system

Abstract

We provide the system. [Solution] An image analysis means for extracting spatial information from image data input by the user, An input method for receiving user-entered preferences and budget information, A generation means that proposes the optimal arrangement of items based on the extracted spatial information and user preferences and budget information, An augmented reality generation means that visualizes the proposed arrangement of items in real space, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In interior selection, the problems faced by users are the difficulty of grasping the size and placement suitability of items in space. Also, due to the wide variety of item types, it is difficult for users to appropriately select items that match their preferences and budget. Furthermore, there is a lack of means to visually confirm how the selected items will look in the actual space, so the process until an optimal selection is made is cumbersome and burdensome for users.

Means for Solving the Problems

[0005] This invention includes an image analysis means for extracting spatial information from image data entered by the user, and an input means for receiving the user's preferences and budget information. This allows for the aggregation of the user's specific requests. Furthermore, it includes a generation means for proposing the optimal arrangement of items based on the extracted spatial information and the user's preferences and budget information, and provides an augmented reality generation means for visualizing the proposed arrangement of items in the real space, allowing the user to easily check the image of the arrangement before purchasing items. In addition, the generation means links with inventory information in real time to realize optimal suggestions. This significantly streamlines the user's selection process and enables the creation of an attractive interior for the user.

[0006] A "user" refers to an individual or group that uses the system to receive assistance in selecting and deciding on the layout of interior furnishings.

[0007] "Image data" refers to digital files containing visual information about rooms or spaces that users provide to the system.

[0008] "Spatial information" refers to information such as the size and shape of a room, the location of windows and doors, and available space, which is obtained by the system analyzing image data.

[0009] "Image analysis means" refers to the techniques and processes for extracting spatial information from input image data.

[0010] "Input means" refers to interfaces or devices used to communicate user preferences, budgets, and other requests to the system.

[0011] "Generation means" refers to algorithms and programs that propose the optimal arrangement of items based on user input information and spatial information.

[0012] "Arrangement of items" refers to the method of arranging furniture, home appliances, and other decorative items that make up an interior.

[0013] "Augmented reality generation means" refers to visual technology that allows users to verify proposed object arrangements in real space.

[0014] "Data transmission means" refers to the technology or device used to transmit the generated visualization data to the user's device.

[0015] "Inventory synchronization method" refers to a technology that integrates with a system to check the inventory status of selected items in real time and reflect that information in the proposal. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0019] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system that assists users in optimizing the interior of their living spaces, and in particular, by using image analysis technology and augmented reality technology, it enables users to select and arrange items that are ideal for them.

[0038] First, the user takes photos of their room or the entire living space using a smart device. These image data are immediately sent to a server via the network. The server analyzes the received images and extracts spatial information such as the size and shape of the room and the arrangement of furniture.

[0039] Next, the terminal provides an interface for the user to enter information about their preferences and budget, and the user enters their requests into this form. This information is sent to the server, where the interior style, colors, and functionality requirements that meet the user's requests are recorded.

[0040] Based on collected spatial information and user requests, the server uses the latest generative AI technology to generate suggested furniture and appliance placements. This process ensures that items harmonize with the user's desired interior style.

[0041] Furthermore, the suggested items are checked for inventory in real time by the server, and this information is reflected in the generated layout. This allows users to immediately see which items are available for order.

[0042] The device visualizes suggested layouts provided by the server using augmented reality, helping users to see them in their actual space. Through this AR display, users can intuitively understand how the selected furniture will be placed in their own room.

[0043] For example, if a user requests a new living room layout, the system analyzes the spatial dimensions from a photo of the room and proposes a furniture arrangement based on a modern, white-based style. This proposal is displayed in real-time using augmented reality (AR) on the user's device, and the user can purchase their preferred layout directly.

[0044] Thus, the present invention is a system that streamlines the conventional furniture selection process and provides users with a seamless and intuitive means of choosing interior furnishings.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user takes a picture of the room with a smart device and uploads the image to the application.

[0048] Step 2:

[0049] The terminal receives image data and initiates communication to send it to the server.

[0050] Step 3:

[0051] The server analyzes the received image data to extract spatial information, such as the room's size, shape, the location of windows and doors, and the arrangement of existing furniture.

[0052] Step 4:

[0053] The device displays a form for the user to input their preferred style, budget, color and material choices, etc.

[0054] Step 5:

[0055] The user enters their preferred information into a form, and the device sends that information to the server.

[0056] Step 6:

[0057] The server combines spatial information obtained from image analysis with user-inputted preference information and uses a generative AI to generate an optimal furniture and appliance placement plan.

[0058] Step 7:

[0059] Based on the proposed deployment plan, the server retrieves and updates inventory information in real time to check if the relevant products are available for purchase.

[0060] Step 8:

[0061] The server generates visualization data for augmented reality and sends it to the terminal, allowing the user to actually see the suggested furniture and appliance placement.

[0062] Step 9:

[0063] The device uses augmented reality technology to display suggested furniture and appliance placement images on the user's device.

[0064] Step 10:

[0065] The user reviews the displayed suggestions, selects a product they like, and proceeds with the purchase.

[0066] Step 11:

[0067] The server processes the purchase of the selected items and confirms the order in conjunction with the flea market app.

[0068] Step 12:

[0069] The server notifies the user that the purchase is complete and provides shipping information for the product.

[0070] (Example 1)

[0071] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0072] In traditional interior design selection processes, it was difficult to intuitively visualize the user's ideal spatial design and to select and arrange products that reflected real-time inventory status. Furthermore, it was not possible to quickly generate appropriate suggestions tailored to the user's preferences.

[0073] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0074] In this invention, the server includes processing means for analyzing and extracting spatial information from image data captured by the user, acquisition means for receiving information on the user's preferences and budget, and generation processing means for generating an optimal product arrangement based on the extracted spatial information and the user's preferences and budget. This enables the user to intuitively visualize their desired interior and makes it possible to select and arrange products realistically while reflecting inventory status.

[0075] A "user" is the entity that provides input information and image data and receives interior design suggestions.

[0076] "Information about space" refers to data such as room dimensions, shape, and furniture arrangement obtained through the analysis of image data.

[0077] A "processing means" is an element that has the function of analyzing and extracting spatial information from image data.

[0078] "Means of acquisition" refers to elements that have the function of receiving and recording information about the user's selected preferences and budget.

[0079] A "generation processing means" is an element that has the function of generating the optimal product arrangement based on spatial information and the user's preferences and budget.

[0080] "Augmented reality display means" refers to a function that uses technology to visualize a proposed product arrangement by overlaying it onto real space.

[0081] "Inventory information" refers to real-time data on how readily available a product is.

[0082] A "data transmission function" is an element that has the function of sending data necessary for visualization to the user terminal.

[0083] This invention provides a system for optimizing the interior of a user's living space, specifically utilizing image analysis technology and augmented reality technology. To implement the invention, a server, terminal, and user each need to play specific roles. Details are described below.

[0084] First, the user takes photos of their room or living space using a suitable device such as a smartphone or tablet. This device has a dedicated application installed and is equipped with the function to send the captured image data to a server. The data is sent to the server via a network connection, along with the user's specified preferences and budget information.

[0085] Next, the server analyzes the received image data. Specifically, it uses software libraries such as OpenCV and TENSORFLOW® to perform image processing and object recognition. This extracts spatial information such as room dimensions, shape, and furniture arrangement. The extracted information is stored as a digital model on the server and used in subsequent generation processes. This generation process uses generation AI such as the OpenAI® GPT model to propose an optimal interior plan based on the user's prompts.

[0086] Subsequently, the device uses augmented reality (AR) technology to visualize the proposed interior layout. The device utilizes AR software such as ARKit (iOS) and ARCore (Android®), enabling users to experience placing virtual furniture within a real-world space through the device. This allows users to intuitively evaluate the suitability of the proposed interior.

[0087] For example, if a user is considering renovating their living room, the system performs image analysis and suggests a furniture arrangement based on a modern interior style with a white color scheme. This suggestion is displayed in AR on the device, allowing the user to view the visualized environment and easily proceed to the ordering process if they like it.

[0088] Examples of prompts for efficiently managing the above process include, "Please propose an interior design plan with a modern style and a white color scheme."

[0089] This system allows users to significantly streamline the interior design process, making it easier to select and realize their ideal living environment.

[0090] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0091] Step 1:

[0092] The user takes images of their room or living space using a smart device. These captured images become the input for processing. The user selects images through a dedicated application and sends them to a server via the network. The output of this step is the image data sent to the server.

[0093] Step 2:

[0094] The server analyzes the received image data and extracts spatial information. Specifically, the server uses image analysis libraries such as OpenCV to process the dimensions of furniture and rooms within the image and extracts the room structure as digital data. The input for this step is the image data sent by the user, and the output is the extracted spatial information.

[0095] Step 3:

[0096] The terminal prompts the user to input information about their preferences and budget through the user interface. The user enters their desired style and budget into a form on the screen, and this information is sent to the server. The input in this step is the information entered into the user interface, and the output is the recorded user preferences and budget information.

[0097] Step 4:

[0098] The server generates an optimal interior plan using a generative AI model based on extracted spatial information and user input. The generative AI, such as a GPT model, calculates the appropriate furniture placement for the room according to the user's prompts. The input for this step is spatial information and user input, and the output is the generated interior plan.

[0099] Step 5:

[0100] The server uses the generated interior plan to check inventory information. This process verifies whether the suggested furniture and appliances are immediately available for order and reflects the inventory status in the interior plan. The input for this step is the generated interior plan, and the output is the plan with the inventory status reflected.

[0101] Step 6:

[0102] The terminal provides the user with a proposed plan received from the server using augmented reality (AR) technology. Specifically, it uses ARKit or ARCore to display a virtual interior when the user views the room through the device. The input for this step is an interior plan that reflects inventory status, and the output is the visualization result using augmented reality.

[0103] Step 7:

[0104] The user reviews the presented augmented reality layout and proceeds with the purchase if they like it. The user selects options on the terminal and confirms the order for the selected furniture and appliances. The input for this step is the augmented reality visualization, and the output is the confirmed order.

[0105] (Application Example 1)

[0106] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0107] In recent years, there has been a growing need for users to select interior items that suit their personal preferences when optimizing their living spaces. However, conventional systems make it difficult for users to visualize how items will look when actually placed in a home, and the lack of real-time inventory information and in-store support makes the purchase decision-making process cumbersome. Against this backdrop, there is a need for technology that improves the user experience and efficiently supports the selection of optimal items.

[0108] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0109] In this invention, the server includes: an image analysis means for extracting spatial information from image data entered by the user; an input means for receiving preference and budget information entered by the user; a generation means for proposing an optimal arrangement of items based on the extracted spatial information and the user's preference and budget information; an augmented reality generation means for visualizing the proposed arrangement of items in the real world; an information acquisition means using a visual device for acquiring and analyzing real-world items; a function means using a device for visualizing and presenting the proposed arrangement of items; and a data linkage means for acquiring and presenting corresponding item information in real time. This enables the user to intuitively experience the arrangement of interiors in their living space and to efficiently and quickly select and purchase appropriate furniture.

[0110] "Image analysis means" refers to technology for analyzing spatial shape and arrangement information from image data input by the user.

[0111] An "input method" is a function that provides an interface for receiving user requests such as preferences and budget.

[0112] The "generation method" is a technology that proposes the optimal arrangement of items based on extracted spatial information and user requests.

[0113] "Augmented reality generation means" refers to a technology for displaying the proposed arrangement of objects superimposed onto real space.

[0114] "Information acquisition means" refers to a function that uses visual devices to acquire and analyze information about real-world objects.

[0115] A "functional means" is an operating device for visualizing and presenting the arrangement of proposed items to the user.

[0116] "Data linkage means" refers to technology for acquiring real-time information about necessary items and presenting it appropriately to the user.

[0117] The system of the present invention is designed to optimize the interior of a user's living space and is realized using image analysis technology and augmented reality technology. Specific embodiments for carrying out the present invention are shown below.

[0118] First, the user uses a smart device to take an image of the entire living space and sends the data to the server. At this stage, the server uses "image analysis tools" to analyze the received image data and extract information such as the size and shape of the space and the arrangement of existing furniture. This process uses Python and image processing libraries such as OpenCV.

[0119] Next, the user inputs information about their preferences and budget through the terminal's interface. This information is sent to the server, which receives it as "input." The server then uses "generation tools" to generate the optimal arrangement of items that matches the style the user desires. For example, generation AI technology may be used for this generation.

[0120] The generated proposals are visualized on the device via an "augmented reality generation mechanism." This allows users to experience the proposed arrangement superimposed on real space. Specifically, Unity or ARKit could be used for augmented reality display.

[0121] Furthermore, the system can acquire and analyze item information using visual devices within a physical store through its "information acquisition means." This supports the user's purchasing experience while in a physical store. The "functional means" work to present the proposed item arrangement to the user, and one of the functions used is providing an interface on smart glasses.

[0122] The system also uses a "data linkage mechanism" to acquire inventory information for suggested items in real time and present it to the user. This allows the user to seamlessly proceed through the process from selecting interior items to purchasing them.

[0123] As a concrete example, consider a scenario where a user is looking for the perfect sofa for their new living room. By inputting the user's preferences and living space information through smart glasses, it's possible to use a "generative AI model" to suggest sofa placements that match the style. An example of a prompt in this case would be, "The user is looking for a sofa that suits a modern, white-themed living room."

[0124] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0125] Step 1:

[0126] The user takes images of their living space using a smart device and sends the image data to a server. The input is the image data taken by the user, and the output is the image data sent to the server. This image data includes an overall view of the room and existing furniture.

[0127] Step 2:

[0128] The server processes the received image data using "image analysis tools" to extract spatial information such as the dimensions and shape of the space and the location of existing furniture. The input is image data sent to the server. In this step, data analysis is performed using image processing libraries such as Python or OpenCV, and the output is in the form of spatial information.

