system

Abstract

We provide the system. [Solution] Input means for collecting spatial data, An analysis means for analyzing input spatial data and extracting the physical characteristics of the space, A selection method for choosing a product range based on the desired decorative style and budget, A generation means for generating a virtual three-dimensional space in which the selected product group is arranged, A display means for displaying a virtual three-dimensional space, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, due to various changes in lifestyle, there has been an increasing need to easily realize an ideal living or working environment according to personal preferences and budgets while effectively utilizing limited space. However, the conventional furniture selection and arrangement process is very time-consuming, and there has been a problem that it is difficult for general users without specialized knowledge to efficiently carry out a comprehensive interior plan. In addition, the methods for pre-checking how the selected furniture fits into the actual space are limited, and there have been many cases of regret after purchase.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system including an input means for collecting spatial data, an analysis means for analyzing the input spatial data and extracting the physical characteristics of the space, a selection means for selecting a group of products based on a desired decorative style and budget, a generation means for generating a virtual three-dimensional space in which the selected group of products are arranged, and a display means for displaying the virtual three-dimensional space. Furthermore, by providing a function to obtain user feedback on the displayed virtual three-dimensional space and update the group of products and their arrangement based on the obtained feedback, it becomes possible to efficiently realize an interior space that satisfies the user. As a result, the user can make the most use of limited space and design a space that meets their individual needs.

[0006] "Spatial data" refers to information that describes the physical characteristics and dimensions of a user's living or working space.

[0007] "Input means" refers to an interface or device for a user to input spatial data into a system.

[0008] "Analysis means" refers to a technology or device that processes input spatial data and recognizes and extracts the physical characteristics of that space.

[0009] "Selection method" refers to a method or apparatus for identifying and selecting an appropriate product group based on the user's desired style and budget.

[0010] "Generation means" refers to a technology or apparatus for constructing a virtual three-dimensional space in which the selected product group is arranged.

[0011] "Display means" refers to a device or technology for visually showing the generated virtual three-dimensional space to the user.

[0012] A "feedback mechanism" is a method or device for receiving opinions and requests for improvement regarding a virtual three-dimensional space from users.

[0013] "Update means" refers to a method or apparatus for adjusting the product group and its arrangement based on the feedback received. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention provides a system that enables users to effectively utilize limited space and realize interiors tailored to their individual preferences. This system primarily includes means for collecting, analyzing, selecting, generating, and displaying spatial data, thereby proposing an optimal interior design that meets the user's needs.

[0036] When starting to use the system, the user inputs images of the room, floor plan data, budget, and style preferences using a terminal. The terminal formats this data and sends it to the server. The server processes the input image data using image analysis technology and extracts the physical characteristics of the room. Next, based on this data, the server selects appropriate furniture and decorations, taking into account the user's desired style and budget.

[0037] The furniture selected by the selection method is constructed as a virtual three-dimensional space by the generation method. The server sends this data to the terminal, which provides the user with an environment in which they can visually confirm the virtual space. At this stage, the user can experience the virtual space through the terminal and provide feedback.

[0038] As a concrete example, consider a case where a user wants to decorate their living room in a "Nordic style." The user inputs a photo of the room and their desired style into their device. The server recognizes it as a Nordic style and lists warm wooden furniture and simple decorations within the budget. Next, the user uses a VR device to simulate the generated 3D layout plan. Through this simulation, the user checks how the selected furniture fits into the space and, if necessary, inputs feedback into the device, which the server then adjusts the layout plan.

[0039] If the user is ultimately satisfied with the proposal, they can complete the purchase process on their terminal, completing the efficient interior coordination and implementation throughout the entire system. In this way, users can easily create a space that suits their own style and lifestyle.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. This information is received by the terminal, formatted in the appropriate format, and then sent to the server.

[0043] Step 2:

[0044] The server uses computer vision technology to analyze the received image data and extract the physical features and dimensions of the room. It also analyzes the floor plan data and organizes the spatial layout information.

[0045] Step 3:

[0046] The server uses natural language processing technology to estimate the user's style preferences and budget information. Then, using generative AI, it selects the most suitable furniture and decorative items based on this information and creates a product list.

[0047] Step 4:

[0048] The server uses a generation mechanism to place the selected product list in a virtual three-dimensional space, constructing an interior layout plan. This data is converted into a three-dimensional model and prepared for the user to visually review.

[0049] Step 5:

[0050] The server sends the generated 3D data to the terminal. The terminal receives this data and displays a virtual interior space to the user through an AR or VR device, providing an environment that simulates how it would look in the actual space.

[0051] Step 6:

[0052] The user reviews the displayed virtual space and inputs feedback on the furniture selection and placement, including opinions and suggestions for improvement, into the terminal.

[0053] Step 7:

[0054] The terminal sends user feedback to the server. Based on this feedback, the server updates the selected product group and its deployment plan as needed, and then proposes it to the user again.

[0055] Step 8:

[0056] If the user is satisfied with the proposal and decides to purchase, they proceed with the purchase process from their terminal. The server manages the information necessary for the purchase process and automatically handles inventory checks for the selected items, payment processing, and arrangements for delivery and installation.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] In modern living environments, there is a demand for the effective use of limited space and the realization of interiors that suit the lifestyles and preferences of individual users. However, existing systems require considerable effort to extract physical characteristics and select interior design candidates, making it difficult for users to easily create their ideal space. This invention aims to solve these problems and provide a system that allows for the efficient and intuitive design of interiors tailored to individual desires.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server comprises an input device means for collecting spatial data, an analysis device means for analyzing the collected spatial data and extracting physical features, a selection device means for selecting a group of products based on a desired decorative style and budget, a generation device means for generating a virtual three-dimensional space using the selected group of products, a display device means for displaying the generated virtual three-dimensional space, and a feedback device means for obtaining user feedback on the displayed virtual three-dimensional space. Furthermore, it includes an update device means for updating the group of products and their arrangement using a generation AI model based on the feedback obtained from the feedback means. This enables the proposal and adjustment of practical and user-optimized interiors.

[0062] "Spatial data" refers to data that includes physical information and characteristics related to residential and commercial spaces, and may include image data and floor plan information.

[0063] An "input device" is a device or interface that provides functions for users to easily input spatial data into a system.

[0064] An "analysis device" is a computer program or system configuration that has the function of processing input spatial data and extracting its physical characteristics.

[0065] A "selection device" is a component of a system that selects a range of products that match a specific decorative style and budget based on extracted characteristics.

[0066] A "generation device" is a program or hardware configuration that uses a selected group of products to create a virtual three-dimensional space.

[0067] A "display device" is a device or software that visualizes a generated virtual three-dimensional space, allowing users to visually confirm that space.

[0068] A "feedback device" is a mechanism or system configuration for collecting user opinions and suggestions for improvement regarding the displayed virtual three-dimensional space.

[0069] A "renewal device" is part of a system that uses a generated AI model to modify the product group and its placement based on information obtained through feedback.

[0070] A "generative AI model" is an algorithm or model that utilizes machine learning technology to propose the optimal interior design plan based on the input conditions.

[0071] A "prompt statement" is a text-based instruction that provides specific instructions or conditions to a generative AI model.

[0072] In a form for carrying out the invention, this system provides a series of processes for efficiently realizing user-specific interior design. The user first collects spatial data using a terminal. This is done by inputting relevant information such as images of the room, floor plan information, budget, and desired interior style. The terminal then formats the collected information into an appropriate format and transmits it to the server.

[0073] The server analyzes the received data. Here, OpenCV or similar libraries are used to extract the physical features of the space using image analysis techniques. These extracted features play a crucial role in interior design proposals.

[0074] Next, the server uses the generated AI model to select a range of products that match the user's desired style and budget. At this time, specific instructions such as "Please select furniture suitable for a Scandinavian-style living room within the budget" are input to the AI ​​model as prompts. The selected product range is used as the basic data for generating a virtual three-dimensional space.

[0075] 3D modeling software such as Blender is used to generate the virtual three-dimensional space. This makes it possible to visually construct how the selected interior items will be placed in the space.

[0076] The generated virtual space is presented to the user via a terminal. The user can experience this space using VR devices, etc., and intuitively check the suitability of the interior. At this stage, the user's feedback is used on the server side to re-select the product range and placement. Furthermore, the generating AI model is used again for updates, resulting in an efficient process and enabling suggestions optimized for the user.

[0077] Ultimately, if the user is satisfied with the proposal, they can proceed with purchasing the product using the terminal. This allows users to easily realize a space that suits their preferences. This entire process is a powerful tool for users to comfortably and efficiently create a space that reflects their unique style.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The user uses a terminal to input the necessary spatial data. This input includes images of the room, floor plan information, budget, and desired interior style. The terminal formats the data entered by the user and converts it into a digital format. This data is then sent to the server in an appropriate format as it is required for subsequent processing.

[0081] Step 2:

[0082] The server receives data sent from the terminal. Physical features are extracted from the received image data using image analysis libraries such as OpenCV. These features include ceiling height, wall placement, floor area, and the location of windows and doors. Once the analysis is complete, the feature information is output and used as input for the next selection step.

[0083] Step 3:

[0084] The server generates prompt messages using a generative AI model based on the analysis results, the user's desired style, and budget information. These prompt messages may include instructions such as, "Please select furniture suitable for a Scandinavian-style living room within your budget." The generative AI model then uses these prompt messages to output a list of suitable furniture and decorative items.

[0085] Step 4:

[0086] The server generates a virtual three-dimensional space using a list of furniture selected by a generated AI model. 3D modeling software such as Blender is used for this generation. The server creates virtual space data while considering the placement and combination of furniture. This data is prepared for the user to visually review.

[0087] Step 5:

[0088] The server sends the generated virtual three-dimensional space data to the terminal. The terminal provides a viewing interface on a VR headset or display to facilitate the user's experience of this virtual space. The user can check the layout and style of the interior in the virtual space and input improvements and feedback into the terminal.

[0089] Step 6:

[0090] Upon receiving the feedback, the server uses the generated AI model again to adjust the suggested furniture and its placement. This process results in the optimal interior layout that aligns with the user's preferences. The adjusted results are then sent back to the terminal for the user to confirm.

[0091] Step 7:

[0092] If the user is satisfied with the final proposal, they can proceed with purchasing the selected products on their device. This will result in the actual installation of the proposed interior design, completing the creation of an efficient living space.

[0093] (Application Example 1)

[0094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] The goal is to provide a system that efficiently utilizes limited space and allows users to visually experience and select interior designs that meet their diverse needs. Furthermore, it is essential to quickly and effectively update the proposed designs based on user feedback. This will improve user satisfaction and support decision-making in interior design selection.

[0096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0097] In this invention, the server includes input means for collecting spatial data, analysis means for analyzing the input spatial data and extracting the physical characteristics of the space, selection means for selecting a group of products based on a desired decorative style and budget, generation means for generating a virtual three-dimensional space in which the selected group of products are arranged, visualization means for providing an experience in a digital environment, feedback means for obtaining user feedback on the displayed virtual three-dimensional space, and automatic generation means for generating prompt sentences and proposing new interior designs using a generation AI model. As a result, users can visually confirm the optimal interior design based on their individual preferences through an interior experience in a virtual space and flexibly adjust the design with real-time feedback.

[0098] "Input means for collecting spatial data" refers to devices or interfaces for users to register information such as photos of rooms, floor plans, budgets, and style preferences.

[0099] "Analysis means for analyzing input spatial data and extracting the physical characteristics of space" refers to a program or processing system for identifying physical characteristics such as dimensions and shape from images or drawings input by the user.

[0100] "A selection method for selecting a product range based on the desired decorative style and budget" refers to an algorithm or software for generating a list of appropriate furniture and decorative items based on the user's requirements.

[0101] "Generative means for generating a virtual three-dimensional space with selected product groups arranged" refers to computer graphics technology for arranging selected interior items and representing them in 3D.

[0102] "Display means for displaying a virtual three-dimensional space" refers to display devices or VR devices that visually present the generated 3D model to the user.

[0103] "Visualization means for providing experiences in a digital environment" refers to interfaces and technologies that allow users to interactively manipulate virtual spaces and obtain realistic experiences.

[0104] "Feedback means for obtaining user feedback on the displayed virtual three-dimensional space" refers to functions or devices that allow users to evaluate a proposed design and provide opinions and feedback.

[0105] "An automated generation method for generating prompt text and proposing new interior designs using a generation AI model" refers to a system or method that uses AI technology to create new design proposals and present them to users.

[0106] The system for realizing this invention is initiated by the user using a device such as a smartphone or tablet. First, the user inputs photos of the room they want to decorate, floor plan data, budget, and desired style into the device. This data is then transmitted to a server in the cloud via the internet.

[0107] The server processes the submitted photos of the room using image analysis techniques and extracts physical features (e.g., room shape, size, window placement, etc.). At this stage, a deep learning library such as TENSORFLOW® may be used.

[0108] Next, the server considers the user's desired style and budget, and uses a selection method to list appropriate interior products. Here, furniture and decorative items that match the selection criteria are extracted from the database.

[0109] Subsequently, the selected products are placed in a virtual three-dimensional space using a 3D engine such as Unity, and the visualization is transmitted to the user's terminal. At this stage, the virtual space must be user-friendly and interactively operable.

[0110] The user carefully examines the virtual space presented on their device and provides feedback. This feedback is sent to the server, where an automated generation system generates prompt text, which is then used by a generation AI model to update the design. For example, if the user provides feedback such as "I want to make it a more relaxing space," the generation AI model will receive a prompt such as "How can I create a relaxing space?"

