes as needed. The input data is the 3D model, and the output data is the interface that the user can view and edit.

[0235] Step 8:

[0236] Users can adjust the settings of the 3D model in real time within the application. For example, if they change the furniture arrangement or wall color, the changes are immediately reflected in the 3D model. The input data are the user's changes, and the output data is the updated 3D model.

[0237] Through these steps, the system of the present invention provides users with personalized interior design proposals and realizes advanced design simulations that can also be applied to virtual stores.

[0238] 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.

[0239] The interior design proposal system of the present invention analyzes photos of rooms provided by users, generates personalized interior designs based on the user's preferences and emotions, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[0240] System Overview

[0241] 1. Upload a photo

[0242] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[0243] 2. Receiving and analyzing photos

[0244] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[0245] 3. Collecting user preference information

[0246] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[0247] 4. User Emotion Recognition

[0248] The terminal and server are equipped with an emotion engine for analyzing the user's emotions, which evaluates the user's current emotional state in real time through facial expression recognition and text analysis.

[0249] 5. Generate design proposals

[0250] The server integrates the results of the room analysis, the user's preference information, and the user's emotional state to generate personalized interior design proposals. The proposals are dynamically adjusted based on the information from the emotion engine, providing a design that suits the user's mood. The server also selects optimal products within the user's budget.

[0251] 6. Generating and displaying 3D models

[0252] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in virtual space and make any necessary changes.

[0253] Program implementation example

[0254] 1. Upload a photo

[0255] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[0256] Examples:

[0257] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[0258] 2. Receiving and analyzing photos

[0259] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[0260] Examples:

[0261] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[0262] 3. Collecting user preference information

[0263] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[0264] Examples:

[0265] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[0266] 4. User Emotion Recognition

[0267] The device captures the user's facial expressions with a camera, and the emotion engine analyzes them. It also determines the user's emotional state through questionnaires and text input.

[0268] Examples:

[0269] The emotion engine recognizes that User A is in a calm mood through facial expression analysis, and also determines from text input that he or she desires a relaxed atmosphere.

[0270] 5. Generate design proposals

[0271] The server generates interior design suggestions based on the photo analysis results, the user's preference information, and data from the emotion engine. For example, if the user is in a relaxed emotional state, a design with calming colors will be suggested.

[0272] Examples:

[0273] The server proposes a modern interior design with calm tones to User A. Furniture and decorations that can be purchased within the user's budget are also selected.

[0274] 6. Generating and displaying 3D models

[0275] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[0276] Examples:

[0277] User A opens the app, checks the 3D model, and confirms that the proposed design is in line with the relaxing atmosphere. Even if they change the sofa position or wall color, it is updated on the fly.

[0278] The system of the present invention proposes interior design ideas that take the user's emotions into consideration, which has the effect of increasing the user's psychological satisfaction, allowing the user to effectively coordinate the interior of their home without the help of a professional.

[0279] The processing flow will be explained below.

[0280] Step 1:

[0281] Users take photos of their rooms with their smartphones, including the living room, bedroom, kitchen, and other rooms they need.

[0282] Step 2:

[0283] The device displays the captured photos to the user, allowing them to be selected. The user selects the photos to upload and presses the upload button.

[0284] Step 3:

[0285] The terminal uploads the photo files of the selected room to the server, where the uploaded photos are converted into a format that can be processed within the system.

[0286] Step 4:

[0287] The server receives the photos uploaded by the user and verifies that the photos received are correct.

[0288] Step 5:

[0289] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[0290] Step 6:

[0291] The server generates the analysis results and stores the information in a temporary file or database, which records the room's characteristics as data.

[0292] Step 7:

[0293] The device provides the user with an interface that prompts them to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[0294] Step 8:

[0295] The user selects a preferred design style and color palette, and presses the OK button to transmit the selection to the server.

[0296] Step 9:

[0297] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[0298] Step 10:

[0299] The device captures the user's facial expressions with a camera or the user inputs text, which is then sent to the server in real time.

[0300] Step 11:

[0301] The server uses an emotion engine that captures facial expressions and analyzes text to recognize the user's emotions and evaluate their state. This process determines whether the user is relaxed or excited.

[0302] Step 12:

[0303] The server combines the results of photo analysis, user preference information, and emotional data from an emotion engine to generate personalized interior design proposals. The proposals are dynamically adjusted based on the emotional data.

[0304] Step 13:

[0305] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed.

[0306] Step 14:

[0307] The server sends the 3D model to the device, where the user can view it and check the design.

[0308] Step 15:

[0309] The device displays the 3D model to the user in an interactive manner, allowing the user to examine the interior design in detail and make adjustments as needed.

[0310] Step 16:

[0311] Users can change the furniture placement, color, and design style while viewing the 3D model. Users can change the sofa position, wall color, and more in real time.

[0312] Step 17:

[0313] The device sends the user's changes to the server, which reflects them and updates the 3D model in real time.

[0314] Step 18:

[0315] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[0316] Step 19:

[0317] The server generates the final design and a list of required products and sends them to the terminal. The user can then review the final design and product list and obtain information for carrying out interior coordination.

[0318] Through these steps, the system of the present invention provides interior design suggestions that take the user's emotions into consideration, increasing the user's psychological satisfaction and enabling the user to effectively coordinate the interior of their home without the help of a professional.

[0319] Example 2

[0320] 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."

[0321] Conventional interior design proposal systems have difficulty providing personalized designs that take into account the user's preferences and emotional state. They also lack the ability to adjust designs in real time or select optimal products within a budget. This creates a need for systems that can increase user satisfaction and achieve effective interior coordination.

[0322] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0323] In this invention, the server includes means for receiving photos of a room taken by a user, means for analyzing the photos to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional information in real time, means for generating personalized interior design proposals based on the room's features and the user's preferences, and means for converting the interior design proposals into 3D models and displaying them to the user. This enables personalized design proposals tailored to the user's preferences and emotional state, increasing user satisfaction and facilitating effective interior coordination.

[0324] "User" refers to a person who uses the system and receives interior design suggestions.

[0325] A "terminal" refers to an electronic device that allows a user to access and operate the system, and examples include smartphones and personal computers.

[0326] "Server" refers to a computer that manages and processes data received from connected devices and provides the overall functionality of the system.

[0327] "Receiving a photo" refers to the process in which a user sends photo data of a room taken by the user to the server and the server receives the photo data.

[0328] "Photo analysis" refers to the process of using AI models to identify room layout, furniture placement, color, and lighting arrangement based on the photo data received by the server.

[0329] "Collecting user preferences" refers to the process of obtaining information about design styles and color palettes from users via their terminals.

[0330] "Emotional information analysis" refers to the process of assessing a user's emotional state in real time using the device's camera and text input.

[0331] "Generating interior design proposals" refers to the process in which the server constructs the optimal interior design for the user based on the results of photo analysis and the user's preferences and emotional information.

[0332] "3D modeling" refers to the creation of a three-dimensional representation of the generated interior design proposal, allowing users to visually confirm the design in a virtual space.

[0333] "Product selection within budget" refers to the process in which the server selects and recommends furniture and decorations that can be purchased within the budget set by the user.

[0334] "Design changes" refers to adjustments or modifications made by a user to a proposed interior design.

[0335] The interior design proposal system of the present invention is designed to analyze a room photo provided by a user, generate a personalized interior design based on the user's preferences and emotions, and provide it as a 3D model. The following specific hardware and software configurations are used to implement the present invention.

[0336] Hardware Configuration

[0337] 1. Terminal: The device that a user uses to interact with the system. Specific examples include smartphones, tablets, and personal computers.

[0338] 2. Server: A dedicated computer system that receives data, analyzes it, and generates design proposals.

[0339] Software Configuration

[0340] 1. Photo analysis module (AI model): Runs on the server and analyzes photos of rooms uploaded by users. It uses deep learning techniques to identify the room layout, furniture placement, color, and lighting location.

[0341] 2. Emotion Engine: Analyzes the user's facial expressions and text inputs to assess their emotional state in real time, using image recognition algorithms and natural language processing techniques.

[0342] 3. Interface application: Runs on the device and provides a GUI (graphical user interface) for users to upload photos, input design preferences, and provide emotional information.

[0343] 4. 3D modeling engine: Software that converts design proposals generated on the server into 3D models and displays them on the device.

[0344] Specific examples

[0345] For example, if a user wants to improve the interior design of their living room, they can take a photo of the room with their smartphone and upload it to the server through an application on their device. The application is simple to use; just select the photo and press the "upload" button.

[0346] The server analyzes the received photos and uses AI models to determine the room layout, sofa and table placement, wall color, and lighting location. The device then provides an interface that lets the user select a design style (e.g., modern, classic) and color palette. Once the user completes their selection, the information is sent to the server in real time.

[0347] Furthermore, the device's camera captures the user's facial expressions, and the emotion engine analyzes the user's mood (e.g., relaxed, calm). At the same time, the user can express their preferred mood through text input.

[0348] The server analyzes the photos, integrates the user's preferences and emotional data, and generates optimal interior design suggestions. Using a generative AI model, personalized designs are created based on the emotional data. For example, a modern design with calming colors is offered to match the emotional state of wanting to relax.

[0349] Finally, the server creates a 3D model of the generated design and sends it to the terminal. The user can then visually check the design in the virtual space and make any necessary changes. For example, they can adjust the position of the sofa or the color of the walls. In this way, the system of the present invention can provide the user with a satisfactory interior design proposal.

[0350] Examples of prompt statements

[0351] "Take a photo of your living room with the app and upload it."

[0352] "Choose your preferred design style, for example, modern or classic."

[0353] "Tell me how you're feeling right now. If you want to relax, type relax."

[0354] "View the proposed design in 3D and adjust any changes you want to make."

[0355] As a result, users can effectively coordinate the interior of their homes through the system.

[0356] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0357] Step 1:

[0358] The user takes a photo of the room and uploads it to the server via an application on the device.

[0359] Specifically, the user takes a photo of the room with their smartphone camera, clicks the "Select Photo" button in the app, selects the photo, and then presses the "Upload" button. This action sends the photo data to the server.

[0360] Input: A photo of the room taken with a camera

[0361] Output: Photo data sent to the server

[0362] Step 2:

[0363] The server analyzes the received photo data, and an AI model identifies the room layout, furniture placement, color, and lighting position.

[0364] Specifically, after the server receives the photo data, it launches the AI ​​analysis module and begins analysis, using a deep learning model to identify the sofa, table, wall color, and lighting position.

[0365] Input: Photo data uploaded by the user to the server

[0366] Output: Analyzed room layout, furniture placement, color, and lighting location information

[0367] Step 3:

[0368] The device collects the user's design preferences (style, color palette) and sends them to the server.

[0369] Specifically, the user operates the device interface, selects a modern style or warm color palette, presses the "OK" button, and sends the selection to the server.

[0370] Input: User-selected design style and color palette

[0371] Output: User's design preference information sent to the server

[0372] Step 4:

[0373] The device collects the user's real-time emotional information, which is then analyzed by the server's emotion engine.

[0374] Specifically, the device's camera captures the user's facial expressions, and the emotion engine analyzes them. Emotional information is also supplemented by questionnaire and text input.

[0375] Input: User's facial expressions, questionnaire input, text input

[0376] Output: Real-time emotional state information of the user

[0377] Step 5:

[0378] The server integrates the results of photo analysis, user preferences, and emotional information to generate personalized interior design proposals.

[0379] Specifically, the AI ​​model creates an optimal design based on the analysis results and the user's preferences, and generates a proposal. At the same time, it also takes into account the user's emotional information and adjusts the color tone and style of the design.

[0380] Input: Photo analysis results, user's design style and color palette, emotional state information

[0381] Output: Personalized interior design proposals

[0382] Step 6:

[0383] The server converts the generated interior design proposal into a 3D model and sends it to the terminal.

[0384] Specifically, the server-side 3D modeling engine converts the proposed design into a 3D model and sends it to the device, where the user can view the 3D model within the application and interactively modify it as needed.

[0385] Input: Generated interior design proposal

[0386] Output: 3D model data displayed on the device

[0387] (Application example 2)

[0388] 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."

[0389] Conventional interior design systems propose designs based on the user's preferences and room layout, but they have the problem of being unable to take into account the user's current emotional state. Furthermore, they lack a means to visualize the proposed design concretely or to confirm whether the selected products are within the user's budget. Therefore, a system that can propose appropriate interior designs while enhancing the user's psychological satisfaction and respecting financial constraints is needed.

[0390] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a room photo taken by a user, means for analyzing the photo to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional state, means for generating personalized interior design proposals based on the room's features, the user's preferences, and the user's emotional state, and means for creating a 3D model of the interior design proposal and displaying it to the user. This enables interior design proposals that take the user's current emotional state into consideration. Furthermore, the server can select and visually confirm optimal products within the user's budget, making it possible to provide proposals that fit within economic constraints.

[0391] A "user" is someone who uses the system to receive interior design proposals.

[0392] The "means for receiving photos" is a function for receiving photos of the room taken by the user and uploaded to the system.

[0393] "Means for analyzing and recognizing room features, existing furniture, colors, and lighting arrangements" refers to a function that uses digital image analysis technology to analyze received photos and identify the room layout, installed objects, colors, and lighting locations.

[0394] "Means for collecting information about a user's preferred design style and color palette" refers to a function that records and collects design style and color preferences input by a user through an interface.

[0395] The "means for analyzing the user's emotional state" is a function that analyzes the user's facial expressions and input text and evaluates the user's emotions in real time.

[0396] The "means for generating personalized interior design proposals" is a function that creates an interior design suited to each user based on the room's characteristics, the user's preferences, and their emotional state.

[0397] "Means for creating a 3D model of an interior design proposal and displaying it to the user" refers to a function that uses three-dimensional modeling technology to create a model of the generated design proposal and display it so that the user can visually confirm it.

[0398] "Means to select the best products within a budget" is a function that selects furniture and decoration items that can be purchased within a price range set by the user.

[0399] "Means for making changes to the proposed design" refers to a function that allows the user to make changes to the initial design proposal, such as changes to the position or color.

[0400] This interior design proposal system provides users with personalized designs through the following series of steps: The entire system is composed mainly of user terminals (mainly smartphones) and a server.

[0401] First, the user takes a photo of their room with their smartphone and uploads it to the server through an application on their device. The user uses an interface that allows them to easily upload photos. The server receives the photo uploaded by the user and analyzes it using an AI model. Specifically, it recognizes the room layout, furniture type and placement, color, lighting arrangement, etc.

[0402] The device then provides an interface for the user to input their preferences, such as design style and color palette. The information entered by the user is sent to the server and stored. At the same time, the device's camera captures the user's facial expressions, and an emotion engine is used to analyze the user's emotional state in real time. This emotion information is also sent to the server.

[0403] The server combines the results of photo analysis, the user's preferences, and their emotional state, and uses a generative AI model to generate personalized interior design suggestions. If the user's emotional state indicates a desire for relaxation, designs with calming colors and soft lighting will be suggested. Additionally, products that are affordable within the user's budget are selected.

[0404] The generated interior design proposal is converted into a 3D model on the server and sent to the device. The user can use the device application to visually check this 3D model and make changes as needed. For example, if they change the proposed sofa position or wall color, it will be updated on the fly.

[0405] The main hardware used includes the user's smartphone and a server, and the main software includes an AI model, an emotion engine, and a 3D modeling tool, which uses the EmotionRecognition library.

[0406] For example, user A takes a photo of their living room, selects a modern style and a warm color palette using the app, and recognizes their emotional state of wanting to relax through facial expression analysis. Based on this data, the server proposes a relaxing, modern interior design and displays it to user A as a 3D model.

[0407] An example of a prompt for a generative AI model is as follows:

[0408] "Please suggest an interior design for a living room. The user's preference is for a modern style with a warm color palette. The user also wants to feel relaxed. The budget is ¥100,000."

