System

Abstract

A system is provided.SOLUTION: A system comprising: means for scanning an environment in a spatial computing device; means for transmitting a scan result to a server; means for generating an interior design using image generation artificial intelligence in the server; and means for transmitting the generated design to the device for real-time display.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional interior designs are difficult to change on a daily basis because of the high cost and time required for changes. Furthermore, the limited interior design options mean that it is difficult to meet the diverse needs of users. Therefore, the present invention aims to solve these problems by providing a system that allows interior designs to be changed flexibly and at low cost on a daily basis by combining spatial computing technology and image generation artificial intelligence. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following: A system is constructed in which a spatial computing device has a means for scanning the environment and a means for transmitting the scan results to a server, the server generates an interior design using image generation artificial intelligence, and a means for transmitting the generated design to the device and displaying it in real time. Furthermore, the system includes a means for identifying markers or low-power wide-area communication tags placed in the environment, thereby improving the accuracy of the scan, and a means for enabling the user to check and adjust the design through a user interface, thereby enabling the user to easily change the interior design.

[0006] A "spatial computing device" is a device that recreates real physical space in combination with digital information, allowing users to engage in virtual interactions.

[0007] "Means for scanning the environment" refers to the ability to read the shape and position information of the real-world environment using optical sensors and depth cameras.

[0008] "Means for transmitting scan results to a server" refers to a technology for sending environmental data acquired by a terminal to a remote server via a network.

[0009] "Image generation artificial intelligence" is an artificial intelligence technology that automatically generates interior designs based on user preferences or specific themes.

[0010] The "server" is a computer system that processes the received data, uses image generation artificial intelligence to generate a new interior design, and returns the data.

[0011] "Means for transmitting the generated design to the device and displaying it in real time" refers to a technology that allows the interior design generated on the server to be sent to the user's device without any time lag and displayed superimposed on the real space.

[0012] A "marker or low-power wide-area communication tag" is an identification tag or beacon that is placed to indicate a specific location in physical space and is used to improve scanning accuracy.

[0013] "User interface" refers to the visual and operational touch points that allow a user to view and adjust the interior design. [Brief explanation of the drawings]

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

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

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

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

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

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

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

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

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

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

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

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0035] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize interior design changes easily and at low cost. This system functions through collaboration between users, terminals, and servers, and performs the following program processing.

[0036] System Overview

[0037] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends the generated design back to the device. The device then displays the design in real space in real time, allowing the user to review it and make adjustments as needed.

[0038] Program processing

[0039] The user sends a request from the device

[0040] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[0041] The device scans the environment

[0042] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[0043] The device sends environmental data to the server

[0044] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[0045] The server starts the image generation AI

[0046] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[0047] The server generates a design and sends it to the device.

[0048] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[0049] The device adapts the design to the interior

[0050] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[0051] User checks and adjusts the design

[0052] The user can use the device to check the new design and make fine adjustments to the color, pattern, etc., if necessary. Once the adjustments are complete, the design is finalized and reflected in the interior.

[0053] Specific examples

[0054] For example, if a user requests a winter-themed interior update, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy theme and a rug design that resembles snowflakes. The generated design is then sent to the device for the user to review. The user can then adjust the rug's hue to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[0055] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] A user activates a spatial computing device. The user sends a request through the device's interface to select a "winter theme" interior design.

[0059] Step 2:

[0060] The device receives the user's request. It then uses its built-in camera and depth sensor to begin a 3D scan of the room. During the scanning process, it recognizes the shape and position of walls, floors, ceilings, furniture, and other elements in detail. It also reads existing markers and low-power wide-area communication tags to supplement the environmental information.

[0061] Step 3:

[0062] The device compiles the scan results and marker / tag data into a single dataset, which also includes the user's request information, and sends the dataset to the server via the network.

[0063] Step 4:

[0064] The server analyzes the received data set. The server sets the parameters of the image generation AI based on the user's preferences and requests. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[0065] Step 5:

[0066] The server encodes the generated interior design data and converts it into a format that can be efficiently transmitted. The server then transmits the design data to the terminal.

[0067] Step 6:

[0068] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[0069] Step 7:

[0070] The user visually checks the new interior design displayed on the device. The user operates the interface to adjust design details (e.g., the color or pattern of the rug) as needed.

[0071] Step 8:

[0072] The device reflects the user's adjustments and confirms the final design. Once the user confirms the final design, the entire room's interior is updated with a "winter theme."

[0073] By following the above steps, users can easily and inexpensively change their interior design and enjoy a comfortable living space based on a new theme.

[0074] Example 1

[0075] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0076] Conventional interior design modification methods have the drawbacks of being time-consuming and expensive, and are difficult for users to implement easily. In addition, there are few ways to connect the real world with the design in real time, making it difficult to check and fine-tune the design.

[0077] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0078] In this invention, the server includes a means for setting parameters for the image generation AI based on a user request, a means for analyzing the scan results, and a means for generating an interior design using the image generation AI, thereby enabling the user to easily and inexpensively check and adjust the interior design in real time.

[0079] A "spatial computing device" is a device that includes hardware and software for recognizing and processing real-world physical environments in conjunction with digital information.

[0080] "Means for scanning the environment" refers to the ability to use built-in cameras and depth sensors to recognize the shape of physical space and the location of objects in detail.

[0081] "Means for sending scan results to a server" refers to the function of uploading the acquired data set to a remote server via a network.

[0082] "Image generation artificial intelligence" refers to algorithms or models that use machine learning or deep learning to generate images based on specified conditions.

[0083] "Means for setting parameters of the image generation artificial intelligence based on a user's request" refers to a function for adjusting settings for image generation in accordance with a design request input by a user.

[0084] "Means for transmitting the generated design to the device and displaying it in real time" refers to the function of efficiently delivering design data generated on the server to the terminal and displaying it immediately.

[0085] "Means for decoding and displaying in real time" refers to the function of quickly processing received design data and visualizing it overlaid on real space.

[0086] "Means for users to check and adjust the design" refers to a function that allows users to check the details of the design through a user interface and make any necessary changes or fine adjustments.

[0087] This invention is a system that allows users to easily and inexpensively change interior designs by combining spatial computing technology and image generation artificial intelligence (AI). This system works through the collaboration of users, terminals, and a server.

[0088] Hardware and Software Used

[0089] Specifically, the system uses the following hardware and software:

[0090] Spatial computing devices: Devices that recognize and process the real-world physical environment in conjunction with digital information, such as HoloLens® and Magic Leap.

[0091] Camera and depth sensor: Used to recognize the shape of the room and the position of objects in detail, allowing for a 3D scan of the environment.

[0092] Image-generating artificial intelligence (AI): Includes algorithms for generating interior designs based on user requests, such as DALL-E and Stable Diffusion.

[0093] Server: Analyzes data, sets AI parameters, and generates designs.

[0094] User Interface (UI): The interface through which users enter their requests and review and adjust the generated designs.

[0095] Data processing and calculation

[0096] The device first activates its camera and depth sensor to perform a 3D scan of the room specified by the user. This scan data includes the shape and location information of the walls, floor, ceiling, furniture, etc. The accuracy of the data can be improved by reading markers and low-power wide-area communication tags.

[0097] The device then compiles the scanned data into a single dataset and sends it to the server along with the user's request. The server then analyzes the dataset and sets the parameters for the image-generating AI. For example, if the user selects a "winter theme," the AI ​​will generate snowy landscapes and interior designs with cool colors.

[0098] The generated design data is efficiently transmitted to the device, which decodes it in real time and displays it overlaid on the real world. The user can view this display and make fine adjustments to the design through the interface.

[0099] Examples of concrete examples and prompts

[0100] When a user inputs a request into the device, such as "I want to update my interior with a winter theme," the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy landscape motif and a rug design with snowflakes that suits the winter theme. The generated design is sent to the device and displayed to the user. The user can then fine-tune the color and pattern of the design and finalize the design.

[0101] Example prompt sentence:

[0102] "I'd like to update my interior with a winter theme. Please suggest wallpaper with a snowy landscape motif to match the theme, and a rug design that resembles snowflakes."

[0103] This invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Step 1:

[0106] The user starts the spatial computing device and inputs a request for a new interior design through the interface. For example, the user inputs a prompt statement such as "I want to update the interior with a winter theme." The device then receives this input information and performs an initial setup. It receives the user's request information as input and outputs the initial setup.

[0107] Step 2:

[0108] The device activates its built-in camera and depth sensor and begins a 3D scan of the entire room. The user walks around the room following the device's instructions, with the camera collecting image data and the depth sensor collecting distance data. This allows the device to recognize the shapes and positions of walls, floors, ceilings, furniture, and more in detail. The device receives room image data and distance data as input and outputs it as 3D scan data.

[0109] Step 3:

[0110] The device combines the acquired image data and distance data into a single dataset. It also adds information from markers and low-power wide-area communication tags installed in the room to improve the accuracy of the data. This dataset also includes user request information. It receives image data, distance data, tag information, and user request information as input and outputs this as an integrated dataset.

[0111] Step 4:

[0112] The device sends the integrated data set to the server, typically over Wi-Fi or a wired network. The server receives the data set. It takes the integrated data set as input and outputs the data in a format that can be analyzed by the server.

[0113] Step 5:

[0114] The server analyzes the received dataset and sets the parameters of the image generation AI. For example, if a user selects a "winter theme," the server instructs the AI ​​to generate snowy landscapes and interior designs with cool colors. It receives the integrated dataset as input and outputs the AI ​​parameters.

[0115] Step 6:

[0116] The server launches an image generation AI based on the set parameters to generate a new interior design. The generated design is then converted into a format suitable for compression and transfer within the server. The server receives AI parameters as input and outputs the generated design data.

[0117] Step 7:

[0118] The server sends the generated design data to the terminal, which receives the design data and prepares to decode it in real time. It receives the generated design data as input and outputs the decoded design data.

[0119] Step 8:

[0120] The device overlays the decoded design data in real space, allowing the user to visually confirm the new design in their room. For example, new snowy wallpaper is displayed on the wall and a snowflake-patterned rug is layered on the floor. The device receives decoded design data as input and outputs the design to be displayed in real space.

[0121] Step 9:

[0122] The user uses the device interface to fine-tune the color, pattern, and placement of the new design—for example, changing the wallpaper color to a slightly bluer hue or tweaking the pattern on the rug—and then finalizes the design. The system takes the user's adjustments as input and outputs the final design.

[0123] (Application example 1)

[0124] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0125] With conventional interior design systems, changing store layouts and updating displays requires time and effort, and requires specialized knowledge, making it difficult to implement easily and efficiently. Furthermore, there was a lack of a way to check the application to the real space in real time and make fine adjustments, which limited the user experience.

[0126] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0127] In this invention, the server includes a means for generating a new design based on a design theme selected by a user, a means for scanning the environment, and a means for transmitting the generated design to the device and displaying it in real time, thereby enabling the interior design of a store to be updated quickly and efficiently, maximizing the visual effect.

[0128] A "spatial computing device" is an integrated system of hardware and software for scanning physical space and processing it as digital data.

[0129] "Means for scanning the environment" refers to the ability to acquire 3D data of physical space using cameras and depth sensors.

[0130] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via a network.

[0131] "Image generation artificial intelligence" is an AI model that automatically generates interior designs that meet the user's specifications based on the data it receives.

[0132] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated design data to the user's device quickly and efficiently and displaying it overlaid on the real space.

[0133] The "means for generating a new design based on a design theme selected by the user" is a function that automatically generates a customized design according to a theme and parameters selected by the user.

[0134] The "means for identifying markers or low-power wide-area communication tags" refers to a function that recognizes identification markers or tags placed in the physical environment and acquires their positions and information.

[0135] "Means that allow the user to check and adjust the design through a user interface" refers to an interactive interface that allows the user to visually check the design and adjust the color, placement, etc. as necessary.

[0136] MODE FOR CARRYING OUT THE INVENTION

[0137] System Overview

[0138] This invention is a system that combines spatial computing technology and image generation artificial intelligence to enable easy and low-cost interior design changes. This system functions through collaboration between users, devices (such as smartphones), and a server.

[0139] Hardware

[0140] Device (smartphone): Equipped with a camera, depth sensor, and display.

[0141] Server: Responsible for data processing and running generative AI models.

[0142] Identification marker or low-power wide-area communication tag: Installed to supplement environmental information.

[0143] software

[0144] 3D scanning application: Takes scans of the environment and sends them to a server.

[0145] Generative AI model: Generate designs using image-generating AI.

[0146] Interface application: Provides a user interface for theme selection, design display, and adjustment.

[0147] Process Overview

[0148] Scanning the Environment

[0149] Users use their smartphone's camera and depth sensor to scan the entire environment of a physical store. The 3D data acquired through the scan is centralized on the terminal. Identification markers and low-power wide-area communication tags are also read to improve the accuracy of the data.

[0150] Sending data to the server

[0151] The device sends the acquired scan data and information about the design theme selected by the user to a server, which analyzes the data and performs advanced processing.

[0152] Generate the design

[0153] The server uses a generative AI model (e.g., DALL-E or GPT-4 (registered trademark) related models) to generate new interior designs. The generative AI automatically creates customized designs based on a theme selected by the user. For example, when generating a "design for a summer sales campaign," the generative AI provides a design based on bright blue and white.

[0154] Applying and adjusting the design

[0155] The generated design is sent as digital data from the server to the device and displayed in real time in the real world. Through the device's user interface, the user can check the design and fine-tune the color and placement as needed.

[0156] Examples and prompts

[0157] For example, if a user selects "Design for Summer Sale Campaign," the following prompt sentence is input to the generative AI model:

[0158] Generate an interior design for a store's summer sale campaign. The theme should be "light blue and white," with summery decorations and a poster displaying the text "Summer Sale."

[0159] This process allows users to quickly and effectively update their store's interior design and maximize visual impact.

[0160] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0161] Program processing flow

[0162] Step 1:

[0163] The user launches a dedicated application on their smartphone and selects a new interior design theme through the application interface, for example, selecting "Summer Sale Campaign Design."

[0164] Specific behavior:

[0165] The user operates the theme selection UI and selects the desired theme.

[0166] Input: User design theme selection

[0167] Output: Selected theme information

[0168] Step 2:

[0169] The device uses the smartphone's camera and depth sensor to perform a 3D scan of the entire physical store environment.

[0170] Specific behavior:

[0171] The device captures camera images and collects distance data using a depth sensor.

[0172] Generate mesh data and integrate spatial information.

[0173] Input: Camera footage of the environment and depth sensor data

[0174] Output: 3D spatial data (mesh data)

[0175] Step 3:

[0176] The terminal transmits the scan data and the design theme information selected by the user together to the server.

[0177] Specific behavior:

[0178] The device combines the scan data and thematic information into a single dataset.

[0179] Send it to the server using a data communication protocol.

[0180] Input: Scan data and subject information

[0181] Output: The dataset sent to the server

[0182] Step 4:

[0183] The server analyzes the received dataset and generates a new interior design using a generative AI model.

[0184] Specific behavior:

[0185] The server analyzes the dataset and extracts conditions based on spatial structure and themes.

[0186] A prompt is input into a generative AI model (e.g., DALL-E or a GPT-4-related model) to generate a design based on a specified theme.

[0187] Input: Dataset sent to the server, prompt statement

[0188] Output: Generated interior design data

[0189] Step 5:

[0190] The server sends the generated design data to a smartphone.

[0191] Specific behavior:

[0192] The server converts the generated design data into a highly efficient data format.

[0193] It is sent to a smartphone using a data communication protocol.

[0194] Input: Generated interior design data

[0195] Output: Design data sent to your smartphone

[0196] Step 6:

[0197] The design data received by the device is displayed in real space in real time.

[0198] Specific behavior:

[0199] The device decodes the design data and uses AR technology to overlay it onto the real world.

[0200] Input: Design data sent to your smartphone

[0201] Output: Interior design overlaid on real space

[0202] Step 7:

[0203] The user can use the device interface to view the new design and make any necessary adjustments to the color, pattern, etc.

[0204] Specific behavior:

[0205] The user operates the UI to fine-tune the design (changing the color and layout).

[0206] The adjustments are applied in real time and the display is updated.

[0207] Input: User adjustments

[0208] Output: Coordinated interior design

[0209] Step 8:

[0210] Once the adjustments are complete, the user finalizes the design and incorporates it into the interior.

[0211] Specific behavior:

[0212] The user presses the confirm button for the design.

