system

Abstract

Provide a system. 【Solution means】 Means for receiving spatial image data and request data from a user, Means for analyzing the received spatial image data and request data to generate proposed data, Means for generating three-dimensional space display data using the proposed data, Means for transmitting the three-dimensional space display data to the user's display device, Means for simulating article placement based on the three-dimensional space display data on the user's display device, Means for allowing the user to view the articles selected by the user in a virtual arrangement via the display device, Means for automatically performing an electronic transaction procedure to facilitate the purchase of articles in the store A system including.

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 performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In order to realize the interior desired by the user within a limited space and budget, it is important to select appropriate furniture and arrange it properly. However, there are problems such as design inconsistencies when combining furniture from different manufacturers, insufficient visual images of furniture arrangements, and difficulties in arranging for quick purchase and installation. There is a need to develop a system that can solve these problems efficiently and effectively and realize the optimal interior for the user.

Means for Solving the Problems

[0005] This invention provides a system that receives and analyzes image data and request data of a room provided by a user, generates appropriate furniture suggestion data, and further generates three-dimensional spatial display data, which is then transmitted to the user's terminal. This allows the user to perform real-time furniture placement simulations on their terminal and select from multiple furniture placement plans. Furthermore, it enables the system to automatically handle furniture purchase procedures and delivery and installation arrangements based on the selected plan, thereby reducing the burden on the user.

[0006] "User" refers to an individual or group that uses this system and is the entity responsible for arranging and selecting interior elements.

[0007] "Image data" refers to visual information provided by the user that shows the current state of the room, and specifically consists of photographs and image files.

[0008] "Request data" refers to information about the user's desired interior style, budget, and intended use, and serves as a condition for furniture selection.

[0009] "Means of receiving" refers to the function or process by which this system acquires data from an external source.

[0010] "Means of analysis" refers to the process of extracting necessary information from received data and understanding its content.

[0011] "Suggested data" refers to data generated based on analyzed information, including furniture and layout suggestions that meet user needs.

[0012] "Three-dimensional spatial display data" refers to data used to visually reproduce the placement of furniture in the user's real-world space, and includes information such as 3D models.

[0013] "Means of transmission" refers to the function or process for transferring the generated data to the user's device.

[0014] "Methods for simulating furniture placement" refer to processes that allow users to virtually place furniture in a real-world space on their terminal and visually confirm the placement. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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.

[0019] 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.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is a system that allows users to achieve their ideal interior layout with minimal effort. The system consists of a user, a terminal, and a server.

[0037] First, the user takes image data of their room using a device and inputs data such as their desired interior style and budget. The device then sends this data to the server, and the process begins.

[0038] The server analyzes the received image data to understand the physical characteristics of the room, such as its size and shape. Furthermore, it uses the request data to identify the interior style desired by the user and generates suggestion data. This suggestion data includes furniture types and arrangement ideas that match the user's requirements.

[0039] Next, the server creates three-dimensional spatial display data based on the generated proposal data. This data is designed to allow the user to visually confirm the image of the furniture being placed in real space with accurate size and position. At this stage, the server generates multiple furniture combination options for the user to select from.

[0040] The terminal receives 3D spatial display data transmitted from the server and uses a dedicated application to simulate furniture placement. Using the terminal, users can utilize AR or VR technology to virtually display furniture in their real room and check its placement and design in real time. As a result, they can select the optimal interior plan from multiple proposals.

[0041] For example, if a user desires a natural style for an 8-tatami mat room, the server might suggest wood-grain tables and sofas. By performing an AR simulation on their device, the user can instantly check how the placement and design match. If the user is satisfied with the simulation results, they can confirm the purchase, and the server will automatically handle the furniture delivery and installation procedures.

[0042] This process allows users to efficiently select the optimal interior design within limited space and budget, and to make effective use of the space.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user uses a device to take pictures of their room and inputs data such as their desired interior style and budget. The device then prepares to send this data to the server.

[0046] Step 2:

[0047] The terminal sends the created data package (image data and request data) to the server. Once the server receives this data, the next process begins.