[0111] Ultimately, if the user is satisfied with the proposed design, they can easily proceed with the purchase. Overall, this process efficiently supports the user in choosing interior design elements and provides a realistic design experience.

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] Users input spatial data such as photos of their rooms, floor plans, budget, and style preferences using their smartphones or tablets, and send this data to a server in the cloud. This data is then sent directly to the server and prepared for the next analysis process.

[0115] Step 2:

[0116] The server analyzes the received room photo data using an image analysis engine (e.g., TensorFlow) to extract the physical features of the room. Here, the image data is extracted as features, and specific numerical information such as the shape and size of the room, and the location of windows and doors is obtained.

[0117] Step 3:

[0118] The server selects appropriate interior product sets from the database based on the user's specified style and budget. This process involves filtering based on the user's input data to list furniture and decorative items that meet the selection criteria, and then outputs the selection results.

[0119] Step 4:

[0120] The server uses a 3D engine such as Unity to place selected interior products in a virtual three-dimensional space and generate visualization data. The generated 3D placement data is rendered in a format viewable on the terminal and returned to the user as output.

[0121] Step 5:

[0122] Users visually review the virtual space visualizations they receive on their devices and provide feedback. They input their opinions and advice on specific interiors in text format and send that data to the server.

[0123] Step 6:

[0124] Based on user feedback, the server utilizes a generative AI model to create prompt messages and proposes new interior designs. Here, feedback data is taken as input, text is generated by the generative AI model, and the updated design proposal is presented to the user as a prompt output.

[0125] Step 7:

[0126] If the user is satisfied with the newly proposed design, they proceed with the purchase on their device. The user's final selection is processed as purchase data, and the design is completed.

[0127] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0128] This invention is a system for efficiently realizing the space desired by the user, and in addition to inputting, analyzing, generating, and displaying spatial information, it also has a function to recognize the user's emotions and optimize interior design proposals.

[0129] First, the user inputs images of the room, floor plan data, budget, and desired interior style from their device. The device then formats the data and sends it to the server. The server analyzes the received image data to identify the physical characteristics of the room. It also analyzes the floor plan to collect information on the layout of the usable space.

[0130] Next, the server uses a generative AI to create a product list, selecting the most suitable furniture and decorative items based on the user's style preferences and budget. This product list is then placed in a virtual three-dimensional space, and an interior design proposal is constructed using the generative system. The generated three-dimensional data is sent to the terminal, where the user can experience the virtual space and visually confirm the proposed interior.

[0131] A newly integrated emotion engine recognizes the user's emotions in real time while they are experiencing the virtual space. This emotion data is sent to a server, which automatically adjusts suggestions based on the user's responses. This process enables personalized interior design suggestions that align with the user's latent preferences.

[0132] For example, if a user is looking for a "relaxing modern style" for their living room, the server identifies the space through image analysis and selects furniture that matches the modern style. As the user experiences the virtual space constructed through a VR device, the emotion engine identifies emotions such as satisfaction and excitement from the user's facial expressions and voice. If the user appears restless, the server updates its suggestions based on this information, adjusting to furniture and layouts that are more relaxing.

[0133] In this way, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback. Furthermore, if they are satisfied with the final suggestion, they can complete the purchase process for the selected items using their device, and the server will automatically check inventory and arrange delivery, enabling a smooth interior design process.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The user uses a terminal to input images of the room, floor plan information, budget, and desired interior style. This information is formatted on the terminal and sent to the server.

[0137] Step 2:

[0138] The server analyzes the received image data and extracts physical features such as the dimensions and shape of the space. At the same time, it also analyzes the floor plan data to obtain layout information.

[0139] Step 3:

[0140] The server uses a generative AI to select the most suitable furniture and decorative items, taking into account the user's style preferences and budget. It then creates a product list with the selected items.

[0141] Step 4:

[0142] The server constructs a virtual three-dimensional space using a generation method based on the product list. The selected product group is placed within this space.

[0143] Step 5:

[0144] The server sends the generated virtual three-dimensional space to the terminal, and the terminal provides a visual interface to allow the user to experience that space in AR or VR.

[0145] Step 6:

[0146] While the user is experiencing the virtual space, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[0147] Step 7:

[0148] The server receives data from the emotion engine and dynamically adjusts product selection and placement based on the recognized emotions. For example, if it determines that the user is not satisfied, the server updates its recommendations.

[0149] Step 8:

[0150] If the user is satisfied with the updated proposal, they proceed with the purchase process through their device. The server processes the purchase information and automatically manages inventory checks, payment processing, delivery, and installation arrangements.

[0151] (Example 2)

[0152] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0153] Conventional interior design proposal systems lack the efficiency of designing spaces based on user preferences, and they struggle to provide personalized proposals that reflect users' emotions and latent preferences. As a result, it is difficult to create spaces that truly satisfy users.

[0154] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0155] In this invention, the server includes means for inputting spatial information, means for recognizing the user's emotions and automatically optimizing interior design suggestions based on the virtual space experience, and means for updating the product collection and its arrangement in real time based on information obtained from the emotion recognition means. This enables more efficient spatial design in line with the user's wishes and personalized interior design suggestions based on emotions.

[0156] "Spatial information" refers to data about location, layout, and decorative elements in a physical environment.

[0157] A "three-dimensional virtual space" refers to a three-dimensional, reproducible virtual environment generated on a computer.

[0158] A "product set" refers to a group of furniture and decorative items selected based on a specific spatial style or budget.

[0159] "Means for recognizing user emotions" refers to technologies that analyze emotions from a user's facial expressions and voice.

[0160] "Methods for updating in real time" refers to technologies that allow for immediate modification and change of proposals and layouts based on continuously obtained data.

[0161] "Means for automatically optimizing interior design proposals" refers to technology that dynamically adjusts the optimal interior design based on user feedback and emotional data.

[0162] This invention is a system that efficiently realizes the space desired by the user and provides personalized interior design proposals. This system comprehensively manages the input, analysis, generation, and display of spatial information and has a function to recognize the user's emotions and optimize interior design proposals.

[0163] First, the user uses a terminal to input room images, floor plan data, budget, and preferences related to interior style. Spatial information such as images and floor plans is formatted by the terminal, and the data is sent to the server. The terminal uses a computer or mobile device for information input and data formatting.

[0164] The server performs analysis based on the received spatial information. For image analysis, image recognition software is used, and for floor plan analysis, layout analysis algorithms are employed. Specific software used for image analysis includes general libraries such as OpenCV. Design software like AutoCAD is also included.

[0165] Next, the server uses a generative AI model to create a product list that matches the user's style preferences and budget. The generative AI model employs a natural language processing engine such as OpenAI® to select furniture and decorative items. As a result, a virtual three-dimensional space is constructed and visualized using modeling software such as Blender or Unity.

[0166] The generated virtual space data is sent to the terminal. The user can experience this virtual space on the terminal and visually confirm the proposed interior. Using a VR device allows for a more immersive experience. In addition, an emotion engine is incorporated to recognize emotions in real time from the facial expressions and voices the user displays during the experience.

[0167] Emotional data is sent to the server, and suggestions are automatically adjusted based on the user's response. This enables personalized suggestions that align with the user's potential preferences.

[0168] For example, if a user enters a prompt such as, "I want a calm, modern style interior for my living room. My budget is 300,000 yen," the server will use generative AI to suggest a suitable furniture list. Through this process, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. The terminal formats the input data according to the specified format. At this point, the input images are resized to the appropriate resolution, and the floor plan data is converted to a specific format. This formatted data is then passed on to subsequent processing.

[0172] Step 2:

[0173] The terminal sends the formatted data to the server. Here, the HTTP protocol is used to securely transfer the data. The data received by the server includes room images, floor plan information, budget, and style preferences. This data is then used in the subsequent analysis process.

[0174] Step 3:

[0175] The server analyzes the received image data to identify the physical features of the room. Image recognition uses libraries such as OpenCV to recognize the locations of walls and furniture. Floor plan data is also analyzed to extract layout information of the usable space. The output information includes room size, shape, and the location of existing interior furnishings.

[0176] Step 4:

[0177] The server uses a generative AI model to generate a product list optimized for the user's style preferences and budget. The generative AI model performs natural language processing based on the prompt text. The generated list consists of furniture and decorative items that match the style within the budget. This list is then used in the next step.

[0178] Step 5:

[0179] The server constructs a virtual three-dimensional space based on the generated product list. Products are placed using 3D modeling software such as Blender or Unity. The server generates three-dimensional data and prepares to send it to the terminal.

[0180] Step 6:

[0181] The terminal receives three-dimensional data transmitted from the server and allows the user to experience a virtual space. In practice, using a VR device enables the user to have an immersive experience. Based on the visually confirmed virtual space, the user can obtain information.

[0182] Step 7:

[0183] The device operates an emotion engine that recognizes the user's emotions in real time while they are experiencing the virtual space. Face API and other technologies are used for facial recognition, and speech recognition technology is utilized for voice analysis. During this process, information about the user's satisfaction level and stress level is obtained.

[0184] Step 8:

[0185] The server adjusts the interior design suggestions in real time based on emotional data transmitted from the terminal. If the user appears restless, the system automatically adjusts to more relaxing options. The final suggestion creates an optimal interior space that aligns with the user's emotions.

[0186] (Application Example 2)

[0187] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0188] When efficiently realizing the interior design desired by users, it is difficult to provide personalized suggestions that fully take into account the user's individual style and emotions. Therefore, in order to enhance user satisfaction, there is a need to provide an interior design suggestion system that can adapt to the emotional responses of individual users.

[0189] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0190] In this invention, the server includes acquisition means for collecting spatial data, analysis means for analyzing the acquired spatial data and extracting the physical characteristics of the space, selection means for selecting a group of items based on a desired decorative style and budget, and emotion recognition means for acquiring emotional information. This makes it possible to dynamically adjust interior design suggestions based on the user's emotional response and provide more personalized interior designs.

[0191] "Spatial data" refers to data that describes the physical characteristics of a room or environment, including information necessary for interior design.

[0192] "Acquisition means" refers to devices and methods used to collect spatial data from the user's environment.

[0193] "Analysis means" refers to a function for processing acquired spatial data and identifying physical characteristics.

[0194] A "selected items group" is a collection of furniture and decorative items chosen by the user based on their desired style and budget.

[0195] "Selection means" refers to a process or apparatus for selecting the optimal group of articles based on desired criteria.

[0196] A "virtual three-dimensional space" is a space visualized by arranging a selected group of items in three dimensions.

[0197] "Presentation means" refers to methods or devices for displaying the generated virtual three-dimensional space to the user.

[0198] "Emotion recognition means" refers to devices or methods for analyzing and recognizing a user's emotions in real time.

[0199] An "emotional feedback mechanism" is a function that acquires and processes the emotional responses that a user shows to a virtual 3D space.

[0200] "Adjustment means" refers to a function that adaptively modifies the proposed group of items or layout based on acquired emotional information.

[0201] This invention is a system for providing suggestions that meet the user's interior design preferences. Specific embodiments thereof are described below.

[0202] The server first receives spatial data transmitted from the user's terminal. This data includes images of the room, floor plan information, and the user's desired style and budget information. The server uses image processing software to analyze the physical characteristics of the space from this data.

[0203] Next, based on the acquired analysis information, a set of items that fit the desired style and budget is selected. Here, a generative AI model is used to propose the optimal combination from a large amount of interior design data. The selected set of items is placed in a virtual 3D space and presented visually to the user.

[0204] Users experience this virtual space using devices such as head-mounted displays. During the experience, emotion recognition software analyzes the user's facial expressions and voice in real time to recognize their emotions. The recognized emotion data is sent back to the server, and the selected items and layout are dynamically adjusted based on the user's responses.

[0205] For example, if a user desires a modern style and a relaxed atmosphere, the generating AI model will suggest furniture and arrangements that meet those criteria. An example of a prompt might be: "Based on the interior style the user has chosen for their living room, please generate personalized suggestions that reflect their satisfaction level. Considering the emotion recognition results, please suggest the optimal furniture arrangement based on a natural style."

[0206] In this way, the server provides interior design suggestions that adapt to the user's emotions in real time, enabling the efficient creation of a design space that is more satisfying to the user.

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The terminal receives room images, floor plans, desired style, and budget as input from the user, and formats this as spatial data. The formatted spatial data is then sent to the server. This ensures that the server receives input based on the user's requests.

[0210] Step 2:

[0211] The server uses image processing software to analyze the received spatial data as input. Here, it identifies the physical characteristics and layout of the room and outputs this as structural data. This results in data tailored to the user's environment.

[0212] Step 3:

[0213] The server uses an AI model that generates data based on structural data, user style, and budget to select a group of items. The selection results are output as suggested data, forming the foundation of the virtual 3D space. Here, the optimal combination is generated from a large amount of interior design data.

[0214] Step 4:

[0215] The server sends virtual 3D space data containing the selected items to the terminal. The terminal receives this data, and the user experiences it through a head-mounted display. In this step, the user can visually confirm the selected interior.

[0216] Step 5:

[0217] While the user is experiencing the virtual space, the terminal uses emotion recognition software to analyze the user's facial expressions and voice. The analyzed emotion data is sent to a server. This allows the user's emotions to be obtained in real time.

[0218] Step 6:

[0219] The server re-evaluates the suggested data using emotional data as input and dynamically adjusts the item group and its placement using a generative AI model. The updated suggested data is then sent to the terminal. This results in interior design suggestions that are adapted to the user's emotions.