[0409] This allows the system to provide optimal interior design within a budget, taking into account the user's current emotional state.

[0410] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0411] Step 1:

[0412] The user takes a photo of the room and uploads it to the server through the device application. Specifically, the user takes a photo of the room using the smartphone camera and taps the upload button in the app. The input is the photo data of the room, and the photo is sent to the server as the output.

[0413] Step 2:

[0414] The server analyzes the received photos using an AI model. Specifically, the server inputs the photo data, and the AI ​​model recognizes the room layout, furniture type and placement, color, and lighting position. As a result of the analysis, these attributes are identified and output as data.

[0415] Step 3:

[0416] The user inputs their preferred design style and color palette using a terminal application. The terminal receives this through an interface and sends it to the server. The input is the user's preference information, and the output is recorded on the server.

[0417] Step 4:

[0418] The device's camera captures the user's facial expressions, which are then analyzed by the emotion engine. Specifically, the EmotionRecognition library identifies the user's emotions in real time and sends the results to the server. The input is the captured facial expression data, and the output is the analyzed emotional information.

[0419] Step 5:

[0420] The server integrates the photo analysis results, user preference information, and emotional information, and uses a generative AI model to generate personalized interior design proposals. Specifically, this data is input into the AI ​​model as prompts to generate the proposed design. The input is the integrated data, and the output is the design proposal.

[0421] Step 6:

[0422] The server creates a 3D model of the interior design proposal and sends it to the device. Specifically, it uses a 3D modeling tool to create a three-dimensional design. The input is the design proposal, and the output is the 3D model data.

[0423] Step 7:

[0424] The user can view the 3D model in the terminal application and make changes as needed. As the user makes changes, the data is sent from the terminal to the server, and the 3D model is updated in real time. The input is the user's changes, and the output is the updated 3D model.

[0425] This series of steps provides a visually verifiable interior design that takes into account the user's preferences and emotions, thereby increasing user satisfaction.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] [Second embodiment]

[0430] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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."

[0442] The interior design proposal system of the present invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[0443] System Overview

[0444] 1. Upload a photo

[0445] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[0446] 2. Receiving and analyzing photos

[0447] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[0448] 3. Collecting user preference information

[0449] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[0450] 4. Generate design proposals

[0451] The server combines the room analysis results with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting options, curtains, etc. It also selects optimal products within the user's budget.

[0452] 5. 3D Model Generation and Display

[0453] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in a virtual space and make any necessary changes.

[0454] Program implementation example

[0455] 1. Upload a photo

[0456] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[0457] Examples:

[0458] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[0459] 2. Receiving and analyzing photos

[0460] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[0461] Examples:

[0462] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[0463] 3. Collecting user preference information

[0464] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[0465] Examples:

[0466] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[0467] 4. Generate design proposals

[0468] The server generates interior design proposals based on the results of photo analysis and the user's preferences, and also selects the best products based on the user's budget.

[0469] Examples:

[0470] The server generates suggestions for user A, such as a modern sofa and an orange accent wall, and selects furniture that can be purchased within the user's budget.

[0471] 5. 3D Model Generation and Display

[0472] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[0473] Examples:

[0474] When User A opens the app, checks the 3D model, and changes the sofa position or wall color, it is updated in real time.

[0475] As described above, the system of the present invention provides a means for users to easily find and realize interior designs that suit their tastes, allowing users to easily coordinate the interior of their home without the help of a professional.

[0476] The processing flow will be explained below.

[0477] Step 1:

[0478] The user takes a photo of their room. The user uses a smartphone or a digital camera to take a photo of a room such as a living room, bedroom, or kitchen.

[0479] Step 2:

[0480] The device displays the photos that have been taken so that the user can select them. The user selects a photo on the device screen and presses the upload button.

[0481] Step 3:

[0482] The terminal uploads a photo of the selected room to the server, where it is converted into a format that can be processed within the system.

[0483] Step 4:

[0484] The server receives the photos uploaded by the user and verifies that the photos were received correctly.

[0485] Step 5:

[0486] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[0487] Step 6:

[0488] The server generates the analysis results and stores the information in a temporary file or database, thereby recording the room's characteristics as data.

[0489] Step 7:

[0490] The terminal displays an interface for the user to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[0491] Step 8:

[0492] The user selects a preferred design style and color palette and performs an operation to transmit that information to the system.

[0493] Step 9:

[0494] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[0495] Step 10:

[0496] The server combines the results of photo analysis with user preference information, and generates personalized interior design suggestions based on this information.

[0497] Step 11:

[0498] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed by the user.

[0499] Step 12:

[0500] The server generates a 3D model and sends it to the device, where the user can view the model.

[0501] Step 13:

[0502] The device displays the 3D model to the user and provides an interactive interface, allowing the user to examine the proposed design in detail.

[0503] Step 14:

[0504] Users can make changes to the layout and design while viewing the 3D model, such as changing the sofa position or wall color.

[0505] Step 15:

[0506] The device sends the user's changes to the server, which then reflects the changes in real time and updates the 3D model.

[0507] Step 16:

[0508] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[0509] Step 17:

[0510] The server generates the final design and a list of necessary products and sends them to the terminal, which the user can use to coordinate the interior.

[0511] Through these steps, the system of the present invention proposes an optimal interior design for the user's room and helps the user to easily realize it.

[0512] Example 1

[0513] 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."

[0514] Conventional interior design systems have difficulty efficiently generating design proposals based on a user's individual preferences. Even when a user sets a budget, the system lacks the functionality to select the optimal product within that budget. Furthermore, the system lacks an interface that allows users to make changes to the proposed design, which can lead to reduced user satisfaction.

[0515] 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.

[0516] In this invention, the server includes means for receiving images of a space taken by a user, means for analyzing the images to recognize the layout of the space, existing fixtures, colors, and lighting arrangement, means for collecting information regarding the user's preferred design style and color selection, means for generating a personalized interior design proposal, means for creating a three-dimensional model of the interior design proposal and displaying it to the user, means for selecting optimal products within a user-specified budget, and means for the user to make changes to the proposed design. This allows the server to generate personalized interior design proposals that meet the user's individual preferences, provide optimal products within a user's budget, and enable the user to make changes to the design in real time.

[0517] A "user" is an individual or corporation that uses the system to request an interior design for their space.

[0518] A "space image" is a photograph or image data taken by a user that shows the interior scenery or layout of a room.

[0519] "Means for receiving" refers to the function of importing image data uploaded by users via the Internet into a server.

[0520] The "means of analysis" refers to algorithms or software that process the received image data and recognize the spatial layout, type and placement of fixtures, colors, lighting position, etc.

[0521] "Fixtures" refers to furniture and interior items placed in a room.

[0522] "Color" refers to the various color combinations and color schemes that exist within a space.

[0523] "Lighting arrangement" refers to the location of lighting fixtures within a space and the distribution of light they provide.

[0524] "Design style" is a concept that describes the overall theme or aesthetic of an interior design, and examples include modern, classic, and minimalist.

[0525] "Color selection" refers to the user's preferred color palette or color combination.

[0526] "Individualized interior design proposal" means an interior design plan that is customized based on the user's preferences and the characteristics of the space.

[0527] "3D modeling" refers to the process of digitally representing a design proposal as a three-dimensional visual model.

[0528] "Displaying means" refers to software and hardware functions for displaying the generated three-dimensional model on the user's terminal.

[0529] "Budget" refers to the total amount of money the user can spend on the interior design.

[0530] "Product selection tools" are algorithms and system functions that select the best furniture and interior items within the user's budget.

[0531] "Means for making changes" refers to the interface and functionality that allows a user to make corrections or adjustments to the proposed design.

[0532] The interior design proposal system of the present invention analyzes images of spaces provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as three-dimensional models. Specific technical means and operational examples of the present invention are described below.

[0533] Hardware and Software Configuration

[0534] Users take images of the room using a device such as a smartphone or tablet. A dedicated application is installed on the device, and the user uploads the images to the server through this application. The server receives and stores the image data via the internet. The AI ​​models used include TensorFlow and PyTorch, and Blender and Unity for 3D modeling. These software programs are used within the server to generate design proposals and create 3D models.

[0535] Program processing flow

[0536] When the server receives images uploaded by users, it uses an AI model to analyze them. Specifically, it recognizes the spatial layout, fixture types and placement, colors, and lighting position from the received images. The results of this analysis later become the basis for generating design proposals.

[0537] The device then collects information about the user's preferred design style and color choices through the interface. This information is sent to the server and stored along with the analysis results. For example, if a user selects a modern style and a warm color palette, that information is sent to the server.

[0538] The server uses a generative AI model (e.g., OpenAI GPT-4) to generate interior design proposals based on the analyzed image data and the user's preferences. These proposals include new fixture placement, wall color, lighting selection, curtains, etc. The server also selects optimal products within the user's budget. These design proposals are then converted into 3D models. For example, the server may generate a proposal for User A, such as a modern sofa and an orange accent wall, and select furniture that can be purchased within the user's budget.

[0539] The generated 3D model is sent from the server to the device, where the user can visually check the design in the virtual space. The dedicated application allows the user to make changes to the displayed 3D model, and the changes are reflected in real time. For example, if User A changes the position of a sofa in the app, the changes are immediately reflected in the 3D model.

[0540] Prompt Sentence Examples

[0541] "Analyze a photo of a living room and suggest a modern interior design. Use a warm color palette and choose the best furniture for the user's budget."

[0542] The above is a concrete example of the technical means and operation of the interior design suggestion system of the present invention. This system allows users to easily find and realize an interior design that suits their tastes.

[0543] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0544] Step 1:

[0545] A user takes a picture of their room with their smartphone and uploads it to the device's application. Specifically, the user selects the image they took from the gallery and presses the "upload" button. This operation causes the image data to be sent to the server by the application.

[0546] Input: A room image taken with a smartphone

[0547] Output: Image data sent to the server

[0548] Step 2:

[0549] The server receives images uploaded by users and saves the received data in a specified folder.

[0550] Input: Uploaded image data

[0551] Output: Saved image file

[0552] Step 3:

[0553] The server inputs the received image data into an AI model (e.g., TensorFlow) for analysis. During the analysis process, image features are extracted and the spatial layout, fixture types and placement, colors, lighting position, etc. are recognized.

[0554] Input: Saved image file

[0555] Output: Analysis results including spatial layout, fixture types and placement, color, and lighting position

[0556] Step 4:

[0557] The device provides a user with an interface to collect information about interior design preferences, where the user inputs design styles (e.g., modern, classic, minimalist) and color preferences (e.g., warm, cool), which are then transmitted to a server in real time.

[0558] Input: User's preferred design style and color selection

[0559] Output: User preference data sent to the server

[0560] Step 5:

[0561] The server combines the received user preference data with the results of the image analysis. It then uses a generative AI model (e.g., OpenAI GPT-4) to generate personalized interior design suggestions. These suggestions include new fixture placement, wall colors, lighting choices, curtains, etc. It also selects the best products within the user's budget.

[0562] Input: User preference data and image analysis results

[0563] Output: personalized interior design suggestions and a list of optimal products

[0564] Step 6:

[0565] The server then creates a 3D model of the interior design proposal and sends it to the device using software such as Blender or Unity.

[0566] Input: personalized interior design proposals

[0567] Output: 3D model and its transmission data

[0568] Step 7:

[0569] The device displays the received 3D model data. The user can then view the 3D model within the application and make changes as needed. For example, if the user changes the position of a sofa or the color of a wall in the virtual space, the changes are reflected in real time.

[0570] Input: 3D model data

[0571] Output: User-visible interface and real-time changes

[0572] By following the above steps, users can easily find and realize an interior design that suits their tastes.

[0573] (Application example 1)

[0574] 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."

[0575] While conventional interior design proposal systems can generate personalized design proposals by analyzing photos taken by users, they lack specific functionality for simulating the interior design of virtual stores. In particular, they lack the functionality to automatically recognize the store layout, existing equipment, product placement, and lighting position, suggest optimal products based on the desired design style and budget, and make adjustments in real time. Therefore, a comprehensive design proposal system for virtual stores is needed.

[0576] 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.

[0577] In this invention, the server includes means for receiving photos of a room taken by a user, means for collecting information on the user's preferred design style and color palette, means for generating personalized interior design proposals based on the room's characteristics and the user's preferences, means for converting the interior design proposals into 3D models and displaying them to the user, means for simulating the interior design of a virtual store, means for analyzing uploaded photos to recognize the store's layout, existing equipment, product placement, and lighting location, means for inputting the desired design style and budget, means for proposing optimal products within the budget, and means for displaying the generated 3D model and allowing the user to make adjustments in real time. This enables advanced interior design proposals to be made in virtual stores without the need for specialized knowledge.

[0578] "User" means an individual or organization that uses the system to receive interior design proposals.

[0579] A "photo" is image data showing an image of the interior of a room or store taken by a user.

[0580] "Receiving" is the process by which the system takes in image data uploaded by the user.

[0581] "Analysis" is the process of using AI models and algorithms to extract characteristics of rooms or stores from image data.

[0582] "Room characteristics" refers to the physical characteristics of a room or store, such as its layout, structure, area, and wall color.

[0583] "Existing Furniture" means furniture and decor items that are already installed and are shown in the photograph.

[0584] "Color" refers to the color combinations used on the walls, floors, furniture, etc. of a room or store.

[0585] "Lighting arrangement" refers to the location and type of lighting fixtures in a room or store, and their placement.

[0586] "Design style" refers to the overall interior theme or aesthetic preferred by a user, including modern, classic, minimalist, etc.

[0587] A "color palette" refers to a particular combination of colors that a user prefers.

[0588] "Personalization" is the process of applying a specific design based on a user's individual preferences and requirements.

[0589] "Interior design proposal" refers to a new design plan that reflects the analysis results and the user's preferences.

[0590] A "3D model" is data that represents an interior design proposal in three dimensions.

[0591] A "virtual store" refers to a store model built in a digital space.

[0592] "Simulation" is the process of replicating a real-world design in a virtual environment.

[0593] "Layout" refers to the physical arrangement and structure of the interior of a store or room.

[0594] "Existing Installations" means pre-installed lighting fixtures and fixtures.

[0595] "Product placement" refers to the location of products and displays within a store.

[0596] "Budget" is the amount of money the user prepares for interior design.

[0597] "Optimal products" are the best furniture and interior items selected based on the user's preferences and budget.

[0598] "Real-time" means immediate response and changes are implemented without any time delay.

[0599] The interior design proposal system of this invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. This system can also be applied to virtual stores.

[0600] System configuration and operation method

[0601] 1. Upload a photo

[0602] Users use their smartphones to take photos of their rooms or stores and then upload them to the system through the application, which uses a simple interface.

[0603] 2. Receiving and analyzing photos

[0604] The server receives photos uploaded by users, which are then analyzed using an AI model (such as ImageAI's ResNet). This analysis process recognizes the room layout, existing furniture, color scheme, and lighting arrangement.

[0605] 3. Collecting user preference information

[0606] The terminal provides the user with an interface where they can input information such as their desired design style, preferred color palette, budget, etc. This information is then sent to the server.

[0607] 4. Generate design proposals

[0608] The server combines the results of photo analysis with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting choices, curtain designs, etc. It also selects optimal products within the user's budget.

[0609] 5. 3D Model Generation and Display

[0610] The server then converts the generated interior design proposal into a 3D model and sends it to the user's device for display, allowing the user to visually check the design in a virtual space and make changes as needed.