[0048] Step 3:

[0049] The server analyzes image data to determine the room dimensions and layout. It also uses the requested data to confirm the user's preferred interior style and budget.

[0050] Step 4:

[0051] The server generates multiple furniture placement plans based on the analysis results. It selects furniture that meets the criteria from the database and compiles it as suggested data.

[0052] Step 5:

[0053] The server uses the proposed data to generate three-dimensional spatial display data. This data includes information for AR or VR to simulate furniture placement.

[0054] Step 6:

[0055] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and prepares for the next processing step.

[0056] Step 7:

[0057] The device uses the received three-dimensional spatial display data to start a furniture placement simulation using AR or VR. Through this simulation, the user can virtually place furniture in the room and visually confirm its placement.

[0058] Step 8:

[0059] The user reviews the simulation results and selects the plan they deem best from among the proposed furniture arrangement options. Once the user confirms their selection, the process proceeds.

[0060] Step 9:

[0061] The server generates information for purchasing furniture based on the user's selected interior design plan. It also automatically arranges furniture delivery and installation, enabling rapid service delivery.

[0062] (Example 1)

[0063] 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."

[0064] In modern society, efficiently and effectively planning the interior layout of living spaces is a time-consuming and laborious task for many people. In particular, achieving an ideal layout within limited space and budget is a significant challenge. This invention aims to solve these problems and provide a system that allows users to easily arrange the optimal interior for their own space.

[0065] 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.

[0066] In this invention, the server includes means for receiving image information and request information from the user, means for analyzing the received image information and extracting spatial features, and means for utilizing a generation AI model based on the request information to generate suggestion information. This enables the user to automatically and intuitively plan complex interior layouts.

[0067] A "user" is a person who uses the system and is the entity that provides information regarding interior design.

[0068] "Image information" refers to visual data of the living space provided by the user, which is used to analyze the dimensions and characteristics of the room.

[0069] "Request information" refers to data about the user's desired interior style and budget, and serves as the basis for proposing interior layouts.

[0070] A "generative AI model" is an artificial intelligence technology that generates interior layout suggestions from given information, and is an algorithm that derives the optimal solution based on the user's requests.

[0071] "Suggested information" refers to data on interior layout plans and options that match the user's requests, generated by a generative AI model.

[0072] "Three-dimensional display information" refers to visually three-dimensional data created based on proposed information, and serves as the foundation for users to confirm interior layouts in a virtual space.

[0073] An "information processing terminal" is an electronic device used by users to operate a system, and is a device used for capturing image information and confirming virtualized interior layouts.

[0074] "Arrangement of items" refers to the act or plan of specifically placing furniture and decorative items as interior furnishings within a space.

[0075] "Acquisition and Transfer Procedures" refers to all necessary procedures for delivering the selected items to the user, encompassing the entire process from purchase to delivery.

[0076] This invention is a system for efficiently planning the interior layout of a living space. The system consists of a user, a terminal, and a server. The user first uses the terminal to capture images of their living space and inputs desired information such as their preferred interior style and budget. A dedicated application is installed on the terminal, and data is transmitted to the server via this application.

[0077] The server uses image recognition software (e.g., OpenCV) to analyze the received image information and identify physical features such as spatial dimensions and shape. Next, the server uses a generative AI model (e.g., a large-scale language model) to generate prompts based on the user's request information and identify an appropriate interior style. An example of such a prompt is: "Please suggest a natural style interior layout suitable for an 8-tatami mat room. The budget is 200,000 yen, and the preferred furniture is a wood-grain table and sofa."

[0078] Based on this information, the server generates suggestion data, including furniture types and placement options that meet the user's requirements. The server then uses 3D modeling software (e.g., Blender or Unity) to visualize this suggestion data as a 3D display. This display data is then sent to the user's device.

[0079] The terminal displays the received 3D information using a dedicated application, allowing users to virtually try out interior layouts within a living space using AR or VR technology. During this process, users can review the layout options in real time and select the optimal interior plan.