[0129] Step 3:

[0130] The user uses the terminal's interface to input information about their preferences and budget. This input, containing data about the user's personal preferences and budget, is sent from the terminal to the server, which receives it as input. The output is the user's request data recorded on the server.

[0131] Step 4:

[0132] The server, based on the spatial information obtained in the previous step and the user's request data, utilizes the "generation method" to propose the optimal item placement. The input consists of spatial information and the user's requests. The generation AI model processes this data and outputs an item placement that suits the user's preferences.

[0133] Step 5:

[0134] The generated proposals are visualized on the device using an "augmented reality generation method." The device receives object placement data output from the server and allows the user to see them overlaid on a real-world room. The output is the object placement displayed in augmented reality. Here, visualization in real space is performed using Unity or ARKit.

[0135] Step 6:

[0136] When a user visits a physical store, information about the actual items is acquired and analyzed using a visual device and an "information acquisition means." The input is information about the actual items acquired through the visual device. The output is specific item data presented to the user.

[0137] Step 7:

[0138] The suggested items are linked to a "data linkage system" which retrieves relevant data, including inventory information, in real time. This information is then fed back to the user, who can then make a purchase decision based on it. The input is information about the suggested items, and the output is real-time item information, including inventory.

[0139] Step 8:

[0140] Users review the item placement visualized in augmented reality, and once they've decided to purchase, they order the selected items through the terminal. The input is the information of the final selected items, and the output is the purchase procedure information. This process supports a seamless purchasing experience.

[0141] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0142] This invention is a system that provides interior design suggestions while taking into account the user's emotional state. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, and spatial information such as the size and shape of the room and the current furniture arrangement is extracted by an image analysis means.

[0143] Next, the terminal displays an interface for the user to input their interior design preferences and budget, and the user enters this information. This data is sent to the server and recorded as the user's request.

[0144] A key feature of this system is its use of an emotion engine to understand the user's emotional state. When a user registers their facial expressions with the system via voice input or camera, the emotion engine analyzes the data and recognizes the user's emotions, such as their level of stress or joy. This emotional information, along with other request information entered by the user, is provided to the generation mechanism.

[0145] The server integrates this information and uses AI to generate an optimal furniture and appliance placement plan. During this process, suggestions are made to enhance comfort and relaxation, tailored to the user's emotional state. Furthermore, the server retrieves real-time inventory information and selects items that are available for purchase.

[0146] Subsequently, the server-generated suggestions are visualized using augmented reality technology, and the data is sent to the terminal for display on the user's device. This AR display allows the user to intuitively understand what the selected furniture would look like when actually placed in the room.

[0147] For example, if a user is leading a busy life and seeks a relaxing effect from their living room decor, the system will recognize the user's calm emotional state and suggest furniture with relaxing colors and arrangements. In this way, the present invention aims to improve the user's living environment by providing interior design suggestions that take the user's emotions into consideration.

[0148] The following describes the processing flow.

[0149] Step 1:

[0150] Users take photos of their rooms with their smart devices and upload the image data by opening the application.

[0151] Step 2:

[0152] After the terminal receives the image data, it initiates communication to send it to the server.

[0153] Step 3:

[0154] The server analyzes the received image data and extracts spatial information, including the room's size, shape, and current furniture arrangement.

[0155] Step 4:

[0156] The device displays a form for the user to enter their interior design preferences, desired budget, and other requests.

[0157] Step 5:

[0158] The user enters information such as their preferences and budget into a form on their device and sends it to the server.

[0159] Step 6:

[0160] The device uses the user's camera and microphone to capture the user's face and voice, and sends that data to the emotion engine.

[0161] Step 7:

[0162] The emotion engine analyzes the user's emotional state from their facial expressions and voice, recognizing, for example, their stress level and satisfaction level.

[0163] Step 8:

[0164] The server integrates spatial information, user request information, and emotional information from the emotion engine, and uses generative AI to formulate the optimal furniture and appliance placement plan.

[0165] Step 9:

[0166] The server checks inventory information in real time via an online database and reflects available items in the final proposal.

[0167] Step 10:

[0168] The server generates the proposed furniture and appliance placement plan as augmented reality data and sends it to the terminal.

[0169] Step 11:

[0170] Based on the augmented reality data transmitted by the device, the suggested furniture arrangement is displayed in AR on the user's device for the user to confirm.

[0171] Step 12:

[0172] Users view AR displays, select furniture and appliances based on their preferred suggestions, and proceed with the purchase process.

[0173] Step 13:

[0174] The server processes the purchase of the selected items and confirms the order with the partnered online sales platform.

[0175] Step 14:

[0176] The server sends a purchase completion notification to the user and provides information such as shipping details for the product.

[0177] (Example 2)

[0178] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0179] Traditional interior design proposal systems could suggest item placements based on user preferences and budget, but they lacked the ability to consider the user's emotional state. This made it difficult to create truly comfortable spaces that users desired. Therefore, it is necessary to provide interior design proposals that are more tailored to individual needs, incorporating information that includes the user's emotional state.

[0180] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0181] In this invention, the server includes an image analysis means for extracting spatial information from image data entered by the user, an input means for receiving preference and budget information entered by the user, and an emotion analysis means for analyzing the emotional state and providing the results to the generation means. This makes it possible to propose the optimal arrangement of items according to the user's emotional state and to realize a comfortable interior space tailored to individual needs.

[0182] "Image analysis means" refers to technical means for extracting spatial information from image data input by a user.

[0183] An "input method" refers to a means of providing an interface for users to input their interior design preferences and budget information into the system.

[0184] A "generation method" is a means for proposing the optimal arrangement of items based on extracted spatial information and user preferences and budget information.

[0185] "Emotional analysis means" refers to a technical means that analyzes the user's emotional state and provides the results to the generation means.

[0186] An "augmented reality generation method" is a technical means for visualizing a proposed arrangement of objects in real space.

[0187] "Inventory synchronization means" refers to technical means that enable the acquisition of inventory information in real time.

[0188] "Data transmission means" refers to means for transmitting data necessary for the augmented reality generation means to visualize the proposed item arrangement on the user device.

[0189] This system proposes furniture arrangements that take into account the user's emotional state in order to create a comfortable interior space. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, which uses image analysis to extract spatial information such as the size and shape of the room and the current furniture arrangement.

[0190] Next, the terminal displays an interface to the user, prompting them to input their interior design preferences and budget. The user enters this information through the terminal's interface, and the terminal sends this data to a server to record the user's preferences.

[0191] Regarding the emotion analysis method, the user inputs their emotional state into the system using voice input or a camera on their smart device. The server uses the emotion analysis method to analyze the voice and facial expression data to recognize the user's emotional state. This extracts emotional information such as the degree of stress or joy.

[0192] The server uses collected spatial information, user preferences and budget, and emotional information to generate an optimal furniture placement plan using a generative AI model. This generative AI model is based on, for example, a common generative AI framework. The generated placement plan is optimized for the user's emotional state and incorporates color schemes and designs aimed at promoting relaxation.

[0193] Furthermore, the server acquires real-time market inventory information through inventory synchronization and selects items that are available for purchase. The server uses augmented reality generation to visualize the proposed interior layout using AR technology and transmits the data to the terminal. Through the terminal, the user can obtain a visual image of how the furniture would look when placed in an actual room.

[0194] For example, if a user leads a busy life and desires relaxation in their living room, the system analyzes the user's emotional state as "easy to relax." Based on this, it suggests furniture with natural colors and soft arrangements that are expected to have a relaxing effect. By inputting a prompt such as "Please suggest living room interiors that will help the user relax" into the AI ​​model, users can receive specific suggestions.

[0195] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0196] Step 1:

[0197] The user takes a photo of the room with a smart device and uploads the image data to the system. This image data becomes the input. The server receives this image data and uses image analysis to extract spatial information such as the room's size, shape, and furniture arrangement. The extracted spatial information becomes the output.

[0198] Step 2:

[0199] The terminal allows the user to input their interior design preferences and budget through an interface. This input becomes the input data. The terminal then sends this information to a server, where it is recorded as the user's request. The recorded information becomes the output.

[0200] Step 3:

[0201] Users register their emotional state with the system using voice input or camera on their smart devices to collect emotional information. This audio / video data becomes the input. The server analyzes the data using emotion analysis tools to recognize the degree of stress or joy. The analyzed emotional information becomes the output.

[0202] Step 4:

[0203] The server integrates spatial information obtained from image analysis, user preferences and budget information, and emotional information obtained from emotion analysis, and uses these as input data for a generative AI model. The server then uses this generative AI model to generate an optimal furniture arrangement plan. This plan generation process takes into account suggestions based on the user's emotional state. The output is the generated furniture arrangement plan.

[0204] Step 5:

[0205] The server uses an inventory synchronization method to obtain inventory information in real time. Inventory information retrieved from the market database is the input, and a list of available items is output. Based on this information, products suitable for the generated furniture placement plan are selected.

[0206] Step 6:

[0207] The server uses the generated furniture layout plan and selected product information to create visualization data using an augmented reality generation system. This visualization data is sent to the terminal. The transmitted visualization data becomes the output.

[0208] Step 7:

[0209] The device uses augmented reality (AR) technology to display a suggested furniture arrangement on the user's device, based on visualization data sent from the server. The user can then review this display and get an idea of ​​how the furniture would actually look in their room. The output is the AR display presented to the user.

[0210] (Application Example 2)

[0211] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0212] Interior design and item placement suggestions made without considering the user's emotional state may not necessarily address the user's current mood or emotional needs. This presents a challenge in creating optimal spatial designs for users. Furthermore, in actual retail shopping experiences, users may find it difficult to visualize the suggested interior design in real-time, making purchase decisions challenging.

[0213] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0214] In this invention, the server includes an image analysis means for extracting spatial information from image data input by the user, an emotion analysis means for analyzing user-inputted preferences, budget information, and the user's emotional state and acquiring the data, a generation means for proposing the optimal item arrangement based on these, and an augmented reality generation means for visualizing the proposed item arrangement in the real space. This makes it possible to propose interiors and items that are best suited to the user's emotional state in real time, making the purchasing experience more intuitive and supporting the realization of a comfortable living space.

[0215] "Image analysis means" refers to a technology that extracts spatial information such as the size and shape of a space and the current furniture arrangement from image data input by the user.

[0216] "Input method" refers to the interface used by users to input their interior design preferences and budget information.

[0217] "Emotion analysis methods" refer to technologies that analyze a user's facial expressions and voice data to obtain data on their current emotional state.

[0218] The "generation method" is a method for proposing the optimal arrangement of items based on extracted spatial information, user preferences and budget information, and emotional state information.

[0219] "Augmented reality generation means" is a technology that visually reflects a proposed arrangement of objects in real space.

[0220] "Inventory synchronization methods" refer to technologies that use real-time inventory information to verify whether proposed items are actually available for purchase.

[0221] A "data transmission means" is a mechanism for transmitting data necessary to visualize the proposed item arrangement on the user's device.

[0222] The embodiments of the present invention will now be described. The system of the present invention consists of a smart device used by the user, an analysis engine on a server, and augmented reality technology for displaying the proposed results.

[0223] The user takes a picture of the room using a smartphone or other smart device. This image data is uploaded from the device to a server. On the server, spatial information such as the size, shape, and furniture arrangement of the space is extracted using OpenCV or TensorFlow as image analysis tools.

[0224] Next, the user inputs their interior design preferences and budget information through the device's interface. This information is also sent to the server and recorded as the user's request. Furthermore, the user uses the camera function to capture their facial expressions, and emotional data such as stress and relaxation levels are registered on the server using emotion analysis tools such as Microsoft® Azure® Face API and Google® Cloud AI.

[0225] The server integrates this data and uses a generative AI model (e.g., GPT-4®) to generate a plan that suggests the optimal placement of items while taking the user's emotions into consideration. This plan includes furniture with colors and designs that suit the user's space, and also uses Firebase Realtime Database for real-time inventory checks.

[0226] The proposed item placements are visualized on the user's device using augmented reality generation tools such as ARKit and ARCore. This allows users to intuitively understand what furniture and decorative items they are considering purchasing would look like when actually placed in a room.

[0227] For example, imagine a user seeking relaxation amidst a busy daily life who wants to redecorate their room to alleviate fatigue. In this case, the system suggests calming colors and furniture with relaxing effects, and shows how to arrange these items in the actual space. Through this process, it becomes possible to propose a living space that is optimal for the user's emotions.

[0228] Examples of prompts include: "Generate an interior design plan to suggest a relaxing living room for a stressed customer. The room is 15m², and you should select furniture in calming colors."

[0229] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0230] Step 1:

[0231] The user takes a picture of the room using a smart device. The image data taken by the user is uploaded to the server. The server receives this image data as input and uses OpenCV and TensorFlow to extract information such as the size and shape of the space and the arrangement of furniture. In this way, the physical characteristics of the room are provided to the server as digital data.

[0232] Step 2:

[0233] Users input their interior design preferences and budget information using a smart device interface. This input information is sent to a server. The server stores this user information in a database and uses it as basic data for generating designs. Here, the user's desired design style and budget range are clarified.

[0234] Step 3:

[0235] Users capture their facial expressions using their smart device's camera and register their emotional state. This image data is analyzed by emotion analysis tools such as Microsoft Azure Face API and Google Cloud AI, and emotional information such as stress and joy is analyzed on a server. As a result, the user's emotional state is obtained as numerical data and used as input for a generative AI model.

[0236] Step 4:

[0237] The server inputs acquired spatial information, user preferences, budget, and emotional state into a generating AI model (e.g., GPT-4) to generate an optimal item placement plan. The generating AI model uses prompts to devise the most suitable furniture and design options for the user. In this step, natural color tones and layouts are generated, and an interior design tailored to the user's needs is proposed.

[0238] Step 5:

[0239] The server retrieves inventory information in real time via Firebase Realtime Database and filters the generated placement plan to include only items that are actually available for purchase. This enables realistic product recommendations based on inventory levels.