[0220] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0221] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0222] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0223] [Second Embodiment]

[0224] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0225] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0226] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0227] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0228] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0229] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0230] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0231] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0232] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0233] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0234] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0235] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0236] This invention provides a system that enables users to effectively utilize limited space and realize interiors tailored to their individual preferences. This system primarily includes means for collecting, analyzing, selecting, generating, and displaying spatial data, thereby proposing an optimal interior design that meets the user's needs.

[0237] When starting to use the system, the user inputs images of the room, floor plan data, budget, and style preferences using a terminal. The terminal formats this data and sends it to the server. The server processes the input image data using image analysis technology and extracts the physical characteristics of the room. Next, based on this data, the server selects appropriate furniture and decorations, taking into account the user's desired style and budget.

[0238] The furniture selected by the selection method is constructed as a virtual three-dimensional space by the generation method. The server sends this data to the terminal, which provides the user with an environment in which they can visually confirm the virtual space. At this stage, the user can experience the virtual space through the terminal and provide feedback.

[0239] As a concrete example, consider a case where a user wants to decorate their living room in a "Nordic style." The user inputs a photo of the room and their desired style into their device. The server recognizes it as a Nordic style and lists warm wooden furniture and simple decorations within the budget. Next, the user uses a VR device to simulate the generated 3D layout plan. Through this simulation, the user checks how the selected furniture fits into the space and, if necessary, inputs feedback into the device, which the server then adjusts the layout plan.

[0240] If the user is ultimately satisfied with the proposal, they can complete the purchase process on their terminal, completing the efficient interior coordination and implementation throughout the entire system. In this way, users can easily create a space that suits their own style and lifestyle.

[0241] The following describes the processing flow.

[0242] Step 1:

[0243] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. This information is received by the terminal, formatted in the appropriate format, and then sent to the server.

[0244] Step 2:

[0245] The server uses computer vision technology to analyze the received image data and extract the physical features and dimensions of the room. It also analyzes the floor plan data and organizes the spatial layout information.

[0246] Step 3:

[0247] The server uses natural language processing technology to estimate the user's style preferences and budget information. Then, using generative AI, it selects the most suitable furniture and decorative items based on this information and creates a product list.

[0248] Step 4:

[0249] The server uses a generation mechanism to place the selected product list in a virtual three-dimensional space, constructing an interior layout plan. This data is converted into a three-dimensional model and prepared for the user to visually review.

[0250] Step 5:

[0251] The server sends the generated 3D data to the terminal. The terminal receives this data and displays a virtual interior space to the user through an AR or VR device, providing an environment that simulates how it would look in the actual space.

[0252] Step 6:

[0253] The user reviews the displayed virtual space and inputs feedback on the furniture selection and placement, including opinions and suggestions for improvement, into the terminal.

[0254] Step 7:

[0255] The terminal sends user feedback to the server. Based on this feedback, the server updates the selected product group and its deployment plan as needed, and then proposes it to the user again.

[0256] Step 8:

[0257] If the user is satisfied with the proposal and decides to purchase, they proceed with the purchase process from their terminal. The server manages the information necessary for the purchase process and automatically handles inventory checks for the selected items, payment processing, and arrangements for delivery and installation.

[0258] (Example 1)

[0259] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0260] In modern living environments, there is a demand for the effective use of limited space and the realization of interiors that suit the lifestyles and preferences of individual users. However, existing systems require considerable effort to extract physical characteristics and select interior design candidates, making it difficult for users to easily create their ideal space. This invention aims to solve these problems and provide a system that allows for the efficient and intuitive design of interiors tailored to individual desires.

[0261] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0262] In this invention, the server comprises an input device means for collecting spatial data, an analysis device means for analyzing the collected spatial data and extracting physical features, a selection device means for selecting a group of products based on a desired decorative style and budget, a generation device means for generating a virtual three-dimensional space using the selected group of products, a display device means for displaying the generated virtual three-dimensional space, and a feedback device means for obtaining user feedback on the displayed virtual three-dimensional space. Furthermore, it includes an update device means for updating the group of products and their arrangement using a generation AI model based on the feedback obtained from the feedback means. This enables the proposal and adjustment of practical and user-optimized interiors.

[0263] "Spatial data" refers to data that includes physical information and characteristics related to residential and commercial spaces, and may include image data and floor plan information.

[0264] An "input device" is a device or interface that provides functions for users to easily input spatial data into a system.

[0265] An "analysis device" is a computer program or system configuration that has the function of processing input spatial data and extracting its physical characteristics.

[0266] A "selection device" is a component of a system that selects a range of products that match a specific decorative style and budget based on extracted characteristics.

[0267] A "generation device" is a program or hardware configuration that uses a selected group of products to create a virtual three-dimensional space.

[0268] A "display device" is a device or software that visualizes a generated virtual three-dimensional space, allowing users to visually confirm that space.

[0269] A "feedback device" is a mechanism or system configuration for collecting user opinions and suggestions for improvement regarding the displayed virtual three-dimensional space.

[0270] A "renewal device" is part of a system that uses a generated AI model to modify the product group and its placement based on information obtained through feedback.

[0271] A "generative AI model" is an algorithm or model that utilizes machine learning technology to propose the optimal interior design plan based on the input conditions.

[0272] A "prompt statement" is a text-based instruction that provides specific instructions or conditions to a generative AI model.

[0273] In a form for carrying out the invention, this system provides a series of processes for efficiently realizing user-specific interior design. The user first collects spatial data using a terminal. This is done by inputting relevant information such as images of the room, floor plan information, budget, and desired interior style. The terminal then formats the collected information into an appropriate format and transmits it to the server.

[0274] The server analyzes the received data. Here, OpenCV or similar libraries are used to extract the physical features of the space using image analysis techniques. These extracted features play a crucial role in interior design proposals.

[0275] Next, the server uses the generated AI model to select a range of products that match the user's desired style and budget. At this time, specific instructions such as "Please select furniture suitable for a Scandinavian-style living room within the budget" are input to the AI ​​model as prompts. The selected product range is used as the basic data for generating a virtual three-dimensional space.

[0276] 3D modeling software such as Blender is used to generate the virtual three-dimensional space. This makes it possible to visually construct how the selected interior items will be placed in the space.

[0277] The generated virtual space is presented to the user via a terminal. The user can experience this space using VR devices, etc., and intuitively check the suitability of the interior. At this stage, the user's feedback is used on the server side to re-select the product range and placement. Furthermore, the generating AI model is used again for updates, resulting in an efficient process and enabling suggestions optimized for the user.

[0278] Ultimately, if the user is satisfied with the proposal, they can proceed with purchasing the product using the terminal. This allows users to easily realize a space that suits their preferences. This entire process is a powerful tool for users to comfortably and efficiently create a space that reflects their unique style.

[0279] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0280] Step 1:

[0281] The user uses a terminal to input the necessary spatial data. This input includes images of the room, floor plan information, budget, and desired interior style. The terminal formats the data entered by the user and converts it into a digital format. This data is then sent to the server in an appropriate format as it is required for subsequent processing.

[0282] Step 2:

[0283] The server receives data sent from the terminal. For the received image data, physical features are extracted using an image analysis library such as OpenCV. What is extracted here are the ceiling height, wall arrangement, floor area, positions of windows and doors, etc. After the analysis is completed, feature information is output and used as the input for the next selection step.

[0284] Step 3:

[0285] Based on the analysis results, the user's desired style, and budget information, the server generates a prompt sentence using a generative AI model. The prompt sentence includes instructions such as "Please select furniture suitable for a Nordic-style living room within the budget". The generative AI model uses this prompt sentence to output a list of suitable furniture and decorations.

[0286] Step 4:

[0287] The server uses the list of furniture selected by the generative AI model to generate a virtual three-dimensional space. For this generation, 3D modeling software such as Blender is used. The server creates virtual space data while considering the arrangement and combination of furniture. This data is prepared for the user to visually confirm.

[0288] Step 5:

[0289] The server sends the generated virtual three-dimensional space data to the terminal. The terminal provides a confirmation interface on a VR headset or display so that the user can easily experience this virtual space. The user can check the interior arrangement and style in the virtual space and input improvement points and feedback to the terminal.

[0290] Step 6:

[0291] Upon receiving the feedback, the server uses the generated AI model again to adjust the suggested furniture and its placement. This process results in the optimal interior layout that aligns with the user's preferences. The adjusted results are then sent back to the terminal for the user to confirm.

[0292] Step 7:

[0293] If the user is satisfied with the final proposal, they can proceed with purchasing the selected products on their device. This will result in the actual installation of the proposed interior design, completing the creation of an efficient living space.

[0294] (Application Example 1)

[0295] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0296] The goal is to provide a system that efficiently utilizes limited space and allows users to visually experience and select interior designs that meet their diverse needs. Furthermore, it is essential to quickly and effectively update the proposed designs based on user feedback. This will improve user satisfaction and support decision-making in interior design selection.

[0297] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0298] In this invention, the server includes input means for collecting spatial data, analysis means for analyzing the input spatial data and extracting the physical characteristics of the space, selection means for selecting a group of products based on a desired decorative style and budget, generation means for generating a virtual three-dimensional space in which the selected group of products are arranged, visualization means for providing an experience in a digital environment, feedback means for obtaining user feedback on the displayed virtual three-dimensional space, and automatic generation means for generating prompt sentences and proposing new interior designs using a generation AI model. As a result, users can visually confirm the optimal interior design based on their individual preferences through an interior experience in a virtual space and flexibly adjust the design with real-time feedback.

[0299] "Input means for collecting spatial data" refers to devices or interfaces for users to register information such as photos of rooms, floor plans, budgets, and style preferences.

[0300] "Analysis means for analyzing input spatial data and extracting the physical characteristics of space" refers to a program or processing system for identifying physical characteristics such as dimensions and shape from images or drawings input by the user.

[0301] "A selection method for selecting a product range based on the desired decorative style and budget" refers to an algorithm or software for generating a list of appropriate furniture and decorative items based on the user's requirements.

[0302] "Generative means for generating a virtual three-dimensional space with selected product groups arranged" refers to computer graphics technology for arranging selected interior items and representing them in 3D.

[0303] "Display means for displaying a virtual three-dimensional space" refers to display devices or VR devices that visually present the generated 3D model to the user.

[0304] "Visualization means for providing an experience in a digital environment" refers to an interface or technology that allows users to interactively manipulate a virtual space and obtain a real experience.

[0305] "Feedback means for obtaining feedback from users on the displayed virtual three-dimensional space" refers to a function or device that allows users to evaluate a proposed design and provide opinions and feelings.

[0306] "Automatic generation means for generating prompt sentences and using a generation AI model to propose a new interior design" refers to a system or method that uses AI technology to create a new design proposal and present it to users.

[0307] The system for realizing this invention is initiated when a user uses a terminal such as a smartphone or tablet. First, the user inputs a photo of the room for which they want to coordinate the interior, floor plan data, budget, and style preferences into the terminal. These data are transmitted to a server on the cloud via the Internet.

[0308] The server uses image analysis technology to process the transmitted photo of the room and extracts physical features (e.g., room shape, size, window position, etc.). At this stage, a deep learning library such as TensorFlow may be used.

[0309] Next, the server lists up appropriate interior products using a selection means, taking into account the style and budget desired by the user. Here, furniture and decorations that meet the selection criteria are extracted from the database.

[0310] After that, the selected products are placed in a virtual three-dimensional space using a 3D engine such as Unity and transmitted to the user's terminal by the visualization means. At this time, the virtual space is required to be easy for the user to view and operable interactively.

[0311] The user carefully examines the virtual space presented on their device and provides feedback. This feedback is sent to the server, where an automated generation system generates prompt text, which is then used by a generation AI model to update the design. For example, if the user provides feedback such as "I want to make it a more relaxing space," the generation AI model will receive a prompt such as "How can I create a relaxing space?"

[0312] Ultimately, if the user is satisfied with the proposed design, they can easily proceed with the purchase. Overall, this process efficiently supports the user in choosing interior design elements and provides a realistic design experience.

[0313] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0314] Step 1:

[0315] Users input spatial data such as photos of their rooms, floor plans, budget, and style preferences using their smartphones or tablets, and send this data to a server in the cloud. This data is then sent directly to the server and prepared for the next analysis process.

[0316] Step 2:

[0317] The server analyzes the received room photo data using an image analysis engine (e.g., TensorFlow) to extract the physical features of the room. Here, the image data is extracted as features, and specific numerical information such as the shape and size of the room, and the location of windows and doors is obtained.

[0318] Step 3:

[0319] The server selects appropriate interior product sets from the database based on the user's specified style and budget. This process involves filtering based on the user's input data to list furniture and decorative items that meet the selection criteria, and then outputs the selection results.

[0320] Step 4:

[0321] The server uses a 3D engine such as Unity to place selected interior products in a virtual three-dimensional space and generate visualization data. The generated 3D placement data is rendered in a format viewable on the terminal and returned to the user as output.

[0322] Step 5:

[0323] Users visually review the virtual space visualizations they receive on their devices and provide feedback. They input their opinions and advice on specific interiors in text format and send that data to the server.

[0324] Step 6:

[0325] Based on user feedback, the server utilizes a generative AI model to create prompt messages and proposes new interior designs. Here, feedback data is taken as input, text is generated by the generative AI model, and the updated design proposal is presented to the user as a prompt output.

[0326] Step 7:

[0327] If the user is satisfied with the newly proposed design, they proceed with the purchase on their device. The user's final selection is processed as purchase data, and the design is completed.

[0328] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0329] This invention is a system for efficiently realizing the space desired by the user, and in addition to inputting, analyzing, generating, and displaying spatial information, it also has a function to recognize the user's emotions and optimize interior design proposals.