[0080] This platform allows users to effectively select interior design elements while taking space and budget constraints into consideration, maximizing the appeal of their living spaces.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] Users use a device to photograph their living space and input the image information into a dedicated application on the device. At this time, users also input information such as their desired interior style and budget. The input data is initially processed by the application and prepared for transmission to the server. The output consists of the image information and request information ready for transmission to the server.

[0084] Step 2:

[0085] The server analyzes the image information received from the terminal. Specifically, it uses image recognition software such as OpenCV to extract physical features such as spatial dimensions and shape from the image. This data processing allows for an understanding of the characteristics of the user's living space. The analysis results are output as spatial feature data that can be used to identify interior styles.

[0086] Step 3:

[0087] The server utilizes a generative AI model to generate prompt messages based on the request information. These are instructions to determine the optimal interior style based on the user's preferences. This model processes the input request information as text and outputs it as prompt messages.

[0088] Step 4:

[0089] The server uses a generative AI model to generate suggestion information based on the prompt text and spatial feature data. This suggestion information includes furniture types and placement suggestions based on an interior style that matches the user's requests. The generated suggestion information is then prepared as input for the next step.

[0090] Step 5:

[0091] The server uses the proposed information to generate 3D display information. Using 3D modeling software such as Blender or Unity, it creates data that visualizes the proposed furniture and arrangement in 3D space. This 3D display information is output and sent to the terminal.

[0092] Step 6:

[0093] The terminal displays 3D information received from the server within a dedicated application, providing an environment where users can virtually experience interior layouts using AR or VR technology. Users can use the virtually displayed interior to check and compare layout options in real time and select the optimal plan. The output is the interior plan selected by the user, and this data is passed on to subsequent processing.

[0094] (Application Example 1)

[0095] 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."

[0096] The goal is to efficiently simulate interior layouts and provide users with a means to visually confirm them before purchase. Furthermore, utilizing virtual simulations is required to improve the in-store experience while simplifying the purchase process. Traditional methods carry the risk of users realizing after purchase that the design doesn't suit them; therefore, it's necessary to prevent this and facilitate smooth purchasing.

[0097] 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.

[0098] In this invention, the server includes means for receiving spatial image data and request data from a user, means for analyzing the received spatial image data and request data to generate proposal data, and means for generating three-dimensional spatial display data using the proposal data. This enables the user to virtually confirm the arrangement of items and automatically perform electronic transaction procedures.

[0099] "Spatial image data" refers to image data containing visual information about a user's room or space.

[0100] "Request data" refers to data that includes information about the user's desired interior style and budget.

[0101] "Proposal data" refers to data generated based on analyzed spatial image data and request data, used for item placement plans and product selection.

[0102] "Three-dimensional spatial display data" refers to data generated based on proposed data that allows users to virtually visualize the placement of items.

[0103] A "display device" is an electronic device used by users to view three-dimensional spatial display data, and includes smartphones and tablets.

[0104] A "virtual arrangement" is a digital display that virtually reproduces the arrangement of objects in a real-world space.

[0105] "Electronic transaction procedures" refer to the process of automatically carrying out procedures related to the purchase of goods electronically.

[0106] "Transportation procedures" refer to the automated process of arranging and managing the delivery of items selected by the user to a specified location.

[0107] The system that realizes this application allows users to efficiently simulate interior layouts and facilitate the purchase process. First, the user uses a display device such as a smartphone or tablet to input spatial image data of the room and request data. This request data includes the desired interior style and budget.

[0108] Next, the user's terminal sends the input data to the server. The server analyzes the received spatial image data to understand the physical characteristics of the room. Based on this, the server generates appropriate suggestion data while considering the requested data. This process utilizes the image analysis library OpenCV and the machine learning framework TENSORFLOW®.

[0109] Subsequently, the server generates three-dimensional spatial display data using the proposed data and sends it to the user's display device. This data visualizes the placement of objects in a virtual reality space using AR technologies such as Unity and ARCore. The user can virtually check the placement of objects in the real space and select them from the virtual array.