[0213] The finalized design data is saved and the final display is maintained.

[0214] Input: User's final confirmation operation

[0215] Output: Finalized interior design

[0216] Through the above processing steps, users can quickly and effectively update the interior design of their physical store.

[0217] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0218] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize easy and low-cost interior design changes. It also includes an emotion engine that recognizes the user's emotions in real time and dynamically adjusts the interior design based on those emotions. This system functions through collaboration between the user, terminals, and server, and performs the following program processing:

[0219] System Overview

[0220] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends it back to the device. The device displays this design in real space in real time, recognizing the user's emotions with an emotion engine and adjusting the design accordingly. The user can review the design and make further adjustments as needed.

[0221] Program processing

[0222] The user sends a request from the device

[0223] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[0224] The device scans the environment

[0225] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[0226] The device sends environmental data to the server

[0227] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[0228] The server starts the image generation AI

[0229] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[0230] The server generates a design and sends it to the device.

[0231] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[0232] The device adapts the design to the interior

[0233] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[0234] Emotion recognition by emotion engine

[0235] The device uses a built-in emotion engine to analyze the user's facial expressions and voice data in real time to recognize their emotions. For example, if the system determines that the user is relaxed, it will change the color tone of the design to a softer tone.

[0236] Emotion-based design adjustments

[0237] The device dynamically adjusts the hue and brightness of the design based on the user's emotions. If the system determines that the user is feeling stressed, it will change the color tone or pattern of the design to provide a more relaxing environment.

[0238] User checks and adjusts the design

[0239] The user can use the device to check the new design and, if necessary, further adjust the color, pattern, etc. Once the adjustments are complete, the design is finalized and reflected in the interior.

[0240] Specific examples

[0241] For example, if a user requests to update their interior with a winter theme, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy motif and a rug design that resembles snowflakes. The generated designs are then sent to the device for the user to review. The emotion engine then analyzes the user's facial expressions and, if it determines that the user is relaxed, adjusts the wallpaper color to a softer tone. The user can then adjust the rug's color to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[0242] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis, and further allows them to enjoy a comfortable living space that suits their own feelings.

[0243] The processing flow will be explained below.

[0244] Step 1:

[0245] A user activates a spatial computing device. The user sends a request to select a "winter theme" interior design from the device's interface.

[0246] Step 2:

[0247] The device receives the user's request and begins a 3D scan of the entire room using its built-in camera and depth sensor. During the scanning process, the device recognizes the shape and position of the walls, floor, ceiling, furniture, etc. in detail.

[0248] Step 3:

[0249] The device reads markers and low-power wide-area communication tags to complement the acquired scan data, thereby improving the accuracy of environmental data.

[0250] Step 4:

[0251] The device sends a dataset containing the scan results and marker / tag data to the server via the network, along with user request information.

[0252] Step 5:

[0253] The server analyzes the received data set. Based on the user's preferences and requests, the server sets the parameters of the image generation AI. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[0254] Step 6:

[0255] The server converts and encodes the generated interior design data into a format that can be efficiently transmitted, and then transmits the design data to the terminal.

[0256] Step 7:

[0257] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[0258] Step 8:

[0259] The device uses its built-in emotion engine to analyze the user's facial expressions and voice data in real time and recognize their emotions, for example, determining when the user is relaxed.

[0260] Step 9:

[0261] The device dynamically adjusts the hue and brightness of the interior design based on the perceived emotion, for example, changing the color palette to softer tones if the user is relaxed.

[0262] Step 10:

[0263] The user visually checks the new interior design displayed on the device, and then operates the interface to further adjust the design details (e.g., the color or pattern of the rug) as needed.

[0264] Step 11:

[0265] The device will reflect the user's adjustments and finalize the design, updating the entire room's interior with a "winter theme."

[0266] This system allows users to easily and inexpensively change their interior design, and enjoy a comfortable living space that suits their own emotions.

[0267] Example 2

[0268] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0269] Conventional interior design systems require users to manually adjust the design, which is inefficient. Furthermore, they cannot adjust the design based on the user's feelings, which can lead to low user satisfaction. Furthermore, there is a lack of a way to check and adjust the design in real time.

[0270] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0271] In this invention, the server includes a means for scanning the environment, a means for transmitting the scan results to the server, a means for generating an interior design using image generation artificial intelligence, a means for transmitting the generated design to the device and displaying it in real time, an emotion recognition means for recognizing a user's emotions in real time, and a means for dynamically adjusting the design using the emotion recognition means. This enables automatic generation and adjustment of interior designs based on the user's emotions, improving user satisfaction. Furthermore, the ability to check and adjust the design in real time allows for efficient interior design.

[0272] A "spatial computing device" is a device that can digitize real-world physical spaces and overlay information using 3D scanning and augmented reality (AR) technology.

[0273] "Means for scanning the environment" refers to the function of using a spatial computing device to obtain the shape, position, dimensions, etc. of a room or object in 3D.

[0274] The "means for transmitting the scan results to the server" is a communication function for transmitting the scan data to the server via the network.

[0275] "Image generation artificial intelligence" is an AI technology that automatically generates interior designs based on received data and specified parameters.

[0276] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function that transmits the interior design data generated by the server to the device and visually displays the design superimposed on the real space.

[0277] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotions in real time.

[0278] The "means for dynamically adjusting the design using emotion recognition means" is a function that automatically adjusts the interior design based on the emotion recognition results.

[0279] A "marker" is a physical landmark that a spatial computing device references to accurately scan its environment.

[0280] A "low-power wide-area communication tag" is a tag device that can communicate over a wide area using very little power, and is used to identify information and the location of objects.

[0281] A "user interface" is a screen or operation panel that allows a user to interact with a system, and is an element that allows the user to check and adjust the design.

[0282] This system combines spatial computing technology and image generation artificial intelligence (AI) to enable easy and low-cost interior design changes. It also features an emotion engine that recognizes user emotions in real time and dynamically adjusts the interior design based on those emotions.

[0283] System configuration

[0284] The system mainly consists of the following components:

[0285] 1. Spatial computing equipment (e.g., spatial computing device)

[0286] 2. Server (e.g., cloud server)

[0287] 3. Device (e.g., smartphone or tablet)

[0288] Hardware and software used

[0289] Spatial Computing Device: Use a Microsoft® HoloLens 2 or similar device to perform a 3D scan of the environment.

[0290] Device: A mobile device such as an iPhone (registered trademark) or iPad (registered trademark) Pro is used to provide the user interface and real-time display.

[0291] Server: Cloud servers such as Amazon Web Services (AWS®) and Google® Cloud Platform (GCP) are used to analyze data and run the image generation AI.

[0292] Image generation AI: Automatically generate interior designs using OpenAI's (registered trademark) DALL-E and GAN-based generative models.

[0293] Emotion Recognition Software: Use emotion recognition technology such as the Affectiva SDK to analyze user emotions in real time.

[0294] System Operation

[0295] First, a user uses a spatial computing device to operate the interface and input their interior design request. For example, if they select a "winter theme," the device performs a 3D scan of the environment and sends the scan data to a server. The server then analyzes the data and uses image generation AI to generate a new interior design.

[0296] The generated design is sent to the device and displayed in real time. The device is also equipped with an emotion recognition engine that analyzes the user's facial expressions and voice and adjusts the design based on their emotion. For example, if the system determines that the user is relaxed, it will change the wallpaper color to a softer tone. The user can also review the final design on the device and manually adjust the color and pattern as needed.

[0297] Specific examples

[0298] For example, if a user requests a "relaxing living room," the following system actions will occur:

[0299] 1. The user enters a request into the terminal and sends it.

[0300] 2. The device performs a 3D scan of the entire room and sends the scan data to the server.

[0301] 3. The server uses the generative AI model to generate a relaxing interior design, for example, automatically placing furniture and decorations in bright blue and green tones.

[0302] 4. The generated design is sent to the device, where the user can view it in real time using AR technology.

[0303] 5. The emotion engine analyzes the user's facial expressions and, in some cases, automatically adjusts color and placement.

[0304] 6. The user performs a final review and makes any necessary manual adjustments before finalizing the design.

[0305] Prompt Sentence Examples

[0306] Examples of prompts you might enter into a generative AI model include:

[0307] "The user requested that the living room be a relaxing space. Please generate calming colors and natural designs."

[0308] "A user wants to update their interior design with a winter theme. Generate designs for wallpaper with a snowy landscape motif and a snowflake-inspired rug."

[0309] "The system has determined that the user is stressed. Please generate a more relaxing design."

[0310] As described above, the system of the present invention combines a spatial computing device, image generation AI, and emotion recognition technology to enable the automatic generation and adjustment of interior designs based on the user's emotions.

[0311] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0312] Step 1:

[0313] The user sends a request from the device

[0314] The user operates the spatial computing device and inputs a request. The input may include an "interior design theme" or a "specific color scheme." The device then sends this request data to the server. The output is the user's request data.

[0315] Step 2:

[0316] The device scans the environment

[0317] The device's built-in camera and depth sensor are used to perform a 3D scan of the entire room. For example, the shape and position of walls, floors, ceilings, furniture, etc. are recognized. Scan data is collected, and markers and low-power wide-area communication tags are also read. The input is physical environment information, and the output is 3D scan data.

[0318] Step 3:

[0319] The device sends environmental data to the server

[0320] The scan data and user request data are combined into a single dataset and sent to the server. Specifically, it includes 3D model data and location information of the scanned object. This dataset is sent to the server in JSON format or similar. The input is the 3D scan data and request data, and the output is an integrated dataset.

[0321] Step 4:

[0322] The server starts the image generation AI

[0323] The server analyzes the received dataset. Based on the user request and the environmental data, it sets the parameters of a generative AI model (e.g., OpenAI's DALL-E). The image generation AI generates a new interior design. The input is the integrated dataset, and the output is the generated design data.

[0324] Step 5:

[0325] The server generates a design and sends it to the device.

[0326] The generated design is converted back into a data format and efficiently transmitted to the terminal. Data compression techniques and network optimization are used to minimize delays. The input is the generated design data, and the output is the transmitted design data.

[0327] Step 6:

[0328] The device adapts the design to the interior

[0329] The device decodes the received design data and displays it overlaid on the real space. For example, using AR technology, new wallpaper and furniture arrangements are displayed in real time as the user looks around the room. The input is the transmitted design data, and the output is the application of the design to the real space.

[0330] Step 7:

[0331] Emotion recognition by emotion engine

[0332] The device uses a built-in emotion engine to analyze the user's facial expressions and voice in real time. Emotion recognition software (e.g., Affectiva SDK) determines the user's emotions. The input is the user's facial expressions and voice data, and the output is the emotion recognition results.

[0333] Step 8:

[0334] Emotion-based design adjustments

[0335] The device dynamically adjusts the design based on the emotion recognition results. For example, if it determines that the user is relaxed, it changes the color to a softer tone. Conversely, if it determines that the user is stressed, it adjusts the design to be more relaxing. The input is the emotion recognition result, and the output is the adjusted design.

[0336] Step 9:

[0337] User checks and adjusts the design

[0338] The user can use the device to check the final design and manually adjust it as needed, for example, changing the wallpaper color from blue to green. Once the adjustments are complete, the design is finalized and reflected in the interior. The input is the adjusted design, and the output is the finalized design.

[0339] (Application example 2)

[0340] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0341] Conventional interior design change systems require manual adjustments by users or expert intervention, resulting in time-consuming and costly changes. Furthermore, it is difficult to reflect users' emotions and preferences in real time, making it difficult to achieve optimal interior designs. Especially in brick-and-mortar stores, interior changes directly affect customers' purchasing behavior and experiences, so instant and effective design changes are required.

[0342] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0343] In this invention, the server includes means for scanning the environment, means for transmitting the scan results to the server, means for generating an interior design using image generation AI, means for transmitting the generated design to the device and displaying it in real time, and means for recognizing a user's emotions in real time and dynamically adjusting the design based on the emotions. This allows the user to instantly and effortlessly change the interior design to the optimum one, which is expected to improve the customer experience, especially in physical stores.

[0344] "Means for scanning the environment" refers to a function that uses a camera, depth sensor, etc. to acquire the target's physical environment as 3D data.

[0345] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via the Internet or wireless communication.

[0346] "Image generation artificial intelligence" is a technology that automatically generates images and designs from input data using a generative AI model.

[0347] The "server that generates interior designs" is a server computer that uses image generation artificial intelligence to generate new interior designs based on received environmental data and user requests.

[0348] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated interior design to the terminal and displaying the design superimposed on the real space.

[0349] "Means for recognizing user emotions in real time" refers to technology that uses a camera and microphone to analyze the user's facial expressions and voice and identify their emotions.

[0350] The "means for dynamically adjusting design based on emotions" is a function that automatically changes the color and pattern of the interior design according to the recognized emotions of the user.

[0351] An "identification marker" is a visual marker used to recognize and track a specific object or location.

[0352] A "low-power communication tag" is a tag that consumes very little power and enables low-power communication, and is used as a means of identifying specific objects or locations within an environment.

[0353] "User interface" is a general term for software that provides interactive screens and control elements for users to operate a system.

[0354] To implement this invention, a spatial computing device, smart glasses, a server, an image generation artificial intelligence (generative AI model), an emotion recognition engine, and a user interface are required.

[0355] First, a user puts on the smart glasses and inputs a request for a new interior design through the interface, specifying specific design requirements by entering prompt statements such as, "Generate a spring-themed interior design. Use cherry blossom-themed wallpaper and a pale pink color palette."

[0356] The smart glasses use a built-in camera and depth sensor to 3D scan the environment in the store. The resulting data is sent to a server via a communication module. The hardware used here is smart glasses (e.g., Microsoft HoloLens).

[0357] The server receives the scan results and automatically generates a new interior design using a generative AI model, such as OpenAI's DALL-E 2. This model generates an interior design that matches a specified theme based on the prompt text and scan data provided by the user.

[0358] The generated design is converted into a digital format and sent to the smart glasses, which decode the design data and display it in real time overlaid on the real space inside the store, allowing users to visually confirm the new interior design.

[0359] Additionally, the smart glasses are equipped with a built-in camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The emotion recognition engine uses Affectiva's technology. The recognized emotions are dynamically reflected in the new interior design through an emotion-responsive design module. For example, if the user is relaxed, the system will change the design's color palette to a softer tone.

[0360] Users can make additional adjustments to the generated design through the smart glasses interface, and the final design will be finalized and implemented as the interior design for the physical store.

[0361] Through this system's series of processes, the interior design of a physical store can respond to the emotions and desires of users and be kept in an optimal state at all times. By using this system, the customer experience in the store can be improved, and sales are expected to increase.

[0362] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0363] Step 1:

[0364] The user activates the smart glasses and inputs a request for a new interior design through the interface. The user enters a prompt such as, "Generate a spring-themed interior design. Use wallpaper with a cherry blossom motif and a color palette based on pale pink." This prompt becomes the input data.

[0365] Step 2:

[0366] The smart glasses use a built-in camera and depth sensor to perform a 3D scan of the store's environment, capturing detailed information about the shape and position of walls, floors, ceilings, furniture, etc. The acquired scan data is used as output data.

[0367] Step 3:

[0368] The smart glasses use a communication module to send the resulting data, including the prompt text entered by the user and the 3D scan data of the environment, to a server, which receives this data set.

[0369] Step 4:

[0370] The server automatically generates a new interior design using a generative AI model based on the received prompt and scan data. The image generation AI (e.g., OpenAI's DALL-E 2) generates design images based on the specified theme. These generated design images become the output data.

[0371] Step 5:

[0372] The server converts the generated design image into a digital format and sends it to the smart glasses, which receive the design data, decode it, and display it overlaid on the real world in real time, allowing the user to visually check the interior design.

[0373] Step 6:

[0374] The smart glasses use a built-in camera and microphone to analyze the user's facial expressions and voice in real time, and then use an emotion recognition engine (e.g., Affectiva) to identify the user's emotions. The recognized emotion data is the output.

[0375] Step 7:

[0376] The server uses an emotion-responsive design module to dynamically adjust the color and pattern of the interior design based on the recognized emotion data. For example, if the user is determined to be relaxed, the system will change the color of the design to a softer tone. The result of this adjustment becomes the output data.

[0377] Step 8:

[0378] The user can make further adjustments to the generated design through the smart glasses interface. The user fine-tunes the color and pattern on the screen and then confirms the result as the final design. The final design is then output.