[0240] Step 6:

[0241] The generated item placement suggestions are visualized on the user's smart device using augmented reality generation tools such as ARKit and ARCore. Augmented reality technology allows users to virtually check the furniture placement in their home and make purchase decisions based on visual feedback. In this step, users can more easily grasp the suggested interior design intuitively.

[0242] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0243] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0244] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0245] [Second Embodiment]

[0246] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0247] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0248] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0249] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0250] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0251] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0252] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0253] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0254] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0255] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0256] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0257] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0258] This invention is a system that assists users in optimizing the interior of their living spaces, and in particular, by using image analysis technology and augmented reality technology, it enables users to select and arrange items that are ideal for them.

[0259] First, the user takes photos of their room or the entire living space using a smart device. These image data are immediately sent to a server via the network. The server analyzes the received images and extracts spatial information such as the size and shape of the room and the arrangement of furniture.

[0260] Next, the terminal provides an interface for the user to enter information about their preferences and budget, and the user enters their requests into this form. This information is sent to the server, where the interior style, colors, and functionality requirements that meet the user's requests are recorded.

[0261] Based on collected spatial information and user requests, the server uses the latest generative AI technology to generate suggested furniture and appliance placements. This process ensures that items harmonize with the user's desired interior style.

[0262] Furthermore, the suggested items are checked for inventory in real time by the server, and this information is reflected in the generated layout. This allows users to immediately see which items are available for order.

[0263] The device visualizes suggested layouts provided by the server using augmented reality, helping users to see them in their actual space. Through this AR display, users can intuitively understand how the selected furniture will be placed in their own room.

[0264] For example, if a user requests a new living room layout, the system analyzes the spatial dimensions from a photo of the room and proposes a furniture arrangement based on a modern, white-based style. This proposal is displayed in real-time using augmented reality (AR) on the user's device, and the user can purchase their preferred layout directly.

[0265] Thus, the present invention is a system that streamlines the conventional furniture selection process and provides users with a seamless and intuitive means of choosing interior furnishings.

[0266] The following describes the processing flow.

[0267] Step 1:

[0268] The user takes a picture of the room with a smart device and uploads the image to the application.

[0269] Step 2:

[0270] The terminal receives image data and initiates communication to send it to the server.

[0271] Step 3:

[0272] The server analyzes the received image data to extract spatial information, such as the room's size, shape, the location of windows and doors, and the arrangement of existing furniture.

[0273] Step 4:

[0274] The device displays a form for the user to input their preferred style, budget, color and material choices, etc.

[0275] Step 5:

[0276] The user enters their preferred information into a form, and the device sends that information to the server.

[0277] Step 6:

[0278] The server combines spatial information obtained from image analysis with user-inputted preference information and uses a generative AI to generate an optimal furniture and appliance placement plan.

[0279] Step 7:

[0280] Based on the proposed deployment plan, the server retrieves and updates inventory information in real time to check if the relevant products are available for purchase.

[0281] Step 8:

[0282] The server generates visualization data for augmented reality and sends it to the terminal, allowing the user to actually see the suggested furniture and appliance placement.

[0283] Step 9:

[0284] The terminal uses augmented reality technology to display the proposed layout images of furniture and home appliances on the user device.

[0285] Step 10:

[0286] The user checks the displayed proposals, selects the products they like, and proceeds with the purchase process.

[0287] Step 11:

[0288] The server processes the purchase of the selected products and coordinates with the flea market app to finalize the order.

[0289] Step 12:

[0290] The server notifies the user of the purchase completion and provides the shipping information of the product.

[0291] (Example 1)

[0292] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0293] In the conventional interior selection process, it was difficult for users to intuitively visualize the ideal space design and perform product selection and layout that reflected the inventory status in real time. Also, it was not possible to quickly generate appropriate proposals according to the user's preferences.

[0294] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0295] In this invention, the server includes processing means for analyzing and extracting spatial information from image data captured by the user, acquisition means for receiving information on the user's preferences and budget, and generation processing means for generating an optimal product arrangement based on the extracted spatial information and the user's preferences and budget. This enables the user to intuitively visualize their desired interior and makes it possible to select and arrange products realistically while reflecting inventory status.

[0296] A "user" is the entity that provides input information and image data and receives interior design suggestions.

[0297] "Information about space" refers to data such as room dimensions, shape, and furniture arrangement obtained through the analysis of image data.

[0298] A "processing means" is an element that has the function of analyzing and extracting spatial information from image data.

[0299] "Acquisition method" refers to an element that has the function of receiving and recording information about the user's selected preferences and budget.

[0300] A "generation processing means" is an element that has the function of generating the optimal product arrangement based on spatial information and the user's preferences and budget.

[0301] "Augmented reality display means" refers to a function that uses technology to visualize a proposed product arrangement by overlaying it onto a real-world space.

[0302] "Inventory information" refers to real-time data on how readily available a product is.

[0303] A "data transmission function" is an element that has the function of sending data necessary for visualization to the user terminal.

[0304] This invention provides a system for optimizing the interior of a user's living space, specifically utilizing image analysis technology and augmented reality technology. To implement the invention, a server, a terminal, and a user each need to play specific roles. Details will be described below.

[0305] First, the user uses an appropriate device such as a smartphone or tablet to take photos of their own room or living space. This device is installed with a dedicated application and has the function of sending the captured image data to the server. It is sent to the server via a network connection along with the user-specified preference and budget information.

[0306] Next, the server analyzes the received image data. Specifically, software libraries such as OpenCV and TensorFlow are used to perform image processing and object recognition. Thereby, spatial information such as the dimensions, shape of the room, and the arrangement of furniture is extracted. The extracted information is stored as a digital model in the server and used for subsequent generation processing. For this generation processing, generative AI such as the OpenAI GPT model is used to propose an optimal interior plan based on the user's prompt text.

[0307] After that, the terminal uses augmented reality (AR) technology to visualize the proposed interior arrangement. The terminal utilizes AR software such as ARKit (iOS) or ARCore (Android) to enable the user to experience placing virtual furniture within the real space through the device. Thereby, the user can intuitively evaluate the suitability of the proposed interior.

[0308] As a specific example, when the user is considering renovating the living room, the system performs image analysis and proposes an arrangement of furniture with a modern interior style and a white base tone. This proposal is displayed in AR on the terminal, and the user can directly view the visualized environment. If they like it, they can easily proceed to the ordering process.

[0309] Examples of prompts for efficiently managing the above process include, "Please propose an interior design plan based on a modern style with a white color scheme."

[0310] This system allows users to significantly streamline the interior design process, making it easier to select and realize their ideal living environment.

[0311] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0312] Step 1:

[0313] The user takes pictures of their room or living space using a smart device. These captured images become the input for processing. The user selects images through a dedicated application and sends them to a server via the network. The output of this step is the image data sent to the server.

[0314] Step 2:

[0315] The server analyzes the received image data and extracts spatial information. Specifically, the server uses image analysis libraries such as OpenCV to process the dimensions of furniture and rooms within the image and extracts the room structure as digital data. The input for this step is the image data sent by the user, and the output is the extracted spatial information.

[0316] Step 3:

[0317] The terminal prompts the user to input information about their preferences and budget through the user interface. The user enters their desired style and budget into a form on the screen, and this information is sent to the server. The input in this step is the information entered into the user interface, and the output is the recorded user preferences and budget information.

[0318] Step 4:

[0319] The server generates an optimal interior plan using a generative AI model based on extracted spatial information and user input. The generative AI, such as a GPT model, calculates the appropriate furniture placement for the room according to the user's prompts. The input for this step is spatial information and user input, and the output is the generated interior plan.

[0320] Step 5:

[0321] The server uses the generated interior plan to check inventory information. This process verifies whether the suggested furniture and appliances are immediately available for order and reflects the inventory status in the interior plan. The input for this step is the generated interior plan, and the output is the plan with the inventory status reflected.

[0322] Step 6:

[0323] The terminal provides the user with a proposed plan received from the server using augmented reality (AR) technology. Specifically, it uses ARKit or ARCore to display a virtual interior when the user views the room through the device. The input for this step is an interior plan that reflects inventory status, and the output is the visualization result using augmented reality.

[0324] Step 7:

[0325] The user reviews the presented augmented reality layout and proceeds with the purchase if they like it. The user selects options on the terminal and confirms the order for the selected furniture and appliances. The input for this step is the augmented reality visualization, and the output is the confirmed order.

[0326] (Application Example 1)

[0327] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0328] In recent years, there has been a growing need for users to select interior items that suit their personal preferences when optimizing their living spaces. However, conventional systems make it difficult for users to visualize how items will look when actually placed in a home, and the lack of real-time inventory information and in-store support makes the purchase decision-making process cumbersome. Against this backdrop, there is a need for technology that improves the user experience and efficiently supports the selection of optimal items.

[0329] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0330] In this invention, the server includes: an image analysis means for extracting spatial information from image data entered by the user; an input means for receiving preference and budget information entered by the user; a generation means for proposing an optimal arrangement of items based on the extracted spatial information and the user's preference and budget information; an augmented reality generation means for visualizing the proposed arrangement of items in the real world; an information acquisition means using a visual device for acquiring and analyzing real-world items; a function means using a device for visualizing and presenting the proposed arrangement of items; and a data linkage means for acquiring and presenting corresponding item information in real time. This enables the user to intuitively experience the arrangement of interiors in their living space and to efficiently and quickly select and purchase appropriate furniture.

[0331] "Image analysis means" refers to technology for analyzing spatial shape and arrangement information from image data input by the user.

[0332] An "input method" is a function that provides an interface for receiving user requests such as preferences and budget.

[0333] The "generation method" is a technology that proposes the optimal arrangement of items based on extracted spatial information and user requests.

[0334] "Augmented reality generation means" refers to a technology for displaying the proposed arrangement of objects superimposed onto real space.

[0335] "Information acquisition means" refers to a function that uses visual devices to acquire and analyze information about real-world objects.

[0336] A "functional means" is an operating device for visualizing and presenting the arrangement of proposed items to the user.

[0337] "Data linkage means" refers to technology for acquiring real-time information about necessary items and presenting it appropriately to the user.

[0338] The system of the present invention is designed to optimize the interior of a user's living space and is realized using image analysis technology and augmented reality technology. Specific embodiments for carrying out the present invention are shown below.

[0339] First, the user uses a smart device to take an image of the entire living space and sends the data to the server. At this stage, the server uses "image analysis tools" to analyze the received image data and extract information such as the size and shape of the space and the arrangement of existing furniture. This process uses Python and image processing libraries such as OpenCV.

[0340] Next, the user inputs information about their preferences and budget through the terminal's interface. This information is sent to the server, which receives it as "input." The server then uses "generation tools" to generate the optimal arrangement of items that matches the style the user desires. For example, generation AI technology may be used for this generation.

[0341] The generated proposals are visualized on the device via an "augmented reality generation mechanism." This allows users to experience the proposed arrangement superimposed on real space. Specifically, Unity or ARKit could be used for augmented reality display.

[0342] Furthermore, the system can acquire and analyze item information using visual devices within a physical store through its "information acquisition means." This supports the user's purchasing experience while in a physical store. The "functional means" work to present the proposed item arrangement to the user, and one of the functions used is providing an interface on smart glasses.

[0343] The system also uses a "data linkage mechanism" to acquire inventory information for suggested items in real time and present it to the user. This allows the user to seamlessly proceed through the process from selecting interior items to purchasing them.

[0344] As a concrete example, consider a scenario where a user is looking for the perfect sofa for their new living room. By inputting the user's preferences and living space information through smart glasses, it's possible to use a "generative AI model" to suggest sofa placements that match the style. An example of a prompt in this case would be, "The user is looking for a sofa that suits a modern, white-themed living room."

[0345] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0346] Step 1:

[0347] The user takes images of their living space using a smart device and sends the image data to a server. The input is the image data taken by the user, and the output is the image data sent to the server. This image data includes an overall view of the room and existing furniture.

[0348] Step 2:

[0349] The server processes the received image data using "image analysis tools" to extract spatial information such as the dimensions and shape of the space and the location of existing furniture. The input is image data sent to the server. In this step, data analysis is performed using image processing libraries such as Python or OpenCV, and the output is in the form of spatial information.

[0350] Step 3:

[0351] The user uses the terminal's interface to input information about their preferences and budget. This input, containing data about the user's personal preferences and budget, is sent from the terminal to the server, which receives it as input. The output is the user's request data recorded on the server.

[0352] Step 4:

[0353] The server, based on the spatial information obtained in the previous step and the user's request data, utilizes the "generation method" to propose the optimal item placement. The input consists of spatial information and the user's requests. The generation AI model processes this data and outputs an item placement that suits the user's preferences.

[0354] Step 5:

[0355] The generated proposals are visualized on the device using an "augmented reality generation method." The device receives object placement data output from the server and allows the user to see them overlaid on a real-world room. The output is the object placement displayed in augmented reality. Here, visualization in real space is performed using Unity or ARKit.

[0356] Step 6:

[0357] When a user visits a physical store, information about the actual items is acquired and analyzed using a visual device and an "information acquisition means." The input is information about the actual items acquired through the visual device. The output is specific item data presented to the user.

[0358] Step 7:

[0359] The suggested items are linked to a "data linkage system" which retrieves relevant data, including inventory information, in real time. This information is then fed back to the user, who can then make a purchase decision based on it. The input is information about the suggested items, and the output is real-time item information, including inventory.

[0360] Step 8:

[0361] Users review the item placement visualized in augmented reality, and once they've decided to purchase, they order the selected items through the terminal. The input is the information of the final selected items, and the output is the purchase procedure information. This process supports a seamless purchasing experience.

[0362] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0363] This invention is a system that provides interior design suggestions while taking into account the user's emotional state. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, and spatial information such as the size and shape of the room and the current furniture arrangement is extracted by an image analysis means.

[0364] Next, the terminal displays an interface for the user to input their interior design preferences and budget, and the user enters this information. This data is sent to the server and recorded as the user's request.