[0330] First, the user inputs images of the room, floor plan data, budget, and desired interior style from their device. The device then formats the data and sends it to the server. The server analyzes the received image data to identify the physical characteristics of the room. It also analyzes the floor plan to collect information on the layout of the usable space.

[0331] Next, the server uses a generative AI to create a product list, selecting the most suitable furniture and decorative items based on the user's style preferences and budget. This product list is then placed in a virtual three-dimensional space, and an interior design proposal is constructed using the generative system. The generated three-dimensional data is sent to the terminal, where the user can experience the virtual space and visually confirm the proposed interior.

[0332] A newly integrated emotion engine recognizes the user's emotions in real time while they are experiencing the virtual space. This emotion data is sent to a server, which automatically adjusts suggestions based on the user's responses. This process enables personalized interior design suggestions that align with the user's latent preferences.

[0333] For example, if a user is looking for a "relaxing modern style" for their living room, the server identifies the space through image analysis and selects furniture that matches the modern style. As the user experiences the virtual space constructed through a VR device, the emotion engine identifies emotions such as satisfaction and excitement from the user's facial expressions and voice. If the user appears restless, the server updates its suggestions based on this information, adjusting to furniture and layouts that are more relaxing.

[0334] In this way, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback. Furthermore, if they are satisfied with the final suggestion, they can complete the purchase process for the selected items using their device, and the server will automatically check inventory and arrange delivery, enabling a smooth interior design process.

[0335] The following describes the processing flow.

[0336] Step 1:

[0337] The user uses a terminal to input images of the room, floor plan information, budget, and desired interior style. This information is formatted on the terminal and sent to the server.

[0338] Step 2:

[0339] The server analyzes the received image data and extracts physical features such as the dimensions and shape of the space. At the same time, it also analyzes the floor plan data to obtain layout information.

[0340] Step 3:

[0341] The server uses a generative AI to select the most suitable furniture and decorative items, taking into account the user's style preferences and budget. It then creates a product list with the selected items.

[0342] Step 4:

[0343] The server constructs a virtual three-dimensional space using a generation method based on the product list. The selected product group is placed within this space.

[0344] Step 5:

[0345] The server sends the generated virtual three-dimensional space to the terminal, and the terminal provides a visual interface to allow the user to experience that space in AR or VR.

[0346] Step 6:

[0347] While the user is experiencing the virtual space, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[0348] Step 7:

[0349] The server receives data from the emotion engine and dynamically adjusts product selection and placement based on the recognized emotions. For example, if it determines that the user is not satisfied, the server updates its recommendations.

[0350] Step 8:

[0351] If the user is satisfied with the updated proposal, they proceed with the purchase process through their device. The server processes the purchase information and automatically manages inventory checks, payment processing, delivery, and installation arrangements.

[0352] (Example 2)

[0353] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0354] Conventional interior design proposal systems lack the efficiency of designing spaces based on user preferences, and they struggle to provide personalized proposals that reflect users' emotions and latent preferences. As a result, it is difficult to create spaces that truly satisfy users.

[0355] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0356] In this invention, the server includes means for inputting spatial information, means for recognizing the user's emotions and automatically optimizing interior design suggestions based on the virtual space experience, and means for updating the product collection and its arrangement in real time based on information obtained from the emotion recognition means. This enables more efficient spatial design in line with the user's wishes and personalized interior design suggestions based on emotions.

[0357] "Spatial information" refers to data about location, layout, and decorative elements in a physical environment.

[0358] A "three-dimensional virtual space" refers to a three-dimensional, reproducible virtual environment generated on a computer.

[0359] A "product set" refers to a group of furniture and decorative items selected based on a specific spatial style or budget.

[0360] "Means for recognizing user emotions" refers to technologies that analyze emotions from a user's facial expressions and voice.

[0361] "Methods for updating in real time" refers to technologies that allow for immediate modification and change of proposals and layouts based on continuously obtained data.

[0362] "Means for automatically optimizing interior design proposals" refers to technology that dynamically adjusts the optimal interior design based on user feedback and emotional data.

[0363] This invention is a system that efficiently realizes the space desired by the user and provides personalized interior design proposals. This system comprehensively manages the input, analysis, generation, and display of spatial information and has a function to recognize the user's emotions and optimize interior design proposals.

[0364] First, the user uses a terminal to input room images, floor plan data, budget, and preferences related to interior style. Spatial information such as images and floor plans is formatted by the terminal, and the data is sent to the server. The terminal uses a computer or mobile device for information input and data formatting.

[0365] The server performs analysis based on the received spatial information. For image analysis, image recognition software is used, and for floor plan analysis, layout analysis algorithms are employed. Specific software used for image analysis includes general libraries such as OpenCV. Design software like AutoCAD is also included.

[0366] Next, the server uses a generative AI model to create a product list that matches the user's style preferences and budget. The generative AI model employs a natural language processing engine such as OpenAI to select furniture and decorative items. As a result, a virtual three-dimensional space is constructed and visualized using modeling software such as Blender or Unity.

[0367] The generated virtual space data is sent to the terminal. The user can experience this virtual space on the terminal and visually confirm the proposed interior. Using a VR device allows for a more immersive experience. In addition, an emotion engine is incorporated to recognize emotions in real time from the facial expressions and voices the user displays during the experience.

[0368] Emotional data is sent to the server, and suggestions are automatically adjusted based on the user's response. This enables personalized suggestions that align with the user's potential preferences.

[0369] For example, if a user enters a prompt such as, "I want a calm, modern style interior for my living room. My budget is 300,000 yen," the server will use generative AI to suggest a suitable furniture list. Through this process, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback.

[0370] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0371] Step 1:

[0372] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. The terminal formats the input data according to the specified format. At this point, the input images are resized to the appropriate resolution, and the floor plan data is converted to a specific format. This formatted data is then passed on to subsequent processing.

[0373] Step 2:

[0374] The terminal sends the formatted data to the server. Here, the HTTP protocol is used to securely transfer the data. The data received by the server includes room images, floor plan information, budget, and style preferences. This data is then used in the subsequent analysis process.

[0375] Step 3:

[0376] The server analyzes the received image data to identify the physical features of the room. Image recognition uses libraries such as OpenCV to recognize the locations of walls and furniture. Floor plan data is also analyzed to extract layout information of the usable space. The output information includes room size, shape, and the location of existing interior furnishings.

[0377] Step 4:

[0378] The server uses a generative AI model to generate a product list optimized for the user's style preferences and budget. The generative AI model performs natural language processing based on the prompt text. The generated list consists of furniture and decorative items that match the style within the budget. This list is then used in the next step.

[0379] Step 5:

[0380] The server constructs a virtual three-dimensional space based on the generated product list. Products are placed using 3D modeling software such as Blender or Unity. The server generates three-dimensional data and prepares to send it to the terminal.

[0381] Step 6:

[0382] The terminal receives three-dimensional data transmitted from the server and allows the user to experience a virtual space. In practice, using a VR device enables the user to have an immersive experience. Based on the visually confirmed virtual space, the user can obtain information.

[0383] Step 7:

[0384] The device operates an emotion engine that recognizes the user's emotions in real time while they are experiencing the virtual space. Face API and other technologies are used for facial recognition, and speech recognition technology is utilized for voice analysis. During this process, information about the user's satisfaction level and stress level is obtained.

[0385] Step 8:

[0386] The server adjusts the interior design suggestions in real time based on emotional data transmitted from the terminal. If the user appears restless, the system automatically adjusts to more relaxing options. The final suggestion creates an optimal interior space that aligns with the user's emotions.

[0387] (Application Example 2)

[0388] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0389] When efficiently realizing the interior design desired by users, it is difficult to provide personalized suggestions that fully take into account the user's individual style and emotions. Therefore, in order to enhance user satisfaction, there is a need to provide an interior design suggestion system that can adapt to the emotional responses of individual users.

[0390] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0391] In this invention, the server includes acquisition means for collecting spatial data, analysis means for analyzing the acquired spatial data and extracting the physical characteristics of the space, selection means for selecting a group of items based on a desired decorative style and budget, and emotion recognition means for acquiring emotional information. This makes it possible to dynamically adjust interior design suggestions based on the user's emotional response and provide more personalized interior designs.

[0392] "Spatial data" refers to data that describes the physical characteristics of a room or environment, including information necessary for interior design.

[0393] "Acquisition means" refers to devices and methods used to collect spatial data from the user's environment.

[0394] "Analysis means" refers to a function for processing acquired spatial data and identifying physical characteristics.

[0395] A "selected items group" is a collection of furniture and decorative items chosen by the user based on their desired style and budget.

[0396] "Selection means" refers to a process or apparatus for selecting the optimal group of articles based on desired criteria.

[0397] A "virtual three-dimensional space" is a space visualized by arranging a selected group of items in three dimensions.

[0398] "Presentation means" refers to methods or devices for displaying the generated virtual three-dimensional space to the user.

[0399] "Emotion recognition means" refers to devices or methods for analyzing and recognizing a user's emotions in real time.

[0400] An "emotional feedback mechanism" is a function that acquires and processes the emotional responses that a user shows to a virtual 3D space.

[0401] "Adjustment means" refers to a function that adaptively modifies the proposed group of items or layout based on acquired emotional information.

[0402] This invention is a system for providing suggestions that meet the user's interior design preferences. Specific embodiments thereof are described below.

[0403] The server first receives spatial data transmitted from the user's terminal. This data includes images of the room, floor plan information, and the user's desired style and budget information. The server uses image processing software to analyze the physical characteristics of the space from this data.

[0404] Next, based on the acquired analysis information, a set of items that fit the desired style and budget is selected. Here, a generative AI model is used to propose the optimal combination from a large amount of interior design data. The selected set of items is placed in a virtual 3D space and presented visually to the user.

[0405] Users experience this virtual space using devices such as head-mounted displays. During the experience, emotion recognition software analyzes the user's facial expressions and voice in real time to recognize their emotions. The recognized emotion data is sent back to the server, and the selected items and layout are dynamically adjusted based on the user's responses.

[0406] For example, if a user desires a modern style and a relaxed atmosphere, the generating AI model will suggest furniture and arrangements that meet those criteria. An example of a prompt might be: "Based on the interior style the user has chosen for their living room, please generate personalized suggestions that reflect their satisfaction level. Considering the emotion recognition results, please suggest the optimal furniture arrangement based on a natural style."

[0407] In this way, the server provides interior design suggestions that adapt to the user's emotions in real time, enabling the efficient creation of a design space that is more satisfying to the user.

[0408] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0409] Step 1:

[0410] The terminal receives room images, floor plans, desired style, and budget as input from the user, and formats this as spatial data. The formatted spatial data is then sent to the server. This ensures that the server receives input based on the user's requests.

[0411] Step 2:

[0412] The server uses image processing software to analyze the received spatial data as input. Here, it identifies the physical characteristics and layout of the room and outputs this as structural data. This results in data tailored to the user's environment.

[0413] Step 3:

[0414] The server uses an AI model that generates data based on structural data, user style, and budget to select a group of items. The selection results are output as suggested data, forming the foundation of the virtual 3D space. Here, the optimal combination is generated from a large amount of interior design data.

[0415] Step 4:

[0416] The server sends virtual 3D space data containing the selected items to the terminal. The terminal receives this data, and the user experiences it through a head-mounted display. In this step, the user can visually confirm the selected interior.

[0417] Step 5:

[0418] While the user is experiencing the virtual space, the terminal uses emotion recognition software to analyze the user's facial expressions and voice. The analyzed emotion data is sent to a server. This allows the user's emotions to be obtained in real time.

[0419] Step 6:

[0420] The server re-evaluates the suggested data using emotional data as input and dynamically adjusts the item group and its placement using a generative AI model. The updated suggested data is then sent to the terminal. This results in interior design suggestions that are adapted to the user's emotions.

[0421] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0422] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0423] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0424] [Third Embodiment]

[0425] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0426] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0427] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0428] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0429] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0430] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0431] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0432] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0433] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0434] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0435] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0436] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0437] This invention provides a system that enables users to effectively utilize limited space and realize interiors tailored to their individual preferences. This system primarily includes means for collecting, analyzing, selecting, generating, and displaying spatial data, thereby proposing an optimal interior design that meets the user's needs.

[0438] When starting to use the system, the user inputs images of the room, floor plan data, budget, and style preferences using a terminal. The terminal formats this data and sends it to the server. The server processes the input image data using image analysis technology and extracts the physical characteristics of the room. Next, based on this data, the server selects appropriate furniture and decorations, taking into account the user's desired style and budget.

[0439] The furniture selected by the selection method is constructed as a virtual three-dimensional space by the generation method. The server sends this data to the terminal, which provides the user with an environment in which they can visually confirm the virtual space. At this stage, the user can experience the virtual space through the terminal and provide feedback.

[0440] As a concrete example, consider a case where a user wants to decorate their living room in a "Nordic style." The user inputs a photo of the room and their desired style into their device. The server recognizes it as a Nordic style and lists warm wooden furniture and simple decorations within the budget. Next, the user uses a VR device to simulate the generated 3D layout plan. Through this simulation, the user checks how the selected furniture fits into the space and, if necessary, inputs feedback into the device, which the server then adjusts the layout plan.

[0441] If the user is ultimately satisfied with the proposal, they can complete the purchase process on their terminal, completing the efficient interior coordination and implementation throughout the entire system. In this way, users can easily create a space that suits their own style and lifestyle.

[0442] The following describes the processing flow.

[0443] Step 1:

[0444] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. This information is received by the terminal, formatted in the appropriate format, and then sent to the server.