[0379] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0380] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0381] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0382] [Second embodiment]

[0383] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0384] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0385] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0386] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0387] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0388] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0389] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0390] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0391] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0392] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0393] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0394] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0395] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize interior design changes easily and at low cost. This system functions through collaboration between users, terminals, and servers, and performs the following program processing.

[0396] System Overview

[0397] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends the generated design back to the device. The device then displays the design in real space in real time, allowing the user to review it and make adjustments as needed.

[0398] Program processing

[0399] The user sends a request from the device

[0400] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[0401] The device scans the environment

[0402] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[0403] The device sends environmental data to the server

[0404] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[0405] The server starts the image generation AI

[0406] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[0407] The server generates a design and sends it to the device.

[0408] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[0409] The device adapts the design to the interior

[0410] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[0411] User checks and adjusts the design

[0412] The user can use the device to check the new design and make fine adjustments to the color, pattern, etc., if necessary. Once the adjustments are complete, the design is finalized and reflected in the interior.

[0413] Specific examples

[0414] For example, if a user requests a winter-themed interior update, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy theme and a rug design that resembles snowflakes. The generated design is then sent to the device for the user to review. The user can then adjust the rug's hue to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[0415] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[0416] The processing flow will be explained below.

[0417] Step 1:

[0418] A user activates a spatial computing device. The user sends a request through the device's interface to select a "winter theme" interior design.

[0419] Step 2:

[0420] The device receives the user's request. It then uses its built-in camera and depth sensor to begin a 3D scan of the room. During the scanning process, it recognizes the shape and position of walls, floors, ceilings, furniture, and other elements in detail. It also reads existing markers and low-power wide-area communication tags to supplement the environmental information.

[0421] Step 3:

[0422] The device compiles the scan results and marker / tag data into a single dataset, which also includes the user's request information, and sends the dataset to the server via the network.

[0423] Step 4:

[0424] The server analyzes the received data set. The server sets the parameters of the image generation AI based on the user's preferences and requests. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[0425] Step 5:

[0426] The server encodes the generated interior design data and converts it into a format that can be efficiently transmitted. The server then transmits the design data to the terminal.

[0427] Step 6:

[0428] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[0429] Step 7:

[0430] The user visually checks the new interior design displayed on the device. The user operates the interface to adjust design details (e.g., the color or pattern of the rug) as needed.

[0431] Step 8:

[0432] The device reflects the user's adjustments and confirms the final design. Once the user confirms the final design, the entire room's interior is updated with a "winter theme."

[0433] By following the above steps, users can easily and inexpensively change their interior design and enjoy a comfortable living space based on a new theme.

[0434] Example 1

[0435] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0436] Conventional interior design modification methods have the drawbacks of being time-consuming and expensive, and are difficult for users to implement easily. In addition, there are few ways to connect the real world with the design in real time, making it difficult to check and fine-tune the design.

[0437] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0438] In this invention, the server includes a means for setting parameters for the image generation AI based on a user request, a means for analyzing the scan results, and a means for generating an interior design using the image generation AI, thereby enabling the user to easily and inexpensively check and adjust the interior design in real time.

[0439] A "spatial computing device" is a device that includes hardware and software for recognizing and processing real-world physical environments in conjunction with digital information.

[0440] "Means for scanning the environment" refers to the ability to use built-in cameras and depth sensors to recognize the shape of physical space and the location of objects in detail.

[0441] "Means for sending scan results to a server" refers to the function of uploading the acquired data set to a remote server via a network.

[0442] "Image generation artificial intelligence" refers to algorithms or models that use machine learning or deep learning to generate images based on specified conditions.

[0443] "Means for setting parameters of the image generation artificial intelligence based on a user's request" refers to a function for adjusting settings for image generation in accordance with a design request input by a user.

[0444] "Means for transmitting the generated design to the device and displaying it in real time" refers to the function of efficiently delivering design data generated on the server to the terminal and displaying it immediately.

[0445] "Means for decoding and displaying in real time" refers to the function of quickly processing received design data and visualizing it overlaid on real space.

[0446] "Means for users to check and adjust the design" refers to a function that allows users to check the details of the design through a user interface and make any necessary changes or fine adjustments.

[0447] This invention is a system that allows users to easily and inexpensively change interior designs by combining spatial computing technology and image generation artificial intelligence (AI). This system works through the collaboration of users, terminals, and a server.

[0448] Hardware and Software Used

[0449] Specifically, the system uses the following hardware and software:

[0450] Spatial computing devices: Devices such as HoloLens and Magic Leap that recognize and process the real-world physical environment in conjunction with digital information.

[0451] Camera and depth sensor: Used to recognize the shape of the room and the position of objects in detail, allowing for a 3D scan of the environment.

[0452] Image-generating artificial intelligence (AI): Includes algorithms for generating interior designs based on user requests, such as DALL-E and Stable Diffusion.

[0453] Server: Analyzes data, sets AI parameters, and generates designs.

[0454] User Interface (UI): The interface through which users enter their requests and review and adjust the generated designs.

[0455] Data processing and calculation

[0456] The device first activates its camera and depth sensor to perform a 3D scan of the room specified by the user. This scan data includes the shape and location information of the walls, floor, ceiling, furniture, etc. The accuracy of the data can be improved by reading markers and low-power wide-area communication tags.

[0457] The device then compiles the scanned data into a single dataset and sends it to the server along with the user's request. The server then analyzes the dataset and sets the parameters for the image-generating AI. For example, if the user selects a "winter theme," the AI ​​will generate snowy landscapes and interior designs with cool colors.

[0458] The generated design data is efficiently transmitted to the device, which decodes it in real time and displays it overlaid on the real world. The user can view this display and make fine adjustments to the design through the interface.

[0459] Examples of concrete examples and prompts

[0460] When a user inputs a request into the device, such as "I want to update my interior with a winter theme," the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy landscape motif and a rug design with snowflakes that suits the winter theme. The generated design is sent to the device and displayed to the user. The user can then fine-tune the color and pattern of the design and finalize the design.

[0461] Example prompt sentence:

[0462] "I'd like to update my interior with a winter theme. Please suggest wallpaper with a snowy landscape motif to match the theme, and a rug design that resembles snowflakes."

[0463] This invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[0464] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0465] Step 1:

[0466] The user starts the spatial computing device and inputs a request for a new interior design through the interface. For example, the user inputs a prompt statement such as "I want to update the interior with a winter theme." The device then receives this input information and performs an initial setup. It receives the user's request information as input and outputs the initial setup.

[0467] Step 2:

[0468] The device activates its built-in camera and depth sensor and begins a 3D scan of the entire room. The user walks around the room following the device's instructions, with the camera collecting image data and the depth sensor collecting distance data. This allows the device to recognize the shapes and positions of walls, floors, ceilings, furniture, and more in detail. The device receives room image data and distance data as input and outputs it as 3D scan data.

[0469] Step 3:

[0470] The device combines the acquired image data and distance data into a single dataset. It also adds information from markers and low-power wide-area communication tags installed in the room to improve the accuracy of the data. This dataset also includes user request information. It receives image data, distance data, tag information, and user request information as input and outputs this as an integrated dataset.

[0471] Step 4:

[0472] The device sends the integrated data set to the server, typically over Wi-Fi or a wired network. The server receives the data set. It takes the integrated data set as input and outputs the data in a format that can be analyzed by the server.

[0473] Step 5:

[0474] The server analyzes the received dataset and sets the parameters of the image generation AI. For example, if a user selects a "winter theme," the server instructs the AI ​​to generate snowy landscapes and interior designs with cool colors. It receives the integrated dataset as input and outputs the AI ​​parameters.

[0475] Step 6:

[0476] The server launches an image generation AI based on the set parameters to generate a new interior design. The generated design is then converted into a format suitable for compression and transfer within the server. The server receives AI parameters as input and outputs the generated design data.

[0477] Step 7:

[0478] The server sends the generated design data to the terminal, which receives the design data and prepares to decode it in real time. It receives the generated design data as input and outputs the decoded design data.

[0479] Step 8:

[0480] The device overlays the decoded design data in real space, allowing the user to visually confirm the new design in their room. For example, new snowy wallpaper is displayed on the wall and a snowflake-patterned rug is layered on the floor. The device receives decoded design data as input and outputs the design to be displayed in real space.

[0481] Step 9:

[0482] The user uses the device interface to fine-tune the color, pattern, and placement of the new design—for example, changing the wallpaper color to a slightly bluer hue or tweaking the pattern on the rug—and then finalizes the design. The system takes the user's adjustments as input and outputs the final design.

[0483] (Application example 1)

[0484] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0485] With conventional interior design systems, changing store layouts and updating displays requires time and effort, and requires specialized knowledge, making it difficult to implement easily and efficiently. Furthermore, there was a lack of a way to check the application to the real space in real time and make fine adjustments, which limited the user experience.

[0486] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0487] In this invention, the server includes a means for generating a new design based on a design theme selected by a user, a means for scanning the environment, and a means for transmitting the generated design to the device and displaying it in real time, thereby enabling the interior design of a store to be updated quickly and efficiently, maximizing the visual effect.

[0488] A "spatial computing device" is an integrated system of hardware and software for scanning physical space and processing it as digital data.

[0489] "Means for scanning the environment" refers to the ability to acquire 3D data of physical space using cameras and depth sensors.

[0490] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via a network.

[0491] "Image generation artificial intelligence" is an AI model that automatically generates interior designs that meet the user's specifications based on the data it receives.

[0492] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated design data to the user's device quickly and efficiently and displaying it overlaid on the real space.

[0493] The "means for generating a new design based on a design theme selected by the user" is a function that automatically generates a customized design according to a theme and parameters selected by the user.

[0494] The "means for identifying markers or low-power wide-area communication tags" refers to a function that recognizes identification markers or tags placed in the physical environment and acquires their positions and information.

[0495] "Means that allow the user to check and adjust the design through a user interface" refers to an interactive interface that allows the user to visually check the design and adjust the color, placement, etc. as necessary.

[0496] MODE FOR CARRYING OUT THE INVENTION

[0497] System Overview

[0498] This invention is a system that combines spatial computing technology and image generation artificial intelligence to enable easy and low-cost interior design changes. This system functions through collaboration between users, devices (such as smartphones), and a server.

[0499] Hardware

[0500] Device (smartphone): Equipped with a camera, depth sensor, and display.

[0501] Server: Responsible for data processing and running generative AI models.

[0502] Identification marker or low-power wide-area communication tag: Installed to supplement environmental information.

[0503] software

[0504] 3D scanning application: Takes scans of the environment and sends them to a server.

[0505] Generative AI model: Generate designs using image-generating AI.

[0506] Interface application: Provides a user interface for theme selection, design display, and adjustment.

[0507] Process Overview

[0508] Scanning the Environment

[0509] Users use their smartphone's camera and depth sensor to scan the entire environment of a physical store. The 3D data acquired through the scan is centralized on the terminal. Identification markers and low-power wide-area communication tags are also read to improve the accuracy of the data.

[0510] Sending data to the server

[0511] The device sends the acquired scan data and information about the design theme selected by the user to a server, which analyzes the data and performs advanced processing.

[0512] Generate the design

[0513] The server uses a generative AI model (e.g., DALL-E or GPT-4 related models) to generate new interior designs. The generative AI automatically creates customized designs based on a theme selected by the user. For example, when generating a "summer sales campaign design," the generative AI provides a design based on bright blue and white.

[0514] Applying and adjusting the design

[0515] The generated design is sent as digital data from the server to the device and displayed in real time in the real world. Through the device's user interface, the user can check the design and fine-tune the color and placement as needed.

[0516] Examples and prompts

[0517] For example, if a user selects "Design for Summer Sale Campaign," the following prompt sentence is input to the generative AI model:

[0518] Generate an interior design for a store's summer sale campaign. The theme should be "light blue and white," with summery decorations and a poster displaying the text "Summer Sale."

[0519] This process allows users to quickly and effectively update their store's interior design and maximize visual impact.

[0520] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0521] Program processing flow

[0522] Step 1:

[0523] The user launches a dedicated application on their smartphone and selects a new interior design theme through the application interface, for example, selecting "Summer Sale Campaign Design."

[0524] Specific behavior:

[0525] The user operates the theme selection UI and selects the desired theme.

[0526] Input: User design theme selection

[0527] Output: Selected theme information

[0528] Step 2:

[0529] The device uses the smartphone's camera and depth sensor to perform a 3D scan of the entire physical store environment.

[0530] Specific behavior:

[0531] The device captures camera images and collects distance data using a depth sensor.

[0532] Generate mesh data and integrate spatial information.

[0533] Input: Camera footage of the environment and depth sensor data

[0534] Output: 3D spatial data (mesh data)

[0535] Step 3:

[0536] The terminal transmits the scan data and the design theme information selected by the user together to the server.

[0537] Specific behavior:

[0538] The device combines the scan data and thematic information into a single dataset.

[0539] Send it to the server using a data communication protocol.

[0540] Input: Scan data and subject information

[0541] Output: The dataset sent to the server

[0542] Step 4:

[0543] The server analyzes the received dataset and generates a new interior design using a generative AI model.

[0544] Specific behavior:

[0545] The server analyzes the dataset and extracts conditions based on spatial structure and themes.

[0546] A prompt is input into a generative AI model (e.g., DALL-E or a GPT-4-related model) to generate a design based on a specified theme.

[0547] Input: Dataset sent to the server, prompt statement

[0548] Output: Generated interior design data

[0549] Step 5:

[0550] The server sends the generated design data to a smartphone.

[0551] Specific behavior:

[0552] The server converts the generated design data into a highly efficient data format.

[0553] It is sent to a smartphone using a data communication protocol.

[0554] Input: Generated interior design data

[0555] Output: Design data sent to your smartphone

[0556] Step 6:

[0557] The design data received by the device is displayed in real space in real time.

[0558] Specific behavior:

[0559] The device decodes the design data and uses AR technology to overlay it onto the real world.

[0560] Input: Design data sent to your smartphone

[0561] Output: Interior design overlaid on real space

[0562] Step 7:

[0563] The user can use the device interface to view the new design and make any necessary adjustments to the color, pattern, etc.

[0564] Specific behavior:

[0565] The user operates the UI to fine-tune the design (changing the color and layout).

[0566] The adjustments are applied in real time and the display is updated.

[0567] Input: User adjustments

[0568] Output: Coordinated interior design

[0569] Step 8:

[0570] Once the adjustments are complete, the user finalizes the design and incorporates it into the interior.

[0571] Specific behavior:

[0572] The user presses the confirm button for the design.

[0573] The finalized design data is saved and the final display is maintained.

[0574] Input: User's final confirmation operation

[0575] Output: Finalized interior design

[0576] Through the above processing steps, users can quickly and effectively update the interior design of their physical store.

[0577] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0578] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize easy and low-cost interior design changes. It also includes an emotion engine that recognizes the user's emotions in real time and dynamically adjusts the interior design based on those emotions. This system functions through collaboration between the user, terminals, and server, and performs the following program processing:

[0579] System Overview

[0580] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends it back to the device. The device displays this design in real space in real time, recognizing the user's emotions with an emotion engine and adjusting the design accordingly. The user can review the design and make further adjustments as needed.

[0581] Program processing

[0582] The user sends a request from the device

[0583] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[0584] The device scans the environment

[0585] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[0586] The device sends environmental data to the server

[0587] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[0588] The server starts the image generation AI

[0589] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[0590] The server generates a design and sends it to the device.

[0591] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[0592] The device adapts the design to the interior

[0593] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[0594] Emotion recognition by emotion engine

[0595] The device uses a built-in emotion engine to analyze the user's facial expressions and voice data in real time to recognize their emotions. For example, if the system determines that the user is relaxed, it will change the color tone of the design to a softer tone.

[0596] Emotion-based design adjustments

[0597] The device dynamically adjusts the hue and brightness of the design based on the user's emotions. If the system determines that the user is feeling stressed, it will change the color tone or pattern of the design to provide a more relaxing environment.

[0598] User checks and adjusts the design

[0599] The user can use the device to check the new design and, if necessary, further adjust the color, pattern, etc. Once the adjustments are complete, the design is finalized and reflected in the interior.

[0600] Specific examples

[0601] For example, if a user requests to update their interior with a winter theme, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy motif and a rug design that resembles snowflakes. The generated designs are then sent to the device for the user to review. The emotion engine then analyzes the user's facial expressions and, if it determines that the user is relaxed, adjusts the wallpaper color to a softer tone. The user can then adjust the rug's color to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[0602] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis, and further allows them to enjoy a comfortable living space that suits their own feelings.