[0365] A key feature of this system is its use of an emotion engine to understand the user's emotional state. When a user registers their facial expressions with the system via voice input or camera, the emotion engine analyzes the data and recognizes the user's emotions, such as their level of stress or joy. This emotional information, along with other request information entered by the user, is provided to the generation mechanism.

[0366] The server integrates this information and uses AI to generate an optimal furniture and appliance placement plan. During this process, suggestions are made to enhance comfort and relaxation, tailored to the user's emotional state. Furthermore, the server retrieves real-time inventory information and selects items that are available for purchase.

[0367] Subsequently, the server-generated suggestions are visualized using augmented reality technology, and the data is sent to the terminal for display on the user's device. This AR display allows the user to intuitively understand what the selected furniture would look like when actually placed in the room.

[0368] For example, if a user is leading a busy life and seeks a relaxing effect from their living room decor, the system will recognize the user's calm emotional state and suggest furniture with relaxing colors and arrangements. In this way, the present invention aims to improve the user's living environment by providing interior design suggestions that take the user's emotions into consideration.

[0369] The following describes the processing flow.

[0370] Step 1:

[0371] Users take photos of their rooms with their smart devices and upload the image data by opening the application.

[0372] Step 2:

[0373] After the terminal receives the image data, it initiates communication to send it to the server.

[0374] Step 3:

[0375] The server analyzes the received image data and extracts spatial information, including the room's size, shape, and current furniture arrangement.

[0376] Step 4:

[0377] The device displays a form for the user to enter their interior design preferences, desired budget, and other requests.

[0378] Step 5:

[0379] The user enters information such as their preferences and budget into a form on their device and sends it to the server.

[0380] Step 6:

[0381] The device uses the user's camera and microphone to capture the user's face and voice, and sends that data to the emotion engine.

[0382] Step 7:

[0383] The emotion engine analyzes the user's emotional state from their facial expressions and voice, recognizing, for example, their stress level and satisfaction level.

[0384] Step 8:

[0385] The server integrates spatial information, user request information, and emotional information from the emotion engine, and uses generative AI to formulate the optimal furniture and appliance placement plan.

[0386] Step 9:

[0387] The server checks inventory information in real time via an online database and reflects available items in the final proposal.

[0388] Step 10:

[0389] The server generates the proposed furniture and appliance placement plan as augmented reality data and sends it to the terminal.

[0390] Step 11:

[0391] Based on the augmented reality data transmitted by the device, the suggested furniture arrangement is displayed in AR on the user's device for the user to confirm.

[0392] Step 12:

[0393] Users view AR displays, select furniture and appliances based on their preferred suggestions, and proceed with the purchase process.

[0394] Step 13:

[0395] The server processes the purchase of the selected items and confirms the order with the partnered online sales platform.

[0396] Step 14:

[0397] The server sends a purchase completion notification to the user and provides information such as shipping details for the product.

[0398] (Example 2)

[0399] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0400] Traditional interior design proposal systems could suggest item placements based on user preferences and budget, but they lacked the ability to consider the user's emotional state. This made it difficult to create truly comfortable spaces that users desired. Therefore, it is necessary to provide interior design proposals that are more tailored to individual needs, incorporating information that includes the user's emotional state.

[0401] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0402] In this invention, the server includes an image analysis means for extracting spatial information from image data entered by the user, an input means for receiving preference and budget information entered by the user, and an emotion analysis means for analyzing the emotional state and providing the results to the generation means. This makes it possible to propose the optimal arrangement of items according to the user's emotional state and to realize a comfortable interior space tailored to individual needs.

[0403] "Image analysis means" refers to technical means for extracting spatial information from image data input by a user.

[0404] An "input method" refers to a means of providing an interface for users to input their interior design preferences and budget information into the system.

[0405] A "generation method" is a means for proposing the optimal arrangement of items based on extracted spatial information and user preferences and budget information.

[0406] "Emotional analysis means" refers to a technical means that analyzes the user's emotional state and provides the results to the generation means.

[0407] An "augmented reality generation method" is a technical means for visualizing a proposed arrangement of objects in real space.

[0408] "Inventory synchronization means" refers to technical means that enable the acquisition of inventory information in real time.

[0409] "Data transmission means" refers to means for transmitting data necessary for the augmented reality generation means to visualize the proposed item arrangement on the user device.

[0410] This system proposes furniture arrangements that take into account the user's emotional state in order to create a comfortable interior space. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, which uses image analysis to extract spatial information such as the size and shape of the room and the current furniture arrangement.

[0411] Next, the terminal displays an interface to the user, prompting them to input their interior design preferences and budget. The user enters this information through the terminal's interface, and the terminal sends this data to a server to record the user's preferences.

[0412] Regarding the emotion analysis method, the user inputs their emotional state into the system using voice input or a camera on their smart device. The server uses the emotion analysis method to analyze the voice and facial expression data to recognize the user's emotional state. This extracts emotional information such as the degree of stress or joy.

[0413] The server uses collected spatial information, user preferences and budget, and emotional information to generate an optimal furniture placement plan using a generative AI model. This generative AI model is based on, for example, a common generative AI framework. The generated placement plan is optimized for the user's emotional state and incorporates color schemes and designs aimed at promoting relaxation.

[0414] Furthermore, the server acquires real-time market inventory information through inventory synchronization and selects items that are available for purchase. The server uses augmented reality generation to visualize the proposed interior layout using AR technology and transmits the data to the terminal. Through the terminal, the user can obtain a visual image of how the furniture would look when placed in an actual room.

[0415] For example, if a user leads a busy life and desires relaxation in their living room, the system analyzes the user's emotional state as "easy to relax." Based on this, it suggests furniture with natural colors and soft arrangements that are expected to have a relaxing effect. By inputting a prompt such as "Please suggest living room interiors that will help the user relax" into the AI ​​model, users can receive specific suggestions.

[0416] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0417] Step 1:

[0418] The user takes a photo of the room with a smart device and uploads the image data to the system. This image data becomes the input. The server receives this image data and uses image analysis to extract spatial information such as the room's size, shape, and furniture arrangement. The extracted spatial information becomes the output.

[0419] Step 2:

[0420] The terminal allows the user to input their interior design preferences and budget through an interface. This input becomes the input data. The terminal then sends this information to a server, where it is recorded as the user's request. The recorded information becomes the output.

[0421] Step 3:

[0422] Users register their emotional state with the system using voice input or camera on their smart devices to collect emotional information. This audio / video data becomes the input. The server analyzes the data using emotion analysis tools to recognize the degree of stress or joy. The analyzed emotional information becomes the output.

[0423] Step 4:

[0424] The server integrates spatial information obtained from image analysis, user preferences and budget information, and emotional information obtained from emotion analysis, and uses these as input data for a generative AI model. The server then uses this generative AI model to generate an optimal furniture arrangement plan. This plan generation process takes into account suggestions based on the user's emotional state. The output is the generated furniture arrangement plan.

[0425] Step 5:

[0426] The server uses an inventory synchronization method to obtain inventory information in real time. Inventory information retrieved from the market database is the input, and a list of available items is output. Based on this information, products suitable for the generated furniture placement plan are selected.

[0427] Step 6:

[0428] The server uses the generated furniture layout plan and selected product information to create visualization data using an augmented reality generation system. This visualization data is sent to the terminal. The transmitted visualization data becomes the output.

[0429] Step 7:

[0430] The device uses augmented reality (AR) technology to display a suggested furniture arrangement on the user's device, based on visualization data sent from the server. The user can then review this display and get an idea of ​​how the furniture would actually look in their room. The output is the AR display presented to the user.

[0431] (Application Example 2)

[0432] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0433] Interior design and item placement suggestions made without considering the user's emotional state may not necessarily address the user's current mood or emotional needs. This presents a challenge in creating optimal spatial designs for users. Furthermore, in actual retail shopping experiences, users may find it difficult to visualize the suggested interior design in real-time, making purchase decisions challenging.

[0434] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0435] In this invention, the server includes an image analysis means for extracting spatial information from image data input by the user, an emotion analysis means for analyzing user-inputted preferences, budget information, and the user's emotional state and acquiring the data, a generation means for proposing the optimal item arrangement based on these, and an augmented reality generation means for visualizing the proposed item arrangement in the real space. This makes it possible to propose interiors and items that are best suited to the user's emotional state in real time, making the purchasing experience more intuitive and supporting the realization of a comfortable living space.

[0436] "Image analysis means" refers to a technology that extracts spatial information such as the size and shape of a space and the current furniture arrangement from image data input by the user.

[0437] "Input method" refers to the interface used by users to input their interior design preferences and budget information.

[0438] "Emotion analysis methods" refer to technologies that analyze a user's facial expressions and voice data to obtain data on their current emotional state.

[0439] The "generation method" is a method for proposing the optimal arrangement of items based on extracted spatial information, user preferences and budget information, and emotional state information.

[0440] "Augmented reality generation means" refers to a technology that visually reflects a proposed arrangement of objects in real space.

[0441] "Inventory synchronization methods" refer to technologies that use real-time inventory information to verify whether proposed items are actually available for purchase.

[0442] A "data transmission means" is a mechanism for transmitting data necessary to visualize the proposed item arrangement on the user's device.

[0443] The embodiments of the present invention will now be described. The system of the present invention consists of a smart device used by the user, an analysis engine on a server, and augmented reality technology for displaying the proposed results.

[0444] The user takes a picture of the room using a smartphone or other smart device. This image data is uploaded from the device to the server. On the server, spatial information such as the size, shape, and furniture arrangement of the space is extracted using OpenCV or TensorFlow as image analysis tools.

[0445] Next, the user inputs their interior design preferences and budget information through the device's interface. This information is also sent to the server and recorded as the user's request. Furthermore, the user uses the camera function to capture their facial expressions, and emotional data such as stress and relaxation levels are registered on the server using emotion analysis tools such as Microsoft Azure Face API and Google Cloud AI.

[0446] The server integrates this data and uses a generative AI model (e.g., GPT-4) to generate a plan that suggests the optimal placement of items, taking into account the user's emotions. This plan includes furniture with colors and designs that suit the user's space, and also uses Firebase Realtime Database for real-time inventory checks.

[0447] The proposed item placements are visualized on the user's device using augmented reality generation tools such as ARKit and ARCore. This allows users to intuitively understand what furniture and decorative items they are considering purchasing would look like when actually placed in a room.

[0448] For example, imagine a user seeking relaxation amidst a busy daily life who wants to redecorate their room to alleviate fatigue. In this case, the system suggests calming colors and furniture with relaxing effects, and shows how to arrange these items in the actual space. Through this process, it becomes possible to propose a living space that is optimal for the user's emotions.

[0449] Examples of prompts include: "Generate an interior design plan to suggest a relaxing living room for a stressed customer. The room is 15m², and you should select furniture in calming colors."

[0450] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0451] Step 1:

[0452] The user takes a picture of the room using a smart device. The image data taken by the user is uploaded to the server. The server receives this image data as input and uses OpenCV and TensorFlow to extract information such as the size and shape of the space and the arrangement of furniture. In this way, the physical characteristics of the room are provided to the server as digital data.

[0453] Step 2:

[0454] Users input their interior design preferences and budget information using a smart device interface. This input information is sent to a server. The server stores this user information in a database and uses it as basic data for generating designs. Here, the user's desired design style and budget range are clarified.

[0455] Step 3:

[0456] Users capture their facial expressions using their smart device's camera and register their emotional state. This image data is analyzed by emotion analysis tools such as Microsoft Azure Face API and Google Cloud AI, and emotional information such as stress and joy is analyzed on a server. As a result, the user's emotional state is obtained as numerical data and used as input for a generative AI model.

[0457] Step 4:

[0458] The server inputs acquired spatial information, user preferences, budget, and emotional state into a generating AI model (e.g., GPT-4) to generate an optimal item placement plan. The generating AI model uses prompts to devise the most suitable furniture and design options for the user. In this step, natural color tones and layouts are generated, and an interior design tailored to the user's needs is proposed.

[0459] Step 5:

[0460] The server retrieves inventory information in real time via Firebase Realtime Database and filters the generated placement plan to include only items that are actually available for purchase. This enables realistic product recommendations based on inventory levels.

[0461] Step 6:

[0462] The generated item placement suggestions are visualized on the user's smart device using augmented reality generation tools such as ARKit and ARCore. Augmented reality technology allows users to virtually check the furniture placement in their home and make purchase decisions based on visual feedback. In this step, users can more easily grasp the suggested interior design intuitively.

[0463] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0464] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0465] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0466] [Third Embodiment]

[0467] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0468] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0469] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0470] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0471] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0472] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0473] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0474] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0475] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0476] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0477] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0478] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0479] This invention is a system that assists users in optimizing the interior of their living spaces, and in particular, by using image analysis technology and augmented reality technology, it enables users to select and arrange items that are ideal for them.

[0480] First, the user takes photos of their room or the entire living space using a smart device. These image data are immediately sent to a server via the network. The server analyzes the received images and extracts spatial information such as the size and shape of the room and the arrangement of furniture.

[0481] Next, the terminal provides an interface for the user to enter information about their preferences and budget, and the user enters their requests into this form. This information is sent to the server, where the interior style, colors, and functionality requirements that meet the user's requests are recorded.

[0482] Based on collected spatial information and user requests, the server uses the latest generative AI technology to generate suggested furniture and appliance placements. This process ensures that items harmonize with the user's desired interior style.

[0483] Furthermore, the suggested items are checked for inventory in real time by the server, and this information is reflected in the generated layout. This allows users to immediately see which items are available for order.

[0484] The device visualizes suggested layouts provided by the server using augmented reality, helping users to see them in their actual space. Through this AR display, users can intuitively understand how the selected furniture will be placed in their own room.

[0485] For example, if a user requests a new living room layout, the system analyzes the spatial dimensions from a photo of the room and proposes a furniture arrangement based on a modern, white-based style. This proposal is displayed in real-time using augmented reality (AR) on the user's device, and the user can purchase their preferred layout directly.