[0611] Hardware and software used

[0612] Hardware:

[0613] Smartphone (for taking photos and operating applications)

[0614] Server (for photo analysis and design proposal generation)

[0615] software:

[0616] AI models (such as ImageAI's ResNet)

[0617] OpenCV (for image analysis)

[0618] Trimesh and OpenGL (for 3D model generation and display)

[0619] Specific examples

[0620] Consider a scenario in which a user wants to update the design of a virtual store. The user takes a photo of the interior using the camera on their smartphone. They then open the application and upload the photo. Next, the user selects "modern" as the desired design style, "warm" as the color palette, and enters a budget of ¥200,000. The server analyzes the uploaded photo and generates a new interior design based on it. The generated design is displayed as a 3D model, which the user can view in real time and make further adjustments. Finally, the user can review the details of the new design and purchase appropriate products within their budget.

[0621] Example prompt:

[0622] markdown

[0623] To propose an interior design for a room, upload a photo of your store and propose a new design using a modern style and warm color palette. Your budget is ¥200,000.

[0624] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0625] Step 1:

[0626] A user takes a photo of a room or store using a smartphone and uploads the photo to the system via the application. The input data is the photo taken with the smartphone, and this photo is sent to the system.

[0627] Step 2:

[0628] The server receives photos uploaded by users. It uses OpenCV to preprocess (resize, filter, etc.) the received photo data and prepares it for analysis. The output is image data converted into an analyzable format.

[0629] Step 3:

[0630] The server uses an AI model (e.g., ImageAI's ResNet) to analyze the preprocessed image data. This analysis extracts the room or store layout, existing furniture, color, and lighting arrangement. The input data is the preprocessed image, and the output data is metadata describing the physical characteristics.

[0631] Step 4:

[0632] Through a smartphone application, users input their preferred design style (e.g., modern, classic, minimal, etc.), color palette, budget, etc. The input data is the user's preference information and is sent to the server.

[0633] Step 5:

[0634] The server combines the received user preference information with the analyzed physical feature data. Using AI algorithms, it generates personalized interior design proposals based on this data, including furniture placement, wall color, lighting selection, and curtains. The output data is a design proposal based on the user's preferences and the room's features.

[0635] Step 6:

[0636] The server creates a 3D model of the generated design proposal. It uses Trimesh and OpenGL to represent the design proposal in three dimensions. The input data is the design proposal, and the output data is the 3D model.

[0637] Step 7:

[0638] The server sends the generated 3D model to the user's device and displays it within the application. The user can visually check this 3D model and make changes as needed. The input data is the 3D model, and the output data is the interface that the user can view and edit.

[0639] Step 8:

[0640] Users can adjust the settings of the 3D model in real time within the application. For example, if they change the furniture arrangement or wall color, the changes are immediately reflected in the 3D model. The input data are the user's changes, and the output data is the updated 3D model.

[0641] Through these steps, the system of the present invention provides users with personalized interior design proposals and realizes advanced design simulations that can also be applied to virtual stores.

[0642] 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.

[0643] The interior design proposal system of the present invention analyzes photos of rooms provided by users, generates personalized interior designs based on the user's preferences and emotions, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[0644] System Overview

[0645] 1. Upload a photo

[0646] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[0647] 2. Receiving and analyzing photos

[0648] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[0649] 3. Collecting user preference information

[0650] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[0651] 4. User Emotion Recognition

[0652] The terminal and server are equipped with an emotion engine for analyzing the user's emotions, which evaluates the user's current emotional state in real time through facial expression recognition and text analysis.

[0653] 5. Generate design proposals

[0654] The server integrates the results of the room analysis, the user's preference information, and the user's emotional state to generate personalized interior design proposals. The proposals are dynamically adjusted based on the information from the emotion engine, providing a design that suits the user's mood. The server also selects optimal products within the user's budget.

[0655] 6. Generating and displaying 3D models

[0656] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in virtual space and make any necessary changes.

[0657] Program implementation example

[0658] 1. Upload a photo

[0659] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[0660] Examples:

[0661] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[0662] 2. Receiving and analyzing photos

[0663] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[0664] Examples:

[0665] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[0666] 3. Collecting user preference information

[0667] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[0668] Examples:

[0669] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[0670] 4. User Emotion Recognition

[0671] The device captures the user's facial expressions with a camera, and the emotion engine analyzes them. It also determines the user's emotional state through questionnaires and text input.

[0672] Examples:

[0673] The emotion engine recognizes that User A is in a calm mood through facial expression analysis, and also determines from text input that he or she desires a relaxed atmosphere.

[0674] 5. Generate design proposals

[0675] The server generates interior design suggestions based on the photo analysis results, the user's preference information, and data from the emotion engine. For example, if the user is in a relaxed emotional state, a design with calming colors will be suggested.

[0676] Examples:

[0677] The server proposes a modern interior design with calm tones to User A. Furniture and decorations that can be purchased within the user's budget are also selected.

[0678] 6. Generating and displaying 3D models

[0679] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[0680] Examples:

[0681] User A opens the app, checks the 3D model, and confirms that the proposed design is in line with the relaxing atmosphere. Even if they change the sofa position or wall color, it is updated on the fly.

[0682] The system of the present invention proposes interior design ideas that take the user's emotions into consideration, which has the effect of increasing the user's psychological satisfaction, allowing the user to effectively coordinate the interior of their home without the help of a professional.

[0683] The processing flow will be explained below.

[0684] Step 1:

[0685] Users take photos of their rooms with their smartphones, including the living room, bedroom, kitchen, and other rooms they need.

[0686] Step 2:

[0687] The device displays the captured photos to the user, allowing them to be selected. The user selects the photos to upload and presses the upload button.

[0688] Step 3:

[0689] The terminal uploads the photo files of the selected room to the server, where the uploaded photos are converted into a format that can be processed within the system.

[0690] Step 4:

[0691] The server receives the photos uploaded by the user and verifies that the photos received are correct.

[0692] Step 5:

[0693] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[0694] Step 6:

[0695] The server generates the analysis results and stores the information in a temporary file or database, which records the room's characteristics as data.

[0696] Step 7:

[0697] The device provides the user with an interface that prompts them to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[0698] Step 8:

[0699] The user selects a preferred design style and color palette, and presses the OK button to transmit the selection to the server.

[0700] Step 9:

[0701] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[0702] Step 10:

[0703] The device captures the user's facial expressions with a camera or the user inputs text, which is then sent to the server in real time.

[0704] Step 11:

[0705] The server uses an emotion engine that captures facial expressions and analyzes text to recognize the user's emotions and evaluate their state. This process determines whether the user is relaxed or excited.

[0706] Step 12:

[0707] The server combines the results of photo analysis, user preference information, and emotional data from an emotion engine to generate personalized interior design proposals. The proposals are dynamically adjusted based on the emotional data.

[0708] Step 13:

[0709] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed.

[0710] Step 14:

[0711] The server sends the 3D model to the device, where the user can view it and check the design.

[0712] Step 15:

[0713] The device displays the 3D model to the user in an interactive manner, allowing the user to examine the interior design in detail and make adjustments as needed.

[0714] Step 16:

[0715] Users can change the furniture placement, color, and design style while viewing the 3D model. Users can change the sofa position, wall color, and more in real time.

[0716] Step 17:

[0717] The device sends the user's changes to the server, which reflects them and updates the 3D model in real time.

[0718] Step 18:

[0719] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[0720] Step 19:

[0721] The server generates the final design and a list of required products and sends them to the terminal. The user can then review the final design and product list and obtain information for carrying out interior coordination.

[0722] Through these steps, the system of the present invention provides interior design suggestions that take the user's emotions into consideration, increasing the user's psychological satisfaction and enabling the user to effectively coordinate the interior of their home without the help of a professional.

[0723] Example 2

[0724] 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."

[0725] Conventional interior design proposal systems have difficulty providing personalized designs that take into account the user's preferences and emotional state. They also lack the ability to adjust designs in real time or select optimal products within a budget. This creates a need for systems that can increase user satisfaction and achieve effective interior coordination.

[0726] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0727] In this invention, the server includes means for receiving photos of a room taken by a user, means for analyzing the photos to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional information in real time, means for generating personalized interior design proposals based on the room's features and the user's preferences, and means for converting the interior design proposals into 3D models and displaying them to the user. This enables personalized design proposals tailored to the user's preferences and emotional state, increasing user satisfaction and facilitating effective interior coordination.

[0728] "User" refers to a person who uses the system and receives interior design suggestions.

[0729] A "terminal" refers to an electronic device that allows a user to access and operate the system, and examples include smartphones and personal computers.

[0730] "Server" refers to a computer that manages and processes data received from connected devices and provides the overall functionality of the system.

[0731] "Receiving a photo" refers to the process in which a user sends photo data of a room taken by the user to the server and the server receives the photo data.

[0732] "Photo analysis" refers to the process of using AI models to identify room layout, furniture placement, color, and lighting arrangement based on the photo data received by the server.

[0733] "Collecting user preferences" refers to the process of obtaining information about design styles and color palettes from users via their terminals.

[0734] "Emotional information analysis" refers to the process of assessing a user's emotional state in real time using the device's camera and text input.

[0735] "Generating interior design proposals" refers to the process in which the server constructs the optimal interior design for the user based on the results of photo analysis and the user's preferences and emotional information.

[0736] "3D modeling" refers to the creation of a three-dimensional representation of the generated interior design proposal, allowing users to visually confirm the design in a virtual space.

[0737] "Product selection within budget" refers to the process in which the server selects and recommends furniture and decorations that can be purchased within the budget set by the user.

[0738] "Design changes" refers to adjustments or modifications made by a user to a proposed interior design.

[0739] The interior design proposal system of the present invention is designed to analyze a room photo provided by a user, generate a personalized interior design based on the user's preferences and emotions, and provide it as a 3D model. The following specific hardware and software configurations are used to implement the present invention.

[0740] Hardware Configuration

[0741] 1. Terminal: The device that a user uses to interact with the system. Specific examples include smartphones, tablets, and personal computers.

[0742] 2. Server: A dedicated computer system that receives data, analyzes it, and generates design proposals.

[0743] Software Configuration

[0744] 1. Photo analysis module (AI model): Runs on the server and analyzes photos of rooms uploaded by users. It uses deep learning techniques to identify the room layout, furniture placement, color, and lighting location.

[0745] 2. Emotion Engine: Analyzes the user's facial expressions and text inputs to assess their emotional state in real time, using image recognition algorithms and natural language processing techniques.

[0746] 3. Interface application: Runs on the device and provides a GUI (graphical user interface) for users to upload photos, input design preferences, and provide emotional information.

[0747] 4. 3D modeling engine: Software that converts design proposals generated on the server into 3D models and displays them on the device.

[0748] Specific examples

[0749] For example, if a user wants to improve the interior design of their living room, they can take a photo of the room with their smartphone and upload it to the server through an application on their device. The application is simple to use; just select the photo and press the "upload" button.

[0750] The server analyzes the received photos and uses AI models to determine the room layout, sofa and table placement, wall color, and lighting location. The device then provides an interface that lets the user select a design style (e.g., modern, classic) and color palette. Once the user completes their selection, the information is sent to the server in real time.

[0751] Furthermore, the device's camera captures the user's facial expressions, and the emotion engine analyzes the user's mood (e.g., relaxed, calm). At the same time, the user can express their preferred mood through text input.

[0752] The server analyzes the photos, integrates the user's preferences and emotional data, and generates optimal interior design suggestions. Using a generative AI model, personalized designs are created based on the emotional data. For example, a modern design with calming colors is offered to match the emotional state of wanting to relax.

[0753] Finally, the server creates a 3D model of the generated design and sends it to the terminal. The user can then visually check the design in the virtual space and make any necessary changes. For example, they can adjust the position of the sofa or the color of the walls. In this way, the system of the present invention can provide the user with a satisfactory interior design proposal.

[0754] Examples of prompt statements

[0755] "Take a photo of your living room with the app and upload it."

[0756] "Choose your preferred design style, for example, modern or classic."

[0757] "Tell me how you're feeling right now. If you want to relax, type relax."

[0758] "View the proposed design in 3D and adjust any changes you want to make."

[0759] As a result, users can effectively coordinate the interior of their homes through the system.

[0760] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0761] Step 1:

[0762] The user takes a photo of the room and uploads it to the server via an application on the device.

[0763] Specifically, the user takes a photo of the room with their smartphone camera, clicks the "Select Photo" button in the app, selects the photo, and then presses the "Upload" button. This action sends the photo data to the server.

[0764] Input: A photo of the room taken with a camera

[0765] Output: Photo data sent to the server

[0766] Step 2:

[0767] The server analyzes the received photo data, and an AI model identifies the room layout, furniture placement, color, and lighting position.

[0768] Specifically, after the server receives the photo data, it launches the AI ​​analysis module and begins analysis, using a deep learning model to identify the sofa, table, wall color, and lighting position.

[0769] Input: Photo data uploaded by the user to the server

[0770] Output: Analyzed room layout, furniture placement, color, and lighting location information

[0771] Step 3:

[0772] The device collects the user's design preferences (style, color palette) and sends them to the server.

[0773] Specifically, the user operates the device interface, selects a modern style or warm color palette, presses the "OK" button, and sends the selection to the server.

[0774] Input: User-selected design style and color palette

[0775] Output: User's design preference information sent to the server

[0776] Step 4:

[0777] The device collects the user's real-time emotional information, which is then analyzed by the server's emotion engine.

[0778] Specifically, the device's camera captures the user's facial expressions, and the emotion engine analyzes them. Emotional information is also supplemented by questionnaire and text input.

[0779] Input: User's facial expressions, questionnaire input, text input

[0780] Output: Real-time emotional state information of the user

[0781] Step 5:

[0782] The server integrates the results of photo analysis, user preferences, and emotional information to generate personalized interior design proposals.

[0783] Specifically, the AI ​​model creates an optimal design based on the analysis results and the user's preferences, and generates a proposal. At the same time, it also takes into account the user's emotional information and adjusts the color tone and style of the design.

[0784] Input: Photo analysis results, user's design style and color palette, emotional state information

[0785] Output: Personalized interior design proposals

[0786] Step 6:

[0787] The server converts the generated interior design proposal into a 3D model and sends it to the terminal.

[0788] Specifically, the server-side 3D modeling engine converts the proposed design into a 3D model and sends it to the device, where the user can view the 3D model within the application and interactively modify it as needed.

[0789] Input: Generated interior design proposal

[0790] Output: 3D model data displayed on the device

[0791] (Application example 2)

[0792] 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."

[0793] Conventional interior design systems propose designs based on the user's preferences and room layout, but they have the problem of being unable to take into account the user's current emotional state. Furthermore, they lack a means to visualize the proposed design concretely or to confirm whether the selected products are within the user's budget. Therefore, a system that can propose appropriate interior designs while enhancing the user's psychological satisfaction and respecting financial constraints is needed.

[0794] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a room photo taken by a user, means for analyzing the photo to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional state, means for generating personalized interior design proposals based on the room's features, the user's preferences, and the user's emotional state, and means for creating a 3D model of the interior design proposal and displaying it to the user. This enables interior design proposals that take the user's current emotional state into consideration. Furthermore, the server can select and visually confirm optimal products within the user's budget, making it possible to provide proposals that fit within economic constraints.

[0795] A "user" is someone who uses the system to receive interior design proposals.

[0796] The "means for receiving photos" is a function for receiving photos of the room taken by the user and uploaded to the system.

[0797] "Means for analyzing and recognizing room features, existing furniture, colors, and lighting arrangements" refers to a function that uses digital image analysis technology to analyze received photos and identify the room layout, installed objects, colors, and lighting locations.

[0798] "Means for collecting information about a user's preferred design style and color palette" refers to a function that records and collects design style and color preferences input by a user through an interface.

[0799] The "means for analyzing the user's emotional state" is a function that analyzes the user's facial expressions and input text and evaluates the user's emotions in real time.

[0800] The "means for generating personalized interior design proposals" is a function that creates an interior design suited to each user based on the room's characteristics, the user's preferences, and their emotional state.