[0603] The processing flow will be explained below.

[0604] Step 1:

[0605] A user activates a spatial computing device. The user sends a request to select a "winter theme" interior design from the device's interface.

[0606] Step 2:

[0607] The device receives the user's request and begins a 3D scan of the entire room using its built-in camera and depth sensor. During the scanning process, the device recognizes the shape and position of the walls, floor, ceiling, furniture, etc. in detail.

[0608] Step 3:

[0609] The device reads markers and low-power wide-area communication tags to complement the acquired scan data, thereby improving the accuracy of environmental data.

[0610] Step 4:

[0611] The device sends a dataset containing the scan results and marker / tag data to the server via the network, along with user request information.

[0612] Step 5:

[0613] The server analyzes the received data set. Based on the user's preferences and requests, the server sets the parameters of the image generation AI. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[0614] Step 6:

[0615] The server converts and encodes the generated interior design data into a format that can be efficiently transmitted, and then transmits the design data to the terminal.

[0616] Step 7:

[0617] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[0618] Step 8:

[0619] The device uses its built-in emotion engine to analyze the user's facial expressions and voice data in real time and recognize their emotions, for example, determining when the user is relaxed.

[0620] Step 9:

[0621] The device dynamically adjusts the hue and brightness of the interior design based on the perceived emotion, for example, changing the color palette to softer tones if the user is relaxed.

[0622] Step 10:

[0623] The user visually checks the new interior design displayed on the device, and then operates the interface to further adjust the design details (e.g., the color or pattern of the rug) as needed.

[0624] Step 11:

[0625] The device will reflect the user's adjustments and finalize the design, updating the entire room's interior with a "winter theme."

[0626] This system allows users to easily and inexpensively change their interior design, and enjoy a comfortable living space that suits their own emotions.

[0627] Example 2

[0628] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0629] Conventional interior design systems require users to manually adjust the design, which is inefficient. Furthermore, they cannot adjust the design based on the user's feelings, which can lead to low user satisfaction. Furthermore, there is a lack of a way to check and adjust the design in real time.

[0630] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0631] In this invention, the server includes a means for scanning the environment, a means for transmitting the scan results to the server, a means for generating an interior design using image generation artificial intelligence, a means for transmitting the generated design to the device and displaying it in real time, an emotion recognition means for recognizing a user's emotions in real time, and a means for dynamically adjusting the design using the emotion recognition means. This enables automatic generation and adjustment of interior designs based on the user's emotions, improving user satisfaction. Furthermore, the ability to check and adjust the design in real time allows for efficient interior design.

[0632] A "spatial computing device" is a device that can digitize real-world physical spaces and overlay information using 3D scanning and augmented reality (AR) technology.

[0633] "Means for scanning the environment" refers to the function of using a spatial computing device to obtain the shape, position, dimensions, etc. of a room or object in 3D.

[0634] The "means for transmitting the scan results to the server" is a communication function for transmitting the scan data to the server via the network.

[0635] "Image generation artificial intelligence" is an AI technology that automatically generates interior designs based on received data and specified parameters.

[0636] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function that transmits the interior design data generated by the server to the device and visually displays the design superimposed on the real space.

[0637] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotions in real time.

[0638] The "means for dynamically adjusting the design using emotion recognition means" is a function that automatically adjusts the interior design based on the emotion recognition results.

[0639] A "marker" is a physical landmark that a spatial computing device references to accurately scan its environment.

[0640] A "low-power wide-area communication tag" is a tag device that can communicate over a wide area using very little power, and is used to identify information and the location of objects.

[0641] A "user interface" is a screen or operation panel that allows a user to interact with a system, and is an element that allows the user to check and adjust the design.

[0642] This system combines spatial computing technology and image generation artificial intelligence (AI) to enable easy and low-cost interior design changes. It also features an emotion engine that recognizes user emotions in real time and dynamically adjusts the interior design based on those emotions.

[0643] System configuration

[0644] The system mainly consists of the following components:

[0645] 1. Spatial computing equipment (e.g., spatial computing device)

[0646] 2. Server (e.g., cloud server)

[0647] 3. Device (e.g., smartphone or tablet)

[0648] Hardware and software used

[0649] Spatial computing device: Uses a Microsoft HoloLens 2 or similar device to perform 3D scanning of the environment.

[0650] Device: A mobile device such as an iPhone or iPad Pro is used to provide the user interface and real-time display.

[0651] Server: Cloud servers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP) are used to run data analysis and image generation AI.

[0652] Image generation AI: Automatically generate interior designs using OpenAI's DALL-E and GAN-based generative models.

[0653] Emotion Recognition Software: Use emotion recognition technology such as the Affectiva SDK to analyze user emotions in real time.

[0654] System Operation

[0655] First, a user uses a spatial computing device to operate the interface and input their interior design request. For example, if they select a "winter theme," the device performs a 3D scan of the environment and sends the scan data to a server. The server then analyzes the data and uses image generation AI to generate a new interior design.

[0656] The generated design is sent to the device and displayed in real time. The device is also equipped with an emotion recognition engine that analyzes the user's facial expressions and voice and adjusts the design based on their emotion. For example, if the system determines that the user is relaxed, it will change the wallpaper color to a softer tone. The user can also review the final design on the device and manually adjust the color and pattern as needed.

[0657] Specific examples

[0658] For example, if a user requests a "relaxing living room," the following system actions will occur:

[0659] 1. The user enters a request into the terminal and sends it.

[0660] 2. The device performs a 3D scan of the entire room and sends the scan data to the server.

[0661] 3. The server uses the generative AI model to generate a relaxing interior design, for example, automatically placing furniture and decorations in bright blue and green tones.

[0662] 4. The generated design is sent to the device, where the user can view it in real time using AR technology.

[0663] 5. The emotion engine analyzes the user's facial expressions and, in some cases, automatically adjusts color and placement.

[0664] 6. The user performs a final review and makes any necessary manual adjustments before finalizing the design.

[0665] Prompt Sentence Examples

[0666] Examples of prompts you might enter into a generative AI model include:

[0667] "The user requested that the living room be a relaxing space. Please generate calming colors and natural designs."

[0668] "A user wants to update their interior design with a winter theme. Generate designs for wallpaper with a snowy landscape motif and a snowflake-inspired rug."

[0669] "The system has determined that the user is stressed. Please generate a more relaxing design."

[0670] As described above, the system of the present invention combines a spatial computing device, image generation AI, and emotion recognition technology to enable the automatic generation and adjustment of interior designs based on the user's emotions.

[0671] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0672] Step 1:

[0673] The user sends a request from the device

[0674] The user operates the spatial computing device and inputs a request. The input may include an "interior design theme" or a "specific color scheme." The device then sends this request data to the server. The output is the user's request data.

[0675] Step 2:

[0676] The device scans the environment

[0677] The device's built-in camera and depth sensor are used to perform a 3D scan of the entire room. For example, the shape and position of walls, floors, ceilings, furniture, etc. are recognized. Scan data is collected, and markers and low-power wide-area communication tags are also read. The input is physical environment information, and the output is 3D scan data.

[0678] Step 3:

[0679] The device sends environmental data to the server

[0680] The scan data and user request data are combined into a single dataset and sent to the server. Specifically, it includes 3D model data and location information of the scanned object. This dataset is sent to the server in JSON format or similar. The input is the 3D scan data and request data, and the output is an integrated dataset.

[0681] Step 4:

[0682] The server starts the image generation AI

[0683] The server analyzes the received dataset. Based on the user request and the environmental data, it sets the parameters of a generative AI model (e.g., OpenAI's DALL-E). The image generation AI generates a new interior design. The input is the integrated dataset, and the output is the generated design data.

[0684] Step 5:

[0685] The server generates a design and sends it to the device.

[0686] The generated design is converted back into a data format and efficiently transmitted to the terminal. Data compression techniques and network optimization are used to minimize delays. The input is the generated design data, and the output is the transmitted design data.

[0687] Step 6:

[0688] The device adapts the design to the interior

[0689] The device decodes the received design data and displays it overlaid on the real space. For example, using AR technology, new wallpaper and furniture arrangements are displayed in real time as the user looks around the room. The input is the transmitted design data, and the output is the application of the design to the real space.

[0690] Step 7:

[0691] Emotion recognition by emotion engine

[0692] The device uses a built-in emotion engine to analyze the user's facial expressions and voice in real time. Emotion recognition software (e.g., Affectiva SDK) determines the user's emotions. The input is the user's facial expressions and voice data, and the output is the emotion recognition results.

[0693] Step 8:

[0694] Emotion-based design adjustments

[0695] The device dynamically adjusts the design based on the emotion recognition results. For example, if it determines that the user is relaxed, it changes the color to a softer tone. Conversely, if it determines that the user is stressed, it adjusts the design to be more relaxing. The input is the emotion recognition result, and the output is the adjusted design.

[0696] Step 9:

[0697] User checks and adjusts the design

[0698] The user can use the device to check the final design and manually adjust it as needed, for example, changing the wallpaper color from blue to green. Once the adjustments are complete, the design is finalized and reflected in the interior. The input is the adjusted design, and the output is the finalized design.

[0699] (Application example 2)

[0700] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0701] Conventional interior design change systems require manual adjustments by users or expert intervention, resulting in time-consuming and costly changes. Furthermore, it is difficult to reflect users' emotions and preferences in real time, making it difficult to achieve optimal interior designs. Especially in brick-and-mortar stores, interior changes directly affect customers' purchasing behavior and experiences, so instant and effective design changes are required.

[0702] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0703] In this invention, the server includes means for scanning the environment, means for transmitting the scan results to the server, means for generating an interior design using image generation AI, means for transmitting the generated design to the device and displaying it in real time, and means for recognizing a user's emotions in real time and dynamically adjusting the design based on the emotions. This allows the user to instantly and effortlessly change the interior design to the optimum one, which is expected to improve the customer experience, especially in physical stores.

[0704] "Means for scanning the environment" refers to a function that uses a camera, depth sensor, etc. to acquire the target's physical environment as 3D data.

[0705] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via the Internet or wireless communication.

[0706] "Image generation artificial intelligence" is a technology that automatically generates images and designs from input data using a generative AI model.

[0707] The "server that generates interior designs" is a server computer that uses image generation artificial intelligence to generate new interior designs based on received environmental data and user requests.

[0708] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated interior design to the terminal and displaying the design superimposed on the real space.

[0709] "Means for recognizing user emotions in real time" refers to technology that uses a camera and microphone to analyze the user's facial expressions and voice and identify their emotions.

[0710] The "means for dynamically adjusting design based on emotions" is a function that automatically changes the color and pattern of the interior design according to the recognized emotions of the user.

[0711] An "identification marker" is a visual marker used to recognize and track a specific object or location.

[0712] A "low-power communication tag" is a tag that consumes very little power and enables low-power communication, and is used as a means of identifying specific objects or locations within an environment.

[0713] "User interface" is a general term for software that provides interactive screens and control elements for users to operate a system.

[0714] To implement this invention, a spatial computing device, smart glasses, a server, an image generation artificial intelligence (generative AI model), an emotion recognition engine, and a user interface are required.

[0715] First, a user puts on the smart glasses and inputs a request for a new interior design through the interface, specifying specific design requirements by entering prompt statements such as, "Generate a spring-themed interior design. Use cherry blossom-themed wallpaper and a pale pink color palette."

[0716] The smart glasses use a built-in camera and depth sensor to 3D scan the environment in the store. The resulting data is sent to a server via a communication module. The hardware used here is smart glasses (e.g., Microsoft HoloLens).

[0717] The server receives the scan results and automatically generates a new interior design using a generative AI model, such as OpenAI's DALL-E 2. This model generates an interior design that matches a specified theme based on the prompt text and scan data provided by the user.

[0718] The generated design is converted into a digital format and sent to the smart glasses, which decode the design data and display it in real time overlaid on the real space inside the store, allowing users to visually confirm the new interior design.

[0719] Additionally, the smart glasses are equipped with a built-in camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The emotion recognition engine uses Affectiva's technology. The recognized emotions are dynamically reflected in the new interior design through an emotion-responsive design module. For example, if the user is relaxed, the system will change the design's color palette to a softer tone.

[0720] Users can make additional adjustments to the generated design through the smart glasses interface, and the final design will be finalized and implemented as the interior design for the physical store.

[0721] Through this system's series of processes, the interior design of a physical store can respond to the emotions and desires of users and be kept in an optimal state at all times. By using this system, the customer experience in the store can be improved, and sales are expected to increase.

[0722] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0723] Step 1:

[0724] The user activates the smart glasses and inputs a request for a new interior design through the interface. The user enters a prompt such as, "Generate a spring-themed interior design. Use wallpaper with a cherry blossom motif and a color palette based on pale pink." This prompt becomes the input data.

[0725] Step 2:

[0726] The smart glasses use a built-in camera and depth sensor to perform a 3D scan of the store's environment, capturing detailed information about the shape and position of walls, floors, ceilings, furniture, etc. The acquired scan data is used as output data.

[0727] Step 3:

[0728] The smart glasses use a communication module to send the resulting data, including the prompt text entered by the user and the 3D scan data of the environment, to a server, which receives this data set.

[0729] Step 4:

[0730] The server automatically generates a new interior design using a generative AI model based on the received prompt and scan data. The image generation AI (e.g., OpenAI's DALL-E 2) generates design images based on the specified theme. These generated design images become the output data.

[0731] Step 5:

[0732] The server converts the generated design image into a digital format and sends it to the smart glasses, which receive the design data, decode it, and display it overlaid on the real world in real time, allowing the user to visually check the interior design.

[0733] Step 6:

[0734] The smart glasses use a built-in camera and microphone to analyze the user's facial expressions and voice in real time, and then use an emotion recognition engine (e.g., Affectiva) to identify the user's emotions. The recognized emotion data is the output.

[0735] Step 7:

[0736] The server uses an emotion-responsive design module to dynamically adjust the color and pattern of the interior design based on the recognized emotion data. For example, if the user is determined to be relaxed, the system will change the color of the design to a softer tone. The result of this adjustment becomes the output data.

[0737] Step 8:

[0738] The user can make further adjustments to the generated design through the smart glasses interface. The user fine-tunes the color and pattern on the screen and then confirms the result as the final design. The final design is then output.

[0739] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0740] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0741] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0742] [Third embodiment]

[0743] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0744] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0745] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0746] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0747] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0748] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0749] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0750] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0751] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0752] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0753] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0754] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0755] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize interior design changes easily and at low cost. This system functions through collaboration between users, terminals, and servers, and performs the following program processing.

[0756] System Overview

[0757] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends the generated design back to the device. The device then displays the design in real space in real time, allowing the user to review it and make adjustments as needed.

[0758] Program processing

[0759] The user sends a request from the device

[0760] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[0761] The device scans the environment

[0762] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[0763] The device sends environmental data to the server

[0764] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[0765] The server starts the image generation AI

[0766] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[0767] The server generates a design and sends it to the device.

[0768] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[0769] The device adapts the design to the interior

[0770] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[0771] User checks and adjusts the design

[0772] The user can use the device to check the new design and make fine adjustments to the color, pattern, etc., if necessary. Once the adjustments are complete, the design is finalized and reflected in the interior.

[0773] Specific examples

[0774] For example, if a user requests a winter-themed interior update, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy theme and a rug design that resembles snowflakes. The generated design is then sent to the device for the user to review. The user can then adjust the rug's hue to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[0775] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[0776] The processing flow will be explained below.

[0777] Step 1:

[0778] A user activates a spatial computing device. The user sends a request through the device's interface to select a "winter theme" interior design.

[0779] Step 2:

[0780] The device receives the user's request. It then uses its built-in camera and depth sensor to begin a 3D scan of the room. During the scanning process, it recognizes the shape and position of walls, floors, ceilings, furniture, and other elements in detail. It also reads existing markers and low-power wide-area communication tags to supplement the environmental information.

[0781] Step 3:

[0782] The device compiles the scan results and marker / tag data into a single dataset, which also includes the user's request information, and sends the dataset to the server via the network.

[0783] Step 4:

[0784] The server analyzes the received data set. The server sets the parameters of the image generation AI based on the user's preferences and requests. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[0785] Step 5:

[0786] The server encodes the generated interior design data and converts it into a format that can be efficiently transmitted. The server then transmits the design data to the terminal.