[0486] Thus, the present invention is a system that streamlines the conventional furniture selection process and provides users with a seamless and intuitive means of choosing interior furnishings.

[0487] The following describes the processing flow.

[0488] Step 1:

[0489] The user takes a picture of the room with a smart device and uploads the image to the application.

[0490] Step 2:

[0491] The terminal receives image data and initiates communication to send it to the server.

[0492] Step 3:

[0493] The server analyzes the received image data to extract spatial information, such as the room's size, shape, the location of windows and doors, and the arrangement of existing furniture.

[0494] Step 4:

[0495] The device displays a form for the user to input their preferred style, budget, color and material choices, etc.

[0496] Step 5:

[0497] The user enters their preferred information into a form, and the device sends that information to the server.

[0498] Step 6:

[0499] The server combines spatial information obtained from image analysis with user-inputted preference information and uses a generative AI to generate an optimal furniture and appliance placement plan.

[0500] Step 7:

[0501] Based on the proposed deployment plan, the server retrieves and updates inventory information in real time to check if the relevant products are available for purchase.

[0502] Step 8:

[0503] The server generates visualization data for augmented reality and sends it to the terminal, allowing the user to actually see the suggested furniture and appliance placement.

[0504] Step 9:

[0505] The device uses augmented reality technology to display suggested furniture and appliance placement images on the user's device.

[0506] Step 10:

[0507] The user reviews the displayed suggestions, selects a product they like, and proceeds with the purchase.

[0508] Step 11:

[0509] The server processes the purchase of the selected items and confirms the order in conjunction with the flea market app.

[0510] Step 12:

[0511] The server notifies the user that the purchase is complete and provides shipping information for the product.

[0512] (Example 1)

[0513] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0514] In traditional interior design selection processes, it was difficult to intuitively visualize the user's ideal spatial design and to select and arrange products that reflected real-time inventory status. Furthermore, it was not possible to quickly generate appropriate suggestions tailored to the user's preferences.

[0515] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0516] In this invention, the server includes processing means for analyzing and extracting spatial information from image data captured by the user, acquisition means for receiving information on the user's preferences and budget, and generation processing means for generating an optimal product arrangement based on the extracted spatial information and the user's preferences and budget. This enables the user to intuitively visualize their desired interior and makes it possible to select and arrange products realistically while reflecting inventory status.

[0517] A "user" is the entity that provides input information and image data and receives interior design suggestions.

[0518] "Information about space" refers to data such as room dimensions, shape, and furniture arrangement obtained through the analysis of image data.

[0519] A "processing means" is an element that has the function of analyzing and extracting spatial information from image data.

[0520] "Means of acquisition" refers to elements that have the function of receiving and recording information about the user's selected preferences and budget.

[0521] A "generation processing means" is an element that has the function of generating the optimal product arrangement based on spatial information and the user's preferences and budget.

[0522] "Augmented reality display means" refers to a function that uses technology to visualize a proposed product arrangement by overlaying it onto real space.

[0523] "Inventory information" refers to real-time data on how readily available a product is.

[0524] A "data transmission function" is an element that has the function of sending data necessary for visualization to the user terminal.

[0525] This invention provides a system for optimizing the interior of a user's living space, specifically utilizing image analysis technology and augmented reality technology. To implement the invention, a server, terminal, and user each need to play specific roles. Details are described below.

[0526] First, the user takes photos of their room or living space using a suitable device such as a smartphone or tablet. This device has a dedicated application installed and is equipped with the function to send the captured image data to a server. The data is sent to the server via a network connection, along with the user's specified preferences and budget information.

[0527] Next, the server analyzes the received image data. Specifically, it uses software libraries such as OpenCV and TensorFlow to perform image processing and object recognition. This extracts spatial information such as room dimensions, shape, and furniture arrangement. The extracted information is stored as a digital model on the server and used in subsequent generation processes. This generation process uses generative AI such as the OpenAI GPT model to propose an optimal interior plan based on the user's prompts.

[0528] The device then uses augmented reality (AR) technology to visualize the proposed interior layout. AR software such as ARKit (iOS) and ARCore (Android) enables users to experience placing virtual furniture within a real-world space through the device. This allows users to intuitively evaluate the suitability of the proposed interior.

[0529] For example, if a user is considering renovating their living room, the system performs image analysis and suggests a furniture arrangement based on a modern interior style with a white color scheme. This suggestion is displayed in AR on the device, allowing the user to view the visualized environment and easily proceed to the ordering process if they like it.

[0530] Examples of prompts for efficiently managing the above process include, "Please propose an interior design plan with a modern style and a white color scheme."

[0531] This system allows users to significantly streamline the interior design process, making it easier to select and realize their ideal living environment.

[0532] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0533] Step 1:

[0534] The user takes images of their room or living space using a smart device. These captured images become the input for processing. The user selects images through a dedicated application and sends them to a server via the network. The output of this step is the image data sent to the server.

[0535] Step 2:

[0536] The server analyzes the received image data and extracts spatial information. Specifically, the server uses image analysis libraries such as OpenCV to process the dimensions of furniture and rooms within the image and extracts the room structure as digital data. The input for this step is the image data sent by the user, and the output is the extracted spatial information.

[0537] Step 3:

[0538] The terminal prompts the user to input information about their preferences and budget through the user interface. The user enters their desired style and budget into a form on the screen, and this information is sent to the server. The input in this step is the information entered into the user interface, and the output is the recorded user preferences and budget information.

[0539] Step 4:

[0540] The server generates an optimal interior plan using a generative AI model based on extracted spatial information and user input. The generative AI, such as a GPT model, calculates the appropriate furniture placement for the room according to the user's prompts. The input for this step is spatial information and user input, and the output is the generated interior plan.

[0541] Step 5:

[0542] The server uses the generated interior plan to check inventory information. This process verifies whether the suggested furniture and appliances are immediately available for order and reflects the inventory status in the interior plan. The input for this step is the generated interior plan, and the output is the plan with the inventory status reflected.

[0543] Step 6:

[0544] The terminal provides the user with a proposed plan received from the server using augmented reality (AR) technology. Specifically, it uses ARKit or ARCore to display a virtual interior when the user views the room through the device. The input for this step is an interior plan that reflects inventory status, and the output is the visualization result using augmented reality.

[0545] Step 7:

[0546] The user reviews the presented augmented reality layout and proceeds with the purchase if they like it. The user selects options on the terminal and confirms the order for the selected furniture and appliances. The input for this step is the augmented reality visualization, and the output is the confirmed order.

[0547] (Application Example 1)

[0548] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0549] In recent years, there has been a growing need for users to select interior items that suit their personal preferences when optimizing their living spaces. However, conventional systems make it difficult for users to visualize how items will look when actually placed in a home, and the lack of real-time inventory information and in-store support makes the purchase decision-making process cumbersome. Against this backdrop, there is a need for technology that improves the user experience and efficiently supports the selection of optimal items.

[0550] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0551] In this invention, the server includes: an image analysis means for extracting spatial information from image data entered by the user; an input means for receiving preference and budget information entered by the user; a generation means for proposing an optimal arrangement of items based on the extracted spatial information and the user's preference and budget information; an augmented reality generation means for visualizing the proposed arrangement of items in the real world; an information acquisition means using a visual device for acquiring and analyzing real-world items; a function means using a device for visualizing and presenting the proposed arrangement of items; and a data linkage means for acquiring and presenting corresponding item information in real time. This enables the user to intuitively experience the arrangement of interiors in their living space and to efficiently and quickly select and purchase appropriate furniture.

[0552] "Image analysis means" refers to technology for analyzing spatial shape and arrangement information from image data input by the user.

[0553] An "input method" is a function that provides an interface for receiving user requests such as preferences and budget.

[0554] The "generation method" is a technology that proposes the optimal arrangement of items based on extracted spatial information and user requests.

[0555] "Augmented reality generation means" refers to a technology for displaying the proposed arrangement of objects superimposed onto real space.

[0556] "Information acquisition means" refers to a function that uses visual devices to acquire and analyze information about real-world objects.

[0557] A "functional means" is an operating device for visualizing and presenting the arrangement of proposed items to the user.

[0558] "Data linkage means" refers to technology for acquiring real-time information about necessary items and presenting it appropriately to the user.

[0559] The system of the present invention is designed to optimize the interior of a user's living space and is realized using image analysis technology and augmented reality technology. Specific embodiments for carrying out the present invention are shown below.

[0560] First, the user uses a smart device to take an image of the entire living space and sends the data to the server. At this stage, the server uses "image analysis tools" to analyze the received image data and extract information such as the size and shape of the space and the arrangement of existing furniture. This process uses Python and image processing libraries such as OpenCV.

[0561] Next, the user inputs information about their preferences and budget through the terminal's interface. This information is sent to the server, which receives it as "input." The server then uses "generation tools" to generate the optimal arrangement of items that matches the style the user desires. For example, generation AI technology may be used for this generation.

[0562] The generated proposals are visualized on the device via an "augmented reality generation mechanism." This allows users to experience the proposed arrangement superimposed on real space. Specifically, Unity or ARKit could be used for augmented reality display.

[0563] Furthermore, the system can acquire and analyze item information using visual devices within a physical store through its "information acquisition means." This supports the user's purchasing experience while in a physical store. The "functional means" work to present the proposed item arrangement to the user, and one of the functions used is providing an interface on smart glasses.

[0564] The system also uses a "data linkage mechanism" to acquire inventory information for suggested items in real time and present it to the user. This allows the user to seamlessly proceed through the process from selecting interior items to purchasing them.

[0565] As a concrete example, consider a scenario where a user is looking for the perfect sofa for their new living room. By inputting the user's preferences and living space information through smart glasses, it's possible to use a "generative AI model" to suggest sofa placements that match the style. An example of a prompt in this case would be, "The user is looking for a sofa that suits a modern, white-themed living room."

[0566] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0567] Step 1:

[0568] The user takes images of their living space using a smart device and sends the image data to a server. The input is the image data taken by the user, and the output is the image data sent to the server. This image data includes an overall view of the room and existing furniture.

[0569] Step 2:

[0570] The server processes the received image data using "image analysis tools" to extract spatial information such as the dimensions and shape of the space and the location of existing furniture. The input is image data sent to the server. In this step, data analysis is performed using image processing libraries such as Python or OpenCV, and the output is in the form of spatial information.

[0571] Step 3:

[0572] The user uses the terminal's interface to input information about their preferences and budget. This input, containing data about the user's personal preferences and budget, is sent from the terminal to the server, which receives it as input. The output is the user's request data recorded on the server.

[0573] Step 4:

[0574] The server, based on the spatial information obtained in the previous step and the user's request data, utilizes the "generation method" to propose the optimal item placement. The input consists of spatial information and the user's requests. The generation AI model processes this data and outputs an item placement that suits the user's preferences.

[0575] Step 5:

[0576] The generated proposals are visualized on the device using an "augmented reality generation method." The device receives object placement data output from the server and allows the user to see them overlaid on a real-world room. The output is the object placement displayed in augmented reality. Here, visualization in real space is performed using Unity or ARKit.

[0577] Step 6:

[0578] When a user visits a physical store, information about the actual items is acquired and analyzed using a visual device and an "information acquisition means." The input is information about the actual items acquired through the visual device. The output is specific item data presented to the user.

[0579] Step 7:

[0580] The suggested items are linked to a "data linkage system" which retrieves relevant data, including inventory information, in real time. This information is then fed back to the user, who can then make a purchase decision based on it. The input is information about the suggested items, and the output is real-time item information, including inventory.

[0581] Step 8:

[0582] Users review the item placement visualized in augmented reality, and once they've decided to purchase, they order the selected items through the terminal. The input is the information of the final selected items, and the output is the purchase procedure information. This process supports a seamless purchasing experience.

[0583] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0584] This invention is a system that provides interior design suggestions while taking into account the user's emotional state. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, and spatial information such as the size and shape of the room and the current furniture arrangement is extracted by an image analysis means.

[0585] Next, the terminal displays an interface for the user to input their interior design preferences and budget, and the user enters this information. This data is sent to the server and recorded as the user's request.

[0586] A key feature of this system is its use of an emotion engine to understand the user's emotional state. When a user registers their facial expressions with the system via voice input or camera, the emotion engine analyzes the data and recognizes the user's emotions, such as their level of stress or joy. This emotional information, along with other request information entered by the user, is provided to the generation mechanism.

[0587] The server integrates this information and uses AI to generate an optimal furniture and appliance placement plan. During this process, suggestions are made to enhance comfort and relaxation, tailored to the user's emotional state. Furthermore, the server retrieves real-time inventory information and selects items that are available for purchase.

[0588] Subsequently, the server-generated suggestions are visualized using augmented reality technology, and the data is sent to the terminal for display on the user's device. This AR display allows the user to intuitively understand what the selected furniture would look like when actually placed in the room.

[0589] For example, if a user is leading a busy life and seeks a relaxing effect from their living room decor, the system will recognize the user's calm emotional state and suggest furniture with relaxing colors and arrangements. In this way, the present invention aims to improve the user's living environment by providing interior design suggestions that take the user's emotions into consideration.

[0590] The following describes the processing flow.

[0591] Step 1:

[0592] Users take photos of their rooms with their smart devices and upload the image data by opening the application.

[0593] Step 2:

[0594] After the terminal receives the image data, it initiates communication to send it to the server.

[0595] Step 3:

[0596] The server analyzes the received image data and extracts spatial information, including the room's size, shape, and current furniture arrangement.

[0597] Step 4:

[0598] The device displays a form for the user to enter their interior design preferences, desired budget, and other requests.

[0599] Step 5:

[0600] The user enters information such as their preferences and budget into a form on their device and sends it to the server.

[0601] Step 6:

[0602] The device uses the user's camera and microphone to capture the user's face and voice, and sends that data to the emotion engine.