[0110] Furthermore, the purchase process for the items selected by the user is automated through electronic transaction procedures handled by the server. This process utilizes electronic payment APIs (such as the Stripe API). The selected items are then delivered to the user's specified location via appropriate transportation procedures.

[0111] For example, if a user requests a Scandinavian-style interior and inputs spatial image data, the server will suggest furniture primarily made of wood. The user can virtually check the placement via AR display and make a purchase decision on the spot. An example of a prompt to the generating AI model would be, "Analyze the photo of the room and suggest a natural-style furniture arrangement."

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

[0113] Step 1:

[0114] Users take spatial image data of their room using their smartphone or tablet and input their desired interior style and budget. This data is prepared and optimized for transmission by the device.

[0115] Step 2:

[0116] The terminal sends prepared spatial image data and request data to the server. The input includes image files and text data, which the server receives. Here, the data format is checked, and appropriate processing preparations are made.

[0117] Step 3:

[0118] The server uses tools such as OpenCV and TensorFlow to analyze the received spatial image data. It recognizes the physical features and layout of the room from the input data and obtains the analysis results as output. The analysis results include information on the dimensions and shape of the room.

[0119] Step 4:

[0120] The server generates proposal data based on the analysis results, taking the requested data into consideration. This process utilizes a generation AI model to assemble interior layout plans that suit the user's style. The output includes specific furniture types and placement suggestions.

[0121] Step 5:

[0122] The server uses Unity or ARCore to convert the proposed data into 3D spatial display data. The proposed data is used as input, and the output is data in a format that can be displayed in AR.

[0123] Step 6:

[0124] Three-dimensional spatial display data is transmitted to the terminal, and the user can see the virtual placement of objects in the actual space via the display device. Here, the terminal uses AR technology to display the data, resulting in a visual experience where reality and virtuality overlap.

[0125] Step 7:

[0126] The user uses a display device to view and select items in a virtual environment. In this step, they confirm their selected layout using intuitive touch controls or voice input.

[0127] Step 8:

[0128] The server automates the purchase process via an electronic payment API based on the user's selections. It uses the selected data as input and generates purchase confirmation and payment completion data as output.

[0129] Step 9:

[0130] For the selected items, the server arranges transportation procedures and manages delivery to the user's specified location. It processes logistics information and manages the transportation status.

[0131] 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.

[0132] This invention further enhances the user experience by combining an emotion engine with a system that allows users to efficiently select and arrange their ideal interior. The system consists of a user, a terminal, a server, and an emotion engine.

[0133] The user takes a picture of their room through the device and inputs data such as their desired interior style and budget. The device incorporates sensors to detect the user's emotions, such as facial expressions and tone of voice, and this data is sent to the emotion engine in real time.

[0134] The server analyzes the received image data and request data, but also refers to the user's emotional data analyzed by the emotion engine. This makes it possible to determine which interior styles the user has a positive emotional response to.

[0135] Based on sentiment data, the server generates multiple suggestion data tailored to the user's preferences. In this process, the sentiment engine particularly considers the styles and colors that the user finds appealing and adjusts the suggestions accordingly. Furthermore, it generates three-dimensional spatial display data to prepare for the user to visually confirm.

[0136] The device receives the generated 3D spatial display data and simulates furniture placement. Through this simulation, users can virtually place furniture in a room and try out different arrangements in real time. This makes it possible for even first-time users to select the optimal interior plan that resonates with their feelings.

[0137] For example, if a user prefers vibrant colors, the emotion engine analyzes this emotion data and prioritizes suggesting interior plans that include the user's preferred colors and designs. The user can review the selected plan and, if they like it, proceed to purchase. The server automatically arranges the purchase, delivery, and installation of the selected furniture.

[0138] This embodiment of the invention enables the provision of personalized interior plans based on the user's emotions and prompt service, thereby increasing user satisfaction.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] The user uses the device to take pictures of their room and inputs data such as their desired interior style and budget. The device has sensors that capture the user's facial expressions and voice, recording them in real time as emotional data.

[0142] Step 2:

[0143] The device sends image data of the room it photographed, along with request data and emotion data, to the server. This prepares the server to begin processing the data.