[0787] Step 6:

[0788] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[0789] Step 7:

[0790] The user visually checks the new interior design displayed on the device. The user operates the interface to adjust design details (e.g., the color or pattern of the rug) as needed.

[0791] Step 8:

[0792] The device reflects the user's adjustments and confirms the final design. Once the user confirms the final design, the entire room's interior is updated with a "winter theme."

[0793] By following the above steps, users can easily and inexpensively change their interior design and enjoy a comfortable living space based on a new theme.

[0794] Example 1

[0795] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0796] Conventional interior design modification methods have the drawbacks of being time-consuming and expensive, and are difficult for users to implement easily. In addition, there are few ways to connect the real world with the design in real time, making it difficult to check and fine-tune the design.

[0797] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0798] In this invention, the server includes a means for setting parameters for the image generation AI based on a user request, a means for analyzing the scan results, and a means for generating an interior design using the image generation AI, thereby enabling the user to easily and inexpensively check and adjust the interior design in real time.

[0799] A "spatial computing device" is a device that includes hardware and software for recognizing and processing real-world physical environments in conjunction with digital information.

[0800] "Means for scanning the environment" refers to the ability to use built-in cameras and depth sensors to recognize the shape of physical space and the location of objects in detail.

[0801] "Means for sending scan results to a server" refers to the function of uploading the acquired data set to a remote server via a network.

[0802] "Image generation artificial intelligence" refers to algorithms or models that use machine learning or deep learning to generate images based on specified conditions.

[0803] "Means for setting parameters of the image generation artificial intelligence based on a user's request" refers to a function for adjusting settings for image generation in accordance with a design request input by a user.

[0804] "Means for transmitting the generated design to the device and displaying it in real time" refers to the function of efficiently delivering design data generated on the server to the terminal and displaying it immediately.

[0805] "Means for decoding and displaying in real time" refers to the function of quickly processing received design data and visualizing it overlaid on real space.

[0806] "Means for users to check and adjust the design" refers to a function that allows users to check the details of the design through a user interface and make any necessary changes or fine adjustments.

[0807] This invention is a system that allows users to easily and inexpensively change interior designs by combining spatial computing technology and image generation artificial intelligence (AI). This system works through the collaboration of users, terminals, and a server.

[0808] Hardware and Software Used

[0809] Specifically, the system uses the following hardware and software:

[0810] Spatial computing devices: Devices such as HoloLens and Magic Leap that recognize and process the real-world physical environment in conjunction with digital information.

[0811] Camera and depth sensor: Used to recognize the shape of the room and the position of objects in detail, allowing for a 3D scan of the environment.

[0812] Image-generating artificial intelligence (AI): Includes algorithms for generating interior designs based on user requests, such as DALL-E and Stable Diffusion.

[0813] Server: Analyzes data, sets AI parameters, and generates designs.

[0814] User Interface (UI): The interface through which users enter their requests and review and adjust the generated designs.

[0815] Data processing and calculation

[0816] The device first activates its camera and depth sensor to perform a 3D scan of the room specified by the user. This scan data includes the shape and location information of the walls, floor, ceiling, furniture, etc. The accuracy of the data can be improved by reading markers and low-power wide-area communication tags.

[0817] The device then compiles the scanned data into a single dataset and sends it to the server along with the user's request. The server then analyzes the dataset and sets the parameters for the image-generating AI. For example, if the user selects a "winter theme," the AI ​​will generate snowy landscapes and interior designs with cool colors.

[0818] The generated design data is efficiently transmitted to the device, which decodes it in real time and displays it overlaid on the real world. The user can view this display and make fine adjustments to the design through the interface.

[0819] Examples of concrete examples and prompts

[0820] When a user inputs a request into the device, such as "I want to update my interior with a winter theme," the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy landscape motif and a rug design with snowflakes that suits the winter theme. The generated design is sent to the device and displayed to the user. The user can then fine-tune the color and pattern of the design and finalize the design.

[0821] Example prompt sentence:

[0822] "I'd like to update my interior with a winter theme. Please suggest wallpaper with a snowy landscape motif to match the theme, and a rug design that resembles snowflakes."

[0823] This invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[0824] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0825] Step 1:

[0826] The user starts the spatial computing device and inputs a request for a new interior design through the interface. For example, the user inputs a prompt statement such as "I want to update the interior with a winter theme." The device then receives this input information and performs an initial setup. It receives the user's request information as input and outputs the initial setup.

[0827] Step 2:

[0828] The device activates its built-in camera and depth sensor and begins a 3D scan of the entire room. The user walks around the room following the device's instructions, with the camera collecting image data and the depth sensor collecting distance data. This allows the device to recognize the shapes and positions of walls, floors, ceilings, furniture, and more in detail. The device receives room image data and distance data as input and outputs it as 3D scan data.

[0829] Step 3:

[0830] The device combines the acquired image data and distance data into a single dataset. It also adds information from markers and low-power wide-area communication tags installed in the room to improve the accuracy of the data. This dataset also includes user request information. It receives image data, distance data, tag information, and user request information as input and outputs this as an integrated dataset.

[0831] Step 4:

[0832] The device sends the integrated data set to the server, typically over Wi-Fi or a wired network. The server receives the data set. It takes the integrated data set as input and outputs the data in a format that can be analyzed by the server.

[0833] Step 5:

[0834] The server analyzes the received dataset and sets the parameters of the image generation AI. For example, if a user selects a "winter theme," the server instructs the AI ​​to generate snowy landscapes and interior designs with cool colors. It receives the integrated dataset as input and outputs the AI ​​parameters.

[0835] Step 6:

[0836] The server launches an image generation AI based on the set parameters to generate a new interior design. The generated design is then converted into a format suitable for compression and transfer within the server. The server receives AI parameters as input and outputs the generated design data.

[0837] Step 7:

[0838] The server sends the generated design data to the terminal, which receives the design data and prepares to decode it in real time. It receives the generated design data as input and outputs the decoded design data.

[0839] Step 8:

[0840] The device overlays the decoded design data in real space, allowing the user to visually confirm the new design in their room. For example, new snowy wallpaper is displayed on the wall and a snowflake-patterned rug is layered on the floor. The device receives decoded design data as input and outputs the design to be displayed in real space.

[0841] Step 9:

[0842] The user uses the device interface to fine-tune the color, pattern, and placement of the new design—for example, changing the wallpaper color to a slightly bluer hue or tweaking the pattern on the rug—and then finalizes the design. The system takes the user's adjustments as input and outputs the final design.

[0843] (Application example 1)

[0844] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0845] With conventional interior design systems, changing store layouts and updating displays requires time and effort, and requires specialized knowledge, making it difficult to implement easily and efficiently. Furthermore, there was a lack of a way to check the application to the real space in real time and make fine adjustments, which limited the user experience.

[0846] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0847] In this invention, the server includes a means for generating a new design based on a design theme selected by a user, a means for scanning the environment, and a means for transmitting the generated design to the device and displaying it in real time, thereby enabling the interior design of a store to be updated quickly and efficiently, maximizing the visual effect.

[0848] A "spatial computing device" is an integrated system of hardware and software for scanning physical space and processing it as digital data.

[0849] "Means for scanning the environment" refers to the ability to acquire 3D data of physical space using cameras and depth sensors.

[0850] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via a network.

[0851] "Image generation artificial intelligence" is an AI model that automatically generates interior designs that meet the user's specifications based on the data it receives.

[0852] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated design data to the user's device quickly and efficiently and displaying it overlaid on the real space.

[0853] The "means for generating a new design based on a design theme selected by the user" is a function that automatically generates a customized design according to a theme and parameters selected by the user.

[0854] The "means for identifying markers or low-power wide-area communication tags" refers to a function that recognizes identification markers or tags placed in the physical environment and acquires their positions and information.

[0855] "Means that allow the user to check and adjust the design through a user interface" refers to an interactive interface that allows the user to visually check the design and adjust the color, placement, etc. as necessary.

[0856] MODE FOR CARRYING OUT THE INVENTION

[0857] System Overview

[0858] This invention is a system that combines spatial computing technology and image generation artificial intelligence to enable easy and low-cost interior design changes. This system functions through collaboration between users, devices (such as smartphones), and a server.

[0859] Hardware

[0860] Device (smartphone): Equipped with a camera, depth sensor, and display.

[0861] Server: Responsible for data processing and running generative AI models.

[0862] Identification marker or low-power wide-area communication tag: Installed to supplement environmental information.

[0863] software

[0864] 3D scanning application: Takes scans of the environment and sends them to a server.

[0865] Generative AI model: Generate designs using image-generating AI.

[0866] Interface application: Provides a user interface for theme selection, design display, and adjustment.

[0867] Process Overview

[0868] Scanning the Environment

[0869] Users use their smartphone's camera and depth sensor to scan the entire environment of a physical store. The 3D data acquired through the scan is centralized on the terminal. Identification markers and low-power wide-area communication tags are also read to improve the accuracy of the data.

[0870] Sending data to the server

[0871] The device sends the acquired scan data and information about the design theme selected by the user to a server, which analyzes the data and performs advanced processing.

[0872] Generate the design

[0873] The server uses a generative AI model (e.g., DALL-E or GPT-4 related models) to generate new interior designs. The generative AI automatically creates customized designs based on a theme selected by the user. For example, when generating a "summer sales campaign design," the generative AI provides a design based on bright blue and white.

[0874] Applying and adjusting the design

[0875] The generated design is sent as digital data from the server to the device and displayed in real time in the real world. Through the device's user interface, the user can check the design and fine-tune the color and placement as needed.

[0876] Examples and prompts

[0877] For example, if a user selects "Design for Summer Sale Campaign," the following prompt sentence is input to the generative AI model:

[0878] Generate an interior design for a store's summer sale campaign. The theme should be "light blue and white," with summery decorations and a poster displaying the text "Summer Sale."

[0879] This process allows users to quickly and effectively update their store's interior design and maximize visual impact.

[0880] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0881] Program processing flow

[0882] Step 1:

[0883] The user launches a dedicated application on their smartphone and selects a new interior design theme through the application interface, for example, selecting "Summer Sale Campaign Design."

[0884] Specific behavior:

[0885] The user operates the theme selection UI and selects the desired theme.

[0886] Input: User design theme selection

[0887] Output: Selected theme information

[0888] Step 2:

[0889] The device uses the smartphone's camera and depth sensor to perform a 3D scan of the entire physical store environment.

[0890] Specific behavior:

[0891] The device captures camera images and collects distance data using a depth sensor.

[0892] Generate mesh data and integrate spatial information.

[0893] Input: Camera footage of the environment and depth sensor data

[0894] Output: 3D spatial data (mesh data)

[0895] Step 3:

[0896] The terminal transmits the scan data and the design theme information selected by the user together to the server.

[0897] Specific behavior:

[0898] The device combines the scan data and thematic information into a single dataset.

[0899] Send it to the server using a data communication protocol.

[0900] Input: Scan data and subject information

[0901] Output: The dataset sent to the server

[0902] Step 4:

[0903] The server analyzes the received dataset and generates a new interior design using a generative AI model.

[0904] Specific behavior:

[0905] The server analyzes the dataset and extracts conditions based on spatial structure and themes.

[0906] A prompt is input into a generative AI model (e.g., DALL-E or a GPT-4-related model) to generate a design based on a specified theme.

[0907] Input: Dataset sent to the server, prompt statement

[0908] Output: Generated interior design data

[0909] Step 5:

[0910] The server sends the generated design data to a smartphone.

[0911] Specific behavior:

[0912] The server converts the generated design data into a highly efficient data format.

[0913] It is sent to a smartphone using a data communication protocol.

[0914] Input: Generated interior design data

[0915] Output: Design data sent to your smartphone

[0916] Step 6:

[0917] The design data received by the device is displayed in real space in real time.

[0918] Specific behavior:

[0919] The device decodes the design data and uses AR technology to overlay it onto the real world.

[0920] Input: Design data sent to your smartphone

[0921] Output: Interior design overlaid on real space

[0922] Step 7:

[0923] The user can use the device interface to view the new design and make any necessary adjustments to the color, pattern, etc.

[0924] Specific behavior:

[0925] The user operates the UI to fine-tune the design (changing the color and layout).

[0926] The adjustments are applied in real time and the display is updated.

[0927] Input: User adjustments

[0928] Output: Coordinated interior design

[0929] Step 8:

[0930] Once the adjustments are complete, the user finalizes the design and incorporates it into the interior.

[0931] Specific behavior:

[0932] The user presses the confirm button for the design.

[0933] The finalized design data is saved and the final display is maintained.

[0934] Input: User's final confirmation operation

[0935] Output: Finalized interior design

[0936] Through the above processing steps, users can quickly and effectively update the interior design of their physical store.

[0937] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0938] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize easy and low-cost interior design changes. It also includes an emotion engine that recognizes the user's emotions in real time and dynamically adjusts the interior design based on those emotions. This system functions through collaboration between the user, terminals, and server, and performs the following program processing:

[0939] System Overview

[0940] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends it back to the device. The device displays this design in real space in real time, recognizing the user's emotions with an emotion engine and adjusting the design accordingly. The user can review the design and make further adjustments as needed.

[0941] Program processing

[0942] The user sends a request from the device

[0943] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[0944] The device scans the environment

[0945] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[0946] The device sends environmental data to the server

[0947] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[0948] The server starts the image generation AI

[0949] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[0950] The server generates a design and sends it to the device.

[0951] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[0952] The device adapts the design to the interior

[0953] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[0954] Emotion recognition by emotion engine

[0955] The device uses a built-in emotion engine to analyze the user's facial expressions and voice data in real time to recognize their emotions. For example, if the system determines that the user is relaxed, it will change the color tone of the design to a softer tone.

[0956] Emotion-based design adjustments

[0957] The device dynamically adjusts the hue and brightness of the design based on the user's emotions. If the system determines that the user is feeling stressed, it will change the color tone or pattern of the design to provide a more relaxing environment.

[0958] User checks and adjusts the design

[0959] The user can use the device to check the new design and, if necessary, further adjust the color, pattern, etc. Once the adjustments are complete, the design is finalized and reflected in the interior.

[0960] Specific examples

[0961] For example, if a user requests to update their interior with a winter theme, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy motif and a rug design that resembles snowflakes. The generated designs are then sent to the device for the user to review. The emotion engine then analyzes the user's facial expressions and, if it determines that the user is relaxed, adjusts the wallpaper color to a softer tone. The user can then adjust the rug's color to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[0962] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis, and further allows them to enjoy a comfortable living space that suits their own feelings.

[0963] The processing flow will be explained below.

[0964] Step 1:

[0965] A user activates a spatial computing device. The user sends a request to select a "winter theme" interior design from the device's interface.

[0966] Step 2:

[0967] The device receives the user's request and begins a 3D scan of the entire room using its built-in camera and depth sensor. During the scanning process, the device recognizes the shape and position of the walls, floor, ceiling, furniture, etc. in detail.

[0968] Step 3:

[0969] The device reads markers and low-power wide-area communication tags to complement the acquired scan data, thereby improving the accuracy of environmental data.

[0970] Step 4:

[0971] The device sends a dataset containing the scan results and marker / tag data to the server via the network, along with user request information.

[0972] Step 5:

[0973] The server analyzes the received data set. Based on the user's preferences and requests, the server sets the parameters of the image generation AI. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[0974] Step 6:

[0975] The server converts and encodes the generated interior design data into a format that can be efficiently transmitted, and then transmits the design data to the terminal.

[0976] Step 7:

[0977] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[0978] Step 8:

[0979] The device uses its built-in emotion engine to analyze the user's facial expressions and voice data in real time and recognize their emotions, for example, determining when the user is relaxed.

[0980] Step 9:

[0981] The device dynamically adjusts the hue and brightness of the interior design based on the perceived emotion, for example, changing the color palette to softer tones if the user is relaxed.

[0982] Step 10:

[0983] The user visually checks the new interior design displayed on the device, and then operates the interface to further adjust the design details (e.g., the color or pattern of the rug) as needed.

[0984] Step 11:

[0985] The device will reflect the user's adjustments and finalize the design, updating the entire room's interior with a "winter theme."

[0986] This system allows users to easily and inexpensively change their interior design, and enjoy a comfortable living space that suits their own emotions.

[0987] Example 2

[0988] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0989] Conventional interior design systems require users to manually adjust the design, which is inefficient. Furthermore, they cannot adjust the design based on the user's feelings, which can lead to low user satisfaction. Furthermore, there is a lack of a way to check and adjust the design in real time.