[0603] Step 7:

[0604] The emotion engine analyzes the user's emotional state from their facial expressions and voice, recognizing, for example, their stress level and satisfaction level.

[0605] Step 8:

[0606] The server integrates spatial information, user request information, and emotional information from the emotion engine, and uses generative AI to formulate the optimal furniture and appliance placement plan.

[0607] Step 9:

[0608] The server checks inventory information in real time via an online database and reflects available items in the final proposal.

[0609] Step 10:

[0610] The server generates the proposed furniture and appliance placement plan as augmented reality data and sends it to the terminal.

[0611] Step 11:

[0612] Based on the augmented reality data transmitted by the device, the suggested furniture arrangement is displayed in AR on the user's device for the user to confirm.

[0613] Step 12:

[0614] Users view AR displays, select furniture and appliances based on their preferred suggestions, and proceed with the purchase process.

[0615] Step 13:

[0616] The server processes the purchase of the selected items and confirms the order with the partnered online sales platform.

[0617] Step 14:

[0618] The server sends a purchase completion notification to the user and provides information such as shipping details for the product.

[0619] (Example 2)

[0620] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0621] Traditional interior design proposal systems could suggest item placements based on user preferences and budget, but they lacked the ability to consider the user's emotional state. This made it difficult to create truly comfortable spaces that users desired. Therefore, it is necessary to provide interior design proposals that are more tailored to individual needs, incorporating information that includes the user's emotional state.

[0622] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0623] In this invention, the server includes an image analysis means for extracting spatial information from image data entered by the user, an input means for receiving preference and budget information entered by the user, and an emotion analysis means for analyzing the emotional state and providing the results to the generation means. This makes it possible to propose the optimal arrangement of items according to the user's emotional state and to realize a comfortable interior space tailored to individual needs.

[0624] "Image analysis means" refers to technical means for extracting spatial information from image data input by a user.

[0625] An "input method" refers to a means of providing an interface for users to input their interior design preferences and budget information into the system.

[0626] A "generation method" is a means for proposing the optimal arrangement of items based on extracted spatial information and user preferences and budget information.

[0627] "Emotional analysis means" refers to a technical means that analyzes the user's emotional state and provides the results to the generation means.

[0628] An "augmented reality generation method" is a technical means for visualizing a proposed arrangement of objects in real space.

[0629] "Inventory synchronization means" refers to technical means that enable the acquisition of inventory information in real time.

[0630] "Data transmission means" refers to means for transmitting data necessary for the augmented reality generation means to visualize the proposed item arrangement on the user device.

[0631] This system proposes furniture arrangements that take into account the user's emotional state in order to create a comfortable interior space. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, which uses image analysis to extract spatial information such as the size and shape of the room and the current furniture arrangement.

[0632] Next, the terminal displays an interface to the user, prompting them to input their interior design preferences and budget. The user enters this information through the terminal's interface, and the terminal sends this data to a server to record the user's preferences.

[0633] Regarding the emotion analysis method, the user inputs their emotional state into the system using voice input or a camera on their smart device. The server uses the emotion analysis method to analyze the voice and facial expression data to recognize the user's emotional state. This extracts emotional information such as the degree of stress or joy.

[0634] The server uses collected spatial information, user preferences and budget, and emotional information to generate an optimal furniture placement plan using a generative AI model. This generative AI model is based on, for example, a common generative AI framework. The generated placement plan is optimized for the user's emotional state and incorporates color schemes and designs aimed at promoting relaxation.

[0635] Furthermore, the server acquires real-time market inventory information through inventory synchronization and selects items that are available for purchase. The server uses augmented reality generation to visualize the proposed interior layout using AR technology and transmits the data to the terminal. Through the terminal, the user can obtain a visual image of how the furniture would look when placed in an actual room.

[0636] For example, if a user leads a busy life and desires relaxation in their living room, the system analyzes the user's emotional state as "easy to relax." Based on this, it suggests furniture with natural colors and soft arrangements that are expected to have a relaxing effect. By inputting a prompt such as "Please suggest living room interiors that will help the user relax" into the AI ​​model, users can receive specific suggestions.

[0637] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0638] Step 1:

[0639] The user takes a photo of the room with a smart device and uploads the image data to the system. This image data becomes the input. The server receives this image data and uses image analysis to extract spatial information such as the room's size, shape, and furniture arrangement. The extracted spatial information becomes the output.

[0640] Step 2:

[0641] The terminal allows the user to input their interior design preferences and budget through an interface. This input becomes the input data. The terminal then sends this information to a server, where it is recorded as the user's request. The recorded information becomes the output.

[0642] Step 3:

[0643] Users register their emotional state with the system using voice input or camera on their smart devices to collect emotional information. This audio / video data becomes the input. The server analyzes the data using emotion analysis tools to recognize the degree of stress or joy. The analyzed emotional information becomes the output.

[0644] Step 4:

[0645] The server integrates spatial information obtained from image analysis, user preferences and budget information, and emotional information obtained from emotion analysis, and uses these as input data for a generative AI model. The server then uses this generative AI model to generate an optimal furniture arrangement plan. This plan generation process takes into account suggestions based on the user's emotional state. The output is the generated furniture arrangement plan.

[0646] Step 5:

[0647] The server uses an inventory synchronization method to obtain inventory information in real time. Inventory information retrieved from the market database is the input, and a list of available items is output. Based on this information, products suitable for the generated furniture placement plan are selected.

[0648] Step 6:

[0649] The server uses the generated furniture layout plan and selected product information to create visualization data using an augmented reality generation system. This visualization data is sent to the terminal. The transmitted visualization data becomes the output.

[0650] Step 7:

[0651] The device uses augmented reality (AR) technology to display a suggested furniture arrangement on the user's device, based on visualization data sent from the server. The user can then review this display and get an idea of ​​how the furniture would actually look in their room. The output is the AR display presented to the user.

[0652] (Application Example 2)

[0653] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0654] Interior design and item placement suggestions made without considering the user's emotional state may not necessarily address the user's current mood or emotional needs. This presents a challenge in creating optimal spatial designs for users. Furthermore, in actual retail shopping experiences, users may find it difficult to visualize the suggested interior design in real-time, making purchase decisions challenging.

[0655] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0656] In this invention, the server includes an image analysis means for extracting spatial information from image data input by the user, an emotion analysis means for analyzing user-inputted preferences, budget information, and the user's emotional state and acquiring the data, a generation means for proposing the optimal item arrangement based on these, and an augmented reality generation means for visualizing the proposed item arrangement in the real space. This makes it possible to propose interiors and items that are best suited to the user's emotional state in real time, making the purchasing experience more intuitive and supporting the realization of a comfortable living space.

[0657] "Image analysis means" refers to a technology that extracts spatial information such as the size and shape of a space and the current furniture arrangement from image data input by the user.

[0658] "Input method" refers to the interface used by users to input their interior design preferences and budget information.

[0659] "Emotion analysis methods" refer to technologies that analyze a user's facial expressions and voice data to obtain data on their current emotional state.

[0660] The "generation method" is a method for proposing the optimal arrangement of items based on extracted spatial information, user preferences and budget information, and emotional state information.

[0661] "Augmented reality generation means" is a technology that visually reflects a proposed arrangement of objects in real space.

[0662] "Inventory synchronization methods" refer to technologies that use real-time inventory information to verify whether proposed items are actually available for purchase.

[0663] A "data transmission means" is a mechanism for transmitting data necessary to visualize the proposed item arrangement on the user's device.

[0664] The embodiments of the present invention will now be described. The system of the present invention consists of a smart device used by the user, an analysis engine on a server, and augmented reality technology for displaying the proposed results.

[0665] The user takes a picture of the room using a smartphone or other smart device. This image data is uploaded from the device to a server. On the server, spatial information such as the size, shape, and furniture arrangement of the space is extracted using OpenCV or TensorFlow as image analysis tools.

[0666] Next, the user inputs their interior design preferences and budget information through the device's interface. This information is also sent to the server and recorded as the user's request. Furthermore, the user uses the camera function to capture their facial expressions, and emotional data such as stress and relaxation levels are registered on the server using emotion analysis tools such as Microsoft Azure Face API and Google Cloud AI.

[0667] The server integrates this data and uses a generative AI model (e.g., GPT-4) to generate a plan that suggests the optimal placement of items, taking into account the user's emotions. This plan includes furniture with colors and designs that suit the user's space, and also uses Firebase Realtime Database for real-time inventory checks.

[0668] The proposed item placements are visualized on the user's device using augmented reality generation tools such as ARKit and ARCore. This allows users to intuitively understand what furniture and decorative items they are considering purchasing would look like when actually placed in a room.

[0669] For example, imagine a user seeking relaxation amidst a busy daily life who wants to redecorate their room to alleviate fatigue. In this case, the system suggests calming colors and furniture with relaxing effects, and shows how to arrange these items in the actual space. Through this process, it becomes possible to propose a living space that is optimal for the user's emotions.

[0670] Examples of prompts include: "Generate an interior design plan to suggest a relaxing living room for a stressed customer. The room is 15m², and you should select furniture in calming colors."

[0671] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0672] Step 1:

[0673] The user takes a picture of the room using a smart device. The image data taken by the user is uploaded to the server. The server receives this image data as input and uses OpenCV and TensorFlow to extract information such as the size and shape of the space and the arrangement of furniture. In this way, the physical characteristics of the room are provided to the server as digital data.

[0674] Step 2:

[0675] Users input their interior design preferences and budget information using a smart device interface. This input information is sent to a server. The server stores this user information in a database and uses it as basic data for generating designs. Here, the user's desired design style and budget range are clarified.

[0676] Step 3:

[0677] Users capture their facial expressions using their smart device's camera and register their emotional state. This image data is analyzed by emotion analysis tools such as Microsoft Azure Face API and Google Cloud AI, and emotional information such as stress and joy is analyzed on a server. As a result, the user's emotional state is obtained as numerical data and used as input for a generative AI model.

[0678] Step 4:

[0679] The server inputs acquired spatial information, user preferences, budget, and emotional state into a generating AI model (e.g., GPT-4) to generate an optimal item placement plan. The generating AI model uses prompts to devise the most suitable furniture and design options for the user. In this step, natural color tones and layouts are generated, and an interior design tailored to the user's needs is proposed.

[0680] Step 5:

[0681] The server retrieves inventory information in real time via Firebase Realtime Database and filters the generated placement plan to include only items that are actually available for purchase. This enables realistic product recommendations based on inventory levels.

[0682] Step 6:

[0683] The generated item placement suggestions are visualized on the user's smart device using augmented reality generation tools such as ARKit and ARCore. Augmented reality technology allows users to virtually check the furniture placement in their home and make purchase decisions based on visual feedback. In this step, users can more easily grasp the suggested interior design intuitively.

[0684] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0685] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0686] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0687] [Fourth Embodiment]

[0688] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0689] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0690] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0691] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0692] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0693] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0694] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0695] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0696] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0697] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0698] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0699] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0700] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0701] This invention is a system that assists users in optimizing the interior of their living spaces, and in particular, by using image analysis technology and augmented reality technology, it enables users to select and arrange items that are ideal for them.

[0702] First, the user takes photos of their room or the entire living space using a smart device. These image data are immediately sent to a server via the network. The server analyzes the received images and extracts spatial information such as the size and shape of the room and the arrangement of furniture.

[0703] Next, the terminal provides an interface for the user to enter information about their preferences and budget, and the user enters their requests into this form. This information is sent to the server, where the interior style, colors, and functionality requirements that meet the user's requests are recorded.

[0704] Based on collected spatial information and user requests, the server uses the latest generative AI technology to generate suggested furniture and appliance placements. This process ensures that items harmonize with the user's desired interior style.

[0705] Furthermore, the suggested items are checked for inventory in real time by the server, and this information is reflected in the generated layout. This allows users to immediately see which items are available for order.

[0706] The device visualizes suggested layouts provided by the server using augmented reality, helping users to see them in their actual space. Through this AR display, users can intuitively understand how the selected furniture will be placed in their own room.

[0707] For example, if a user requests a new living room layout, the system analyzes the spatial dimensions from a photo of the room and proposes a furniture arrangement based on a modern, white-based style. This proposal is displayed in real-time using augmented reality (AR) on the user's device, and the user can purchase their preferred layout directly.

[0708] Thus, the present invention is a system that streamlines the conventional furniture selection process and provides users with a seamless and intuitive means of choosing interior furnishings.

[0709] The following describes the processing flow.

[0710] Step 1:

[0711] The user takes a picture of the room with a smart device and uploads the image to the application.

[0712] Step 2:

[0713] The terminal receives image data and initiates communication to send it to the server.

[0714] Step 3:

[0715] The server analyzes the received image data to extract spatial information, such as the room's size, shape, the location of windows and doors, and the arrangement of existing furniture.

[0716] Step 4:

[0717] The device displays a form for the user to input their preferred style, budget, color and material choices, etc.

[0718] Step 5:

[0719] The user enters their preferred information into a form, and the device sends that information to the server.

[0720] Step 6:

[0721] The server combines spatial information obtained from image analysis with user-inputted preference information and uses a generative AI to generate an optimal furniture and appliance placement plan.

[0722] Step 7:

[0723] Based on the proposed deployment plan, the server retrieves and updates inventory information in real time to check if the relevant products are available for purchase.

[0724] Step 8:

[0725] The server generates visualization data for augmented reality and sends it to the terminal, allowing the user to actually see the suggested furniture and appliance placement.

[0726] Step 9:

[0727] The device uses augmented reality technology to display suggested furniture and appliance placement images on the user's device.

[0728] Step 10:

[0729] The user reviews the displayed suggestions, selects a product they like, and proceeds with the purchase.

[0730] Step 11:

[0731] The server processes the purchase of the selected items and confirms the order in conjunction with the flea market app.

[0732] Step 12:

[0733] The server notifies the user that the purchase is complete and provides shipping information for the product.