[0144] Step 3:

[0145] The server first analyzes image data to understand the physical characteristics of the room (dimensions, shape). It also uses the request data to confirm the user's desired interior style and budget.

[0146] Step 4:

[0147] The server uses an emotion engine to analyze the user's emotional data. The results of this analysis measure which styles the user responds favorably to.

[0148] Step 5:

[0149] By integrating emotion data and request data, the server generates multiple furniture placement plans. In this process, it reflects the results of the emotion engine and creates suggestion data that takes into account the styles and colors that the user is judged to prefer.

[0150] Step 6:

[0151] The server generates three-dimensional spatial display data based on the proposed data. This data includes 3D models of furniture and suggested placements, which can be visually reviewed by the user.

[0152] Step 7:

[0153] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and starts the simulation for the next stage.

[0154] Step 8:

[0155] The device uses the received 3D spatial display data to perform furniture placement simulations using an AR or VR application. Users can view this in real time and try out different plans.

[0156] Step 9:

[0157] Based on the information obtained from the simulation, the user selects their favorite furniture arrangement plan. Once the selection is complete, they proceed to the next step: purchasing the furniture.

[0158] Step 10:

[0159] The server handles the purchase of furniture and arranges automated delivery and installation based on the user's selected plan. This completes the process, allowing the user to receive their goods quickly.

[0160] (Example 2)

[0161] 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".

[0162] Traditional interior design selection systems have the drawback of failing to adequately reflect users' latent preferences because they offer uniform suggestions without considering the user's feelings. Furthermore, the process from furniture purchase to installation is cumbersome, placing a significant burden on users.

[0163] 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.

[0164] In this invention, the server includes means for receiving image data, request data, and emotion data from the user; means for analyzing the received data and generating proposal data using a generative AI model; and means for generating three-dimensional spatial display data and transmitting it to the user terminal. This enables personalized interior design proposals based on the user's emotions and allows for efficient processing from purchase to installation.

[0165] "Image data" refers to digital data containing visual information of a space captured by a user.

[0166] "Request data" refers to information that users have entered regarding their preferences and requirements for interior design style and budget.

[0167] "Emotional data" refers to information that quantifies or categorizes the psychological state of a user, inferred from their facial expressions, tone of voice, and other factors.

[0168] A "generative AI model" is an algorithm or program that analyzes multiple input data and generates optimal suggested data accordingly.

[0169] "Suggestion data" refers to information that, based on the server's analysis results, presents users with candidate interior designs and layouts.

[0170] "Three-dimensional spatial display data" refers to digital data in a three-dimensional format used to visually represent the layout of an interior space virtually.

[0171] An "information processing device" is a device used by users, such as a computer or smart device, for inputting, processing, and outputting data.

[0172] "Simulation" is a process that allows you to try out actual interior layouts in a virtual environment.

[0173] "Purchase, delivery, and installation procedures" refers to the entire process from arranging for the user to receive the interior items they have selected, to their delivery to the location specified by the user, and their proper placement.

[0174] This invention is a system that helps users efficiently select and arrange their ideal interior, thereby improving their experience. The system's components include a user, a terminal, a server, and an emotion engine.

[0175] Users utilize devices such as smartphones and tablets. They take pictures of their rooms with the device's camera and input their interior design preferences, particularly style and budget, using the device's input function. Furthermore, the devices incorporate facial recognition sensors and microphones, which collect the user's facial expressions and voice tone in real time and transmit this data to the emotion engine.

[0176] The server receives and analyzes image data and request data sent by the user. Image recognition software and natural language processing technology are used for the analysis. The received emotional data is analyzed by an emotion engine, and the user's emotional state is quantified. Based on this data, the server uses a generative AI model to generate interior design suggestions tailored to the user's preferences.

[0177] The proposed data is formed as multiple candidates, particularly emphasizing designs and colors that are likely to evoke positive emotions in users. Based on this data, the server creates three-dimensional spatial display data and sends it to the user's terminal.