[0990] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0991] In this invention, the server includes a means for scanning the environment, a means for transmitting the scan results to the server, a means for generating an interior design using image generation artificial intelligence, a means for transmitting the generated design to the device and displaying it in real time, an emotion recognition means for recognizing a user's emotions in real time, and a means for dynamically adjusting the design using the emotion recognition means. This enables automatic generation and adjustment of interior designs based on the user's emotions, improving user satisfaction. Furthermore, the ability to check and adjust the design in real time allows for efficient interior design.

[0992] A "spatial computing device" is a device that can digitize real-world physical spaces and overlay information using 3D scanning and augmented reality (AR) technology.

[0993] "Means for scanning the environment" refers to the function of using a spatial computing device to obtain the shape, position, dimensions, etc. of a room or object in 3D.

[0994] The "means for transmitting the scan results to the server" is a communication function for transmitting the scan data to the server via the network.

[0995] "Image generation artificial intelligence" is an AI technology that automatically generates interior designs based on received data and specified parameters.

[0996] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function that transmits the interior design data generated by the server to the device and visually displays the design superimposed on the real space.

[0997] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotions in real time.

[0998] The "means for dynamically adjusting the design using emotion recognition means" is a function that automatically adjusts the interior design based on the emotion recognition results.

[0999] A "marker" is a physical landmark that a spatial computing device references to accurately scan its environment.

[1000] A "low-power wide-area communication tag" is a tag device that can communicate over a wide area using very little power, and is used to identify information and the location of objects.

[1001] A "user interface" is a screen or operation panel that allows a user to interact with a system, and is an element that allows the user to check and adjust the design.

[1002] This system combines spatial computing technology and image generation artificial intelligence (AI) to enable easy and low-cost interior design changes. It also features an emotion engine that recognizes user emotions in real time and dynamically adjusts the interior design based on those emotions.

[1003] System configuration

[1004] The system mainly consists of the following components:

[1005] 1. Spatial computing equipment (e.g., spatial computing device)

[1006] 2. Server (e.g., cloud server)

[1007] 3. Device (e.g., smartphone or tablet)

[1008] Hardware and software used

[1009] Spatial computing device: Uses a Microsoft HoloLens 2 or similar device to perform 3D scanning of the environment.

[1010] Device: A mobile device such as an iPhone or iPad Pro is used to provide the user interface and real-time display.

[1011] Server: Cloud servers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP) are used to run data analysis and image generation AI.

[1012] Image generation AI: Automatically generate interior designs using OpenAI's DALL-E and GAN-based generative models.

[1013] Emotion Recognition Software: Use emotion recognition technology such as the Affectiva SDK to analyze user emotions in real time.

[1014] System Operation

[1015] First, a user uses a spatial computing device to operate the interface and input their interior design request. For example, if they select a "winter theme," the device performs a 3D scan of the environment and sends the scan data to a server. The server then analyzes the data and uses image generation AI to generate a new interior design.

[1016] The generated design is sent to the device and displayed in real time. The device is also equipped with an emotion recognition engine that analyzes the user's facial expressions and voice and adjusts the design based on their emotion. For example, if the system determines that the user is relaxed, it will change the wallpaper color to a softer tone. The user can also review the final design on the device and manually adjust the color and pattern as needed.

[1017] Specific examples

[1018] For example, if a user requests a "relaxing living room," the following system actions will occur:

[1019] 1. The user enters a request into the terminal and sends it.

[1020] 2. The device performs a 3D scan of the entire room and sends the scan data to the server.

[1021] 3. The server uses the generative AI model to generate a relaxing interior design, for example, automatically placing furniture and decorations in bright blue and green tones.

[1022] 4. The generated design is sent to the device, where the user can view it in real time using AR technology.

[1023] 5. The emotion engine analyzes the user's facial expressions and, in some cases, automatically adjusts color and placement.

[1024] 6. The user performs a final review and makes any necessary manual adjustments before finalizing the design.

[1025] Prompt Sentence Examples

[1026] Examples of prompts you might enter into a generative AI model include:

[1027] "The user requested that the living room be a relaxing space. Please generate calming colors and natural designs."

[1028] "A user wants to update their interior design with a winter theme. Generate designs for wallpaper with a snowy landscape motif and a snowflake-inspired rug."

[1029] "The system has determined that the user is stressed. Please generate a more relaxing design."

[1030] As described above, the system of the present invention combines a spatial computing device, image generation AI, and emotion recognition technology to enable the automatic generation and adjustment of interior designs based on the user's emotions.

[1031] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1032] Step 1:

[1033] The user sends a request from the device

[1034] The user operates the spatial computing device and inputs a request. The input may include an "interior design theme" or a "specific color scheme." The device then sends this request data to the server. The output is the user's request data.

[1035] Step 2:

[1036] The device scans the environment

[1037] The device's built-in camera and depth sensor are used to perform a 3D scan of the entire room. For example, the shape and position of walls, floors, ceilings, furniture, etc. are recognized. Scan data is collected, and markers and low-power wide-area communication tags are also read. The input is physical environment information, and the output is 3D scan data.

[1038] Step 3:

[1039] The device sends environmental data to the server

[1040] The scan data and user request data are combined into a single dataset and sent to the server. Specifically, it includes 3D model data and location information of the scanned object. This dataset is sent to the server in JSON format or similar. The input is the 3D scan data and request data, and the output is an integrated dataset.

[1041] Step 4:

[1042] The server starts the image generation AI

[1043] The server analyzes the received dataset. Based on the user request and the environmental data, it sets the parameters of a generative AI model (e.g., OpenAI's DALL-E). The image generation AI generates a new interior design. The input is the integrated dataset, and the output is the generated design data.

[1044] Step 5:

[1045] The server generates a design and sends it to the device.

[1046] The generated design is converted back into a data format and efficiently transmitted to the terminal. Data compression techniques and network optimization are used to minimize delays. The input is the generated design data, and the output is the transmitted design data.

[1047] Step 6:

[1048] The device adapts the design to the interior

[1049] The device decodes the received design data and displays it overlaid on the real space. For example, using AR technology, new wallpaper and furniture arrangements are displayed in real time as the user looks around the room. The input is the transmitted design data, and the output is the application of the design to the real space.

[1050] Step 7:

[1051] Emotion recognition by emotion engine

[1052] The device uses a built-in emotion engine to analyze the user's facial expressions and voice in real time. Emotion recognition software (e.g., Affectiva SDK) determines the user's emotions. The input is the user's facial expressions and voice data, and the output is the emotion recognition results.

[1053] Step 8:

[1054] Emotion-based design adjustments

[1055] The device dynamically adjusts the design based on the emotion recognition results. For example, if it determines that the user is relaxed, it changes the color to a softer tone. Conversely, if it determines that the user is stressed, it adjusts the design to be more relaxing. The input is the emotion recognition result, and the output is the adjusted design.

[1056] Step 9:

[1057] User checks and adjusts the design

[1058] The user can use the device to check the final design and manually adjust it as needed, for example, changing the wallpaper color from blue to green. Once the adjustments are complete, the design is finalized and reflected in the interior. The input is the adjusted design, and the output is the finalized design.

[1059] (Application example 2)

[1060] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1061] Conventional interior design change systems require manual adjustments by users or expert intervention, resulting in time-consuming and costly changes. Furthermore, it is difficult to reflect users' emotions and preferences in real time, making it difficult to achieve optimal interior designs. Especially in brick-and-mortar stores, interior changes directly affect customers' purchasing behavior and experiences, so instant and effective design changes are required.

[1062] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1063] In this invention, the server includes means for scanning the environment, means for transmitting the scan results to the server, means for generating an interior design using image generation AI, means for transmitting the generated design to the device and displaying it in real time, and means for recognizing a user's emotions in real time and dynamically adjusting the design based on the emotions. This allows the user to instantly and effortlessly change the interior design to the optimum one, which is expected to improve the customer experience, especially in physical stores.

[1064] "Means for scanning the environment" refers to a function that uses a camera, depth sensor, etc. to acquire the target's physical environment as 3D data.

[1065] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via the Internet or wireless communication.

[1066] "Image generation artificial intelligence" is a technology that automatically generates images and designs from input data using a generative AI model.

[1067] The "server that generates interior designs" is a server computer that uses image generation artificial intelligence to generate new interior designs based on received environmental data and user requests.

[1068] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated interior design to the terminal and displaying the design superimposed on the real space.

[1069] "Means for recognizing user emotions in real time" refers to technology that uses a camera and microphone to analyze the user's facial expressions and voice and identify their emotions.

[1070] The "means for dynamically adjusting design based on emotions" is a function that automatically changes the color and pattern of the interior design according to the recognized emotions of the user.

[1071] An "identification marker" is a visual marker used to recognize and track a specific object or location.

[1072] A "low-power communication tag" is a tag that consumes very little power and enables low-power communication, and is used as a means of identifying specific objects or locations within an environment.

[1073] "User interface" is a general term for software that provides interactive screens and control elements for users to operate a system.

[1074] To implement this invention, a spatial computing device, smart glasses, a server, an image generation artificial intelligence (generative AI model), an emotion recognition engine, and a user interface are required.

[1075] First, a user puts on the smart glasses and inputs a request for a new interior design through the interface, specifying specific design requirements by entering prompt statements such as, "Generate a spring-themed interior design. Use cherry blossom-themed wallpaper and a pale pink color palette."

[1076] The smart glasses use a built-in camera and depth sensor to 3D scan the environment in the store. The resulting data is sent to a server via a communication module. The hardware used here is smart glasses (e.g., Microsoft HoloLens).

[1077] The server receives the scan results and automatically generates a new interior design using a generative AI model, such as OpenAI's DALL-E 2. This model generates an interior design that matches a specified theme based on the prompt text and scan data provided by the user.

[1078] The generated design is converted into a digital format and sent to the smart glasses, which decode the design data and display it in real time overlaid on the real space inside the store, allowing users to visually confirm the new interior design.

[1079] Additionally, the smart glasses are equipped with a built-in camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The emotion recognition engine uses Affectiva's technology. The recognized emotions are dynamically reflected in the new interior design through an emotion-responsive design module. For example, if the user is relaxed, the system will change the design's color palette to a softer tone.

[1080] Users can make additional adjustments to the generated design through the smart glasses interface, and the final design will be finalized and implemented as the interior design for the physical store.

[1081] Through this system's series of processes, the interior design of a physical store can respond to the emotions and desires of users and be kept in an optimal state at all times. By using this system, the customer experience in the store can be improved, and sales are expected to increase.

[1082] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1083] Step 1:

[1084] The user activates the smart glasses and inputs a request for a new interior design through the interface. The user enters a prompt such as, "Generate a spring-themed interior design. Use wallpaper with a cherry blossom motif and a color palette based on pale pink." This prompt becomes the input data.

[1085] Step 2:

[1086] The smart glasses use a built-in camera and depth sensor to perform a 3D scan of the store's environment, capturing detailed information about the shape and position of walls, floors, ceilings, furniture, etc. The acquired scan data is used as output data.

[1087] Step 3:

[1088] The smart glasses use a communication module to send the resulting data, including the prompt text entered by the user and the 3D scan data of the environment, to a server, which receives this data set.

[1089] Step 4:

[1090] The server automatically generates a new interior design using a generative AI model based on the received prompt and scan data. The image generation AI (e.g., OpenAI's DALL-E 2) generates design images based on the specified theme. These generated design images become the output data.

[1091] Step 5:

[1092] The server converts the generated design image into a digital format and sends it to the smart glasses, which receive the design data, decode it, and display it overlaid on the real world in real time, allowing the user to visually check the interior design.

[1093] Step 6:

[1094] The smart glasses use a built-in camera and microphone to analyze the user's facial expressions and voice in real time, and then use an emotion recognition engine (e.g., Affectiva) to identify the user's emotions. The recognized emotion data is the output.

[1095] Step 7:

[1096] The server uses an emotion-responsive design module to dynamically adjust the color and pattern of the interior design based on the recognized emotion data. For example, if the user is determined to be relaxed, the system will change the color of the design to a softer tone. The result of this adjustment becomes the output data.

[1097] Step 8:

[1098] The user can make further adjustments to the generated design through the smart glasses interface. The user fine-tunes the color and pattern on the screen and then confirms the result as the final design. The final design is then output.

[1099] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1100] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1101] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1102] [Fourth embodiment]

[1103] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1104] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1105] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1106] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1107] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1108] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1109] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1110] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1111] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1112] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1113] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1114] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1115] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1116] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize interior design changes easily and at low cost. This system functions through collaboration between users, terminals, and servers, and performs the following program processing.

[1117] System Overview

[1118] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends the generated design back to the device. The device then displays the design in real space in real time, allowing the user to review it and make adjustments as needed.

[1119] Program processing

[1120] The user sends a request from the device

[1121] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[1122] The device scans the environment

[1123] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[1124] The device sends environmental data to the server

[1125] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[1126] The server starts the image generation AI

[1127] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[1128] The server generates a design and sends it to the device.

[1129] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[1130] The device adapts the design to the interior

[1131] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[1132] User checks and adjusts the design

[1133] The user can use the device to check the new design and make fine adjustments to the color, pattern, etc., if necessary. Once the adjustments are complete, the design is finalized and reflected in the interior.

[1134] Specific examples

[1135] For example, if a user requests a winter-themed interior update, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy theme and a rug design that resembles snowflakes. The generated design is then sent to the device for the user to review. The user can then adjust the rug's hue to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[1136] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[1137] The processing flow will be explained below.

[1138] Step 1:

[1139] A user activates a spatial computing device. The user sends a request through the device's interface to select a "winter theme" interior design.

[1140] Step 2:

[1141] The device receives the user's request. It then uses its built-in camera and depth sensor to begin a 3D scan of the room. During the scanning process, it recognizes the shape and position of walls, floors, ceilings, furniture, and other elements in detail. It also reads existing markers and low-power wide-area communication tags to supplement the environmental information.

[1142] Step 3:

[1143] The device compiles the scan results and marker / tag data into a single dataset, which also includes the user's request information, and sends the dataset to the server via the network.

[1144] Step 4:

[1145] The server analyzes the received data set. The server sets the parameters of the image generation AI based on the user's preferences and requests. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[1146] Step 5:

[1147] The server encodes the generated interior design data and converts it into a format that can be efficiently transmitted. The server then transmits the design data to the terminal.

[1148] Step 6:

[1149] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[1150] Step 7:

[1151] The user visually checks the new interior design displayed on the device. The user operates the interface to adjust design details (e.g., the color or pattern of the rug) as needed.

[1152] Step 8:

[1153] The device reflects the user's adjustments and confirms the final design. Once the user confirms the final design, the entire room's interior is updated with a "winter theme."

[1154] By following the above steps, users can easily and inexpensively change their interior design and enjoy a comfortable living space based on a new theme.

[1155] Example 1

[1156] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1157] Conventional interior design modification methods have the drawbacks of being time-consuming and expensive, and are difficult for users to implement easily. In addition, there are few ways to connect the real world with the design in real time, making it difficult to check and fine-tune the design.

[1158] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1159] In this invention, the server includes a means for setting parameters for the image generation AI based on a user request, a means for analyzing the scan results, and a means for generating an interior design using the image generation AI, thereby enabling the user to easily and inexpensively check and adjust the interior design in real time.

[1160] A "spatial computing device" is a device that includes hardware and software for recognizing and processing real-world physical environments in conjunction with digital information.

[1161] "Means for scanning the environment" refers to the ability to use built-in cameras and depth sensors to recognize the shape of physical space and the location of objects in detail.

[1162] "Means for sending scan results to a server" refers to the function of uploading the acquired data set to a remote server via a network.

[1163] "Image generation artificial intelligence" refers to algorithms or models that use machine learning or deep learning to generate images based on specified conditions.

[1164] "Means for setting parameters of the image generation artificial intelligence based on a user's request" refers to a function for adjusting settings for image generation in accordance with a design request input by a user.

[1165] "Means for transmitting the generated design to the device and displaying it in real time" refers to the function of efficiently delivering design data generated on the server to the terminal and displaying it immediately.

[1166] "Means for decoding and displaying in real time" refers to the function of quickly processing received design data and visualizing it overlaid on real space.

[1167] "Means for users to check and adjust the design" refers to a function that allows users to check the details of the design through a user interface and make any necessary changes or fine adjustments.