[0445] Step 2:

[0446] The server uses computer vision technology to analyze the received image data and extract the physical features and dimensions of the room. It also analyzes the floor plan data and organizes the spatial layout information.

[0447] Step 3:

[0448] The server uses natural language processing technology to estimate the user's style preferences and budget information. Then, using generative AI, it selects the most suitable furniture and decorative items based on this information and creates a product list.

[0449] Step 4:

[0450] The server uses a generation mechanism to place the selected product list in a virtual three-dimensional space, constructing an interior layout plan. This data is converted into a three-dimensional model and prepared for the user to visually review.

[0451] Step 5:

[0452] The server sends the generated 3D data to the terminal. The terminal receives this data and displays a virtual interior space to the user through an AR or VR device, providing an environment that simulates how it would look in the actual space.

[0453] Step 6:

[0454] The user reviews the displayed virtual space and inputs feedback on the furniture selection and placement, including opinions and suggestions for improvement, into the terminal.

[0455] Step 7:

[0456] The terminal sends user feedback to the server. Based on this feedback, the server updates the selected product group and its deployment plan as needed, and then proposes it to the user again.

[0457] Step 8:

[0458] If the user is satisfied with the proposal and decides to purchase, they proceed with the purchase process from their terminal. The server manages the information necessary for the purchase process and automatically handles inventory checks for the selected items, payment processing, and arrangements for delivery and installation.

[0459] (Example 1)

[0460] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0461] In modern living environments, there is a demand for the effective use of limited space and the realization of interiors that suit the lifestyles and preferences of individual users. However, existing systems require considerable effort to extract physical characteristics and select interior design candidates, making it difficult for users to easily create their ideal space. This invention aims to solve these problems and provide a system that allows for the efficient and intuitive design of interiors tailored to individual desires.

[0462] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0463] In this invention, the server comprises an input device means for collecting spatial data, an analysis device means for analyzing the collected spatial data and extracting physical features, a selection device means for selecting a group of products based on a desired decorative style and budget, a generation device means for generating a virtual three-dimensional space using the selected group of products, a display device means for displaying the generated virtual three-dimensional space, and a feedback device means for obtaining user feedback on the displayed virtual three-dimensional space. Furthermore, it includes an update device means for updating the group of products and their arrangement using a generation AI model based on the feedback obtained from the feedback means. This enables the proposal and adjustment of practical and user-optimized interiors.

[0464] "Spatial data" refers to data that includes physical information and characteristics related to residential and commercial spaces, and may include image data and floor plan information.

[0465] An "input device" is a device or interface that provides functions for users to easily input spatial data into a system.

[0466] An "analysis device" is a computer program or system configuration that has the function of processing input spatial data and extracting its physical characteristics.

[0467] A "selection device" is a component of a system that selects a range of products that match a specific decorative style and budget based on extracted characteristics.

[0468] A "generation device" is a program or hardware configuration that uses a selected group of products to create a virtual three-dimensional space.

[0469] A "display device" is a device or software that visualizes a generated virtual three-dimensional space, allowing users to visually confirm that space.

[0470] A "feedback device" is a mechanism or system configuration for collecting user opinions and suggestions for improvement regarding the displayed virtual three-dimensional space.

[0471] A "renewal device" is part of a system that uses a generated AI model to modify the product group and its placement based on information obtained through feedback.

[0472] A "generative AI model" is an algorithm or model that utilizes machine learning technology to propose the optimal interior design plan based on the input conditions.

[0473] A "prompt statement" is a text-based instruction that provides specific instructions or conditions to a generative AI model.

[0474] In a form for carrying out the invention, this system provides a series of processes for efficiently realizing user-specific interior design. The user first collects spatial data using a terminal. This is done by inputting relevant information such as images of the room, floor plan information, budget, and desired interior style. The terminal then formats the collected information into an appropriate format and transmits it to the server.

[0475] The server analyzes the received data. Here, OpenCV or similar libraries are used to extract the physical features of the space using image analysis techniques. These extracted features play a crucial role in interior design proposals.

[0476] Next, the server uses the generated AI model to select a range of products that match the user's desired style and budget. At this time, specific instructions such as "Please select furniture suitable for a Scandinavian-style living room within the budget" are input to the AI ​​model as prompts. The selected product range is used as the basic data for generating a virtual three-dimensional space.

[0477] 3D modeling software such as Blender is used to generate the virtual three-dimensional space. This makes it possible to visually construct how the selected interior items will be placed in the space.

[0478] The generated virtual space is presented to the user via a terminal. The user can experience this space using VR devices, etc., and intuitively check the suitability of the interior. At this stage, the user's feedback is used on the server side to re-select the product range and placement. Furthermore, the generating AI model is used again for updates, resulting in an efficient process and enabling suggestions optimized for the user.

[0479] Ultimately, if the user is satisfied with the proposal, they can proceed with purchasing the product using the terminal. This allows users to easily realize a space that suits their preferences. This entire process is a powerful tool for users to comfortably and efficiently create a space that reflects their unique style.

[0480] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0481] Step 1:

[0482] The user uses a terminal to input the necessary spatial data. This input includes images of the room, floor plan information, budget, and desired interior style. The terminal formats the data entered by the user and converts it into a digital format. This data is then sent to the server in an appropriate format as it is required for subsequent processing.

[0483] Step 2:

[0484] The server receives data sent from the terminal. Physical features are extracted from the received image data using image analysis libraries such as OpenCV. These features include ceiling height, wall placement, floor area, and the location of windows and doors. Once the analysis is complete, the feature information is output and used as input for the next selection step.

[0485] Step 3:

[0486] The server generates prompt messages using a generative AI model based on the analysis results, the user's desired style, and budget information. These prompt messages may include instructions such as, "Please select furniture suitable for a Scandinavian-style living room within your budget." The generative AI model then uses these prompt messages to output a list of suitable furniture and decorative items.

[0487] Step 4:

[0488] The server generates a virtual three-dimensional space using a list of furniture selected by a generated AI model. 3D modeling software such as Blender is used for this generation. The server creates virtual space data while considering the placement and combination of furniture. This data is prepared for the user to visually review.

[0489] Step 5:

[0490] The server sends the generated virtual three-dimensional space data to the terminal. The terminal provides a viewing interface on a VR headset or display to facilitate the user's experience of this virtual space. The user can check the layout and style of the interior in the virtual space and input improvements and feedback into the terminal.

[0491] Step 6:

[0492] Upon receiving the feedback, the server uses the generated AI model again to adjust the suggested furniture and its placement. This process results in the optimal interior layout that aligns with the user's preferences. The adjusted results are then sent back to the terminal for the user to confirm.

[0493] Step 7:

[0494] If the user is satisfied with the final proposal, they can proceed with purchasing the selected products on their device. This will result in the actual installation of the proposed interior design, completing the creation of an efficient living space.

[0495] (Application Example 1)

[0496] Next, we will explain Application Example 1. In the following explanation, 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."

[0497] The goal is to provide a system that efficiently utilizes limited space and allows users to visually experience and select interior designs that meet their diverse needs. Furthermore, it is essential to quickly and effectively update the proposed designs based on user feedback. This will improve user satisfaction and support decision-making in interior design selection.

[0498] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0499] In this invention, the server includes input means for collecting spatial data, analysis means for analyzing the input spatial data and extracting the physical characteristics of the space, selection means for selecting a group of products based on a desired decorative style and budget, generation means for generating a virtual three-dimensional space in which the selected group of products are arranged, visualization means for providing an experience in a digital environment, feedback means for obtaining user feedback on the displayed virtual three-dimensional space, and automatic generation means for generating prompt sentences and proposing new interior designs using a generation AI model. As a result, users can visually confirm the optimal interior design based on their individual preferences through an interior experience in a virtual space and flexibly adjust the design with real-time feedback.

[0500] "Input means for collecting spatial data" refers to devices or interfaces for users to register information such as photos of rooms, floor plans, budgets, and style preferences.

[0501] "Analysis means for analyzing input spatial data and extracting the physical characteristics of space" refers to a program or processing system for identifying physical characteristics such as dimensions and shape from images or drawings input by the user.

[0502] "A selection method for selecting a product range based on the desired decorative style and budget" refers to an algorithm or software for generating a list of appropriate furniture and decorative items based on the user's requirements.

[0503] "Generative means for generating a virtual three-dimensional space with selected product groups arranged" refers to computer graphics technology for arranging selected interior items and representing them in 3D.

[0504] "Display means for displaying a virtual three-dimensional space" refers to display devices or VR devices that visually present the generated 3D model to the user.

[0505] "Visualization means for providing experiences in a digital environment" refers to interfaces and technologies that allow users to interactively manipulate virtual spaces and obtain realistic experiences.

[0506] "Feedback means for obtaining user feedback on the displayed virtual three-dimensional space" refers to functions or devices that allow users to evaluate a proposed design and provide opinions and feedback.

[0507] "An automated generation method for generating prompt text and proposing new interior designs using a generation AI model" refers to a system or method that uses AI technology to create new design proposals and present them to users.

[0508] The system for realizing this invention is initiated by the user using a device such as a smartphone or tablet. First, the user inputs photos of the room they want to decorate, floor plan data, budget, and desired style into the device. This data is then transmitted to a server in the cloud via the internet.

[0509] The server processes the submitted photos of the room using image analysis techniques and extracts physical features (e.g., room shape, size, window placement, etc.). At this stage, a deep learning library such as TensorFlow may be used.

[0510] Next, the server considers the user's desired style and budget, and uses a selection method to list appropriate interior products. Here, furniture and decorative items that match the selection criteria are extracted from the database.

[0511] Subsequently, the selected products are placed in a virtual three-dimensional space using a 3D engine such as Unity, and the visualization is transmitted to the user's terminal. At this stage, the virtual space must be user-friendly and interactively operable.

[0512] The user carefully examines the virtual space presented on their device and provides feedback. This feedback is sent to the server, where an automated generation system generates prompt text, which is then used by a generation AI model to update the design. For example, if the user provides feedback such as "I want to make it a more relaxing space," the generation AI model will receive a prompt such as "How can I create a relaxing space?"

[0513] Ultimately, if the user is satisfied with the proposed design, they can easily proceed with the purchase. Overall, this process efficiently supports the user in choosing interior design elements and provides a realistic design experience.

[0514] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0515] Step 1:

[0516] Users input spatial data such as photos of their rooms, floor plans, budget, and style preferences using their smartphones or tablets, and send this data to a server in the cloud. This data is then sent directly to the server and prepared for the next analysis process.

[0517] Step 2:

[0518] The server analyzes the received room photo data using an image analysis engine (e.g., TensorFlow) to extract the physical features of the room. Here, the image data is extracted as features, and specific numerical information such as the shape and size of the room, and the location of windows and doors is obtained.

[0519] Step 3:

[0520] The server selects appropriate interior product sets from the database based on the user's specified style and budget. This process involves filtering based on the user's input data to list furniture and decorative items that meet the selection criteria, and then outputs the selection results.

[0521] Step 4:

[0522] The server uses a 3D engine such as Unity to place selected interior products in a virtual three-dimensional space and generate visualization data. The generated 3D placement data is rendered in a format viewable on the terminal and returned to the user as output.

[0523] Step 5:

[0524] Users visually review the virtual space visualizations they receive on their devices and provide feedback. They input their opinions and advice on specific interiors in text format and send that data to the server.

[0525] Step 6:

[0526] Based on user feedback, the server utilizes a generative AI model to create prompt messages and proposes new interior designs. Here, feedback data is taken as input, text is generated by the generative AI model, and the updated design proposal is presented to the user as a prompt output.

[0527] Step 7:

[0528] If the user is satisfied with the newly proposed design, they proceed with the purchase on their device. The user's final selection is processed as purchase data, and the design is completed.

[0529] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0530] This invention is a system for efficiently realizing the space desired by the user, and in addition to inputting, analyzing, generating, and displaying spatial information, it also has a function to recognize the user's emotions and optimize interior design proposals.

[0531] First, the user inputs images of the room, floor plan data, budget, and desired interior style from their device. The device then formats the data and sends it to the server. The server analyzes the received image data to identify the physical characteristics of the room. It also analyzes the floor plan to collect information on the layout of the usable space.

[0532] Next, the server uses a generative AI to create a product list, selecting the most suitable furniture and decorative items based on the user's style preferences and budget. This product list is then placed in a virtual three-dimensional space, and an interior design proposal is constructed using the generative system. The generated three-dimensional data is sent to the terminal, where the user can experience the virtual space and visually confirm the proposed interior.

[0533] A newly integrated emotion engine recognizes the user's emotions in real time while they are experiencing the virtual space. This emotion data is sent to a server, which automatically adjusts suggestions based on the user's responses. This process enables personalized interior design suggestions that align with the user's latent preferences.

[0534] For example, if a user is looking for a "relaxing modern style" for their living room, the server identifies the space through image analysis and selects furniture that matches the modern style. As the user experiences the virtual space constructed through a VR device, the emotion engine identifies emotions such as satisfaction and excitement from the user's facial expressions and voice. If the user appears restless, the server updates its suggestions based on this information, adjusting to furniture and layouts that are more relaxing.

[0535] In this way, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback. Furthermore, if they are satisfied with the final suggestion, they can complete the purchase process for the selected items using their device, and the server will automatically check inventory and arrange delivery, enabling a smooth interior design process.

[0536] The following describes the processing flow.

[0537] Step 1:

[0538] The user uses a terminal to input images of the room, floor plan information, budget, and desired interior style. This information is formatted on the terminal and sent to the server.