[0801] "Means for creating a 3D model of an interior design proposal and displaying it to the user" refers to a function that uses three-dimensional modeling technology to create a model of the generated design proposal and display it so that the user can visually confirm it.

[0802] "Means to select the best products within a budget" is a function that selects furniture and decoration items that can be purchased within a price range set by the user.

[0803] "Means for making changes to the proposed design" refers to a function that allows the user to make changes to the initial design proposal, such as changes to the position or color.

[0804] This interior design proposal system provides users with personalized designs through the following series of steps: The entire system is composed mainly of user terminals (mainly smartphones) and a server.

[0805] First, the user takes a photo of their room with their smartphone and uploads it to the server through an application on their device. The user uses an interface that allows them to easily upload photos. The server receives the photo uploaded by the user and analyzes it using an AI model. Specifically, it recognizes the room layout, furniture type and placement, color, lighting arrangement, etc.

[0806] The device then provides an interface for the user to input their preferences, such as design style and color palette. The information entered by the user is sent to the server and stored. At the same time, the device's camera captures the user's facial expressions, and an emotion engine is used to analyze the user's emotional state in real time. This emotion information is also sent to the server.

[0807] The server combines the results of photo analysis, the user's preferences, and their emotional state, and uses a generative AI model to generate personalized interior design suggestions. If the user's emotional state indicates a desire for relaxation, designs with calming colors and soft lighting will be suggested. Additionally, products that are affordable within the user's budget are selected.

[0808] The generated interior design proposal is converted into a 3D model on the server and sent to the device. The user can use the device application to visually check this 3D model and make changes as needed. For example, if they change the proposed sofa position or wall color, it will be updated on the fly.

[0809] The main hardware used includes the user's smartphone and a server, and the main software includes an AI model, an emotion engine, and a 3D modeling tool, which uses the EmotionRecognition library.

[0810] For example, user A takes a photo of their living room, selects a modern style and a warm color palette using the app, and recognizes their emotional state of wanting to relax through facial expression analysis. Based on this data, the server proposes a relaxing, modern interior design and displays it to user A as a 3D model.

[0811] An example of a prompt for a generative AI model is as follows:

[0812] "Please suggest an interior design for a living room. The user's preference is for a modern style with a warm color palette. The user also wants to feel relaxed. The budget is ¥100,000."

[0813] This allows the system to provide optimal interior design within a budget, taking into account the user's current emotional state.

[0814] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0815] Step 1:

[0816] The user takes a photo of the room and uploads it to the server through the device application. Specifically, the user takes a photo of the room using the smartphone camera and taps the upload button in the app. The input is the photo data of the room, and the photo is sent to the server as the output.

[0817] Step 2:

[0818] The server analyzes the received photos using an AI model. Specifically, the server inputs the photo data, and the AI ​​model recognizes the room layout, furniture type and placement, color, and lighting position. As a result of the analysis, these attributes are identified and output as data.

[0819] Step 3:

[0820] The user inputs their preferred design style and color palette using a terminal application. The terminal receives this through an interface and sends it to the server. The input is the user's preference information, and the output is recorded on the server.

[0821] Step 4:

[0822] The device's camera captures the user's facial expressions, which are then analyzed by the emotion engine. Specifically, the EmotionRecognition library identifies the user's emotions in real time and sends the results to the server. The input is the captured facial expression data, and the output is the analyzed emotional information.

[0823] Step 5:

[0824] The server integrates the photo analysis results, user preference information, and emotional information, and uses a generative AI model to generate personalized interior design proposals. Specifically, this data is input into the AI ​​model as prompts to generate the proposed design. The input is the integrated data, and the output is the design proposal.

[0825] Step 6:

[0826] The server creates a 3D model of the interior design proposal and sends it to the device. Specifically, it uses a 3D modeling tool to create a three-dimensional design. The input is the design proposal, and the output is the 3D model data.

[0827] Step 7:

[0828] The user can view the 3D model in the terminal application and make changes as needed. As the user makes changes, the data is sent from the terminal to the server, and the 3D model is updated in real time. The input is the user's changes, and the output is the updated 3D model.

[0829] This series of steps provides a visually verifiable interior design that takes into account the user's preferences and emotions, thereby increasing user satisfaction.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] [Third embodiment]

[0834] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0835] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0836] 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).

[0837] 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.

[0838] 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.

[0839] 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).

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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."

[0846] The interior design proposal system of the present invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[0847] System Overview

[0848] 1. Upload a photo

[0849] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[0850] 2. Receiving and analyzing photos

[0851] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[0852] 3. Collecting user preference information

[0853] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[0854] 4. Generate design proposals

[0855] The server combines the room analysis results with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting options, curtains, etc. It also selects optimal products within the user's budget.

[0856] 5. 3D Model Generation and Display

[0857] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in a virtual space and make any necessary changes.

[0858] Program implementation example

[0859] 1. Upload a photo

[0860] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[0861] Examples:

[0862] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[0863] 2. Receiving and analyzing photos

[0864] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[0865] Examples:

[0866] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[0867] 3. Collecting user preference information

[0868] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[0869] Examples:

[0870] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[0871] 4. Generate design proposals

[0872] The server generates interior design proposals based on the results of photo analysis and the user's preferences, and also selects the best products based on the user's budget.

[0873] Examples:

[0874] The server generates suggestions for user A, such as a modern sofa and an orange accent wall, and selects furniture that can be purchased within the user's budget.

[0875] 5. 3D Model Generation and Display

[0876] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[0877] Examples:

[0878] When User A opens the app, checks the 3D model, and changes the sofa position or wall color, it is updated in real time.

[0879] As described above, the system of the present invention provides a means for users to easily find and realize interior designs that suit their tastes, allowing users to easily coordinate the interior of their home without the help of a professional.

[0880] The processing flow will be explained below.

[0881] Step 1:

[0882] The user takes a photo of their room. The user uses a smartphone or a digital camera to take a photo of a room such as a living room, bedroom, or kitchen.

[0883] Step 2:

[0884] The device displays the photos that have been taken so that the user can select them. The user selects a photo on the device screen and presses the upload button.

[0885] Step 3:

[0886] The terminal uploads a photo of the selected room to the server, where it is converted into a format that can be processed within the system.

[0887] Step 4:

[0888] The server receives the photos uploaded by the user and verifies that the photos were received correctly.

[0889] Step 5:

[0890] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[0891] Step 6:

[0892] The server generates the analysis results and stores the information in a temporary file or database, thereby recording the room's characteristics as data.

[0893] Step 7:

[0894] The terminal displays an interface for the user to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[0895] Step 8:

[0896] The user selects a preferred design style and color palette and performs an operation to transmit that information to the system.

[0897] Step 9:

[0898] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[0899] Step 10:

[0900] The server combines the results of photo analysis with user preference information, and generates personalized interior design suggestions based on this information.

[0901] Step 11:

[0902] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed by the user.

[0903] Step 12:

[0904] The server generates a 3D model and sends it to the device, where the user can view the model.

[0905] Step 13:

[0906] The device displays the 3D model to the user and provides an interactive interface, allowing the user to examine the proposed design in detail.

[0907] Step 14:

[0908] Users can make changes to the layout and design while viewing the 3D model, such as changing the sofa position or wall color.

[0909] Step 15:

[0910] The device sends the user's changes to the server, which then reflects the changes in real time and updates the 3D model.

[0911] Step 16:

[0912] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[0913] Step 17:

[0914] The server generates the final design and a list of necessary products and sends them to the terminal, which the user can use to coordinate the interior.

[0915] Through these steps, the system of the present invention proposes an optimal interior design for the user's room and helps the user to easily realize it.

[0916] Example 1

[0917] 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."

[0918] Conventional interior design systems have difficulty efficiently generating design proposals based on a user's individual preferences. Even when a user sets a budget, the system lacks the functionality to select the optimal product within that budget. Furthermore, the system lacks an interface that allows users to make changes to the proposed design, which can lead to reduced user satisfaction.

[0919] 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.

[0920] In this invention, the server includes means for receiving images of a space taken by a user, means for analyzing the images to recognize the layout of the space, existing fixtures, colors, and lighting arrangement, means for collecting information regarding the user's preferred design style and color selection, means for generating a personalized interior design proposal, means for creating a three-dimensional model of the interior design proposal and displaying it to the user, means for selecting optimal products within a user-specified budget, and means for the user to make changes to the proposed design. This allows the server to generate personalized interior design proposals that meet the user's individual preferences, provide optimal products within a user's budget, and enable the user to make changes to the design in real time.

[0921] A "user" is an individual or corporation that uses the system to request an interior design for their space.

[0922] A "space image" is a photograph or image data taken by a user that shows the interior scenery or layout of a room.

[0923] "Means for receiving" refers to the function of importing image data uploaded by users via the Internet into a server.

[0924] The "means of analysis" refers to algorithms or software that process the received image data and recognize the spatial layout, type and placement of fixtures, colors, lighting position, etc.

[0925] "Fixtures" refers to furniture and interior items placed in a room.

[0926] "Color" refers to the various color combinations and color schemes that exist within a space.

[0927] "Lighting arrangement" refers to the location of lighting fixtures within a space and the distribution of light they provide.

[0928] "Design style" is a concept that describes the overall theme or aesthetic of an interior design, and examples include modern, classic, and minimalist.

[0929] "Color selection" refers to the user's preferred color palette or color combination.

[0930] "Individualized interior design proposal" means an interior design plan that is customized based on the user's preferences and the characteristics of the space.

[0931] "3D modeling" refers to the process of digitally representing a design proposal as a three-dimensional visual model.

[0932] "Displaying means" refers to software and hardware functions for displaying the generated three-dimensional model on the user's terminal.

[0933] "Budget" refers to the total amount of money the user can spend on the interior design.

[0934] "Product selection tools" are algorithms and system functions that select the best furniture and interior items within the user's budget.

[0935] "Means for making changes" refers to the interface and functionality that allows a user to make corrections or adjustments to the proposed design.

[0936] The interior design proposal system of the present invention analyzes images of spaces provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as three-dimensional models. Specific technical means and operational examples of the present invention are described below.

[0937] Hardware and Software Configuration

[0938] Users take images of the room using a device such as a smartphone or tablet. A dedicated application is installed on the device, and the user uploads the images to the server through this application. The server receives and stores the image data via the internet. The AI ​​models used include TensorFlow and PyTorch, and Blender and Unity for 3D modeling. These software programs are used within the server to generate design proposals and create 3D models.

[0939] Program processing flow

[0940] When the server receives images uploaded by users, it uses an AI model to analyze them. Specifically, it recognizes the spatial layout, fixture types and placement, colors, and lighting position from the received images. The results of this analysis later become the basis for generating design proposals.

[0941] The device then collects information about the user's preferred design style and color choices through the interface. This information is sent to the server and stored along with the analysis results. For example, if a user selects a modern style and a warm color palette, that information is sent to the server.

[0942] The server uses a generative AI model (e.g., OpenAI GPT-4) to generate interior design proposals based on the analyzed image data and the user's preferences. These proposals include new fixture placement, wall color, lighting selection, curtains, etc. The server also selects optimal products within the user's budget. These design proposals are then converted into 3D models. For example, the server may generate a proposal for User A, such as a modern sofa and an orange accent wall, and select furniture that can be purchased within the user's budget.

[0943] The generated 3D model is sent from the server to the device, where the user can visually check the design in the virtual space. The dedicated application allows the user to make changes to the displayed 3D model, and the changes are reflected in real time. For example, if User A changes the position of a sofa in the app, the changes are immediately reflected in the 3D model.

[0944] Prompt Sentence Examples

[0945] "Analyze a photo of a living room and suggest a modern interior design. Use a warm color palette and choose the best furniture for the user's budget."

[0946] The above is a concrete example of the technical means and operation of the interior design suggestion system of the present invention. This system allows users to easily find and realize an interior design that suits their tastes.

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

[0948] Step 1:

[0949] A user takes a picture of their room with their smartphone and uploads it to the device's application. Specifically, the user selects the image they took from the gallery and presses the "upload" button. This operation causes the image data to be sent to the server by the application.

[0950] Input: A room image taken with a smartphone

[0951] Output: Image data sent to the server

[0952] Step 2:

[0953] The server receives images uploaded by users and saves the received data in a specified folder.

[0954] Input: Uploaded image data

[0955] Output: Saved image file

[0956] Step 3:

[0957] The server inputs the received image data into an AI model (e.g., TensorFlow) for analysis. During the analysis process, image features are extracted and the spatial layout, fixture types and placement, colors, lighting position, etc. are recognized.

[0958] Input: Saved image file

[0959] Output: Analysis results including spatial layout, fixture types and placement, color, and lighting position

[0960] Step 4:

[0961] The device provides a user with an interface to collect information about interior design preferences, where the user inputs design styles (e.g., modern, classic, minimalist) and color preferences (e.g., warm, cool), which are then transmitted to a server in real time.

[0962] Input: User's preferred design style and color selection

[0963] Output: User preference data sent to the server

[0964] Step 5:

[0965] The server combines the received user preference data with the results of the image analysis. It then uses a generative AI model (e.g., OpenAI GPT-4) to generate personalized interior design suggestions. These suggestions include new fixture placement, wall colors, lighting choices, curtains, etc. It also selects the best products within the user's budget.

[0966] Input: User preference data and image analysis results

[0967] Output: personalized interior design suggestions and a list of optimal products

[0968] Step 6:

[0969] The server then creates a 3D model of the interior design proposal and sends it to the device using software such as Blender or Unity.

[0970] Input: personalized interior design proposals

[0971] Output: 3D model and its transmission data

[0972] Step 7:

[0973] The device displays the received 3D model data. The user can then view the 3D model within the application and make changes as needed. For example, if the user changes the position of a sofa or the color of a wall in the virtual space, the changes are reflected in real time.

[0974] Input: 3D model data

[0975] Output: User-visible interface and real-time changes

[0976] By following the above steps, users can easily find and realize an interior design that suits their tastes.

[0977] (Application example 1)

[0978] 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."

[0979] While conventional interior design proposal systems can generate personalized design proposals by analyzing photos taken by users, they lack specific functionality for simulating the interior design of virtual stores. In particular, they lack the functionality to automatically recognize the store layout, existing equipment, product placement, and lighting position, suggest optimal products based on the desired design style and budget, and make adjustments in real time. Therefore, a comprehensive design proposal system for virtual stores is needed.

[0980] 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.

[0981] In this invention, the server includes means for receiving photos of a room taken by a user, means for collecting information on the user's preferred design style and color palette, means for generating personalized interior design proposals based on the room's characteristics and the user's preferences, means for converting the interior design proposals into 3D models and displaying them to the user, means for simulating the interior design of a virtual store, means for analyzing uploaded photos to recognize the store's layout, existing equipment, product placement, and lighting location, means for inputting the desired design style and budget, means for proposing optimal products within the budget, and means for displaying the generated 3D model and allowing the user to make adjustments in real time. This enables advanced interior design proposals to be made in virtual stores without the need for specialized knowledge.

[0982] "User" means an individual or organization that uses the system to receive interior design proposals.

[0983] A "photo" is image data showing an image of the interior of a room or store taken by a user.

[0984] "Receiving" is the process by which the system takes in image data uploaded by the user.

[0985] "Analysis" is the process of using AI models and algorithms to extract characteristics of rooms or stores from image data.

[0986] "Room characteristics" refers to the physical characteristics of a room or store, such as its layout, structure, area, and wall color.

[0987] "Existing Furniture" means furniture and decor items that are already installed and are shown in the photograph.

[0988] "Color" refers to the color combinations used on the walls, floors, furniture, etc. of a room or store.

[0989] "Lighting arrangement" refers to the location and type of lighting fixtures in a room or store, and their placement.