[1168] This invention is a system that allows users to easily and inexpensively change interior designs by combining spatial computing technology and image generation artificial intelligence (AI). This system works through the collaboration of users, terminals, and a server.

[1169] Hardware and Software Used

[1170] Specifically, the system uses the following hardware and software:

[1171] Spatial computing devices: Devices such as HoloLens and Magic Leap that recognize and process the real-world physical environment in conjunction with digital information.

[1172] Camera and depth sensor: Used to recognize the shape of the room and the position of objects in detail, allowing for a 3D scan of the environment.

[1173] Image-generating artificial intelligence (AI): Includes algorithms for generating interior designs based on user requests, such as DALL-E and Stable Diffusion.

[1174] Server: Analyzes data, sets AI parameters, and generates designs.

[1175] User Interface (UI): The interface through which users enter their requests and review and adjust the generated designs.

[1176] Data processing and calculation

[1177] The device first activates its camera and depth sensor to perform a 3D scan of the room specified by the user. This scan data includes the shape and location information of the walls, floor, ceiling, furniture, etc. The accuracy of the data can be improved by reading markers and low-power wide-area communication tags.

[1178] The device then compiles the scanned data into a single dataset and sends it to the server along with the user's request. The server then analyzes the dataset and sets the parameters for the image-generating AI. For example, if the user selects a "winter theme," the AI ​​will generate snowy landscapes and interior designs with cool colors.

[1179] The generated design data is efficiently transmitted to the device, which decodes it in real time and displays it overlaid on the real world. The user can view this display and make fine adjustments to the design through the interface.

[1180] Examples of concrete examples and prompts

[1181] When a user inputs a request into the device, such as "I want to update my interior with a winter theme," the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy landscape motif and a rug design with snowflakes that suits the winter theme. The generated design is sent to the device and displayed to the user. The user can then fine-tune the color and pattern of the design and finalize the design.

[1182] Example prompt sentence:

[1183] "I'd like to update my interior with a winter theme. Please suggest wallpaper with a snowy landscape motif to match the theme, and a rug design that resembles snowflakes."

[1184] This invention allows users to easily and inexpensively update their interior design on a daily basis and enjoy a comfortable living space.

[1185] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1186] Step 1:

[1187] The user starts the spatial computing device and inputs a request for a new interior design through the interface. For example, the user inputs a prompt statement such as "I want to update the interior with a winter theme." The device then receives this input information and performs an initial setup. It receives the user's request information as input and outputs the initial setup.

[1188] Step 2:

[1189] The device activates its built-in camera and depth sensor and begins a 3D scan of the entire room. The user walks around the room following the device's instructions, with the camera collecting image data and the depth sensor collecting distance data. This allows the device to recognize the shapes and positions of walls, floors, ceilings, furniture, and more in detail. The device receives room image data and distance data as input and outputs it as 3D scan data.

[1190] Step 3:

[1191] The device combines the acquired image data and distance data into a single dataset. It also adds information from markers and low-power wide-area communication tags installed in the room to improve the accuracy of the data. This dataset also includes user request information. It receives image data, distance data, tag information, and user request information as input and outputs this as an integrated dataset.

[1192] Step 4:

[1193] The device sends the integrated data set to the server, typically over Wi-Fi or a wired network. The server receives the data set. It takes the integrated data set as input and outputs the data in a format that can be analyzed by the server.

[1194] Step 5:

[1195] The server analyzes the received dataset and sets the parameters of the image generation AI. For example, if a user selects a "winter theme," the server instructs the AI ​​to generate snowy landscapes and interior designs with cool colors. It receives the integrated dataset as input and outputs the AI ​​parameters.

[1196] Step 6:

[1197] The server launches an image generation AI based on the set parameters to generate a new interior design. The generated design is then converted into a format suitable for compression and transfer within the server. The server receives AI parameters as input and outputs the generated design data.

[1198] Step 7:

[1199] The server sends the generated design data to the terminal, which receives the design data and prepares to decode it in real time. It receives the generated design data as input and outputs the decoded design data.

[1200] Step 8:

[1201] The device overlays the decoded design data in real space, allowing the user to visually confirm the new design in their room. For example, new snowy wallpaper is displayed on the wall and a snowflake-patterned rug is layered on the floor. The device receives decoded design data as input and outputs the design to be displayed in real space.

[1202] Step 9:

[1203] The user uses the device interface to fine-tune the color, pattern, and placement of the new design—for example, changing the wallpaper color to a slightly bluer hue or tweaking the pattern on the rug—and then finalizes the design. The system takes the user's adjustments as input and outputs the final design.

[1204] (Application example 1)

[1205] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1206] With conventional interior design systems, changing store layouts and updating displays requires time and effort, and requires specialized knowledge, making it difficult to implement easily and efficiently. Furthermore, there was a lack of a way to check the application to the real space in real time and make fine adjustments, which limited the user experience.

[1207] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1208] In this invention, the server includes a means for generating a new design based on a design theme selected by a user, a means for scanning the environment, and a means for transmitting the generated design to the device and displaying it in real time, thereby enabling the interior design of a store to be updated quickly and efficiently, maximizing the visual effect.

[1209] A "spatial computing device" is an integrated system of hardware and software for scanning physical space and processing it as digital data.

[1210] "Means for scanning the environment" refers to the ability to acquire 3D data of physical space using cameras and depth sensors.

[1211] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via a network.

[1212] "Image generation artificial intelligence" is an AI model that automatically generates interior designs that meet the user's specifications based on the data it receives.

[1213] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated design data to the user's device quickly and efficiently and displaying it overlaid on the real space.

[1214] The "means for generating a new design based on a design theme selected by the user" is a function that automatically generates a customized design according to a theme and parameters selected by the user.

[1215] The "means for identifying markers or low-power wide-area communication tags" refers to a function that recognizes identification markers or tags placed in the physical environment and acquires their positions and information.

[1216] "Means that allow the user to check and adjust the design through a user interface" refers to an interactive interface that allows the user to visually check the design and adjust the color, placement, etc. as necessary.

[1217] MODE FOR CARRYING OUT THE INVENTION

[1218] System Overview

[1219] This invention is a system that combines spatial computing technology and image generation artificial intelligence to enable easy and low-cost interior design changes. This system functions through collaboration between users, devices (such as smartphones), and a server.

[1220] Hardware

[1221] Device (smartphone): Equipped with a camera, depth sensor, and display.

[1222] Server: Responsible for data processing and running generative AI models.

[1223] Identification marker or low-power wide-area communication tag: Installed to supplement environmental information.

[1224] software

[1225] 3D scanning application: Takes scans of the environment and sends them to a server.

[1226] Generative AI model: Generate designs using image-generating AI.

[1227] Interface application: Provides a user interface for theme selection, design display, and adjustment.

[1228] Process Overview

[1229] Scanning the Environment

[1230] Users use their smartphone's camera and depth sensor to scan the entire environment of a physical store. The 3D data acquired through the scan is centralized on the terminal. Identification markers and low-power wide-area communication tags are also read to improve the accuracy of the data.

[1231] Sending data to the server

[1232] The device sends the acquired scan data and information about the design theme selected by the user to a server, which analyzes the data and performs advanced processing.

[1233] Generate the design

[1234] The server uses a generative AI model (e.g., DALL-E or GPT-4 related models) to generate new interior designs. The generative AI automatically creates customized designs based on a theme selected by the user. For example, when generating a "summer sales campaign design," the generative AI provides a design based on bright blue and white.

[1235] Applying and adjusting the design

[1236] The generated design is sent as digital data from the server to the device and displayed in real time in the real world. Through the device's user interface, the user can check the design and fine-tune the color and placement as needed.

[1237] Examples and prompts

[1238] For example, if a user selects "Design for Summer Sale Campaign," the following prompt sentence is input to the generative AI model:

[1239] Generate an interior design for a store's summer sale campaign. The theme should be "light blue and white," with summery decorations and a poster displaying the text "Summer Sale."

[1240] This process allows users to quickly and effectively update their store's interior design and maximize visual impact.

[1241] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1242] Program processing flow

[1243] Step 1:

[1244] The user launches a dedicated application on their smartphone and selects a new interior design theme through the application interface, for example, selecting "Summer Sale Campaign Design."

[1245] Specific behavior:

[1246] The user operates the theme selection UI and selects the desired theme.

[1247] Input: User design theme selection

[1248] Output: Selected theme information

[1249] Step 2:

[1250] The device uses the smartphone's camera and depth sensor to perform a 3D scan of the entire physical store environment.

[1251] Specific behavior:

[1252] The device captures camera images and collects distance data using a depth sensor.

[1253] Generate mesh data and integrate spatial information.

[1254] Input: Camera footage of the environment and depth sensor data

[1255] Output: 3D spatial data (mesh data)

[1256] Step 3:

[1257] The terminal transmits the scan data and the design theme information selected by the user together to the server.

[1258] Specific behavior:

[1259] The device combines the scan data and thematic information into a single dataset.

[1260] Send it to the server using a data communication protocol.

[1261] Input: Scan data and subject information

[1262] Output: The dataset sent to the server

[1263] Step 4:

[1264] The server analyzes the received dataset and generates a new interior design using a generative AI model.

[1265] Specific behavior:

[1266] The server analyzes the dataset and extracts conditions based on spatial structure and themes.

[1267] A prompt is input into a generative AI model (e.g., DALL-E or a GPT-4-related model) to generate a design based on a specified theme.

[1268] Input: Dataset sent to the server, prompt statement

[1269] Output: Generated interior design data

[1270] Step 5:

[1271] The server sends the generated design data to a smartphone.

[1272] Specific behavior:

[1273] The server converts the generated design data into a highly efficient data format.

[1274] It is sent to a smartphone using a data communication protocol.

[1275] Input: Generated interior design data

[1276] Output: Design data sent to your smartphone

[1277] Step 6:

[1278] The design data received by the device is displayed in real space in real time.

[1279] Specific behavior:

[1280] The device decodes the design data and uses AR technology to overlay it onto the real world.

[1281] Input: Design data sent to your smartphone

[1282] Output: Interior design overlaid on real space

[1283] Step 7:

[1284] The user can use the device interface to view the new design and make any necessary adjustments to the color, pattern, etc.

[1285] Specific behavior:

[1286] The user operates the UI to fine-tune the design (changing the color and layout).

[1287] The adjustments are applied in real time and the display is updated.

[1288] Input: User adjustments

[1289] Output: Coordinated interior design

[1290] Step 8:

[1291] Once the adjustments are complete, the user finalizes the design and incorporates it into the interior.

[1292] Specific behavior:

[1293] The user presses the confirm button for the design.

[1294] The finalized design data is saved and the final display is maintained.

[1295] Input: User's final confirmation operation

[1296] Output: Finalized interior design

[1297] Through the above processing steps, users can quickly and effectively update the interior design of their physical store.

[1298] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1299] This invention is a system that combines spatial computing technology and image generation artificial intelligence to realize easy and low-cost interior design changes. It also includes an emotion engine that recognizes the user's emotions in real time and dynamically adjusts the interior design based on those emotions. This system functions through collaboration between the user, terminals, and server, and performs the following program processing:

[1300] System Overview

[1301] A user submits an interior design request through a spatial computing device. The device scans the environment and sends the scan data to a server. The server uses image generation AI to generate a new interior design and sends it back to the device. The device displays this design in real space in real time, recognizing the user's emotions with an emotion engine and adjusting the design accordingly. The user can review the design and make further adjustments as needed.

[1302] Program processing

[1303] The user sends a request from the device

[1304] A user activates a spatial computing device and sends a request through the interface to select a new interior design (e.g., a seasonal theme or a particular color scheme).

[1305] The device scans the environment

[1306] The device uses its built-in camera and depth sensor to begin a 3D scan of the entire room, recognizing the shape and position of the walls, floor, ceiling, furniture, etc. The device also reads markers and low-power wide-area communication tags placed in the room to improve data accuracy.

[1307] The device sends environmental data to the server

[1308] To send the scan results and marker tag data to the server, the device combines these data into a single dataset, which also contains the user's request information.

[1309] The server starts the image generation AI

[1310] The server analyzes the received data set and sets the parameters of the image generation AI based on the user's preferences and requests. Based on this, the image generation AI generates new interior designs. For example, it automatically generates colors and patterns for wallpaper, rugs, and furniture to match the selected theme.

[1311] The server generates a design and sends it to the device.

[1312] The generated design is converted into a data format and efficiently transmitted to the device, which receives the design data and decodes it for real-time display.

[1313] The device adapts the design to the interior

[1314] The device overlays the decoded design data onto the real world, allowing users to visually confirm the new interior design.

[1315] Emotion recognition by emotion engine

[1316] The device uses a built-in emotion engine to analyze the user's facial expressions and voice data in real time to recognize their emotions. For example, if the system determines that the user is relaxed, it will change the color tone of the design to a softer tone.

[1317] Emotion-based design adjustments

[1318] The device dynamically adjusts the hue and brightness of the design based on the user's emotions. If the system determines that the user is feeling stressed, it will change the color tone or pattern of the design to provide a more relaxing environment.

[1319] User checks and adjusts the design

[1320] The user can use the device to check the new design and, if necessary, further adjust the color, pattern, etc. Once the adjustments are complete, the design is finalized and reflected in the interior.

[1321] Specific examples

[1322] For example, if a user requests to update their interior with a winter theme, the device scans the entire room and sends the data to the server. The server then uses image generation AI to generate wallpaper with a snowy motif and a rug design that resembles snowflakes. The generated designs are then sent to the device for the user to review. The emotion engine then analyzes the user's facial expressions and, if it determines that the user is relaxed, adjusts the wallpaper color to a softer tone. The user can then adjust the rug's color to a slightly bluer tone through the interface, review the results, and then confirm the final design.

[1323] In this way, the system of the present invention allows users to easily and inexpensively update their interior design on a daily basis, and further allows them to enjoy a comfortable living space that suits their own feelings.

[1324] The processing flow will be explained below.

[1325] Step 1:

[1326] A user activates a spatial computing device. The user sends a request to select a "winter theme" interior design from the device's interface.

[1327] Step 2:

[1328] The device receives the user's request and begins a 3D scan of the entire room using its built-in camera and depth sensor. During the scanning process, the device recognizes the shape and position of the walls, floor, ceiling, furniture, etc. in detail.

[1329] Step 3:

[1330] The device reads markers and low-power wide-area communication tags to complement the acquired scan data, thereby improving the accuracy of environmental data.

[1331] Step 4:

[1332] The device sends a dataset containing the scan results and marker / tag data to the server via the network, along with user request information.

[1333] Step 5:

[1334] The server analyzes the received data set. Based on the user's preferences and requests, the server sets the parameters of the image generation AI. The server then activates the image generation AI and generates an interior design suited to a "winter theme." For example, it generates wallpaper with a snowy landscape motif or a rug design that resembles a snowflake.

[1335] Step 6:

[1336] The server converts and encodes the generated interior design data into a format that can be efficiently transmitted, and then transmits the design data to the terminal.

[1337] Step 7:

[1338] The device decodes the received design data. The device then performs coordinate conversion with the acquired scan data to apply the design data to the real world. The device then displays the new design overlaid on the real interior in real time.

[1339] Step 8:

[1340] The device uses its built-in emotion engine to analyze the user's facial expressions and voice data in real time and recognize their emotions, for example, determining when the user is relaxed.

[1341] Step 9:

[1342] The device dynamically adjusts the hue and brightness of the interior design based on the perceived emotion, for example, changing the color palette to softer tones if the user is relaxed.

[1343] Step 10:

[1344] The user visually checks the new interior design displayed on the device, and then operates the interface to further adjust the design details (e.g., the color or pattern of the rug) as needed.

[1345] Step 11:

[1346] The device will reflect the user's adjustments and finalize the design, updating the entire room's interior with a "winter theme."

[1347] This system allows users to easily and inexpensively change their interior design, and enjoy a comfortable living space that suits their own emotions.

[1348] Example 2

[1349] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1350] Conventional interior design systems require users to manually adjust the design, which is inefficient. Furthermore, they cannot adjust the design based on the user's feelings, which can lead to low user satisfaction. Furthermore, there is a lack of a way to check and adjust the design in real time.