[0734] (Example 1)

[0735] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0736] In traditional interior design selection processes, it was difficult to intuitively visualize the user's ideal spatial design and to select and arrange products that reflected real-time inventory status. Furthermore, it was not possible to quickly generate appropriate suggestions tailored to the user's preferences.

[0737] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0738] In this invention, the server includes processing means for analyzing and extracting spatial information from image data captured by the user, acquisition means for receiving information on the user's preferences and budget, and generation processing means for generating an optimal product arrangement based on the extracted spatial information and the user's preferences and budget. This enables the user to intuitively visualize their desired interior and makes it possible to select and arrange products realistically while reflecting inventory status.

[0739] A "user" is the entity that provides input information and image data and receives interior design suggestions.

[0740] "Information about space" refers to data such as room dimensions, shape, and furniture arrangement obtained through the analysis of image data.

[0741] A "processing means" is an element that has the function of analyzing and extracting spatial information from image data.

[0742] "Means of acquisition" refers to elements that have the function of receiving and recording information about the user's selected preferences and budget.

[0743] A "generation processing means" is an element that has the function of generating the optimal product arrangement based on spatial information and the user's preferences and budget.

[0744] "Augmented reality display means" refers to a function that uses technology to visualize a proposed product arrangement by overlaying it onto real space.

[0745] "Inventory information" refers to real-time data on how readily available a product is.

[0746] A "data transmission function" is an element that has the function of sending data necessary for visualization to the user terminal.

[0747] This invention provides a system for optimizing the interior of a user's living space, specifically utilizing image analysis technology and augmented reality technology. To implement the invention, a server, terminal, and user each need to play specific roles. Details are described below.

[0748] First, the user takes photos of their room or living space using a suitable device such as a smartphone or tablet. This device has a dedicated application installed and is equipped with the function to send the captured image data to a server. The data is sent to the server via a network connection, along with the user's specified preferences and budget information.

[0749] Next, the server analyzes the received image data. Specifically, it uses software libraries such as OpenCV and TensorFlow to perform image processing and object recognition. This extracts spatial information such as room dimensions, shape, and furniture arrangement. The extracted information is stored as a digital model on the server and used in subsequent generation processes. This generation process uses generative AI such as the OpenAI GPT model to propose an optimal interior plan based on the user's prompts.

[0750] The device then uses augmented reality (AR) technology to visualize the proposed interior layout. AR software such as ARKit (iOS) and ARCore (Android) enables users to experience placing virtual furniture within a real-world space through the device. This allows users to intuitively evaluate the suitability of the proposed interior.

[0751] For example, if a user is considering renovating their living room, the system performs image analysis and suggests a furniture arrangement based on a modern interior style with a white color scheme. This suggestion is displayed in AR on the device, allowing the user to view the visualized environment and easily proceed to the ordering process if they like it.

[0752] Examples of prompts for efficiently managing the above process include, "Please propose an interior design plan with a modern style and a white color scheme."

[0753] This system allows users to significantly streamline the interior design process, making it easier to select and realize their ideal living environment.

[0754] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0755] Step 1:

[0756] The user takes pictures of their room or living space using a smart device. These captured images become the input for processing. The user selects images through a dedicated application and sends them to the server via the network. The output of this step is the image data sent to the server.

[0757] Step 2:

[0758] The server analyzes the received image data and extracts spatial information. Specifically, the server uses image analysis libraries such as OpenCV to process the dimensions of furniture and rooms within the image and extracts the room structure as digital data. The input for this step is the image data sent by the user, and the output is the extracted spatial information.

[0759] Step 3:

[0760] The terminal prompts the user to input information about their preferences and budget through the user interface. The user enters their desired style and budget into a form on the screen, and this information is sent to the server. The input in this step is the information entered into the user interface, and the output is the recorded user preferences and budget information.

[0761] Step 4:

[0762] The server generates an optimal interior plan using a generative AI model based on extracted spatial information and user input. The generative AI, such as a GPT model, calculates the appropriate furniture placement for the room according to the user's prompts. The input for this step is spatial information and user input, and the output is the generated interior plan.

[0763] Step 5:

[0764] The server uses the generated interior plan to check inventory information. This process verifies whether the suggested furniture and appliances are immediately available for order and reflects the inventory status in the interior plan. The input for this step is the generated interior plan, and the output is the plan with the inventory status reflected.

[0765] Step 6:

[0766] The terminal provides the user with a proposed plan received from the server using augmented reality (AR) technology. Specifically, it uses ARKit or ARCore to display a virtual interior when the user views the room through the device. The input for this step is an interior plan that reflects inventory status, and the output is the visualization result using augmented reality.

[0767] Step 7:

[0768] The user reviews the presented augmented reality layout and proceeds with the purchase if they like it. The user selects options on the terminal and confirms the order for the selected furniture and appliances. The input for this step is the augmented reality visualization, and the output is the confirmed order.

[0769] (Application Example 1)

[0770] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0771] In recent years, there has been a growing need for users to select interior items that suit their personal preferences when optimizing their living spaces. However, conventional systems make it difficult for users to visualize how items will look when actually placed in a home, and the lack of real-time inventory information and in-store support makes the purchase decision-making process cumbersome. Against this backdrop, there is a need for technology that improves the user experience and efficiently supports the selection of optimal items.

[0772] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0773] In this invention, the server includes: an image analysis means for extracting spatial information from image data entered by the user; an input means for receiving preference and budget information entered by the user; a generation means for proposing an optimal arrangement of items based on the extracted spatial information and the user's preference and budget information; an augmented reality generation means for visualizing the proposed arrangement of items in the real world; an information acquisition means using a visual device for acquiring and analyzing real-world items; a function means using a device for visualizing and presenting the proposed arrangement of items; and a data linkage means for acquiring and presenting corresponding item information in real time. This enables the user to intuitively experience the arrangement of interiors in their living space and to efficiently and quickly select and purchase appropriate furniture.

[0774] "Image analysis means" refers to technology for analyzing spatial shape and arrangement information from image data input by the user.

[0775] An "input method" is a function that provides an interface for receiving user requests such as preferences and budget.

[0776] The "generation method" is a technology that proposes the optimal arrangement of items based on extracted spatial information and user requests.

[0777] "Augmented reality generation means" refers to a technology for displaying the proposed arrangement of objects superimposed onto real space.

[0778] "Information acquisition means" refers to a function that uses visual devices to acquire and analyze information about real-world objects.

[0779] A "functional means" is an operating device for visualizing and presenting the arrangement of proposed items to the user.

[0780] "Data linkage means" refers to technology for acquiring real-time information about necessary items and presenting it appropriately to the user.

[0781] The system of the present invention is designed to optimize the interior of a user's living space and is realized using image analysis technology and augmented reality technology. Specific embodiments for carrying out the present invention are shown below.

[0782] First, the user uses a smart device to take an image of the entire living space and sends the data to the server. At this stage, the server uses "image analysis tools" to analyze the received image data and extract information such as the size and shape of the space and the arrangement of existing furniture. This process uses Python and image processing libraries such as OpenCV.

[0783] Next, the user inputs information about their preferences and budget through the terminal's interface. This information is sent to the server, which receives it as "input." The server then uses "generation tools" to generate the optimal arrangement of items that matches the style the user desires. For example, generation AI technology may be used for this generation.

[0784] The generated proposals are visualized on the device via an "augmented reality generation mechanism." This allows users to experience the proposed arrangement superimposed on real space. Specifically, Unity or ARKit could be used for augmented reality display.

[0785] Furthermore, the system can acquire and analyze item information using visual devices within a physical store through its "information acquisition means." This supports the user's purchasing experience while in a physical store. The "functional means" work to present the proposed item arrangement to the user, and one of the functions used is providing an interface on smart glasses.

[0786] The system also uses a "data linkage mechanism" to acquire inventory information for suggested items in real time and present it to the user. This allows the user to seamlessly proceed through the process from selecting interior items to purchasing them.

[0787] As a concrete example, consider a scenario where a user is looking for the perfect sofa for their new living room. By inputting the user's preferences and living space information through smart glasses, it's possible to use a "generative AI model" to suggest sofa placements that match the style. An example of a prompt in this case would be, "The user is looking for a sofa that suits a modern, white-themed living room."

[0788] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0789] Step 1:

[0790] The user takes images of their living space using a smart device and sends the image data to a server. The input is the image data taken by the user, and the output is the image data sent to the server. This image data includes an overall view of the room and existing furniture.

[0791] Step 2:

[0792] The server processes the received image data using "image analysis tools" to extract spatial information such as the dimensions and shape of the space and the location of existing furniture. The input is image data sent to the server. In this step, data analysis is performed using image processing libraries such as Python or OpenCV, and the output is in the form of spatial information.

[0793] Step 3:

[0794] The user uses the terminal's interface to input information about their preferences and budget. This input, containing data about the user's personal preferences and budget, is sent from the terminal to the server, which receives it as input. The output is the user's request data recorded on the server.

[0795] Step 4:

[0796] The server, based on the spatial information obtained in the previous step and the user's request data, utilizes the "generation method" to propose the optimal item placement. The input consists of spatial information and the user's requests. The generation AI model processes this data and outputs an item placement that suits the user's preferences.

[0797] Step 5:

[0798] The generated proposals are visualized on the device using an "augmented reality generation method." The device receives object placement data output from the server and allows the user to see them overlaid on a real-world room. The output is the object placement displayed in augmented reality. Here, visualization in real space is performed using Unity or ARKit.

[0799] Step 6:

[0800] When a user visits a physical store, information about the actual items is acquired and analyzed using a visual device and an "information acquisition means." The input is information about the actual items acquired through the visual device. The output is specific item data presented to the user.

[0801] Step 7:

[0802] The suggested items are linked to a "data linkage system" which retrieves relevant data, including inventory information, in real time. This information is then fed back to the user, who can then make a purchase decision based on it. The input is information about the suggested items, and the output is real-time item information, including inventory.

[0803] Step 8:

[0804] Users review the item placement visualized in augmented reality, and once they've decided to purchase, they order the selected items through the terminal. The input is the information of the final selected items, and the output is the purchase procedure information. This process supports a seamless purchasing experience.

[0805] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0806] This invention is a system that provides interior design suggestions while taking into account the user's emotional state. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, and spatial information such as the size and shape of the room and the current furniture arrangement is extracted by an image analysis means.

[0807] Next, the terminal displays an interface for the user to input their interior design preferences and budget, and the user enters this information. This data is sent to the server and recorded as the user's request.

[0808] A key feature of this system is its use of an emotion engine to understand the user's emotional state. When a user registers their facial expressions with the system via voice input or camera, the emotion engine analyzes the data and recognizes the user's emotions, such as their level of stress or joy. This emotional information, along with other request information entered by the user, is provided to the generation mechanism.

[0809] The server integrates this information and uses AI to generate an optimal furniture and appliance placement plan. During this process, suggestions are made to enhance comfort and relaxation, tailored to the user's emotional state. Furthermore, the server retrieves real-time inventory information and selects items that are available for purchase.

[0810] Subsequently, the server-generated suggestions are visualized using augmented reality technology, and the data is sent to the terminal for display on the user's device. This AR display allows the user to intuitively understand what the selected furniture would look like when actually placed in the room.

[0811] For example, if a user is leading a busy life and seeks a relaxing effect from their living room decor, the system will recognize the user's calm emotional state and suggest furniture with relaxing colors and arrangements. In this way, the present invention aims to improve the user's living environment by providing interior design suggestions that take the user's emotions into consideration.

[0812] The following describes the processing flow.

[0813] Step 1:

[0814] Users take photos of their rooms with their smart devices and upload the image data by opening the application.

[0815] Step 2:

[0816] After the terminal receives the image data, it initiates communication to send it to the server.

[0817] Step 3:

[0818] The server analyzes the received image data and extracts spatial information, including the room's size, shape, and current furniture arrangement.

[0819] Step 4:

[0820] The device displays a form for the user to enter their interior design preferences, desired budget, and other requests.

[0821] Step 5:

[0822] The user enters information such as their preferences and budget into a form on their device and sends it to the server.

[0823] Step 6:

[0824] The device uses the user's camera and microphone to capture the user's face and voice, and sends that data to the emotion engine.

[0825] Step 7:

[0826] The emotion engine analyzes the user's emotional state from their facial expressions and voice, recognizing, for example, their stress level and satisfaction level.

[0827] Step 8:

[0828] The server integrates spatial information, user request information, and emotional information from the emotion engine, and uses generative AI to formulate the optimal furniture and appliance placement plan.

[0829] Step 9:

[0830] The server checks inventory information in real time via an online database and reflects available items in the final proposal.

[0831] Step 10:

[0832] The server generates the proposed furniture and appliance placement plan as augmented reality data and sends it to the terminal.

[0833] Step 11:

[0834] Based on the augmented reality data transmitted by the device, the suggested furniture arrangement is displayed in AR on the user's device for the user to confirm.

[0835] Step 12:

[0836] Users view AR displays, select furniture and appliances based on their preferred suggestions, and proceed with the purchase process.

[0837] Step 13:

[0838] The server processes the purchase of the selected items and confirms the order with the partnered online sales platform.

[0839] Step 14:

[0840] The server sends a purchase completion notification to the user and provides information such as shipping details for the product.

[0841] (Example 2)

[0842] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0843] Traditional interior design proposal systems could suggest item placements based on user preferences and budget, but they lacked the ability to consider the user's emotional state. This made it difficult to create truly comfortable spaces that users desired. Therefore, it is necessary to provide interior design proposals that are more tailored to individual needs, incorporating information that includes the user's emotional state.

[0844] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0845] In this invention, the server includes an image analysis means for extracting spatial information from image data entered by the user, an input means for receiving preference and budget information entered by the user, and an emotion analysis means for analyzing the emotional state and providing the results to the generation means. This makes it possible to propose the optimal arrangement of items according to the user's emotional state and to realize a comfortable interior space tailored to individual needs.

[0846] "Image analysis means" refers to technical means for extracting spatial information from image data input by a user.