[0178] The terminal receives three-dimensional spatial display data using a dedicated application, allowing users to experience virtual interior layouts. A touch-enabled interface allows users to visually simulate furniture placement and interactively change its appearance.

[0179] For example, if a user prefers a bright and lively interior style, the emotion sensor detects this preference and transmits it to the server. The server then uses a generative AI model to prioritize suggestions based on this information. As a result, the user can easily find a plan they like and proceed with the purchase.

[0180] An example of a prompt would be, "I'm looking for a bright and lively style to choose for the interior of my room. Can you use sentiment analysis to give me specific interior design suggestions that suit my preferences?"

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] The user uses a device to take image data of the room and inputs data such as interior style and budget. The device has a facial recognition sensor and microphone, which captures emotional data from the user's facial expressions and tone of voice. This data (image data, request data, and emotional data) is transmitted to the server in real time. The input data becomes a valuable source of information about the user's preferences and emotional state, and is necessary for the next processing step.

[0184] Step 2:

[0185] The server analyzes the received image data and request data, and uses image recognition software to understand the characteristics of the space. In addition, it uses natural language processing technology to understand the request data. Emotional data is quantified by an emotion engine, and the user's emotional state is determined. Based on the input data (images, requests, emotions), an AI model is created to generate optimal interior design proposals, producing multiple proposal data. The output consists of multiple interior design proposals tailored to the user's preferences.

[0186] Step 3:

[0187] The server creates three-dimensional spatial display data based on the generated proposal data. This data reflects designs and colors that will attract the user's attention and is prepared in a visually verifiable format. For three-dimensional display, rendering is performed in real time and transmitted to the user's terminal. The output data is three-dimensional spatial display data for visualizing the proposed interior in space.

[0188] Step 4:

[0189] The terminal loads received 3D spatial display data into a dedicated application, providing the user with an interactive interior simulation. Users can try out virtual furniture placements using touch controls. The interface is intuitive, allowing users to experiment with different arrangements according to their preferences. Input is 3D display data from the server, and output is the furniture placement in the virtual space that the user can view.

[0190] Step 5:

[0191] Once a user selects an interior design plan, the information is sent back to the server via their device. The server then automates the process from purchasing the furniture to delivery and installation based on the selected plan. This is done using an e-commerce system, with all necessary processing handled in the backend. The final output is the confirmation of the order and delivery schedule for the furniture items selected by the user.

[0192] (Application Example 2)

[0193] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0194] Conventional interior design systems often lacked optimal suggestions that took user preferences into account, resulting in decreased user satisfaction. Furthermore, it was difficult for users to make interior design choices that reflected their emotions, leading to a less-than-smooth purchase process.

[0195] 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.

[0196] In this invention, the server includes means for receiving image data and request data from the user, means for analyzing the received image data and request data to generate suggestion data, and means for acquiring the user's emotional data, analyzing the emotional data, and adjusting suggestions based on the user's preferences. This makes it possible to propose personalized interior plans based on the user's emotions.

[0197] "Image data" refers to digital information that visually records the user's environment and serves as the basis for the system to analyze the layout of the interior.

[0198] "Request data" refers to information that describes individual requirements, such as the interior style and budget desired by the user.

[0199] "Suggestion data" refers to candidate information for interior plans and items generated based on the user's image data, request data, and emotion data.

[0200] "Three-dimensional spatial display data" refers to three-dimensional visual information used to virtually simulate the placement of interior items on a user's device.

[0201] "Emotional data" refers to information used to analyze a user's feelings and sensations, and is data obtained based on changes in facial expressions and tone of voice.

[0202] "User preferences" refer to the personal tastes and preferences that users have for specific interior styles, colors, and designs.

[0203] A "virtual environment" is a digital space that mimics and reproduces the real world, allowing users to simulate actual placement of interior items.

[0204] To implement this invention, the user first takes a picture of their room using a device such as a smartphone or smart glasses. The captured image data and the user's request data are sent from the device to a server. The server receives this data and analyzes the image data and request data in order to suggest an interior layout.