[1351] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1352] In this invention, the server includes a means for scanning the environment, a means for transmitting the scan results to the server, a means for generating an interior design using image generation artificial intelligence, a means for transmitting the generated design to the device and displaying it in real time, an emotion recognition means for recognizing a user's emotions in real time, and a means for dynamically adjusting the design using the emotion recognition means. This enables automatic generation and adjustment of interior designs based on the user's emotions, improving user satisfaction. Furthermore, the ability to check and adjust the design in real time allows for efficient interior design.

[1353] A "spatial computing device" is a device that can digitize real-world physical spaces and overlay information using 3D scanning and augmented reality (AR) technology.

[1354] "Means for scanning the environment" refers to the function of using a spatial computing device to obtain the shape, position, dimensions, etc. of a room or object in 3D.

[1355] The "means for transmitting the scan results to the server" is a communication function for transmitting the scan data to the server via the network.

[1356] "Image generation artificial intelligence" is an AI technology that automatically generates interior designs based on received data and specified parameters.

[1357] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function that transmits the interior design data generated by the server to the device and visually displays the design superimposed on the real space.

[1358] "Emotion recognition means" is a technology that analyzes a user's facial expressions and voice to determine their emotions in real time.

[1359] The "means for dynamically adjusting the design using emotion recognition means" is a function that automatically adjusts the interior design based on the emotion recognition results.

[1360] A "marker" is a physical landmark that a spatial computing device references to accurately scan its environment.

[1361] A "low-power wide-area communication tag" is a tag device that can communicate over a wide area using very little power, and is used to identify information and the location of objects.

[1362] A "user interface" is a screen or operation panel that allows a user to interact with a system, and is an element that allows the user to check and adjust the design.

[1363] This system combines spatial computing technology and image generation artificial intelligence (AI) to enable easy and low-cost interior design changes. It also features an emotion engine that recognizes user emotions in real time and dynamically adjusts the interior design based on those emotions.

[1364] System configuration

[1365] The system mainly consists of the following components:

[1366] 1. Spatial computing equipment (e.g., spatial computing device)

[1367] 2. Server (e.g., cloud server)

[1368] 3. Device (e.g., smartphone or tablet)

[1369] Hardware and software used

[1370] Spatial computing device: Uses a Microsoft HoloLens 2 or similar device to perform 3D scanning of the environment.

[1371] Device: A mobile device such as an iPhone or iPad Pro is used to provide the user interface and real-time display.

[1372] Server: Cloud servers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP) are used to run data analysis and image generation AI.

[1373] Image generation AI: Automatically generate interior designs using OpenAI's DALL-E and GAN-based generative models.

[1374] Emotion Recognition Software: Use emotion recognition technology such as the Affectiva SDK to analyze user emotions in real time.

[1375] System Operation

[1376] First, a user uses a spatial computing device to operate the interface and input their interior design request. For example, if they select a "winter theme," the device performs a 3D scan of the environment and sends the scan data to a server. The server then analyzes the data and uses image generation AI to generate a new interior design.

[1377] The generated design is sent to the device and displayed in real time. The device is also equipped with an emotion recognition engine that analyzes the user's facial expressions and voice and adjusts the design based on their emotion. For example, if the system determines that the user is relaxed, it will change the wallpaper color to a softer tone. The user can also review the final design on the device and manually adjust the color and pattern as needed.

[1378] Specific examples

[1379] For example, if a user requests a "relaxing living room," the following system actions will occur:

[1380] 1. The user enters a request into the terminal and sends it.

[1381] 2. The device performs a 3D scan of the entire room and sends the scan data to the server.

[1382] 3. The server uses the generative AI model to generate a relaxing interior design, for example, automatically placing furniture and decorations in bright blue and green tones.

[1383] 4. The generated design is sent to the device, where the user can view it in real time using AR technology.

[1384] 5. The emotion engine analyzes the user's facial expressions and, in some cases, automatically adjusts color and placement.

[1385] 6. The user performs a final review and makes any necessary manual adjustments before finalizing the design.

[1386] Prompt Sentence Examples

[1387] Examples of prompts you might enter into a generative AI model include:

[1388] "The user requested that the living room be a relaxing space. Please generate calming colors and natural designs."

[1389] "A user wants to update their interior design with a winter theme. Generate designs for wallpaper with a snowy landscape motif and a snowflake-inspired rug."

[1390] "The system has determined that the user is stressed. Please generate a more relaxing design."

[1391] As described above, the system of the present invention combines a spatial computing device, image generation AI, and emotion recognition technology to enable the automatic generation and adjustment of interior designs based on the user's emotions.

[1392] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1393] Step 1:

[1394] The user sends a request from the device

[1395] The user operates the spatial computing device and inputs a request. The input may include an "interior design theme" or a "specific color scheme." The device then sends this request data to the server. The output is the user's request data.

[1396] Step 2:

[1397] The device scans the environment

[1398] The device's built-in camera and depth sensor are used to perform a 3D scan of the entire room. For example, the shape and position of walls, floors, ceilings, furniture, etc. are recognized. Scan data is collected, and markers and low-power wide-area communication tags are also read. The input is physical environment information, and the output is 3D scan data.

[1399] Step 3:

[1400] The device sends environmental data to the server

[1401] The scan data and user request data are combined into a single dataset and sent to the server. Specifically, it includes 3D model data and location information of the scanned object. This dataset is sent to the server in JSON format or similar. The input is the 3D scan data and request data, and the output is an integrated dataset.

[1402] Step 4:

[1403] The server starts the image generation AI

[1404] The server analyzes the received dataset. Based on the user request and the environmental data, it sets the parameters of a generative AI model (e.g., OpenAI's DALL-E). The image generation AI generates a new interior design. The input is the integrated dataset, and the output is the generated design data.

[1405] Step 5:

[1406] The server generates a design and sends it to the device.

[1407] The generated design is converted back into a data format and efficiently transmitted to the terminal. Data compression techniques and network optimization are used to minimize delays. The input is the generated design data, and the output is the transmitted design data.

[1408] Step 6:

[1409] The device adapts the design to the interior

[1410] The device decodes the received design data and displays it overlaid on the real space. For example, using AR technology, new wallpaper and furniture arrangements are displayed in real time as the user looks around the room. The input is the transmitted design data, and the output is the application of the design to the real space.

[1411] Step 7:

[1412] Emotion recognition by emotion engine

[1413] The device uses a built-in emotion engine to analyze the user's facial expressions and voice in real time. Emotion recognition software (e.g., Affectiva SDK) determines the user's emotions. The input is the user's facial expressions and voice data, and the output is the emotion recognition results.

[1414] Step 8:

[1415] Emotion-based design adjustments

[1416] The device dynamically adjusts the design based on the emotion recognition results. For example, if it determines that the user is relaxed, it changes the color to a softer tone. Conversely, if it determines that the user is stressed, it adjusts the design to be more relaxing. The input is the emotion recognition result, and the output is the adjusted design.

[1417] Step 9:

[1418] User checks and adjusts the design

[1419] The user can use the device to check the final design and manually adjust it as needed, for example, changing the wallpaper color from blue to green. Once the adjustments are complete, the design is finalized and reflected in the interior. The input is the adjusted design, and the output is the finalized design.

[1420] (Application example 2)

[1421] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1422] Conventional interior design change systems require manual adjustments by users or expert intervention, resulting in time-consuming and costly changes. Furthermore, it is difficult to reflect users' emotions and preferences in real time, making it difficult to achieve optimal interior designs. Especially in brick-and-mortar stores, interior changes directly affect customers' purchasing behavior and experiences, so instant and effective design changes are required.

[1423] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1424] In this invention, the server includes means for scanning the environment, means for transmitting the scan results to the server, means for generating an interior design using image generation AI, means for transmitting the generated design to the device and displaying it in real time, and means for recognizing a user's emotions in real time and dynamically adjusting the design based on the emotions. This allows the user to instantly and effortlessly change the interior design to the optimum one, which is expected to improve the customer experience, especially in physical stores.

[1425] "Means for scanning the environment" refers to a function that uses a camera, depth sensor, etc. to acquire the target's physical environment as 3D data.

[1426] The "means for transmitting scan results to a server" is a function for transmitting the acquired scan data to a server via the Internet or wireless communication.

[1427] "Image generation artificial intelligence" is a technology that automatically generates images and designs from input data using a generative AI model.

[1428] The "server that generates interior designs" is a server computer that uses image generation artificial intelligence to generate new interior designs based on received environmental data and user requests.

[1429] "Means for transmitting the generated design to the device and displaying it in real time" refers to a function for transmitting the generated interior design to the terminal and displaying the design superimposed on the real space.

[1430] "Means for recognizing user emotions in real time" refers to technology that uses a camera and microphone to analyze the user's facial expressions and voice and identify their emotions.

[1431] The "means for dynamically adjusting design based on emotions" is a function that automatically changes the color and pattern of the interior design according to the recognized emotions of the user.

[1432] An "identification marker" is a visual marker used to recognize and track a specific object or location.

[1433] A "low-power communication tag" is a tag that consumes very little power and enables low-power communication, and is used as a means of identifying specific objects or locations within an environment.

[1434] "User interface" is a general term for software that provides interactive screens and control elements for users to operate a system.

[1435] To implement this invention, a spatial computing device, smart glasses, a server, an image generation artificial intelligence (generative AI model), an emotion recognition engine, and a user interface are required.

[1436] First, a user puts on the smart glasses and inputs a request for a new interior design through the interface, specifying specific design requirements by entering prompt statements such as, "Generate a spring-themed interior design. Use cherry blossom-themed wallpaper and a pale pink color palette."

[1437] The smart glasses use a built-in camera and depth sensor to 3D scan the environment in the store. The resulting data is sent to a server via a communication module. The hardware used here is smart glasses (e.g., Microsoft HoloLens).

[1438] The server receives the scan results and automatically generates a new interior design using a generative AI model, such as OpenAI's DALL-E 2. This model generates an interior design that matches a specified theme based on the prompt text and scan data provided by the user.

[1439] The generated design is converted into a digital format and sent to the smart glasses, which decode the design data and display it in real time overlaid on the real space inside the store, allowing users to visually confirm the new interior design.

[1440] Additionally, the smart glasses are equipped with a built-in camera and microphone, which are used to analyze the user's facial expressions and voice in real time. The emotion recognition engine uses Affectiva's technology. The recognized emotions are dynamically reflected in the new interior design through an emotion-responsive design module. For example, if the user is relaxed, the system will change the design's color palette to a softer tone.

[1441] Users can make additional adjustments to the generated design through the smart glasses interface, and the final design will be finalized and implemented as the interior design for the physical store.

[1442] Through this system's series of processes, the interior design of a physical store can respond to the emotions and desires of users and be kept in an optimal state at all times. By using this system, the customer experience in the store can be improved, and sales are expected to increase.

[1443] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1444] Step 1:

[1445] The user activates the smart glasses and inputs a request for a new interior design through the interface. The user enters a prompt such as, "Generate a spring-themed interior design. Use wallpaper with a cherry blossom motif and a color palette based on pale pink." This prompt becomes the input data.

[1446] Step 2:

[1447] The smart glasses use a built-in camera and depth sensor to perform a 3D scan of the store's environment, capturing detailed information about the shape and position of walls, floors, ceilings, furniture, etc. The acquired scan data is used as output data.

[1448] Step 3:

[1449] The smart glasses use a communication module to send the resulting data, including the prompt text entered by the user and the 3D scan data of the environment, to a server, which receives this data set.

[1450] Step 4:

[1451] The server automatically generates a new interior design using a generative AI model based on the received prompt and scan data. The image generation AI (e.g., OpenAI's DALL-E 2) generates design images based on the specified theme. These generated design images become the output data.

[1452] Step 5:

[1453] The server converts the generated design image into a digital format and sends it to the smart glasses, which receive the design data, decode it, and display it overlaid on the real world in real time, allowing the user to visually check the interior design.

[1454] Step 6:

[1455] The smart glasses use a built-in camera and microphone to analyze the user's facial expressions and voice in real time, and then use an emotion recognition engine (e.g., Affectiva) to identify the user's emotions. The recognized emotion data is the output.

[1456] Step 7:

[1457] The server uses an emotion-responsive design module to dynamically adjust the color and pattern of the interior design based on the recognized emotion data. For example, if the user is determined to be relaxed, the system will change the color of the design to a softer tone. The result of this adjustment becomes the output data.

[1458] Step 8:

[1459] The user can make further adjustments to the generated design through the smart glasses interface. The user fine-tunes the color and pattern on the screen and then confirms the result as the final design. The final design is then output.

[1460] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1461] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1462] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1463] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1464] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1465] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1466] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1467] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1468] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1469] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1470] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1471] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1472] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1473] 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.

[1474] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1475] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1476] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1477] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1478] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1479] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1480] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1481] The following is further disclosed regarding the above embodiment.

[1482] (Claim 1)

[1483] A spatial computing device, comprising: means for scanning an environment;

[1484] means for transmitting the scan results to a server;

[1485] a server that generates an interior design using image generation artificial intelligence;

[1486] means for transmitting the generated design to a device and displaying it in real time;

[1487] A system including:

[1488] (Claim 2)

[1489] 10. The system of claim 1, further comprising means for identifying markers or low-power wide-area communication tags installed in the environment.

[1490] (Claim 3)

[1491] 10. The system of claim 1, further comprising means for enabling review and adjustment of the design through a user interface.

[1492] "Example 1"

[1493] (Claim 1)

[1494] A spatial computing device, comprising: means for scanning an environment;

[1495] means for transmitting the scan results to a server;

[1496] a server that generates an interior design using image generation artificial intelligence;

[1497] means for transmitting the generated design to a device and displaying it in real time;

[1498] A means for setting parameters of the image generating artificial intelligence based on a user request;

[1499] a means for decoding and displaying the data in real time;

[1500] a means for the user to review and adjust the design;

[1501] A system including:

[1502] (Claim 2)

[1503] 10. The system of claim 1, further comprising means for identifying markers or low-power wide-area communication tags installed in the environment.

[1504] (Claim 3)

[1505] 10. The system of claim 1, further comprising means for enabling review and adjustment of the design through a user interface.

[1506] "Application Example 1"

[1507] (Claim 1)

[1508] A spatial computing device, comprising: means for scanning an environment;

[1509] means for transmitting the scan results to a server;

[1510] a server that generates an interior design using image generation artificial intelligence;

[1511] means for transmitting the generated design to a device and displaying it in real time;

[1512] means for generating a new design based on a user-selected design theme;

[1513] A system including:

[1514] (Claim 2)

[1515] further comprising means for identifying a marker or a low-power wide-area communication tag installed in the environment;

[1516] 10. The system of claim 1.

[1517] (Claim 3)

[1518] further comprising means for enabling review and adjustment of the design through a user interface;

[1519] 10. The system of claim 1.

[1520] "Example 2: Combining Emotion Engines"

[1521] (Claim 1)

[1522] A spatial computing device, comprising: means for scanning an environment;

[1523] means for transmitting the scan results to a server;

[1524] a server that generates an interior design using image generation artificial intelligence;

[1525] means for transmitting the generated design to a device and displaying it in real time;

[1526] emotion recognition means for recognizing the user's emotions in real time;

[1527] a means for dynamically adjusting the design using emotion recognition means;

[1528] A system including:

[1529] (Claim 2)

[1530] 10. The system of claim 1, further comprising means for identifying markers or low-power wide-area communication tags installed in the environment.

[1531] (Claim 3)

[1532] 10. The system of claim 1, further comprising means for enabling review and adjustment of the design through a user interface.

[1533] "Application example 2 when combining emotion engines"

[1534] (Claim 1)

[1535] a means for scanning the environment;

[1536] means for transmitting the scan results to a server;

[1537] a server that generates an interior design using image generation artificial intelligence;

[1538] means for transmitting the generated design to a device and displaying it in real time;

[1539] a means for recognizing user emotions in real time and dynamically adjusting the design based on those emotions;

[1540] A system including:

[1541] (Claim 2)

[1542] 10. The system of claim 1, further comprising means for recognizing an identification marker or a low-power communication tag placed in the environment.

[1543] (Claim 3)

[1544] 10. The system of claim 1, further comprising means for enabling review and adjustment of the design through a user interface. [Explanation of symbols]

[1545] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A spatial computing device, comprising: means for scanning an environment; means for transmitting the scan results to a server; a server that generates an interior design using image generation artificial intelligence; means for transmitting the generated design to a device and displaying it in real time; A system including:

2. The system of claim 1 , further comprising means for identifying markers or low-power wide-area communication tags installed in the environment.

3. The system of claim 1 , further comprising means for enabling review and adjustment of the design through a user interface.

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