[0847] An "input method" refers to a means of providing an interface for users to input their interior design preferences and budget information into the system.

[0848] A "generation method" is a means for proposing the optimal arrangement of items based on extracted spatial information and user preferences and budget information.

[0849] "Emotional analysis means" refers to a technical means that analyzes the user's emotional state and provides the results to the generation means.

[0850] An "augmented reality generation method" is a technical means for visualizing a proposed arrangement of objects in real space.

[0851] "Inventory synchronization means" refers to technical means that enable the acquisition of inventory information in real time.

[0852] "Data transmission means" refers to means for transmitting data necessary for the augmented reality generation means to visualize the proposed item arrangement on the user device.

[0853] This system proposes furniture arrangements that take into account the user's emotional state in order to create a comfortable interior space. First, the user takes a picture of the room using a smart device and uploads the image data to the system. This image data is sent to a server, which uses image analysis to extract spatial information such as the size and shape of the room and the current furniture arrangement.

[0854] Next, the terminal displays an interface to the user, prompting them to input their interior design preferences and budget. The user enters this information through the terminal's interface, and the terminal sends this data to a server to record the user's preferences.

[0855] Regarding the emotion analysis method, the user inputs their emotional state into the system using voice input or a camera on their smart device. The server uses the emotion analysis method to analyze the voice and facial expression data to recognize the user's emotional state. This extracts emotional information such as the degree of stress or joy.

[0856] The server uses collected spatial information, user preferences and budget, and emotional information to generate an optimal furniture placement plan using a generative AI model. This generative AI model is based on, for example, a common generative AI framework. The generated placement plan is optimized for the user's emotional state and incorporates color schemes and designs aimed at promoting relaxation.

[0857] Furthermore, the server acquires real-time market inventory information through inventory synchronization and selects items that are available for purchase. The server uses augmented reality generation to visualize the proposed interior layout using AR technology and transmits the data to the terminal. Through the terminal, the user can obtain a visual image of how the furniture would look when placed in an actual room.

[0858] For example, if a user leads a busy life and desires relaxation in their living room, the system analyzes the user's emotional state as "easy to relax." Based on this, it suggests furniture with natural colors and soft arrangements that are expected to have a relaxing effect. By inputting a prompt such as "Please suggest living room interiors that will help the user relax" into the AI ​​model, users can receive specific suggestions.

[0859] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0860] Step 1:

[0861] The user takes a photo of the room with a smart device and uploads the image data to the system. This image data becomes the input. The server receives this image data and uses image analysis to extract spatial information such as the room's size, shape, and furniture arrangement. The extracted spatial information becomes the output.

[0862] Step 2:

[0863] The terminal allows the user to input their interior design preferences and budget through an interface. This input becomes the input data. The terminal then sends this information to a server, where it is recorded as the user's request. The recorded information becomes the output.

[0864] Step 3:

[0865] Users register their emotional state with the system using voice input or camera on their smart devices to collect emotional information. This audio / video data becomes the input. The server analyzes the data using emotion analysis tools to recognize the degree of stress or joy. The analyzed emotional information becomes the output.

[0866] Step 4:

[0867] The server integrates spatial information obtained from image analysis, user preferences and budget information, and emotional information obtained from emotion analysis, and uses these as input data for a generative AI model. The server then uses this generative AI model to generate an optimal furniture arrangement plan. This plan generation process takes into account suggestions based on the user's emotional state. The output is the generated furniture arrangement plan.

[0868] Step 5:

[0869] The server uses an inventory synchronization method to obtain inventory information in real time. Inventory information retrieved from the market database is the input, and a list of available items is output. Based on this information, products suitable for the generated furniture layout plan are selected.

[0870] Step 6:

[0871] The server uses the generated furniture layout plan and selected product information to create visualization data using an augmented reality generation system. This visualization data is sent to the terminal. The transmitted visualization data becomes the output.

[0872] Step 7:

[0873] The device uses augmented reality (AR) technology to display a suggested furniture arrangement on the user's device, based on visualization data sent from the server. The user can then review this display and get an idea of ​​how the furniture would actually look in their room. The output is the AR display presented to the user.

[0874] (Application Example 2)

[0875] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0876] Interior design and item placement suggestions made without considering the user's emotional state may not necessarily address the user's current mood or emotional needs. This presents a challenge in creating optimal spatial designs for users. Furthermore, in actual retail shopping experiences, users may find it difficult to visualize the suggested interior design in real-time, making purchase decisions challenging.

[0877] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0878] In this invention, the server includes an image analysis means for extracting spatial information from image data input by the user, an emotion analysis means for analyzing user-inputted preferences, budget information, and the user's emotional state and acquiring the data, a generation means for proposing the optimal item arrangement based on these, and an augmented reality generation means for visualizing the proposed item arrangement in the real space. This makes it possible to propose interiors and items that are best suited to the user's emotional state in real time, making the purchasing experience more intuitive and supporting the realization of a comfortable living space.

[0879] "Image analysis means" refers to a technology that extracts spatial information such as the size and shape of a space and the current furniture arrangement from image data input by the user.

[0880] "Input method" refers to the interface used by users to input their interior design preferences and budget information.

[0881] "Emotion analysis methods" refer to technologies that analyze a user's facial expressions and voice data to obtain data on their current emotional state.

[0882] The "generation method" is a method for proposing the optimal arrangement of items based on extracted spatial information, user preferences and budget information, and emotional state information.

[0883] "Augmented reality generation means" is a technology that visually reflects a proposed arrangement of objects in real space.

[0884] "Inventory synchronization methods" refer to technologies that use real-time inventory information to verify whether proposed items are actually available for purchase.

[0885] A "data transmission means" is a mechanism for transmitting data necessary to visualize the proposed item arrangement on the user's device.

[0886] The embodiments of the present invention will now be described. The system of the present invention consists of a smart device used by the user, an analysis engine on a server, and augmented reality technology for displaying the proposed results.

[0887] The user takes a picture of the room using a smartphone or other smart device. This image data is uploaded from the device to a server. On the server, spatial information such as the size, shape, and furniture arrangement of the space is extracted using OpenCV or TensorFlow as image analysis tools.

[0888] Next, the user inputs their interior design preferences and budget information through the device's interface. This information is also sent to the server and recorded as the user's request. Furthermore, the user uses the camera function to capture their facial expressions, and emotional data such as stress and relaxation levels are registered on the server using emotion analysis tools such as Microsoft Azure Face API and Google Cloud AI.

[0889] The server integrates this data and uses a generative AI model (e.g., GPT-4) to generate a plan that suggests the optimal placement of items, taking into account the user's emotions. This plan includes furniture with colors and designs that suit the user's space, and also uses Firebase Realtime Database for real-time inventory checks.

[0890] The proposed item placements are visualized on the user's device using augmented reality generation tools such as ARKit and ARCore. This allows users to intuitively understand what furniture and decorative items they are considering purchasing would look like when actually placed in a room.

[0891] For example, imagine a user seeking relaxation amidst a busy daily life who wants to redecorate their room to alleviate fatigue. In this case, the system suggests calming colors and furniture with relaxing effects, and shows how to arrange these items in the actual space. Through this process, it becomes possible to propose a living space that is optimal for the user's emotions.

[0892] Examples of prompts include: "Generate an interior design plan to suggest a relaxing living room for a stressed customer. The room is 15m², and you should select furniture in calming colors."

[0893] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0894] Step 1:

[0895] The user takes a picture of the room using a smart device. The image data taken by the user is uploaded to the server. The server receives this image data as input and uses OpenCV and TensorFlow to extract information such as the size and shape of the space and the arrangement of furniture. In this way, the physical characteristics of the room are provided to the server as digital data.

[0896] Step 2:

[0897] Users input their interior design preferences and budget information using a smart device interface. This input information is sent to a server. The server stores this user information in a database and uses it as basic data for generating designs. Here, the user's desired design style and budget range are clarified.

[0898] Step 3:

[0899] Users capture their facial expressions using their smart device's camera and register their emotional state. This image data is analyzed by emotion analysis tools such as Microsoft Azure Face API and Google Cloud AI, and emotional information such as stress and joy is analyzed on a server. As a result, the user's emotional state is obtained as numerical data and used as input for a generative AI model.

[0900] Step 4:

[0901] The server inputs acquired spatial information, user preferences, budget, and emotional state into a generating AI model (e.g., GPT-4) to generate an optimal item placement plan. The generating AI model uses prompts to devise the most suitable furniture and design options for the user. In this step, natural color tones and layouts are generated, and an interior design tailored to the user's needs is proposed.

[0902] Step 5:

[0903] The server retrieves inventory information in real time via Firebase Realtime Database and filters the generated placement plan to include only items that are actually available for purchase. This enables realistic product recommendations based on inventory levels.

[0904] Step 6:

[0905] The generated item placement suggestions are visualized on the user's smart device using augmented reality generation tools such as ARKit and ARCore. Augmented reality technology allows users to virtually check the furniture placement in their home and make purchase decisions based on visual feedback. In this step, users can more easily grasp the suggested interior design intuitively.

[0906] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0907] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0908] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0909] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0910] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0911] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0912] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0913] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0914] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0915] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0916] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0917] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0918] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0919] 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.

[0920] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0921] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0922] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0923] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0924] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0925] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0926] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0927] The following is further disclosed regarding the embodiments described above.

[0928] (Claim 1)

[0929] An image analysis means for extracting spatial information from image data input by the user,

[0930] An input method for receiving user-entered preferences and budget information,

[0931] A generation means that proposes the optimal arrangement of items based on the extracted spatial information and user preferences and budget information,

[0932] An augmented reality generation means that visualizes the proposed arrangement of items in real space,

[0933] A system that includes this.

[0934] (Claim 2)

[0935] The system according to claim 1, wherein the generation means for proposing the optimal item includes an inventory linkage means for acquiring inventory information in real time.

[0936] (Claim 3)

[0937] The system according to claim 1, wherein the augmented reality generation means includes data transmission means for transmitting data necessary for visualizing a proposed arrangement of items on a user device.

[0938] "Example 1"

[0939] (Claim 1)

[0940] A processing means for analyzing and extracting spatial information from image data captured by the user,

[0941] A means of receiving information about the user's selected preferences and budget,

[0942] A generation processing means that generates an optimal product arrangement based on the extracted spatial information and the user's preferences and budget,

[0943] An augmented reality display means for realizing the proposed product arrangement,

[0944] A system that includes this.

[0945] (Claim 2)

[0946] The system according to claim 1, further comprising a function to acquire product inventory information in real time and reflect it in the proposed content of the generation processing means.

[0947] (Claim 3)

[0948] The system according to claim 1, comprising a data transmission function that transmits data necessary for visualizing the proposed product arrangement on a user terminal.

[0949] "Application Example 1"

[0950] (Claim 1)

[0951] An image analysis means for extracting spatial information from image data input by the user,

[0952] An input method for receiving user-entered preferences and budget information,

[0953] A generation means that proposes the optimal arrangement of items based on the extracted spatial information and user preferences and budget information,

[0954] An augmented reality generation means that visualizes the proposed arrangement of items in real space,

[0955] Information acquisition means using a visual device that acquires and analyzes real-world objects,

[0956] A functional means using a device that visualizes and presents the arrangement of proposed items,

[0957] A data linkage means that acquires and presents corresponding item information in real time,

[0958] A system that includes this.

[0959] (Claim 2)

[0960] The system according to claim 1, wherein the generation means for proposing the optimal item includes an inventory linkage means for acquiring inventory information in real time.

[0961] (Claim 3)

[0962] The system according to claim 1, wherein the augmented reality generation means includes data transmission means for transmitting data necessary for visualizing a proposed arrangement of items on a user device.

[0963] "Example 2 of combining an emotion engine"

[0964] (Claim 1)

[0965] An image analysis means for extracting spatial information from image data input by the user,

[0966] An input method for receiving user-entered preferences and budget information,

[0967] A generation means that proposes the optimal arrangement of items based on the extracted spatial information and user preferences and budget information,

[0968] An emotion analysis means that analyzes an emotional state and provides the results to a generation means,

[0969] An augmented reality generation means that visualizes the proposed arrangement of items in real space,

[0970] A system that includes this.

[0971] (Claim 2)

[0972] The system according to claim 1, wherein the generation means for proposing the optimal item includes an inventory linkage means for acquiring inventory information in real time.

[0973] (Claim 3)

[0974] The system according to claim 1, wherein the augmented reality generation means includes data transmission means for transmitting data necessary for visualizing a proposed arrangement of items on a user device.

[0975] "Application example 2 of combining emotional engines"

[0976] (Claim 1)

[0977] An image analysis means for extracting spatial information from image data input by the user,

[0978] An input method for receiving user-entered preferences and budget information,

[0979] A means of sentiment analysis that analyzes the user's emotional state and acquires it as data,

[0980] A generation means that proposes the optimal arrangement of items based on the extracted spatial information, user preferences, budget information, and emotional state information,

[0981] An augmented reality generation means that visualizes the proposed arrangement of items in real space,

[0982] A system that includes this.

[0983] (Claim 2)

[0984] The system according to claim 1, wherein the generation means for proposing the optimal item includes an inventory linkage means for acquiring inventory information in real time.

[0985] (Claim 3)

[0986] The system according to claim 1, wherein the augmented reality generation means includes data transmission means for transmitting data necessary for visualizing a proposed arrangement of items on a user device. [Explanation of Symbols]

[0987] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An image analysis means for extracting spatial information from image data input by the user, An input method for receiving user-entered preferences and budget information, A generation means that proposes the optimal arrangement of items based on the extracted spatial information and user preferences and budget information, An augmented reality generation means that visualizes the proposed arrangement of items in real space, A system that includes this.

2. The system according to claim 1, wherein the generation means for proposing the optimal item includes an inventory linkage means for acquiring inventory information in real time.

3. The system according to claim 1, wherein the augmented reality generation means includes data transmission means for transmitting data necessary for visualizing the proposed arrangement of items on a user device.

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