[0205] The server uses an emotion engine to acquire and analyze the user's emotional data. Smartphones and smart glasses utilize sensors to determine emotions, generating emotional data while monitoring the user's facial expressions and tone of voice. Based on the analyzed emotional data, the server generates suggested data tailored to the user's preferred interior style.

[0206] Next, the server generates three-dimensional spatial display data based on the adjusted proposal data and sends it to the user's terminal. The terminal can then use the received three-dimensional spatial display data to simulate furniture placement in a virtual space.

[0207] For example, if a user prefers vibrant colors, the emotion engine will take this into account and suggest an interior design plan that emphasizes those colors and designs. The user can review the suggestion and, if they like it, proceed with the purchase. The server will then automatically handle the process from purchase to delivery and installation.

[0208] An example of a prompt message is as follows: "Based on the user's emotional data and photos of their interior style, please suggest interior items that this user might like. Also, please perform a 3D simulation to show how those items would fit into the room."

[0209] The system of the present invention enables interior design selection based on the user's emotions, thereby significantly improving the user experience.

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The user takes a picture of the room using the device and inputs request data into the interface. During this process, the device's built-in camera and microphone are used to acquire emotional data from facial expressions and tone of voice. This process prepares image data, request data, and emotional data.

[0213] Step 2:

[0214] The device sends captured image data, request data, and acquired emotion data to the server. Based on this input data, the server begins analyzing the data using image processing algorithms and natural language processing. The analysis uses data processing services such as Google Cloud Platform to extract basic elements that match the user's requests and preferences.

[0215] Step 3:

[0216] The server generates suggestion data based on the received data. Here, the emotion engine refers to the user's emotion data and prioritizes selecting designs and colors that the user has responded positively to. Using an AI model, the system provides suggestions that reflect the user's preferences, utilizing prompt text.

[0217] Step 4:

[0218] The server uses the generated proposal data to create three-dimensional spatial display data. This display data is designed to allow the user to visually confirm the proposed interior items. At this stage, a digital simulation is performed using a 3D graphics engine.

[0219] Step 5:

[0220] The server sends three-dimensional spatial display data to the user's terminal. The terminal receives this data and provides the user with the ability to try out interior placement in a virtual space. This allows the user to visually confirm how the furniture will actually be placed.

[0221] Step 6:

[0222] When a user selects a specific interior design plan, that selection is sent from the terminal to the server. The server can then automatically arrange the purchase, delivery, and installation processes for the selected items. In this step, the system integrates with transaction management and logistics systems to prepare for the completion of service delivery.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] [Second Embodiment]

[0227] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0228] 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.

[0229] 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).

[0230] 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.

[0231] 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.

[0232] 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).

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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".

[0239] This invention is a system that allows users to achieve their ideal interior layout with minimal effort. The system consists of a user, a terminal, and a server.

[0240] First, the user takes image data of their room using a device and inputs data such as their desired interior style and budget. The device then sends this data to the server, and the process begins.

[0241] The server analyzes the received image data to understand the physical characteristics of the room, such as its size and shape. Furthermore, it uses the request data to identify the interior style desired by the user and generates suggestion data. This suggestion data includes furniture types and arrangement ideas that match the user's requirements.

[0242] Next, the server creates three-dimensional spatial display data based on the generated proposal data. This data is designed to allow the user to visually confirm the image of the furniture being placed in real space with accurate size and position. At this stage, the server generates multiple furniture combination options for the user to select from.

[0243] The terminal receives 3D spatial display data transmitted from the server and uses a dedicated application to simulate furniture placement. Using the terminal, users can utilize AR or VR technology to virtually display furniture in their real room and check its placement and design in real time. As a result, they can select the optimal interior plan from multiple proposals.

[0244] For example, if a user desires a natural style for an 8-tatami mat room, the server might suggest wood-grain tables and sofas. By performing an AR simulation on their device, the user can instantly check how the placement and design match. If the user is satisfied with the simulation results, they can confirm the purchase, and the server will automatically handle the furniture delivery and installation procedures.