[0539] Step 2:

[0540] The server analyzes the received image data and extracts physical features such as the dimensions and shape of the space. At the same time, it also analyzes the floor plan data to obtain layout information.

[0541] Step 3:

[0542] The server uses a generative AI to select the most suitable furniture and decorative items, taking into account the user's style preferences and budget. It then creates a product list with the selected items.

[0543] Step 4:

[0544] The server constructs a virtual three-dimensional space using a generation method based on the product list. The selected product group is placed within this space.

[0545] Step 5:

[0546] The server sends the generated virtual three-dimensional space to the terminal, and the terminal provides a visual interface to allow the user to experience that space in AR or VR.

[0547] Step 6:

[0548] While the user is experiencing the virtual space, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[0549] Step 7:

[0550] The server receives data from the emotion engine and dynamically adjusts product selection and placement based on the recognized emotions. For example, if it determines that the user is not satisfied, the server updates its recommendations.

[0551] Step 8:

[0552] If the user is satisfied with the updated proposal, they proceed with the purchase process through their device. The server processes the purchase information and automatically manages inventory checks, payment processing, delivery, and installation arrangements.

[0553] (Example 2)

[0554] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0555] Conventional interior design proposal systems lack the efficiency of designing spaces based on user preferences, and they struggle to provide personalized proposals that reflect users' emotions and latent preferences. As a result, it is difficult to create spaces that truly satisfy users.

[0556] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0557] In this invention, the server includes means for inputting spatial information, means for recognizing the user's emotions and automatically optimizing interior design suggestions based on the virtual space experience, and means for updating the product collection and its arrangement in real time based on information obtained from the emotion recognition means. This enables more efficient spatial design in line with the user's wishes and personalized interior design suggestions based on emotions.

[0558] "Spatial information" refers to data about location, layout, and decorative elements in a physical environment.

[0559] A "three-dimensional virtual space" refers to a three-dimensional, reproducible virtual environment generated on a computer.

[0560] A "product set" refers to a group of furniture and decorative items selected based on a specific spatial style or budget.

[0561] "Means for recognizing user emotions" refers to technologies that analyze emotions from a user's facial expressions and voice.

[0562] "Methods for updating in real time" refers to technologies that allow for immediate modification and change of proposals and layouts based on continuously obtained data.

[0563] "Means for automatically optimizing interior design proposals" refers to technology that dynamically adjusts the optimal interior design based on user feedback and emotional data.

[0564] This invention is a system that efficiently realizes the space desired by the user and provides personalized interior design proposals. This system comprehensively manages the input, analysis, generation, and display of spatial information and has a function to recognize the user's emotions and optimize interior design proposals.

[0565] First, the user uses a terminal to input room images, floor plan data, budget, and preferences related to interior style. Spatial information such as images and floor plans is formatted by the terminal, and the data is sent to the server. The terminal uses a computer or mobile device for information input and data formatting.

[0566] The server performs analysis based on the received spatial information. For image analysis, image recognition software is used, and for floor plan analysis, layout analysis algorithms are employed. Specific software used for image analysis includes general libraries such as OpenCV. Design software like AutoCAD is also included.

[0567] Next, the server uses a generative AI model to create a product list that matches the user's style preferences and budget. The generative AI model employs a natural language processing engine such as OpenAI to select furniture and decorative items. As a result, a virtual three-dimensional space is constructed and visualized using modeling software such as Blender or Unity.

[0568] The generated virtual space data is sent to the terminal. The user can experience this virtual space on the terminal and visually confirm the proposed interior. Using a VR device allows for a more immersive experience. In addition, an emotion engine is incorporated to recognize emotions in real time from the facial expressions and voices the user displays during the experience.

[0569] Emotional data is sent to the server, and suggestions are automatically adjusted based on the user's response. This enables personalized suggestions that align with the user's potential preferences.

[0570] For example, if a user enters a prompt such as, "I want a calm, modern style interior for my living room. My budget is 300,000 yen," the server will use generative AI to suggest a suitable furniture list. Through this process, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback.

[0571] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0572] Step 1:

[0573] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. The terminal formats the input data according to the specified format. At this point, the input images are resized to the appropriate resolution, and the floor plan data is converted to a specific format. This formatted data is then passed on to subsequent processing.

[0574] Step 2:

[0575] The terminal sends the formatted data to the server. Here, the HTTP protocol is used to securely transfer the data. The data received by the server includes room images, floor plan information, budget, and style preferences. This data is then used in the subsequent analysis process.

[0576] Step 3:

[0577] The server analyzes the received image data to identify the physical features of the room. Image recognition uses libraries such as OpenCV to recognize the locations of walls and furniture. Floor plan data is also analyzed to extract layout information of the usable space. The output information includes room size, shape, and the location of existing interior furnishings.

[0578] Step 4:

[0579] The server uses a generative AI model to generate a product list optimized for the user's style preferences and budget. The generative AI model performs natural language processing based on the prompt text. The generated list consists of furniture and decorative items that match the style within the budget. This list is then used in the next step.

[0580] Step 5:

[0581] The server constructs a virtual three-dimensional space based on the generated product list. Products are placed using 3D modeling software such as Blender or Unity. The server generates three-dimensional data and prepares to send it to the terminal.

[0582] Step 6:

[0583] The terminal receives three-dimensional data transmitted from the server and allows the user to experience a virtual space. In practice, using a VR device enables the user to have an immersive experience. Based on the visually confirmed virtual space, the user can obtain information.

[0584] Step 7:

[0585] The device operates an emotion engine that recognizes the user's emotions in real time while they are experiencing the virtual space. Face API and other technologies are used for facial recognition, and speech recognition technology is utilized for voice analysis. During this process, information about the user's satisfaction level and stress level is obtained.

[0586] Step 8:

[0587] The server adjusts the interior design suggestions in real time based on emotional data transmitted from the terminal. If the user appears restless, the system automatically adjusts to more relaxing options. The final suggestion creates an optimal interior space that aligns with the user's emotions.

[0588] (Application Example 2)

[0589] Next, we will explain application example 2. In the following explanation, 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."

[0590] When efficiently realizing the interior design desired by users, it is difficult to provide personalized suggestions that fully take into account the user's individual style and emotions. Therefore, in order to enhance user satisfaction, there is a need to provide an interior design suggestion system that can adapt to the emotional responses of individual users.

[0591] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0592] In this invention, the server includes acquisition means for collecting spatial data, analysis means for analyzing the acquired spatial data and extracting the physical characteristics of the space, selection means for selecting a group of items based on a desired decorative style and budget, and emotion recognition means for acquiring emotional information. This makes it possible to dynamically adjust interior design suggestions based on the user's emotional response and provide more personalized interior designs.

[0593] "Spatial data" refers to data that describes the physical characteristics of a room or environment, including information necessary for interior design.

[0594] "Acquisition means" refers to devices and methods used to collect spatial data from the user's environment.

[0595] "Analysis means" refers to a function for processing acquired spatial data and identifying physical characteristics.

[0596] A "selected items group" is a collection of furniture and decorative items chosen by the user based on their desired style and budget.

[0597] "Selection means" refers to a process or apparatus for selecting the optimal group of articles based on desired criteria.

[0598] A "virtual three-dimensional space" is a space visualized by arranging a selected group of items in three dimensions.

[0599] "Presentation means" refers to methods or devices for displaying the generated virtual three-dimensional space to the user.

[0600] "Emotion recognition means" refers to devices or methods for analyzing and recognizing a user's emotions in real time.

[0601] An "emotional feedback mechanism" is a function that acquires and processes the emotional responses that a user shows to a virtual 3D space.

[0602] "Adjustment means" refers to a function that adaptively modifies the proposed group of items or layout based on acquired emotional information.

[0603] This invention is a system for providing suggestions that meet the user's interior design preferences. Specific embodiments thereof are described below.

[0604] The server first receives spatial data transmitted from the user's terminal. This data includes images of the room, floor plan information, and the user's desired style and budget information. The server uses image processing software to analyze the physical characteristics of the space from this data.

[0605] Next, based on the acquired analysis information, a set of items that fit the desired style and budget is selected. Here, a generative AI model is used to propose the optimal combination from a large amount of interior design data. The selected set of items is placed in a virtual 3D space and presented visually to the user.

[0606] Users experience this virtual space using devices such as head-mounted displays. During the experience, emotion recognition software analyzes the user's facial expressions and voice in real time to recognize their emotions. The recognized emotion data is sent back to the server, and the selected items and layout are dynamically adjusted based on the user's responses.

[0607] For example, if a user desires a modern style and a relaxed atmosphere, the generating AI model will suggest furniture and arrangements that meet those criteria. An example of a prompt might be: "Based on the interior style the user has chosen for their living room, please generate personalized suggestions that reflect their satisfaction level. Considering the emotion recognition results, please suggest the optimal furniture arrangement based on a natural style."

[0608] In this way, the server provides interior design suggestions that adapt to the user's emotions in real time, enabling the efficient creation of a design space that is more satisfying to the user.

[0609] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0610] Step 1:

[0611] The terminal receives room images, floor plans, desired style, and budget as input from the user, and formats this as spatial data. The formatted spatial data is then sent to the server. This ensures that the server receives input based on the user's requests.

[0612] Step 2:

[0613] The server uses image processing software to analyze the received spatial data as input. Here, it identifies the physical characteristics and layout of the room and outputs this as structural data. This results in data tailored to the user's environment.

[0614] Step 3:

[0615] The server uses an AI model that generates data based on structural data, user style, and budget to select a group of items. The selection results are output as suggested data, forming the foundation of the virtual 3D space. Here, the optimal combination is generated from a large amount of interior design data.

[0616] Step 4:

[0617] The server sends virtual 3D space data containing the selected items to the terminal. The terminal receives this data, and the user experiences it through a head-mounted display. In this step, the user can visually confirm the selected interior.

[0618] Step 5:

[0619] While the user is experiencing the virtual space, the terminal uses emotion recognition software to analyze the user's facial expressions and voice. The analyzed emotion data is sent to a server. This allows the user's emotions to be obtained in real time.

[0620] Step 6:

[0621] The server re-evaluates the suggested data using emotional data as input and dynamically adjusts the item group and its placement using a generative AI model. The updated suggested data is then sent to the terminal. This results in interior design suggestions that are adapted to the user's emotions.

[0622] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0623] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0624] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0625] [Fourth Embodiment]

[0626] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0627] As shown in Figure 7, the 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.

[0628] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0629] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0630] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0631] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0632] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0633] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0634] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0635] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0636] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0637] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0638] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0639] This invention provides a system that enables users to effectively utilize limited space and realize interiors tailored to their individual preferences. This system primarily includes means for collecting, analyzing, selecting, generating, and displaying spatial data, thereby proposing an optimal interior design that meets the user's needs.

[0640] When starting to use the system, the user inputs images of the room, floor plan data, budget, and style preferences using a terminal. The terminal formats this data and sends it to the server. The server processes the input image data using image analysis technology and extracts the physical characteristics of the room. Next, based on this data, the server selects appropriate furniture and decorations, taking into account the user's desired style and budget.

[0641] The furniture selected by the selection method is constructed as a virtual three-dimensional space by the generation method. The server sends this data to the terminal, which provides the user with an environment in which they can visually confirm the virtual space. At this stage, the user can experience the virtual space through the terminal and provide feedback.

[0642] As a concrete example, consider a case where a user wants to decorate their living room in a "Nordic style." The user inputs a photo of the room and their desired style into their device. The server recognizes it as a Nordic style and lists warm wooden furniture and simple decorations within the budget. Next, the user uses a VR device to simulate the generated 3D layout plan. Through this simulation, the user checks how the selected furniture fits into the space and, if necessary, inputs feedback into the device, which the server then adjusts the layout plan.

[0643] If the user is ultimately satisfied with the proposal, they can complete the purchase process on their terminal, completing the efficient interior coordination and implementation throughout the entire system. In this way, users can easily create a space that suits their own style and lifestyle.

[0644] The following describes the processing flow.

[0645] Step 1:

[0646] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. This information is received by the terminal, formatted in the appropriate format, and then sent to the server.

[0647] Step 2:

[0648] The server uses computer vision technology to analyze the received image data and extract the physical features and dimensions of the room. It also analyzes the floor plan data and organizes the spatial layout information.

[0649] Step 3:

[0650] The server uses natural language processing technology to estimate the user's style preferences and budget information. Then, using generative AI, it selects the most suitable furniture and decorative items based on this information and creates a product list.

[0651] Step 4:

[0652] The server uses a generation mechanism to place the selected product list in a virtual three-dimensional space, constructing an interior layout plan. This data is converted into a three-dimensional model and prepared for the user to visually review.

[0653] Step 5:

[0654] The server sends the generated 3D data to the terminal. The terminal receives this data and displays a virtual interior space to the user through an AR or VR device, providing an environment that simulates how it would look in the actual space.

[0655] Step 6:

[0656] The user reviews the displayed virtual space and inputs feedback on the furniture selection and placement, including opinions and suggestions for improvement, into the terminal.

[0657] Step 7:

[0658] The terminal sends user feedback to the server. Based on this feedback, the server updates the selected product group and its deployment plan as needed, and then proposes it to the user again.

[0659] Step 8:

[0660] If the user is satisfied with the proposal and decides to purchase, they proceed with the purchase process from their terminal. The server manages the information necessary for the purchase process and automatically handles inventory checks for the selected items, payment processing, and arrangements for delivery and installation.