[0990] "Design style" refers to the overall interior theme or aesthetic preferred by a user, including modern, classic, minimalist, etc.

[0991] A "color palette" refers to a particular combination of colors that a user prefers.

[0992] "Personalization" is the process of applying a specific design based on a user's individual preferences and requirements.

[0993] "Interior design proposal" refers to a new design plan that reflects the analysis results and the user's preferences.

[0994] A "3D model" is data that represents an interior design proposal in three dimensions.

[0995] A "virtual store" refers to a store model built in a digital space.

[0996] "Simulation" is the process of replicating a real-world design in a virtual environment.

[0997] "Layout" refers to the physical arrangement and structure of the interior of a store or room.

[0998] "Existing Installations" means pre-installed lighting fixtures and fixtures.

[0999] "Product placement" refers to the location of products and displays within a store.

[1000] "Budget" is the amount of money the user prepares for interior design.

[1001] "Optimal products" are the best furniture and interior items selected based on the user's preferences and budget.

[1002] "Real-time" means immediate response and changes are implemented without any time delay.

[1003] The interior design proposal system of this invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. This system can also be applied to virtual stores.

[1004] System configuration and operation method

[1005] 1. Upload a photo

[1006] Users use their smartphones to take photos of their rooms or stores and then upload them to the system through the application, which uses a simple interface.

[1007] 2. Receiving and analyzing photos

[1008] The server receives photos uploaded by users, which are then analyzed using an AI model (such as ImageAI's ResNet). This analysis process recognizes the room layout, existing furniture, color scheme, and lighting arrangement.

[1009] 3. Collecting user preference information

[1010] The terminal provides the user with an interface where they can input information such as their desired design style, preferred color palette, budget, etc. This information is then sent to the server.

[1011] 4. Generate design proposals

[1012] The server combines the results of photo analysis with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting choices, curtain designs, etc. It also selects optimal products within the user's budget.

[1013] 5. 3D Model Generation and Display

[1014] The server then converts the generated interior design proposal into a 3D model and sends it to the user's device for display, allowing the user to visually check the design in a virtual space and make changes as needed.

[1015] Hardware and software used

[1016] Hardware:

[1017] Smartphone (for taking photos and operating applications)

[1018] Server (for photo analysis and design proposal generation)

[1019] software:

[1020] AI models (such as ImageAI's ResNet)

[1021] OpenCV (for image analysis)

[1022] Trimesh and OpenGL (for 3D model generation and display)

[1023] Specific examples

[1024] Consider a scenario in which a user wants to update the design of a virtual store. The user takes a photo of the interior using the camera on their smartphone. They then open the application and upload the photo. Next, the user selects "modern" as the desired design style, "warm" as the color palette, and enters a budget of ¥200,000. The server analyzes the uploaded photo and generates a new interior design based on it. The generated design is displayed as a 3D model, which the user can view in real time and make further adjustments. Finally, the user can review the details of the new design and purchase appropriate products within their budget.

[1025] Example prompt:

[1026] markdown

[1027] To propose an interior design for a room, upload a photo of your store and propose a new design using a modern style and warm color palette. Your budget is ¥200,000.

[1028] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1029] Step 1:

[1030] A user takes a photo of a room or store using a smartphone and uploads the photo to the system via the application. The input data is the photo taken with the smartphone, and this photo is sent to the system.

[1031] Step 2:

[1032] The server receives photos uploaded by users. It uses OpenCV to preprocess (resize, filter, etc.) the received photo data and prepares it for analysis. The output is image data converted into an analyzable format.

[1033] Step 3:

[1034] The server uses an AI model (e.g., ImageAI's ResNet) to analyze the preprocessed image data. This analysis extracts the room or store layout, existing furniture, color, and lighting arrangement. The input data is the preprocessed image, and the output data is metadata describing the physical characteristics.

[1035] Step 4:

[1036] Through a smartphone application, users input their preferred design style (e.g., modern, classic, minimal, etc.), color palette, budget, etc. The input data is the user's preference information and is sent to the server.

[1037] Step 5:

[1038] The server combines the received user preference information with the analyzed physical feature data. Using AI algorithms, it generates personalized interior design proposals based on this data, including furniture placement, wall color, lighting selection, and curtains. The output data is a design proposal based on the user's preferences and the room's features.

[1039] Step 6:

[1040] The server creates a 3D model of the generated design proposal. It uses Trimesh and OpenGL to represent the design proposal in three dimensions. The input data is the design proposal, and the output data is the 3D model.

[1041] Step 7:

[1042] The server sends the generated 3D model to the user's device and displays it within the application. The user can visually check this 3D model and make changes as needed. The input data is the 3D model, and the output data is the interface that the user can view and edit.

[1043] Step 8:

[1044] Users can adjust the settings of the 3D model in real time within the application. For example, if they change the furniture arrangement or wall color, the changes are immediately reflected in the 3D model. The input data are the user's changes, and the output data is the updated 3D model.

[1045] Through these steps, the system of the present invention provides users with personalized interior design proposals and realizes advanced design simulations that can also be applied to virtual stores.

[1046] 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.

[1047] The interior design proposal system of the present invention analyzes photos of rooms provided by users, generates personalized interior designs based on the user's preferences and emotions, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[1048] System Overview

[1049] 1. Upload a photo

[1050] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[1051] 2. Receiving and analyzing photos

[1052] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[1053] 3. Collecting user preference information

[1054] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[1055] 4. User Emotion Recognition

[1056] The terminal and server are equipped with an emotion engine for analyzing the user's emotions, which evaluates the user's current emotional state in real time through facial expression recognition and text analysis.

[1057] 5. Generate design proposals

[1058] The server integrates the results of the room analysis, the user's preference information, and the user's emotional state to generate personalized interior design proposals. The proposals are dynamically adjusted based on the information from the emotion engine, providing a design that suits the user's mood. The server also selects optimal products within the user's budget.

[1059] 6. Generating and displaying 3D models

[1060] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in virtual space and make any necessary changes.

[1061] Program implementation example

[1062] 1. Upload a photo

[1063] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[1064] Examples:

[1065] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[1066] 2. Receiving and analyzing photos

[1067] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[1068] Examples:

[1069] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[1070] 3. Collecting user preference information

[1071] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[1072] Examples:

[1073] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[1074] 4. User Emotion Recognition

[1075] The device captures the user's facial expressions with a camera, and the emotion engine analyzes them. It also determines the user's emotional state through questionnaires and text input.

[1076] Examples:

[1077] The emotion engine recognizes that User A is in a calm mood through facial expression analysis, and also determines from text input that he or she desires a relaxed atmosphere.

[1078] 5. Generate design proposals

[1079] The server generates interior design suggestions based on the photo analysis results, the user's preference information, and data from the emotion engine. For example, if the user is in a relaxed emotional state, a design with calming colors will be suggested.

[1080] Examples:

[1081] The server proposes a modern interior design with calm tones to User A. Furniture and decorations that can be purchased within the user's budget are also selected.

[1082] 6. Generating and displaying 3D models

[1083] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[1084] Examples:

[1085] User A opens the app, checks the 3D model, and confirms that the proposed design is in line with the relaxing atmosphere. Even if they change the sofa position or wall color, it is updated on the fly.

[1086] The system of the present invention proposes interior design ideas that take the user's emotions into consideration, which has the effect of increasing the user's psychological satisfaction, allowing the user to effectively coordinate the interior of their home without the help of a professional.

[1087] The processing flow will be explained below.

[1088] Step 1:

[1089] Users take photos of their rooms with their smartphones, including the living room, bedroom, kitchen, and other rooms they need.

[1090] Step 2:

[1091] The device displays the captured photos to the user, allowing them to be selected. The user selects the photos to upload and presses the upload button.

[1092] Step 3:

[1093] The terminal uploads the photo files of the selected room to the server, where the uploaded photos are converted into a format that can be processed within the system.

[1094] Step 4:

[1095] The server receives the photos uploaded by the user and verifies that the photos received are correct.

[1096] Step 5:

[1097] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[1098] Step 6:

[1099] The server generates the analysis results and stores the information in a temporary file or database, which records the room's characteristics as data.

[1100] Step 7:

[1101] The device provides the user with an interface that prompts them to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[1102] Step 8:

[1103] The user selects a preferred design style and color palette, and presses the OK button to transmit the selection to the server.

[1104] Step 9:

[1105] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[1106] Step 10:

[1107] The device captures the user's facial expressions with a camera or the user inputs text, which is then sent to the server in real time.

[1108] Step 11:

[1109] The server uses an emotion engine that captures facial expressions and analyzes text to recognize the user's emotions and evaluate their state. This process determines whether the user is relaxed or excited.

[1110] Step 12:

[1111] The server combines the results of photo analysis, user preference information, and emotional data from an emotion engine to generate personalized interior design proposals. The proposals are dynamically adjusted based on the emotional data.

[1112] Step 13:

[1113] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed.

[1114] Step 14:

[1115] The server sends the 3D model to the device, where the user can view it and check the design.

[1116] Step 15:

[1117] The device displays the 3D model to the user in an interactive manner, allowing the user to examine the interior design in detail and make adjustments as needed.

[1118] Step 16:

[1119] Users can change the furniture placement, color, and design style while viewing the 3D model. Users can change the sofa position, wall color, and more in real time.

[1120] Step 17:

[1121] The device sends the user's changes to the server, which reflects them and updates the 3D model in real time.

[1122] Step 18:

[1123] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[1124] Step 19:

[1125] The server generates the final design and a list of required products and sends them to the terminal. The user can then review the final design and product list and obtain information for carrying out interior coordination.

[1126] Through these steps, the system of the present invention provides interior design suggestions that take the user's emotions into consideration, increasing the user's psychological satisfaction and enabling the user to effectively coordinate the interior of their home without the help of a professional.

[1127] Example 2

[1128] 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."

[1129] Conventional interior design proposal systems have difficulty providing personalized designs that take into account the user's preferences and emotional state. They also lack the ability to adjust designs in real time or select optimal products within a budget. This creates a need for systems that can increase user satisfaction and achieve effective interior coordination.

[1130] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1131] In this invention, the server includes means for receiving photos of a room taken by a user, means for analyzing the photos to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional information in real time, means for generating personalized interior design proposals based on the room's features and the user's preferences, and means for converting the interior design proposals into 3D models and displaying them to the user. This enables personalized design proposals tailored to the user's preferences and emotional state, increasing user satisfaction and facilitating effective interior coordination.

[1132] "User" refers to a person who uses the system and receives interior design suggestions.

[1133] A "terminal" refers to an electronic device that allows a user to access and operate the system, and examples include smartphones and personal computers.

[1134] "Server" refers to a computer that manages and processes data received from connected devices and provides the overall functionality of the system.

[1135] "Receiving a photo" refers to the process in which a user sends photo data of a room taken by the user to the server and the server receives the photo data.

[1136] "Photo analysis" refers to the process of using AI models to identify room layout, furniture placement, color, and lighting arrangement based on the photo data received by the server.

[1137] "Collecting user preferences" refers to the process of obtaining information about design styles and color palettes from users via their terminals.

[1138] "Emotional information analysis" refers to the process of assessing a user's emotional state in real time using the device's camera and text input.

[1139] "Generating interior design proposals" refers to the process in which the server constructs the optimal interior design for the user based on the results of photo analysis and the user's preferences and emotional information.

[1140] "3D modeling" refers to the creation of a three-dimensional representation of the generated interior design proposal, allowing users to visually confirm the design in a virtual space.

[1141] "Product selection within budget" refers to the process in which the server selects and recommends furniture and decorations that can be purchased within the budget set by the user.

[1142] "Design changes" refers to adjustments or modifications made by a user to a proposed interior design.

[1143] The interior design proposal system of the present invention is designed to analyze a room photo provided by a user, generate a personalized interior design based on the user's preferences and emotions, and provide it as a 3D model. The following specific hardware and software configurations are used to implement the present invention.

[1144] Hardware Configuration

[1145] 1. Terminal: The device that a user uses to interact with the system. Specific examples include smartphones, tablets, and personal computers.

[1146] 2. Server: A dedicated computer system that receives data, analyzes it, and generates design proposals.

[1147] Software Configuration

[1148] 1. Photo analysis module (AI model): Runs on the server and analyzes photos of rooms uploaded by users. It uses deep learning techniques to identify the room layout, furniture placement, color, and lighting location.

[1149] 2. Emotion Engine: Analyzes the user's facial expressions and text inputs to assess their emotional state in real time, using image recognition algorithms and natural language processing techniques.

[1150] 3. Interface application: Runs on the device and provides a GUI (graphical user interface) for users to upload photos, input design preferences, and provide emotional information.

[1151] 4. 3D modeling engine: Software that converts design proposals generated on the server into 3D models and displays them on the device.

[1152] Specific examples

[1153] For example, if a user wants to improve the interior design of their living room, they can take a photo of the room with their smartphone and upload it to the server through an application on their device. The application is simple to use; just select the photo and press the "upload" button.

[1154] The server analyzes the received photos and uses AI models to determine the room layout, sofa and table placement, wall color, and lighting location. The device then provides an interface that lets the user select a design style (e.g., modern, classic) and color palette. Once the user completes their selection, the information is sent to the server in real time.

[1155] Furthermore, the device's camera captures the user's facial expressions, and the emotion engine analyzes the user's mood (e.g., relaxed, calm). At the same time, the user can express their preferred mood through text input.

[1156] The server analyzes the photos, integrates the user's preferences and emotional data, and generates optimal interior design suggestions. Using a generative AI model, personalized designs are created based on the emotional data. For example, a modern design with calming colors is offered to match the emotional state of wanting to relax.

[1157] Finally, the server creates a 3D model of the generated design and sends it to the terminal. The user can then visually check the design in the virtual space and make any necessary changes. For example, they can adjust the position of the sofa or the color of the walls. In this way, the system of the present invention can provide the user with a satisfactory interior design proposal.

[1158] Examples of prompt statements

[1159] "Take a photo of your living room with the app and upload it."

[1160] "Choose your preferred design style, for example, modern or classic."

[1161] "Tell me how you're feeling right now. If you want to relax, type relax."

[1162] "View the proposed design in 3D and adjust any changes you want to make."

[1163] As a result, users can effectively coordinate the interior of their homes through the system.

[1164] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1165] Step 1:

[1166] The user takes a photo of the room and uploads it to the server via an application on the device.

[1167] Specifically, the user takes a photo of the room with their smartphone camera, clicks the "Select Photo" button in the app, selects the photo, and then presses the "Upload" button. This action sends the photo data to the server.

[1168] Input: A photo of the room taken with a camera

[1169] Output: Photo data sent to the server

[1170] Step 2:

[1171] The server analyzes the received photo data, and an AI model identifies the room layout, furniture placement, color, and lighting position.

[1172] Specifically, after the server receives the photo data, it launches the AI ​​analysis module and begins analysis, using a deep learning model to identify the sofa, table, wall color, and lighting position.

[1173] Input: Photo data uploaded by the user to the server

[1174] Output: Analyzed room layout, furniture placement, color, and lighting location information

[1175] Step 3:

[1176] The device collects the user's design preferences (style, color palette) and sends them to the server.

[1177] Specifically, the user operates the device interface, selects a modern style or warm color palette, presses the "OK" button, and sends the selection to the server.

[1178] Input: User-selected design style and color palette

[1179] Output: User's design preference information sent to the server

[1180] Step 4:

[1181] The device collects the user's real-time emotional information, which is then analyzed by the server's emotion engine.

[1182] Specifically, the device's camera captures the user's facial expressions, and the emotion engine analyzes them. Emotional information is also supplemented by questionnaire and text input.

[1183] Input: User's facial expressions, questionnaire input, text input

[1184] Output: Real-time emotional state information of the user

[1185] Step 5:

[1186] The server integrates the results of photo analysis, user preferences, and emotional information to generate personalized interior design proposals.

[1187] Specifically, the AI ​​model creates an optimal design based on the analysis results and the user's preferences, and generates a proposal. At the same time, it also takes into account the user's emotional information and adjusts the color tone and style of the design.

[1188] Input: Photo analysis results, user's design style and color palette, emotional state information

[1189] Output: Personalized interior design proposals

[1190] Step 6:

[1191] The server converts the generated interior design proposal into a 3D model and sends it to the terminal.

[1192] Specifically, the server-side 3D modeling engine converts the proposed design into a 3D model and sends it to the device, where the user can view the 3D model within the application and interactively modify it as needed.

[1193] Input: Generated interior design proposal

[1194] Output: 3D model data displayed on the device

[1195] (Application example 2)

[1196] 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."

[1197] Conventional interior design systems propose designs based on the user's preferences and room layout, but they have the problem of being unable to take into account the user's current emotional state. Furthermore, they lack a means to visualize the proposed design concretely or to confirm whether the selected products are within the user's budget. Therefore, a system that can propose appropriate interior designs while enhancing the user's psychological satisfaction and respecting financial constraints is needed.

[1198] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a room photo taken by a user, means for analyzing the photo to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional state, means for generating personalized interior design proposals based on the room's features, the user's preferences, and the user's emotional state, and means for creating a 3D model of the interior design proposal and displaying it to the user. This enables interior design proposals that take the user's current emotional state into consideration. Furthermore, the server can select and visually confirm optimal products within the user's budget, making it possible to provide proposals that fit within economic constraints.

[1199] A "user" is someone who uses the system to receive interior design proposals.

[1200] The "means for receiving photos" is a function for receiving photos of the room taken by the user and uploaded to the system.

[1201] "Means for analyzing and recognizing room features, existing furniture, colors, and lighting arrangements" refers to a function that uses digital image analysis technology to analyze received photos and identify the room layout, installed objects, colors, and lighting locations.

[1202] "Means for collecting information about a user's preferred design style and color palette" refers to a function that records and collects design style and color preferences input by a user through an interface.

[1203] The "means for analyzing the user's emotional state" is a function that analyzes the user's facial expressions and input text and evaluates the user's emotions in real time.

[1204] The "means for generating personalized interior design proposals" is a function that creates an interior design suited to each user based on the room's characteristics, the user's preferences, and their emotional state.

[1205] "Means for creating a 3D model of an interior design proposal and displaying it to the user" refers to a function that uses three-dimensional modeling technology to create a model of the generated design proposal and display it so that the user can visually confirm it.

[1206] "Means to select the best products within a budget" is a function that selects furniture and decoration items that can be purchased within a price range set by the user.

[1207] "Means for making changes to the proposed design" refers to a function that allows the user to make changes to the initial design proposal, such as changes to the position or color.

[1208] This interior design proposal system provides users with personalized designs through the following series of steps: The entire system is composed mainly of user terminals (mainly smartphones) and a server.

[1209] First, the user takes a photo of their room with their smartphone and uploads it to the server through an application on their device. The user uses an interface that allows them to easily upload photos. The server receives the photo uploaded by the user and analyzes it using an AI model. Specifically, it recognizes the room layout, furniture type and placement, color, lighting arrangement, etc.

[1210] The device then provides an interface for the user to input their preferences, such as design style and color palette. The information entered by the user is sent to the server and stored. At the same time, the device's camera captures the user's facial expressions, and an emotion engine is used to analyze the user's emotional state in real time. This emotion information is also sent to the server.

[1211] The server combines the results of photo analysis, the user's preferences, and their emotional state, and uses a generative AI model to generate personalized interior design suggestions. If the user's emotional state indicates a desire for relaxation, designs with calming colors and soft lighting will be suggested. Additionally, products that are affordable within the user's budget are selected.

[1212] The generated interior design proposal is converted into a 3D model on the server and sent to the device. The user can use the device application to visually check this 3D model and make changes as needed. For example, if they change the proposed sofa position or wall color, it will be updated on the fly.

[1213] The main hardware used includes the user's smartphone and a server, and the main software includes an AI model, an emotion engine, and a 3D modeling tool, which uses the EmotionRecognition library.

[1214] For example, user A takes a photo of their living room, selects a modern style and a warm color palette using the app, and recognizes their emotional state of wanting to relax through facial expression analysis. Based on this data, the server proposes a relaxing, modern interior design and displays it to user A as a 3D model.

[1215] An example of a prompt for a generative AI model is as follows:

[1216] "Please suggest an interior design for a living room. The user's preference is for a modern style with a warm color palette. The user also wants to feel relaxed. The budget is ¥100,000."

[1217] This allows the system to provide optimal interior design within a budget, taking into account the user's current emotional state.

[1218] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1219] Step 1:

[1220] The user takes a photo of the room and uploads it to the server through the device application. Specifically, the user takes a photo of the room using the smartphone camera and taps the upload button in the app. The input is the photo data of the room, and the photo is sent to the server as the output.

[1221] Step 2:

[1222] The server analyzes the received photos using an AI model. Specifically, the server inputs the photo data, and the AI ​​model recognizes the room layout, furniture type and placement, color, and lighting position. As a result of the analysis, these attributes are identified and output as data.

[1223] Step 3:

[1224] The user inputs their preferred design style and color palette using a terminal application. The terminal receives this through an interface and sends it to the server. The input is the user's preference information, and the output is recorded on the server.

[1225] Step 4:

[1226] The device's camera captures the user's facial expressions, which are then analyzed by the emotion engine. Specifically, the EmotionRecognition library identifies the user's emotions in real time and sends the results to the server. The input is the captured facial expression data, and the output is the analyzed emotional information.

[1227] Step 5:

[1228] The server integrates the photo analysis results, user preference information, and emotional information, and uses a generative AI model to generate personalized interior design proposals. Specifically, this data is input into the AI ​​model as prompts to generate the proposed design. The input is the integrated data, and the output is the design proposal.

[1229] Step 6:

[1230] The server creates a 3D model of the interior design proposal and sends it to the device. Specifically, it uses a 3D modeling tool to create a three-dimensional design. The input is the design proposal, and the output is the 3D model data.

[1231] Step 7:

[1232] The user can view the 3D model in the terminal application and make changes as needed. As the user makes changes, the data is sent from the terminal to the server, and the 3D model is updated in real time. The input is the user's changes, and the output is the updated 3D model.

[1233] This series of steps provides a visually verifiable interior design that takes into account the user's preferences and emotions, thereby increasing user satisfaction.

[1234] 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.

[1235] 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.

[1236] 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.

[1237] [Fourth embodiment]

[1238] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1239] 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.

[1240] 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).

[1241] 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.

[1242] 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.

[1243] 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).

[1244] 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.

[1245] 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.

[1246] 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.

[1247] 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.

[1248] 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.

[1249] 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.

[1250] 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."

[1251] The interior design proposal system of the present invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[1252] System Overview

[1253] 1. Upload a photo

[1254] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[1255] 2. Receiving and analyzing photos

[1256] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[1257] 3. Collecting user preference information

[1258] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[1259] 4. Generate design proposals

[1260] The server combines the room analysis results with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting options, curtains, etc. It also selects optimal products within the user's budget.

[1261] 5. 3D Model Generation and Display

[1262] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in a virtual space and make any necessary changes.

[1263] Program implementation example

[1264] 1. Upload a photo

[1265] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[1266] Examples:

[1267] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[1268] 2. Receiving and analyzing photos

[1269] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[1270] Examples:

[1271] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[1272] 3. Collecting user preference information

[1273] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[1274] Examples:

[1275] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[1276] 4. Generate design proposals

[1277] The server generates interior design proposals based on the results of photo analysis and the user's preferences, and also selects the best products based on the user's budget.

[1278] Examples:

[1279] The server generates suggestions for user A, such as a modern sofa and an orange accent wall, and selects furniture that can be purchased within the user's budget.

[1280] 5. 3D Model Generation and Display

[1281] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[1282] Examples:

[1283] When User A opens the app, checks the 3D model, and changes the sofa position or wall color, it is updated in real time.

[1284] As described above, the system of the present invention provides a means for users to easily find and realize interior designs that suit their tastes, allowing users to easily coordinate the interior of their home without the help of a professional.

[1285] The processing flow will be explained below.

[1286] Step 1:

[1287] The user takes a photo of their room. The user uses a smartphone or a digital camera to take a photo of a room such as a living room, bedroom, or kitchen.

[1288] Step 2:

[1289] The device displays the photos that have been taken so that the user can select them. The user selects a photo on the device screen and presses the upload button.

[1290] Step 3:

[1291] The terminal uploads a photo of the selected room to the server, where it is converted into a format that can be processed within the system.

[1292] Step 4:

[1293] The server receives the photos uploaded by the user and verifies that the photos were received correctly.

[1294] Step 5:

[1295] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[1296] Step 6:

[1297] The server generates the analysis results and stores the information in a temporary file or database, thereby recording the room's characteristics as data.

[1298] Step 7:

[1299] The terminal displays an interface for the user to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[1300] Step 8:

[1301] The user selects a preferred design style and color palette and performs an operation to transmit that information to the system.

[1302] Step 9:

[1303] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[1304] Step 10:

[1305] The server combines the results of photo analysis with user preference information, and generates personalized interior design suggestions based on this information.

[1306] Step 11:

[1307] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed by the user.

[1308] Step 12:

[1309] The server generates a 3D model and sends it to the device, where the user can view the model.

[1310] Step 13:

[1311] The device displays the 3D model to the user and provides an interactive interface, allowing the user to examine the proposed design in detail.

[1312] Step 14:

[1313] Users can make changes to the layout and design while viewing the 3D model, such as changing the sofa position or wall color.

[1314] Step 15:

[1315] The device sends the user's changes to the server, which then reflects the changes in real time and updates the 3D model.

[1316] Step 16:

[1317] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[1318] Step 17:

[1319] The server generates the final design and a list of necessary products and sends them to the terminal, which the user can use to coordinate the interior.

[1320] Through these steps, the system of the present invention proposes an optimal interior design for the user's room and helps the user to easily realize it.

[1321] Example 1

[1322] 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."

[1323] Conventional interior design systems have difficulty efficiently generating design proposals based on a user's individual preferences. Even when a user sets a budget, the system lacks the functionality to select the optimal product within that budget. Furthermore, the system lacks an interface that allows users to make changes to the proposed design, which can lead to reduced user satisfaction.

[1324] 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.

[1325] In this invention, the server includes means for receiving images of a space taken by a user, means for analyzing the images to recognize the layout of the space, existing fixtures, colors, and lighting arrangement, means for collecting information regarding the user's preferred design style and color selection, means for generating a personalized interior design proposal, means for creating a three-dimensional model of the interior design proposal and displaying it to the user, means for selecting optimal products within a user-specified budget, and means for the user to make changes to the proposed design. This allows the server to generate personalized interior design proposals that meet the user's individual preferences, provide optimal products within a user's budget, and enable the user to make changes to the design in real time.

[1326] A "user" is an individual or corporation that uses the system to request an interior design for their space.

[1327] A "space image" is a photograph or image data taken by a user that shows the interior scenery or layout of a room.

[1328] "Means for receiving" refers to the function of importing image data uploaded by users via the Internet into a server.

[1329] The "means of analysis" refers to algorithms or software that process the received image data and recognize the spatial layout, type and placement of fixtures, colors, lighting position, etc.

[1330] "Fixtures" refers to furniture and interior items placed in a room.

[1331] "Color" refers to the various color combinations and color schemes that exist within a space.

[1332] "Lighting arrangement" refers to the location of lighting fixtures within a space and the distribution of light they provide.

[1333] "Design style" is a concept that describes the overall theme or aesthetic of an interior design, and examples include modern, classic, and minimalist.

[1334] "Color selection" refers to the user's preferred color palette or color combination.

[1335] "Individualized interior design proposal" means an interior design plan that is customized based on the user's preferences and the characteristics of the space.

[1336] "3D modeling" refers to the process of digitally representing a design proposal as a three-dimensional visual model.

[1337] "Displaying means" refers to software and hardware functions for displaying the generated three-dimensional model on the user's terminal.

[1338] "Budget" refers to the total amount of money the user can spend on the interior design.

[1339] "Product selection tools" are algorithms and system functions that select the best furniture and interior items within the user's budget.

[1340] "Means for making changes" refers to the interface and functionality that allows a user to make corrections or adjustments to the proposed design.

[1341] The interior design proposal system of the present invention analyzes images of spaces provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as three-dimensional models. Specific technical means and operational examples of the present invention are described below.

[1342] Hardware and Software Configuration

[1343] Users take images of the room using a device such as a smartphone or tablet. A dedicated application is installed on the device, and the user uploads the images to the server through this application. The server receives and stores the image data via the internet. The AI ​​models used include TensorFlow and PyTorch, and Blender and Unity for 3D modeling. These software programs are used within the server to generate design proposals and create 3D models.

[1344] Program processing flow

[1345] When the server receives images uploaded by users, it uses an AI model to analyze them. Specifically, it recognizes the spatial layout, fixture types and placement, colors, and lighting position from the received images. The results of this analysis later become the basis for generating design proposals.

[1346] The device then collects information about the user's preferred design style and color choices through the interface. This information is sent to the server and stored along with the analysis results. For example, if a user selects a modern style and a warm color palette, that information is sent to the server.

[1347] The server uses a generative AI model (e.g., OpenAI GPT-4) to generate interior design proposals based on the analyzed image data and the user's preferences. These proposals include new fixture placement, wall color, lighting selection, curtains, etc. The server also selects optimal products within the user's budget. These design proposals are then converted into 3D models. For example, the server may generate a proposal for User A, such as a modern sofa and an orange accent wall, and select furniture that can be purchased within the user's budget.

[1348] The generated 3D model is sent from the server to the device, where the user can visually check the design in the virtual space. The dedicated application allows the user to make changes to the displayed 3D model, and the changes are reflected in real time. For example, if User A changes the position of a sofa in the app, the changes are immediately reflected in the 3D model.

[1349] Prompt Sentence Examples

[1350] "Analyze a photo of a living room and suggest a modern interior design. Use a warm color palette and choose the best furniture for the user's budget."

[1351] The above is a concrete example of the technical means and operation of the interior design suggestion system of the present invention. This system allows users to easily find and realize an interior design that suits their tastes.

[1352] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1353] Step 1:

[1354] A user takes a picture of their room with their smartphone and uploads it to the device's application. Specifically, the user selects the image they took from the gallery and presses the "upload" button. This operation causes the image data to be sent to the server by the application.

[1355] Input: A room image taken with a smartphone

[1356] Output: Image data sent to the server

[1357] Step 2:

[1358] The server receives images uploaded by users and saves the received data in a specified folder.

[1359] Input: Uploaded image data

[1360] Output: Saved image file

[1361] Step 3:

[1362] The server inputs the received image data into an AI model (e.g., TensorFlow) for analysis. During the analysis process, image features are extracted and the spatial layout, fixture types and placement, colors, lighting position, etc. are recognized.

[1363] Input: Saved image file

[1364] Output: Analysis results including spatial layout, fixture types and placement, color, and lighting position

[1365] Step 4:

[1366] The device provides a user with an interface to collect information about interior design preferences, where the user inputs design styles (e.g., modern, classic, minimalist) and color preferences (e.g., warm, cool), which are then transmitted to a server in real time.

[1367] Input: User's preferred design style and color selection

[1368] Output: User preference data sent to the server

[1369] Step 5:

[1370] The server combines the received user preference data with the results of the image analysis. It then uses a generative AI model (e.g., OpenAI GPT-4) to generate personalized interior design suggestions. These suggestions include new fixture placement, wall colors, lighting choices, curtains, etc. It also selects the best products within the user's budget.