[0661] (Example 1)

[0662] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0663] In modern living environments, there is a demand for the effective use of limited space and the realization of interiors that suit the lifestyles and preferences of individual users. However, existing systems require considerable effort to extract physical characteristics and select interior design candidates, making it difficult for users to easily create their ideal space. This invention aims to solve these problems and provide a system that allows for the efficient and intuitive design of interiors tailored to individual desires.

[0664] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0665] In this invention, the server comprises an input device means for collecting spatial data, an analysis device means for analyzing the collected spatial data and extracting physical features, a selection device means for selecting a group of products based on a desired decorative style and budget, a generation device means for generating a virtual three-dimensional space using the selected group of products, a display device means for displaying the generated virtual three-dimensional space, and a feedback device means for obtaining user feedback on the displayed virtual three-dimensional space. Furthermore, it includes an update device means for updating the group of products and their arrangement using a generation AI model based on the feedback obtained from the feedback means. This enables the proposal and adjustment of practical and user-optimized interiors.

[0666] "Spatial data" refers to data that includes physical information and characteristics related to residential and commercial spaces, and may include image data and floor plan information.

[0667] An "input device" is a device or interface that provides functions for users to easily input spatial data into a system.

[0668] An "analysis device" is a computer program or system configuration that has the function of processing input spatial data and extracting its physical characteristics.

[0669] A "selection device" is a component of a system that selects a range of products that match a specific decorative style and budget based on extracted characteristics.

[0670] A "generation device" is a program or hardware configuration that uses a selected group of products to create a virtual three-dimensional space.

[0671] A "display device" is a device or software that visualizes a generated virtual three-dimensional space, allowing users to visually confirm that space.

[0672] A "feedback device" is a mechanism or system configuration for collecting user opinions and suggestions for improvement regarding the displayed virtual three-dimensional space.

[0673] A "renewal device" is part of a system that uses a generated AI model to modify the product group and its placement based on information obtained through feedback.

[0674] A "generative AI model" is an algorithm or model that utilizes machine learning technology to propose the optimal interior design plan based on the input conditions.

[0675] A "prompt statement" is a text-based instruction that provides specific instructions or conditions to a generative AI model.

[0676] In a form for carrying out the invention, this system provides a series of processes for efficiently realizing user-specific interior design. The user first collects spatial data using a terminal. This is done by inputting relevant information such as images of the room, floor plan information, budget, and desired interior style. The terminal then formats the collected information into an appropriate format and transmits it to the server.

[0677] The server analyzes the received data. Here, OpenCV or similar libraries are used to extract the physical features of the space using image analysis techniques. These extracted features play a crucial role in interior design proposals.

[0678] Next, the server uses the generated AI model to select a range of products that match the user's desired style and budget. At this time, specific instructions such as "Please select furniture suitable for a Scandinavian-style living room within the budget" are input to the AI ​​model as prompts. The selected product range is used as the basic data for generating a virtual three-dimensional space.

[0679] 3D modeling software such as Blender is used to generate the virtual three-dimensional space. This makes it possible to visually construct how the selected interior items will be placed in the space.

[0680] The generated virtual space is presented to the user via a terminal. The user can experience this space using VR devices, etc., and intuitively check the suitability of the interior. At this stage, the user's feedback is used on the server side to re-select the product range and placement. Furthermore, the generating AI model is used again for updates, resulting in an efficient process and enabling suggestions optimized for the user.

[0681] Ultimately, if the user is satisfied with the proposal, they can proceed with purchasing the product using the terminal. This allows users to easily realize a space that suits their preferences. This entire process is a powerful tool for users to comfortably and efficiently create a space that reflects their unique style.

[0682] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0683] Step 1:

[0684] The user uses a terminal to input the necessary spatial data. This input includes images of the room, floor plan information, budget, and desired interior style. The terminal formats the data entered by the user and converts it into a digital format. This data is then sent to the server in an appropriate format as it is required for subsequent processing.

[0685] Step 2:

[0686] The server receives data sent from the terminal. Physical features are extracted from the received image data using image analysis libraries such as OpenCV. These features include ceiling height, wall placement, floor area, and the location of windows and doors. Once the analysis is complete, the feature information is output and used as input for the next selection step.

[0687] Step 3:

[0688] The server generates prompt messages using a generative AI model based on the analysis results, the user's desired style, and budget information. These prompt messages may include instructions such as, "Please select furniture suitable for a Scandinavian-style living room within your budget." The generative AI model then uses these prompt messages to output a list of suitable furniture and decorative items.

[0689] Step 4:

[0690] The server generates a virtual three-dimensional space using a list of furniture selected by a generated AI model. 3D modeling software such as Blender is used for this generation. The server creates virtual space data while considering the placement and combination of furniture. This data is prepared for the user to visually review.

[0691] Step 5:

[0692] The server sends the generated virtual three-dimensional space data to the terminal. The terminal provides a viewing interface on a VR headset or display to facilitate the user's experience of this virtual space. The user can check the layout and style of the interior in the virtual space and input improvements and feedback into the terminal.

[0693] Step 6:

[0694] Upon receiving the feedback, the server uses the generated AI model again to adjust the suggested furniture and its placement. This process results in the optimal interior layout that aligns with the user's preferences. The adjusted results are then sent back to the terminal for the user to confirm.

[0695] Step 7:

[0696] If the user is satisfied with the final proposal, they can proceed with purchasing the selected products on their device. This will result in the actual installation of the proposed interior design, completing the creation of an efficient living space.

[0697] (Application Example 1)

[0698] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0699] The goal is to provide a system that efficiently utilizes limited space and allows users to visually experience and select interior designs that meet their diverse needs. Furthermore, it is essential to quickly and effectively update the proposed designs based on user feedback. This will improve user satisfaction and support decision-making in interior design selection.

[0700] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0701] In this invention, the server includes input means for collecting spatial data, analysis means for analyzing the input spatial data and extracting the physical characteristics of the space, selection means for selecting a group of products based on a desired decorative style and budget, generation means for generating a virtual three-dimensional space in which the selected group of products are arranged, visualization means for providing an experience in a digital environment, feedback means for obtaining user feedback on the displayed virtual three-dimensional space, and automatic generation means for generating prompt sentences and proposing new interior designs using a generation AI model. As a result, users can visually confirm the optimal interior design based on their individual preferences through an interior experience in a virtual space and flexibly adjust the design with real-time feedback.

[0702] "Input means for collecting spatial data" refers to devices or interfaces for users to register information such as photos of rooms, floor plans, budgets, and style preferences.

[0703] "Analysis means for analyzing input spatial data and extracting the physical characteristics of space" refers to a program or processing system for identifying physical characteristics such as dimensions and shape from images or drawings input by the user.

[0704] "A selection method for selecting a product range based on the desired decorative style and budget" refers to an algorithm or software for generating a list of appropriate furniture and decorative items based on the user's requirements.

[0705] "Generative means for generating a virtual three-dimensional space with selected product groups arranged" refers to computer graphics technology for arranging selected interior items and representing them in 3D.

[0706] "Display means for displaying a virtual three-dimensional space" refers to display devices or VR devices that visually present the generated 3D model to the user.

[0707] "Visualization means for providing experiences in a digital environment" refers to interfaces and technologies that allow users to interactively manipulate virtual spaces and obtain realistic experiences.

[0708] "Feedback means for obtaining user feedback on the displayed virtual three-dimensional space" refers to functions or devices that allow users to evaluate a proposed design and provide opinions and feedback.

[0709] "An automated generation method for generating prompt text and proposing new interior designs using a generation AI model" refers to a system or method that uses AI technology to create new design proposals and present them to users.

[0710] The system for realizing this invention is initiated by the user using a device such as a smartphone or tablet. First, the user inputs photos of the room they want to decorate, floor plan data, budget, and desired style into the device. This data is then transmitted to a server in the cloud via the internet.

[0711] The server processes the submitted photos of the room using image analysis techniques and extracts physical features (e.g., room shape, size, window placement, etc.). At this stage, a deep learning library such as TensorFlow may be used.

[0712] Next, the server considers the user's desired style and budget, and uses a selection method to list appropriate interior products. Here, furniture and decorative items that match the selection criteria are extracted from the database.

[0713] Subsequently, the selected products are placed in a virtual three-dimensional space using a 3D engine such as Unity, and the visualization is transmitted to the user's terminal. At this stage, the virtual space must be user-friendly and interactively operable.

[0714] The user carefully examines the virtual space presented on their device and provides feedback. This feedback is sent to the server, where an automated generation system generates prompt text, which is then used by a generation AI model to update the design. For example, if the user provides feedback such as "I want to make it a more relaxing space," the generation AI model will receive a prompt such as "How can I create a relaxing space?"

[0715] Ultimately, if the user is satisfied with the proposed design, they can easily proceed with the purchase. Overall, this process efficiently supports the user in choosing interior design elements and provides a realistic design experience.

[0716] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0717] Step 1:

[0718] Users input spatial data such as photos of their rooms, floor plans, budget, and style preferences using their smartphones or tablets, and send this data to a server in the cloud. This data is then sent directly to the server and prepared for the next analysis process.

[0719] Step 2:

[0720] The server analyzes the received room photo data using an image analysis engine (e.g., TensorFlow) to extract the physical features of the room. Here, the image data is extracted as features, and specific numerical information such as the shape and size of the room, and the location of windows and doors is obtained.

[0721] Step 3:

[0722] The server selects appropriate interior product sets from the database based on the user's specified style and budget. This process involves filtering based on the user's input data to list furniture and decorative items that meet the selection criteria, and then outputs the selection results.

[0723] Step 4:

[0724] The server uses a 3D engine such as Unity to place selected interior products in a virtual three-dimensional space and generate visualization data. The generated 3D placement data is rendered in a format viewable on the terminal and returned to the user as output.

[0725] Step 5:

[0726] Users visually review the virtual space visualizations they receive on their devices and provide feedback. They input their opinions and advice on specific interiors in text format and send that data to the server.

[0727] Step 6:

[0728] Based on user feedback, the server utilizes a generative AI model to create prompt messages and proposes new interior designs. Here, feedback data is taken as input, text is generated by the generative AI model, and the updated design proposal is presented to the user as a prompt output.

[0729] Step 7:

[0730] If the user is satisfied with the newly proposed design, they proceed with the purchase on their device. The user's final selection is processed as purchase data, and the design is completed.

[0731] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0732] This invention is a system for efficiently realizing the space desired by the user, and in addition to inputting, analyzing, generating, and displaying spatial information, it also has a function to recognize the user's emotions and optimize interior design proposals.

[0733] First, the user inputs images of the room, floor plan data, budget, and desired interior style from their device. The device then formats the data and sends it to the server. The server analyzes the received image data to identify the physical characteristics of the room. It also analyzes the floor plan to collect information on the layout of the usable space.

[0734] Next, the server uses a generative AI to create a product list, selecting the most suitable furniture and decorative items based on the user's style preferences and budget. This product list is then placed in a virtual three-dimensional space, and an interior design proposal is constructed using the generative system. The generated three-dimensional data is sent to the terminal, where the user can experience the virtual space and visually confirm the proposed interior.

[0735] A newly integrated emotion engine recognizes the user's emotions in real time while they are experiencing the virtual space. This emotion data is sent to a server, which automatically adjusts suggestions based on the user's responses. This process enables personalized interior design suggestions that align with the user's latent preferences.

[0736] For example, if a user is looking for a "relaxing modern style" for their living room, the server identifies the space through image analysis and selects furniture that matches the modern style. As the user experiences the virtual space constructed through a VR device, the emotion engine identifies emotions such as satisfaction and excitement from the user's facial expressions and voice. If the user appears restless, the server updates its suggestions based on this information, adjusting to furniture and layouts that are more relaxing.

[0737] In this way, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback. Furthermore, if they are satisfied with the final suggestion, they can complete the purchase process for the selected items using their device, and the server will automatically check inventory and arrange delivery, enabling a smooth interior design process.

[0738] The following describes the processing flow.

[0739] Step 1:

[0740] The user uses a terminal to input images of the room, floor plan information, budget, and desired interior style. This information is formatted on the terminal and sent to the server.

[0741] Step 2:

[0742] The server analyzes the received image data and extracts physical features such as the dimensions and shape of the space. At the same time, it also analyzes the floor plan data to obtain layout information.

[0743] Step 3:

[0744] The server uses a generative AI to select the most suitable furniture and decorative items, taking into account the user's style preferences and budget. It then creates a product list with the selected items.

[0745] Step 4:

[0746] The server constructs a virtual three-dimensional space using a generation method based on the product list. The selected product group is placed within this space.

[0747] Step 5:

[0748] The server sends the generated virtual three-dimensional space to the terminal, and the terminal provides a visual interface to allow the user to experience that space in AR or VR.

[0749] Step 6:

[0750] While the user is experiencing the virtual space, the emotion engine analyzes the user's facial expressions and voice to recognize their emotional state in real time.

[0751] Step 7:

[0752] The server receives data from the emotion engine and dynamically adjusts product selection and placement based on the recognized emotions. For example, if it determines that the user is not satisfied, the server updates its recommendations.

[0753] Step 8:

[0754] If the user is satisfied with the updated proposal, they proceed with the purchase process through their device. The server processes the purchase information and automatically manages inventory checks, payment processing, delivery, and installation arrangements.

[0755] (Example 2)

[0756] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0757] Conventional interior design proposal systems lack the efficiency of designing spaces based on user preferences, and they struggle to provide personalized proposals that reflect users' emotions and latent preferences. As a result, it is difficult to create spaces that truly satisfy users.