[1371] Input: User preference data and image analysis results

[1372] Output: personalized interior design suggestions and a list of optimal products

[1373] Step 6:

[1374] The server then creates a 3D model of the interior design proposal and sends it to the device using software such as Blender or Unity.

[1375] Input: personalized interior design proposals

[1376] Output: 3D model and its transmission data

[1377] Step 7:

[1378] The device displays the received 3D model data. The user can then view the 3D model within the application and make changes as needed. For example, if the user changes the position of a sofa or the color of a wall in the virtual space, the changes are reflected in real time.

[1379] Input: 3D model data

[1380] Output: User-visible interface and real-time changes

[1381] By following the above steps, users can easily find and realize an interior design that suits their tastes.

[1382] (Application example 1)

[1383] 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."

[1384] While conventional interior design proposal systems can generate personalized design proposals by analyzing photos taken by users, they lack specific functionality for simulating the interior design of virtual stores. In particular, they lack the functionality to automatically recognize the store layout, existing equipment, product placement, and lighting position, suggest optimal products based on the desired design style and budget, and make adjustments in real time. Therefore, a comprehensive design proposal system for virtual stores is needed.

[1385] 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.

[1386] In this invention, the server includes means for receiving photos of a room taken by a user, means for collecting information on the user's preferred design style and color palette, means for generating personalized interior design proposals based on the room's characteristics and the user's preferences, means for converting the interior design proposals into 3D models and displaying them to the user, means for simulating the interior design of a virtual store, means for analyzing uploaded photos to recognize the store's layout, existing equipment, product placement, and lighting location, means for inputting the desired design style and budget, means for proposing optimal products within the budget, and means for displaying the generated 3D model and allowing the user to make adjustments in real time. This enables advanced interior design proposals to be made in virtual stores without the need for specialized knowledge.

[1387] "User" means an individual or organization that uses the system to receive interior design proposals.

[1388] A "photo" is image data showing an image of the interior of a room or store taken by a user.

[1389] "Receiving" is the process by which the system takes in image data uploaded by the user.

[1390] "Analysis" is the process of using AI models and algorithms to extract characteristics of rooms or stores from image data.

[1391] "Room characteristics" refers to the physical characteristics of a room or store, such as its layout, structure, area, and wall color.

[1392] "Existing Furniture" means furniture and decor items that are already installed and are shown in the photograph.

[1393] "Color" refers to the color combinations used on the walls, floors, furniture, etc. of a room or store.

[1394] "Lighting arrangement" refers to the location and type of lighting fixtures in a room or store, and their placement.

[1395] "Design style" refers to the overall interior theme or aesthetic preferred by a user, including modern, classic, minimalist, etc.

[1396] A "color palette" refers to a particular combination of colors that a user prefers.

[1397] "Personalization" is the process of applying a specific design based on a user's individual preferences and requirements.

[1398] "Interior design proposal" refers to a new design plan that reflects the analysis results and the user's preferences.

[1399] A "3D model" is data that represents an interior design proposal in three dimensions.

[1400] A "virtual store" refers to a store model built in a digital space.

[1401] "Simulation" is the process of replicating a real-world design in a virtual environment.

[1402] "Layout" refers to the physical arrangement and structure of the interior of a store or room.

[1403] "Existing Installations" means pre-installed lighting fixtures and fixtures.

[1404] "Product placement" refers to the location of products and displays within a store.

[1405] "Budget" is the amount of money the user prepares for interior design.

[1406] "Optimal products" are the best furniture and interior items selected based on the user's preferences and budget.

[1407] "Real-time" means immediate response and changes are implemented without any time delay.

[1408] The interior design proposal system of this invention analyzes room photos provided by users, generates personalized interior designs based on the user's preferences and budget, and provides them as 3D models. This system can also be applied to virtual stores.

[1409] System configuration and operation method

[1410] 1. Upload a photo

[1411] Users use their smartphones to take photos of their rooms or stores and then upload them to the system through the application, which uses a simple interface.

[1412] 2. Receiving and analyzing photos

[1413] The server receives photos uploaded by users, which are then analyzed using an AI model (such as ImageAI's ResNet). This analysis process recognizes the room layout, existing furniture, color scheme, and lighting arrangement.

[1414] 3. Collecting user preference information

[1415] The terminal provides the user with an interface where they can input information such as their desired design style, preferred color palette, budget, etc. This information is then sent to the server.

[1416] 4. Generate design proposals

[1417] The server combines the results of photo analysis with the user's preferences to generate personalized interior design suggestions, including new furniture placement, wall colors, lighting choices, curtain designs, etc. It also selects optimal products within the user's budget.

[1418] 5. 3D Model Generation and Display

[1419] The server then converts the generated interior design proposal into a 3D model and sends it to the user's device for display, allowing the user to visually check the design in a virtual space and make changes as needed.

[1420] Hardware and software used

[1421] Hardware:

[1422] Smartphone (for taking photos and operating applications)

[1423] Server (for photo analysis and design proposal generation)

[1424] software:

[1425] AI models (such as ImageAI's ResNet)

[1426] OpenCV (for image analysis)

[1427] Trimesh and OpenGL (for 3D model generation and display)

[1428] Specific examples

[1429] Consider a scenario in which a user wants to update the design of a virtual store. The user takes a photo of the interior using the camera on their smartphone. They then open the application and upload the photo. Next, the user selects "modern" as the desired design style, "warm" as the color palette, and enters a budget of ¥200,000. The server analyzes the uploaded photo and generates a new interior design based on it. The generated design is displayed as a 3D model, which the user can view in real time and make further adjustments. Finally, the user can review the details of the new design and purchase appropriate products within their budget.

[1430] Example prompt:

[1431] markdown

[1432] To propose an interior design for a room, upload a photo of your store and propose a new design using a modern style and warm color palette. Your budget is ¥200,000.

[1433] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1434] Step 1:

[1435] A user takes a photo of a room or store using a smartphone and uploads the photo to the system via the application. The input data is the photo taken with the smartphone, and this photo is sent to the system.

[1436] Step 2:

[1437] The server receives photos uploaded by users. It uses OpenCV to preprocess (resize, filter, etc.) the received photo data and prepares it for analysis. The output is image data converted into an analyzable format.

[1438] Step 3:

[1439] The server uses an AI model (e.g., ImageAI's ResNet) to analyze the preprocessed image data. This analysis extracts the room or store layout, existing furniture, color, and lighting arrangement. The input data is the preprocessed image, and the output data is metadata describing the physical characteristics.

[1440] Step 4:

[1441] Through a smartphone application, users input their preferred design style (e.g., modern, classic, minimal, etc.), color palette, budget, etc. The input data is the user's preference information and is sent to the server.

[1442] Step 5:

[1443] The server combines the received user preference information with the analyzed physical feature data. Using AI algorithms, it generates personalized interior design proposals based on this data, including furniture placement, wall color, lighting selection, and curtains. The output data is a design proposal based on the user's preferences and the room's features.

[1444] Step 6:

[1445] The server creates a 3D model of the generated design proposal. It uses Trimesh and OpenGL to represent the design proposal in three dimensions. The input data is the design proposal, and the output data is the 3D model.

[1446] Step 7:

[1447] The server sends the generated 3D model to the user's device and displays it within the application. The user can visually check this 3D model and make changes as needed. The input data is the 3D model, and the output data is the interface that the user can view and edit.

[1448] Step 8:

[1449] Users can adjust the settings of the 3D model in real time within the application. For example, if they change the furniture arrangement or wall color, the changes are immediately reflected in the 3D model. The input data are the user's changes, and the output data is the updated 3D model.

[1450] Through these steps, the system of the present invention provides users with personalized interior design proposals and realizes advanced design simulations that can also be applied to virtual stores.

[1451] 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.

[1452] The interior design proposal system of the present invention analyzes photos of rooms provided by users, generates personalized interior designs based on the user's preferences and emotions, and provides them as 3D models. Specific embodiments for implementing the system of the present invention are described below.

[1453] System Overview

[1454] 1. Upload a photo

[1455] Users take photos of their rooms and upload them to the system via their devices. These photos include various rooms such as the living room, bedroom, and kitchen.

[1456] 2. Receiving and analyzing photos

[1457] The server receives photos uploaded by users, which are then analyzed by an AI model to recognize the room layout, existing furniture types and placement, colors, lighting position, and more.

[1458] 3. Collecting user preference information

[1459] The device provides the user with an interface that allows them to input their preferred design style (e.g., modern, classic, minimal, etc.) and color palette, and this information is sent to the server.

[1460] 4. User Emotion Recognition

[1461] The terminal and server are equipped with an emotion engine for analyzing the user's emotions, which evaluates the user's current emotional state in real time through facial expression recognition and text analysis.

[1462] 5. Generate design proposals

[1463] The server integrates the results of the room analysis, the user's preference information, and the user's emotional state to generate personalized interior design proposals. The proposals are dynamically adjusted based on the information from the emotion engine, providing a design that suits the user's mood. The server also selects optimal products within the user's budget.

[1464] 6. Generating and displaying 3D models

[1465] The server then converts the generated interior design proposal into a 3D model and sends it to the device, where the user can visually check the design in virtual space and make any necessary changes.

[1466] Program implementation example

[1467] 1. Upload a photo

[1468] Users take photos of their rooms with their smartphones and upload them to the server through an application on their devices, a process that can be completed with just a few taps.

[1469] Examples:

[1470] User A takes a photo of the living room, opens the app, selects the image, and presses the upload button to send it to the server.

[1471] 2. Receiving and analyzing photos

[1472] When the server receives a photo from the user, it uses an AI model to analyze the photo, recognizing the room layout, furniture type and placement, colors, lighting position, and more.

[1473] Examples:

[1474] The server analyzes the photos of the living room it receives and identifies the location of the sofa, table, lamps, and the color of the walls.

[1475] 3. Collecting user preference information

[1476] The device provides the user with an interface to select their interior preferences: they choose a modern style and a warm color palette, and then send this information to the server.

[1477] Examples:

[1478] User A selects a modern style and warm color palette in the app, presses the OK button, and sends it to the server.

[1479] 4. User Emotion Recognition

[1480] The device captures the user's facial expressions with a camera, and the emotion engine analyzes them. It also determines the user's emotional state through questionnaires and text input.

[1481] Examples:

[1482] The emotion engine recognizes that User A is in a calm mood through facial expression analysis, and also determines from text input that he or she desires a relaxed atmosphere.

[1483] 5. Generate design proposals

[1484] The server generates interior design suggestions based on the photo analysis results, the user's preference information, and data from the emotion engine. For example, if the user is in a relaxed emotional state, a design with calming colors will be suggested.

[1485] Examples:

[1486] The server proposes a modern interior design with calm tones to User A. Furniture and decorations that can be purchased within the user's budget are also selected.

[1487] 6. Generating and displaying 3D models

[1488] The server then converts the generated design into a 3D model and sends it to the device, where the user can view the 3D model in the app and make any necessary adjustments.

[1489] Examples:

[1490] User A opens the app, checks the 3D model, and confirms that the proposed design is in line with the relaxing atmosphere. Even if they change the sofa position or wall color, it is updated on the fly.

[1491] The system of the present invention proposes interior design ideas that take the user's emotions into consideration, which has the effect of increasing the user's psychological satisfaction, allowing the user to effectively coordinate the interior of their home without the help of a professional.

[1492] The processing flow will be explained below.

[1493] Step 1:

[1494] Users take photos of their rooms with their smartphones, including the living room, bedroom, kitchen, and other rooms they need.

[1495] Step 2:

[1496] The device displays the captured photos to the user, allowing them to be selected. The user selects the photos to upload and presses the upload button.

[1497] Step 3:

[1498] The terminal uploads the photo files of the selected room to the server, where the uploaded photos are converted into a format that can be processed within the system.

[1499] Step 4:

[1500] The server receives the photos uploaded by the user and verifies that the photos received are correct.

[1501] Step 5:

[1502] The server inputs the received photos into an AI model that begins analyzing them, recognizing the room's layout, the type and placement of existing furniture, color, and lighting arrangement.

[1503] Step 6:

[1504] The server generates the analysis results and stores the information in a temporary file or database, which records the room's characteristics as data.

[1505] Step 7:

[1506] The device provides the user with an interface that prompts them to select a design style and color palette. The user selects their preferred design style (e.g., modern, classic, minimal, etc.) and color palette.

[1507] Step 8:

[1508] The user selects a preferred design style and color palette, and presses the OK button to transmit the selection to the server.

[1509] Step 9:

[1510] The terminal sends the user's preference information to the server, which adds the user's preferences to the database.

[1511] Step 10:

[1512] The device captures the user's facial expressions with a camera or the user inputs text, which is then sent to the server in real time.

[1513] Step 11:

[1514] The server uses an emotion engine that captures facial expressions and analyzes text to recognize the user's emotions and evaluate their state. This process determines whether the user is relaxed or excited.

[1515] Step 12:

[1516] The server combines the results of photo analysis, user preference information, and emotional data from an emotion engine to generate personalized interior design proposals. The proposals are dynamically adjusted based on the emotional data.

[1517] Step 13:

[1518] The server then creates a 3D model of the generated design proposal, which is then generated as a virtual space that can be visually confirmed.

[1519] Step 14:

[1520] The server sends the 3D model to the device, where the user can view it and check the design.

[1521] Step 15:

[1522] The device displays the 3D model to the user in an interactive manner, allowing the user to examine the interior design in detail and make adjustments as needed.

[1523] Step 16:

[1524] Users can change the furniture placement, color, and design style while viewing the 3D model. Users can change the sofa position, wall color, and more in real time.

[1525] Step 17:

[1526] The device sends the user's changes to the server, which reflects them and updates the 3D model in real time.

[1527] Step 18:

[1528] When the user has finally decided on a design that satisfies them, they can perform a "final design confirmation" operation on their device, which will finalize the design.

[1529] Step 19:

[1530] The server generates the final design and a list of required products and sends them to the terminal. The user can then review the final design and product list and obtain information for carrying out interior coordination.

[1531] Through these steps, the system of the present invention provides interior design suggestions that take the user's emotions into consideration, increasing the user's psychological satisfaction and enabling the user to effectively coordinate the interior of their home without the help of a professional.

[1532] Example 2

[1533] 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."

[1534] Conventional interior design proposal systems have difficulty providing personalized designs that take into account the user's preferences and emotional state. They also lack the ability to adjust designs in real time or select optimal products within a budget. This creates a need for systems that can increase user satisfaction and achieve effective interior coordination.

[1535] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1536] In this invention, the server includes means for receiving photos of a room taken by a user, means for analyzing the photos to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional information in real time, means for generating personalized interior design proposals based on the room's features and the user's preferences, and means for converting the interior design proposals into 3D models and displaying them to the user. This enables personalized design proposals tailored to the user's preferences and emotional state, increasing user satisfaction and facilitating effective interior coordination.

[1537] "User" refers to a person who uses the system and receives interior design suggestions.

[1538] A "terminal" refers to an electronic device that allows a user to access and operate the system, and examples include smartphones and personal computers.

[1539] "Server" refers to a computer that manages and processes data received from connected devices and provides the overall functionality of the system.

[1540] "Receiving a photo" refers to the process in which a user sends photo data of a room taken by the user to the server and the server receives the photo data.

[1541] "Photo analysis" refers to the process of using AI models to identify room layout, furniture placement, color, and lighting arrangement based on the photo data received by the server.

[1542] "Collecting user preferences" refers to the process of obtaining information about design styles and color palettes from users via their terminals.

[1543] "Emotional information analysis" refers to the process of assessing a user's emotional state in real time using the device's camera and text input.

[1544] "Generating interior design proposals" refers to the process in which the server constructs the optimal interior design for the user based on the results of photo analysis and the user's preferences and emotional information.

[1545] "3D modeling" refers to the creation of a three-dimensional representation of the generated interior design proposal, allowing users to visually confirm the design in a virtual space.

[1546] "Product selection within budget" refers to the process in which the server selects and recommends furniture and decorations that can be purchased within the budget set by the user.

[1547] "Design changes" refers to adjustments or modifications made by a user to a proposed interior design.

[1548] The interior design proposal system of the present invention is designed to analyze a room photo provided by a user, generate a personalized interior design based on the user's preferences and emotions, and provide it as a 3D model. The following specific hardware and software configurations are used to implement the present invention.

[1549] Hardware Configuration

[1550] 1. Terminal: The device that a user uses to interact with the system. Specific examples include smartphones, tablets, and personal computers.

[1551] 2. Server: A dedicated computer system that receives data, analyzes it, and generates design proposals.

[1552] Software Configuration

[1553] 1. Photo analysis module (AI model): Runs on the server and analyzes photos of rooms uploaded by users. It uses deep learning techniques to identify the room layout, furniture placement, color, and lighting location.

[1554] 2. Emotion Engine: Analyzes the user's facial expressions and text inputs to assess their emotional state in real time, using image recognition algorithms and natural language processing techniques.

[1555] 3. Interface application: Runs on the device and provides a GUI (graphical user interface) for users to upload photos, input design preferences, and provide emotional information.

[1556] 4. 3D modeling engine: Software that converts design proposals generated on the server into 3D models and displays them on the device.

[1557] Specific examples

[1558] For example, if a user wants to improve the interior design of their living room, they can take a photo of the room with their smartphone and upload it to the server through an application on their device. The application is simple to use; just select the photo and press the "upload" button.

[1559] The server analyzes the received photos and uses AI models to determine the room layout, sofa and table placement, wall color, and lighting location. The device then provides an interface that lets the user select a design style (e.g., modern, classic) and color palette. Once the user completes their selection, the information is sent to the server in real time.

[1560] Furthermore, the device's camera captures the user's facial expressions, and the emotion engine analyzes the user's mood (e.g., relaxed, calm). At the same time, the user can express their preferred mood through text input.

[1561] The server analyzes the photos, integrates the user's preferences and emotional data, and generates optimal interior design suggestions. Using a generative AI model, personalized designs are created based on the emotional data. For example, a modern design with calming colors is offered to match the emotional state of wanting to relax.

[1562] Finally, the server creates a 3D model of the generated design and sends it to the terminal. The user can then visually check the design in the virtual space and make any necessary changes. For example, they can adjust the position of the sofa or the color of the walls. In this way, the system of the present invention can provide the user with a satisfactory interior design proposal.

[1563] Examples of prompt statements

[1564] "Take a photo of your living room with the app and upload it."

[1565] "Choose your preferred design style, for example, modern or classic."

[1566] "Tell me how you're feeling right now. If you want to relax, type relax."

[1567] "View the proposed design in 3D and adjust any changes you want to make."

[1568] As a result, users can effectively coordinate the interior of their homes through the system.

[1569] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1570] Step 1:

[1571] The user takes a photo of the room and uploads it to the server via an application on the device.

[1572] Specifically, the user takes a photo of the room with their smartphone camera, clicks the "Select Photo" button in the app, selects the photo, and then presses the "Upload" button. This action sends the photo data to the server.

[1573] Input: A photo of the room taken with a camera

[1574] Output: Photo data sent to the server

[1575] Step 2:

[1576] The server analyzes the received photo data, and an AI model identifies the room layout, furniture placement, color, and lighting position.

[1577] Specifically, after the server receives the photo data, it launches the AI ​​analysis module and begins analysis, using a deep learning model to identify the sofa, table, wall color, and lighting position.

[1578] Input: Photo data uploaded by the user to the server

[1579] Output: Analyzed room layout, furniture placement, color, and lighting location information

[1580] Step 3:

[1581] The device collects the user's design preferences (style, color palette) and sends them to the server.

[1582] Specifically, the user operates the device interface, selects a modern style or warm color palette, presses the "OK" button, and sends the selection to the server.

[1583] Input: User-selected design style and color palette

[1584] Output: User's design preference information sent to the server

[1585] Step 4:

[1586] The device collects the user's real-time emotional information, which is then analyzed by the server's emotion engine.

[1587] Specifically, the device's camera captures the user's facial expressions, and the emotion engine analyzes them. Emotional information is also supplemented by questionnaire and text input.

[1588] Input: User's facial expressions, questionnaire input, text input

[1589] Output: Real-time emotional state information of the user

[1590] Step 5:

[1591] The server integrates the results of photo analysis, user preferences, and emotional information to generate personalized interior design proposals.

[1592] Specifically, the AI ​​model creates an optimal design based on the analysis results and the user's preferences, and generates a proposal. At the same time, it also takes into account the user's emotional information and adjusts the color tone and style of the design.

[1593] Input: Photo analysis results, user's design style and color palette, emotional state information

[1594] Output: Personalized interior design proposals

[1595] Step 6:

[1596] The server converts the generated interior design proposal into a 3D model and sends it to the terminal.

[1597] Specifically, the server-side 3D modeling engine converts the proposed design into a 3D model and sends it to the device, where the user can view the 3D model within the application and interactively modify it as needed.

[1598] Input: Generated interior design proposal

[1599] Output: 3D model data displayed on the device

[1600] (Application example 2)

[1601] 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."

[1602] Conventional interior design systems propose designs based on the user's preferences and room layout, but they have the problem of being unable to take into account the user's current emotional state. Furthermore, they lack a means to visualize the proposed design concretely or to confirm whether the selected products are within the user's budget. Therefore, a system that can propose appropriate interior designs while enhancing the user's psychological satisfaction and respecting financial constraints is needed.

[1603] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a room photo taken by a user, means for analyzing the photo to recognize the room's features, existing furniture, colors, and lighting arrangement, means for collecting information on the user's preferred design style and color palette, means for analyzing the user's emotional state, means for generating personalized interior design proposals based on the room's features, the user's preferences, and the user's emotional state, and means for creating a 3D model of the interior design proposal and displaying it to the user. This enables interior design proposals that take the user's current emotional state into consideration. Furthermore, the server can select and visually confirm optimal products within the user's budget, making it possible to provide proposals that fit within economic constraints.

[1604] A "user" is someone who uses the system to receive interior design proposals.

[1605] The "means for receiving photos" is a function for receiving photos of the room taken by the user and uploaded to the system.

[1606] "Means for analyzing and recognizing room features, existing furniture, colors, and lighting arrangements" refers to a function that uses digital image analysis technology to analyze received photos and identify the room layout, installed objects, colors, and lighting locations.

[1607] "Means for collecting information about a user's preferred design style and color palette" refers to a function that records and collects design style and color preferences input by a user through an interface.

[1608] The "means for analyzing the user's emotional state" is a function that analyzes the user's facial expressions and input text and evaluates the user's emotions in real time.

[1609] The "means for generating personalized interior design proposals" is a function that creates an interior design suited to each user based on the room's characteristics, the user's preferences, and their emotional state.

[1610] "Means for creating a 3D model of an interior design proposal and displaying it to the user" refers to a function that uses three-dimensional modeling technology to create a model of the generated design proposal and display it so that the user can visually confirm it.

[1611] "Means to select the best products within a budget" is a function that selects furniture and decoration items that can be purchased within a price range set by the user.

[1612] "Means for making changes to the proposed design" refers to a function that allows the user to make changes to the initial design proposal, such as changes to the position or color.

[1613] This interior design proposal system provides users with personalized designs through the following series of steps: The entire system is composed mainly of user terminals (mainly smartphones) and a server.

[1614] First, the user takes a photo of their room with their smartphone and uploads it to the server through an application on their device. The user uses an interface that allows them to easily upload photos. The server receives the photo uploaded by the user and analyzes it using an AI model. Specifically, it recognizes the room layout, furniture type and placement, color, lighting arrangement, etc.

[1615] The device then provides an interface for the user to input their preferences, such as design style and color palette. The information entered by the user is sent to the server and stored. At the same time, the device's camera captures the user's facial expressions, and an emotion engine is used to analyze the user's emotional state in real time. This emotion information is also sent to the server.

[1616] The server combines the results of photo analysis, the user's preferences, and their emotional state, and uses a generative AI model to generate personalized interior design suggestions. If the user's emotional state indicates a desire for relaxation, designs with calming colors and soft lighting will be suggested. Additionally, products that are affordable within the user's budget are selected.

[1617] The generated interior design proposal is converted into a 3D model on the server and sent to the device. The user can use the device application to visually check this 3D model and make changes as needed. For example, if they change the proposed sofa position or wall color, it will be updated on the fly.

[1618] The main hardware used includes the user's smartphone and a server, and the main software includes an AI model, an emotion engine, and a 3D modeling tool, which uses the EmotionRecognition library.

[1619] For example, user A takes a photo of their living room, selects a modern style and a warm color palette using the app, and recognizes their emotional state of wanting to relax through facial expression analysis. Based on this data, the server proposes a relaxing, modern interior design and displays it to user A as a 3D model.

[1620] An example of a prompt for a generative AI model is as follows:

[1621] "Please suggest an interior design for a living room. The user's preference is for a modern style with a warm color palette. The user also wants to feel relaxed. The budget is ¥100,000."

[1622] This allows the system to provide optimal interior design within a budget, taking into account the user's current emotional state.

[1623] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1624] Step 1:

[1625] The user takes a photo of the room and uploads it to the server through the device application. Specifically, the user takes a photo of the room using the smartphone camera and taps the upload button in the app. The input is the photo data of the room, and the photo is sent to the server as the output.

[1626] Step 2:

[1627] The server analyzes the received photos using an AI model. Specifically, the server inputs the photo data, and the AI ​​model recognizes the room layout, furniture type and placement, color, and lighting position. As a result of the analysis, these attributes are identified and output as data.

[1628] Step 3:

[1629] The user inputs their preferred design style and color palette using a terminal application. The terminal receives this through an interface and sends it to the server. The input is the user's preference information, and the output is recorded on the server.

[1630] Step 4:

[1631] The device's camera captures the user's facial expressions, which are then analyzed by the emotion engine. Specifically, the EmotionRecognition library identifies the user's emotions in real time and sends the results to the server. The input is the captured facial expression data, and the output is the analyzed emotional information.

[1632] Step 5:

[1633] The server integrates the photo analysis results, user preference information, and emotional information, and uses a generative AI model to generate personalized interior design proposals. Specifically, this data is input into the AI ​​model as prompts to generate the proposed design. The input is the integrated data, and the output is the design proposal.

[1634] Step 6:

[1635] The server creates a 3D model of the interior design proposal and sends it to the device. Specifically, it uses a 3D modeling tool to create a three-dimensional design. The input is the design proposal, and the output is the 3D model data.

[1636] Step 7:

[1637] The user can view the 3D model in the terminal application and make changes as needed. As the user makes changes, the data is sent from the terminal to the server, and the 3D model is updated in real time. The input is the user's changes, and the output is the updated 3D model.

[1638] This series of steps provides a visually verifiable interior design that takes into account the user's preferences and emotions, thereby increasing user satisfaction.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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).

[1646] 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.

[1647] 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."

[1648] 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.

[1649] 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).

[1650] 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.

[1651] 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.

[1652] 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.

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] 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.

[1658] 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.

[1659] 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.

[1660] The following is further disclosed regarding the above embodiment.

[1661] (Claim 1)

[1662] means for receiving a photo of the room taken by a user;

[1663] A means of analyzing said photograph to recognize the room's features, existing furniture, color, and lighting arrangement;

[1664] a means of collecting information about a user's preferred design style and color palette;

[1665] means for generating personalized interior design suggestions based on the room characteristics and user preferences;

[1666] A means to create a 3D model of the above interior design proposal and display it to users.

[1667] A system including:

[1668] (Claim 2)

[1669] 10. The system of claim 1, further comprising means for selecting an optimal product within a budget set by a user.

[1670] (Claim 3)

[1671] 10. The system of claim 1, further comprising means for allowing a user to make changes to the proposed design.

[1672] "Example 1"

[1673] (Claim 1)

[1674] means for receiving an image of a space captured by a user;

[1675] A means for analyzing the image to recognize the spatial layout, existing fixtures, colors, and lighting arrangement;

[1676] means for collecting information regarding a user's preferred design style and color choices;

[1677] means for generating personalized interior design suggestions based on the layout of the space and user preferences;

[1678] a means for creating a three-dimensional model of the interior design proposal and displaying it to a user;

[1679] A system including:

[1680] (Claim 2)

[1681] 10. The system of claim 1, further comprising means for selecting an optimal product within a budget set by a user.

[1682] (Claim 3)

[1683] 10. The system of claim 1, further comprising means for allowing a user to make changes to the proposed design.

[1684] "Application Example 1"

[1685] (Claim 1)

[1686] means for receiving a photo of the room taken by a user;

[1687] A means of analyzing said photograph to recognize the room's features, existing furniture, color, and lighting arrangement;

[1688] a means of collecting information about a user's preferred design style and color palette;

[1689] means for generating personalized interior design suggestions based on the room characteristics and user preferences;

[1690] A means to create a 3D model of the above interior design proposal and display it to users.

[1691] A means for simulating the interior design of a virtual store;

[1692] A method to analyze uploaded photos and recognize the layout of the store, existing equipment, product placement, and lighting position.

[1693] A way to input your desired design style and budget,

[1694] A way to suggest the best product within your budget,

[1695] A means for users to view the generated 3D model and make adjustments in real time;

[1696] A system including:

[1697] (Claim 2)

[1698] 10. The system of claim 1, further comprising means for selecting an optimal product within a budget set by a user.

[1699] (Claim 3)

[1700] 10. The system of claim 1, further comprising means for allowing a user to make changes to the proposed design.

[1701] "Example 2: Combining Emotion Engines"

[1702] (Claim 1)

[1703] means for receiving a photo of the room taken by a user;

[1704] A means of analyzing said photograph to recognize the room's features, existing furniture, color, and lighting arrangement;

[1705] a means of collecting information about a user's preferred design style and color palette;

[1706] A means for analyzing user emotional information in real time;

[1707] means for generating personalized interior design suggestions based on the room characteristics and user preferences;

[1708] A means to create a 3D model of the above interior design proposal and display it to users.

[1709] A system including:

[1710] (Claim 2)

[1711] 10. The system of claim 1, further comprising means for selecting an optimal product within a budget set by a user.

[1712] (Claim 3)

[1713] 10. The system of claim 1, further comprising means for allowing a user to make changes to the proposed design.

[1714] "Application example 2 when combining emotion engines"

[1715] (Claim 1)

[1716] means for receiving a photo of the room taken by a user;

[1717] A means of analyzing said photograph to recognize the room's features, existing furniture, color, and lighting arrangement;

[1718] a means of collecting information about a user's preferred design style and color palette;

[1719] means for analyzing the emotional state of a user;

[1720] means for generating personalized interior design suggestions based on the room characteristics and the user's preferences and emotional state;

[1721] A means to create a 3D model of the above interior design proposal and display it to users.

[1722] A system including:

[1723] (Claim 2)

[1724] 10. The system of claim 1, further comprising means for selecting an optimal product within a budget set by a user.

[1725] (Claim 3)

[1726] 10. The system of claim 1, further comprising means for allowing a user to make changes to the proposed design. [Explanation of symbols]

[1727] 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. means for receiving a photo of the room taken by a user; A means of analyzing said photograph to recognize the room's features, existing furniture, color, and lighting arrangement; a means of collecting information about a user's preferred design style and color palette; means for generating personalized interior design suggestions based on the room characteristics and user preferences; A means to create a 3D model of the above interior design proposal and display it to users. A system including:

2. 10. The system according to claim 1, further comprising means for selecting an optimum product within a budget set by a user.

3. 10. The system of claim 1, further comprising means for allowing a user to make changes to the proposed design.

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