[0758] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0759] In this invention, the server includes means for inputting spatial information, means for recognizing the user's emotions and automatically optimizing interior design suggestions based on the virtual space experience, and means for updating the product collection and its arrangement in real time based on information obtained from the emotion recognition means. This enables more efficient spatial design in line with the user's wishes and personalized interior design suggestions based on emotions.

[0760] "Spatial information" refers to data about location, layout, and decorative elements in a physical environment.

[0761] A "three-dimensional virtual space" refers to a three-dimensional, reproducible virtual environment generated on a computer.

[0762] A "product set" refers to a group of furniture and decorative items selected based on a specific spatial style or budget.

[0763] "Means for recognizing user emotions" refers to technologies that analyze emotions from a user's facial expressions and voice.

[0764] "Methods for updating in real time" refers to technologies that allow for immediate modification and change of proposals and layouts based on continuously obtained data.

[0765] "Means for automatically optimizing interior design proposals" refers to technology that dynamically adjusts the optimal interior design based on user feedback and emotional data.

[0766] This invention is a system that efficiently realizes the space desired by the user and provides personalized interior design proposals. This system comprehensively manages the input, analysis, generation, and display of spatial information and has a function to recognize the user's emotions and optimize interior design proposals.

[0767] First, the user uses a terminal to input room images, floor plan data, budget, and preferences related to interior style. Spatial information such as images and floor plans is formatted by the terminal, and the data is sent to the server. The terminal uses a computer or mobile device for information input and data formatting.

[0768] The server performs analysis based on the received spatial information. For image analysis, image recognition software is used, and for floor plan analysis, layout analysis algorithms are employed. Specific software used for image analysis includes general libraries such as OpenCV. Design software like AutoCAD is also included.

[0769] Next, the server uses a generative AI model to create a product list that matches the user's style preferences and budget. The generative AI model employs a natural language processing engine such as OpenAI to select furniture and decorative items. As a result, a virtual three-dimensional space is constructed and visualized using modeling software such as Blender or Unity.

[0770] The generated virtual space data is sent to the terminal. The user can experience this virtual space on the terminal and visually confirm the proposed interior. Using a VR device allows for a more immersive experience. In addition, an emotion engine is incorporated to recognize emotions in real time from the facial expressions and voices the user displays during the experience.

[0771] Emotional data is sent to the server, and suggestions are automatically adjusted based on the user's response. This enables personalized suggestions that align with the user's potential preferences.

[0772] For example, if a user enters a prompt such as, "I want a calm, modern style interior for my living room. My budget is 300,000 yen," the server will use generative AI to suggest a suitable furniture list. Through this process, users can achieve their ideal interior space through emotion-recognition-based feedback without having to directly input feedback.

[0773] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0774] Step 1:

[0775] The user uses a terminal to input images of the room, floor plan data, budget, and desired interior style. The terminal formats the input data according to the specified format. At this point, the input images are resized to the appropriate resolution, and the floor plan data is converted to a specific format. This formatted data is then passed on to subsequent processing.

[0776] Step 2:

[0777] The terminal sends the formatted data to the server. Here, the HTTP protocol is used to securely transfer the data. The data received by the server includes room images, floor plan information, budget, and style preferences. This data is then used in the subsequent analysis process.

[0778] Step 3:

[0779] The server analyzes the received image data to identify the physical features of the room. Image recognition uses libraries such as OpenCV to recognize the locations of walls and furniture. Floor plan data is also analyzed to extract layout information of the usable space. The output information includes room size, shape, and the location of existing interior furnishings.

[0780] Step 4:

[0781] The server uses a generative AI model to generate a product list optimized for the user's style preferences and budget. The generative AI model performs natural language processing based on the prompt text. The generated list consists of furniture and decorative items that match the style within the budget. This list is then used in the next step.

[0782] Step 5:

[0783] The server constructs a virtual three-dimensional space based on the generated product list. Products are placed using 3D modeling software such as Blender or Unity. The server generates three-dimensional data and prepares to send it to the terminal.

[0784] Step 6:

[0785] The terminal receives three-dimensional data transmitted from the server and allows the user to experience a virtual space. In practice, using a VR device enables the user to have an immersive experience. Based on the visually confirmed virtual space, the user can obtain information.

[0786] Step 7:

[0787] The device operates an emotion engine that recognizes the user's emotions in real time while they are experiencing the virtual space. Face API and other technologies are used for facial recognition, and speech recognition technology is utilized for voice analysis. During this process, information about the user's satisfaction level and stress level is obtained.

[0788] Step 8:

[0789] The server adjusts the interior design suggestions in real time based on emotional data transmitted from the terminal. If the user appears restless, the system automatically adjusts to more relaxing options. The final suggestion creates an optimal interior space that aligns with the user's emotions.

[0790] (Application Example 2)

[0791] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0792] When efficiently realizing the interior design desired by users, it is difficult to provide personalized suggestions that fully take into account the user's individual style and emotions. Therefore, in order to enhance user satisfaction, there is a need to provide an interior design suggestion system that can adapt to the emotional responses of individual users.

[0793] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0794] In this invention, the server includes acquisition means for collecting spatial data, analysis means for analyzing the acquired spatial data and extracting the physical characteristics of the space, selection means for selecting a group of items based on a desired decorative style and budget, and emotion recognition means for acquiring emotional information. This makes it possible to dynamically adjust interior design suggestions based on the user's emotional response and provide more personalized interior designs.

[0795] "Spatial data" refers to data that describes the physical characteristics of a room or environment, including information necessary for interior design.

[0796] "Acquisition means" refers to devices and methods used to collect spatial data from the user's environment.

[0797] "Analysis means" refers to a function for processing acquired spatial data and identifying physical characteristics.

[0798] A "selected items group" is a collection of furniture and decorative items chosen by the user based on their desired style and budget.

[0799] "Selection means" refers to a process or apparatus for selecting the optimal group of articles based on desired criteria.

[0800] A "virtual three-dimensional space" is a space visualized by arranging a selected group of items in three dimensions.

[0801] "Presentation means" refers to methods or devices for displaying the generated virtual three-dimensional space to the user.

[0802] "Emotion recognition means" refers to devices or methods for analyzing and recognizing a user's emotions in real time.

[0803] An "emotional feedback mechanism" is a function that acquires and processes the emotional responses that a user shows to a virtual 3D space.

[0804] "Adjustment means" refers to a function that adaptively modifies the proposed group of items or layout based on acquired emotional information.

[0805] This invention is a system for providing suggestions that meet the user's interior design preferences. Specific embodiments thereof are described below.

[0806] The server first receives spatial data transmitted from the user's terminal. This data includes images of the room, floor plan information, and the user's desired style and budget information. The server uses image processing software to analyze the physical characteristics of the space from this data.

[0807] Next, based on the acquired analysis information, a set of items that fit the desired style and budget is selected. Here, a generative AI model is used to propose the optimal combination from a large amount of interior design data. The selected set of items is placed in a virtual 3D space and presented visually to the user.

[0808] Users experience this virtual space using devices such as head-mounted displays. During the experience, emotion recognition software analyzes the user's facial expressions and voice in real time to recognize their emotions. The recognized emotion data is sent back to the server, and the selected items and layout are dynamically adjusted based on the user's responses.

[0809] For example, if a user desires a modern style and a relaxed atmosphere, the generating AI model will suggest furniture and arrangements that meet those criteria. An example of a prompt might be: "Based on the interior style the user has chosen for their living room, please generate personalized suggestions that reflect their satisfaction level. Considering the emotion recognition results, please suggest the optimal furniture arrangement based on a natural style."

[0810] In this way, the server provides interior design suggestions that adapt to the user's emotions in real time, enabling the efficient creation of a design space that is more satisfying to the user.

[0811] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0812] Step 1:

[0813] The terminal receives room images, floor plans, desired style, and budget as input from the user, and formats this as spatial data. The formatted spatial data is then sent to the server. This ensures that the server receives input based on the user's requests.

[0814] Step 2:

[0815] The server uses image processing software to analyze the received spatial data as input. Here, it identifies the physical characteristics and layout of the room and outputs this as structural data. This results in data tailored to the user's environment.

[0816] Step 3:

[0817] The server uses an AI model that generates data based on structural data, user style, and budget to select a group of items. The selection results are output as suggested data, forming the foundation of the virtual 3D space. Here, the optimal combination is generated from a large amount of interior design data.

[0818] Step 4:

[0819] The server sends virtual 3D space data containing the selected items to the terminal. The terminal receives this data, and the user experiences it through a head-mounted display. In this step, the user can visually confirm the selected interior.

[0820] Step 5:

[0821] While the user is experiencing the virtual space, the terminal uses emotion recognition software to analyze the user's facial expressions and voice. The analyzed emotion data is sent to a server. This allows the user's emotions to be obtained in real time.

[0822] Step 6:

[0823] The server re-evaluates the suggested data using emotional data as input and dynamically adjusts the item group and its placement using a generative AI model. The updated suggested data is then sent to the terminal. This results in interior design suggestions that are adapted to the user's emotions.

[0824] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0825] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0826] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0827] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0828] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0829] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0830] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0831] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0832] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0833] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0834] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0835] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0836] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0837] 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.

[0838] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0839] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0840] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0841] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0842] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0843] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0844] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0845] The following is further disclosed regarding the embodiments described above.

[0846] (Claim 1)

[0847] Input means for collecting spatial data,

[0848] An analysis means for analyzing input spatial data and extracting the physical characteristics of the space,

[0849] A selection method for choosing a product range based on the desired decorative style and budget,

[0850] A generation means for generating a virtual three-dimensional space in which the selected product group is arranged,

[0851] A display means for displaying a virtual three-dimensional space,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, further comprising feedback means for obtaining user feedback on a displayed virtual three-dimensional space.

[0855] (Claim 3)

[0856] The system according to claim 2, further comprising an update means for updating the product group and its arrangement based on feedback obtained from a feedback means.

[0857] "Example 1"

[0858] (Claim 1)

[0859] Input device means for collecting spatial data,

[0860] An analysis device means for analyzing collected spatial data and extracting physical features,

[0861] A selection device means for selecting a product group based on the desired decorative style and budget,

[0862] A generation apparatus means for generating a virtual three-dimensional space using a selected group of products,

[0863] A display device for displaying the generated virtual three-dimensional space,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, comprising a feedback device for obtaining user feedback on a displayed virtual three-dimensional space.

[0867] (Claim 3)

[0868] The update device according to claim 2, which updates the product group and its arrangement using a generating AI model based on feedback obtained from a feedback means.

[0869] "Application Example 1"

[0870] (Claim 1)

[0871] Input means for collecting spatial data,

[0872] An analysis means for analyzing input spatial data and extracting the physical characteristics of the space,

[0873] A selection method for choosing a product range based on the desired decorative style and budget,

[0874] A generation means for generating a virtual three-dimensional space in which the selected product group is arranged,

[0875] A display means for displaying a virtual three-dimensional space,

[0876] Visualization tools for providing experiences in a digital environment,

[0877] A system that includes this.

[0878] (Claim 2)

[0879] The system according to claim 1, further comprising feedback means for obtaining user feedback on a displayed virtual three-dimensional space.

[0880] (Claim 3)

[0881] An update means that updates the product group and its arrangement based on feedback obtained from the feedback means,

[0882] The system according to claim 1, comprising an automatic generation means for generating prompt text and proposing new interior designs using a generation AI model.

[0883] "Example 2 of combining an emotion engine"

[0884] (Claim 1)

[0885] Means of inputting spatial information,

[0886] A means for analyzing input spatial information and extracting physical characteristics,

[0887] A means of selecting a product set based on the user's desired decorating style and budget,

[0888] A means for arranging a selected set of products and generating a three-dimensional virtual space,

[0889] A means of presenting the generated three-dimensional virtual space,

[0890] A means to recognize user emotions and automatically optimize interior design suggestions based on the virtual space experience,

[0891] A system that includes this.

[0892] (Claim 2)

[0893] The system according to claim 1, comprising means for recognizing in real time the user's emotions toward a presented three-dimensional virtual space.

[0894] (Claim 3)

[0895] The system according to claim 1, comprising means for updating a product collection and its arrangement in real time based on information obtained from emotion recognition means.

[0896] "Application example 2 when combining with an emotional engine"

[0897] (Claim 1)

[0898] Means for acquiring spatial data,

[0899] An analytical means for analyzing acquired spatial data and extracting the physical characteristics of the space,

[0900] A selection method for selecting a group of items based on the desired decorative style and budget,

[0901] A generation means for generating a virtual three-dimensional space in which the selected group of items are arranged,

[0902] A means for displaying a virtual three-dimensional space,

[0903] A means of emotion recognition for acquiring user emotion information,

[0904] An adjustment means for adjusting the selected group of items and their arrangement based on emotional information,

[0905] A system that includes this.

[0906] (Claim 2)

[0907] The system according to claim 1, comprising emotional feedback means for obtaining emotional feedback from a user regarding a displayed virtual three-dimensional space.

[0908] (Claim 3)

[0909] The system according to claim 1, further comprising means for improving the arrangement of a group of articles based on emotional feedback obtained from an emotional feedback means. [Explanation of Symbols]

[0910] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Input means for collecting spatial data, An analysis means for analyzing input spatial data and extracting the physical characteristics of the space, A selection method for choosing a product range based on the desired decorative style and budget, A generation means for generating a virtual three-dimensional space in which the selected product group is arranged, A display means for displaying a virtual three-dimensional space, A system that includes this.

2. The system according to claim 1, further comprising feedback means for obtaining user feedback on the displayed virtual three-dimensional space.

3. The system according to claim 2, further comprising an update means for updating the product group and its arrangement based on feedback obtained from a feedback means.

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