[0245] This process allows users to efficiently select the optimal interior design within limited space and budget, and to make effective use of the space.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user uses a device to take pictures of their room and inputs data such as their desired interior style and budget. The device then prepares to send this data to the server.

[0249] Step 2:

[0250] The terminal sends the created data package (image data and request data) to the server. Once the server receives this data, the next process begins.

[0251] Step 3:

[0252] The server analyzes image data to determine the room dimensions and layout. It also uses the requested data to confirm the user's preferred interior style and budget.

[0253] Step 4:

[0254] The server generates multiple furniture placement plans based on the analysis results. It selects furniture that meets the criteria from the database and compiles it as suggested data.

[0255] Step 5:

[0256] The server uses the proposed data to generate three-dimensional spatial display data. This data includes information for AR or VR to simulate furniture placement.

[0257] Step 6:

[0258] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and prepares for the next processing step.

[0259] Step 7:

[0260] The device uses the received three-dimensional spatial display data to start a furniture placement simulation using AR or VR. Through this simulation, the user can virtually place furniture in the room and visually confirm its placement.

[0261] Step 8:

[0262] The user reviews the simulation results and selects the plan they deem best from among the proposed furniture arrangement options. Once the user confirms their selection, the process proceeds.

[0263] Step 9:

[0264] The server generates information for purchasing furniture based on the user's selected interior design plan. It also automatically arranges furniture delivery and installation, enabling rapid service delivery.

[0265] (Example 1)

[0266] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0267] In modern society, efficiently and effectively planning the interior layout of living spaces is a time-consuming and laborious task for many people. In particular, achieving an ideal layout within limited space and budget is a significant challenge. This invention aims to solve these problems and provide a system that allows users to easily arrange the optimal interior for their own space.

[0268] 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.

[0269] In this invention, the server includes means for receiving image information and request information from the user, means for analyzing the received image information and extracting spatial features, and means for utilizing a generation AI model based on the request information to generate suggestion information. This enables the user to automatically and intuitively plan complex interior layouts.

[0270] A "user" is a person who uses the system and is the entity that provides information regarding interior design.

[0271] "Image information" refers to visual data of the living space provided by the user, which is used to analyze the dimensions and characteristics of the room.

[0272] "Request information" refers to data about the user's desired interior style and budget, and serves as the basis for proposing interior layouts.

[0273] A "generative AI model" is an artificial intelligence technology that generates interior layout suggestions from given information, and is an algorithm that derives the optimal solution based on the user's requests.

[0274] "Suggested information" refers to data on interior layout plans and options that match the user's requests, generated by a generative AI model.

[0275] "Three-dimensional display information" refers to visually three-dimensional data created based on proposed information, and serves as the foundation for users to confirm interior layouts in a virtual space.

[0276] An "information processing terminal" is an electronic device used by users to operate a system, and is a device used for capturing image information and confirming virtualized interior layouts.

[0277] "Arrangement of items" refers to the act or plan of specifically placing furniture and decorative items as interior furnishings within a space.

[0278] "Acquisition and Transfer Procedures" refers to all necessary procedures for delivering the selected items to the user, encompassing the entire process from purchase to delivery.

[0279] This invention is a system for efficiently planning the interior layout of a living space. The system consists of a user, a terminal, and a server. The user first uses the terminal to capture images of their living space and inputs desired information such as their preferred interior style and budget. A dedicated application is installed on the terminal, and data is transmitted to the server via this application.

[0280] The server uses image recognition software (e.g., OpenCV) to analyze the received image information and identify physical features such as spatial dimensions and shape. Next, the server uses a generative AI model (e.g., a large-scale language model) to generate prompts based on the user's request information and identify an appropriate interior style. An example of such a prompt is: "Please suggest a natural style interior layout suitable for an 8-tatami mat room. The budget is 200,000 yen, and the preferred furniture is a wood-grain table and sofa."

[0281] Based on this information, the server generates suggestion data, including furniture types and placement options that meet the user's requirements. The server then uses 3D modeling software (e.g., Blender or Unity) to visualize this suggestion data as a 3D display. This display data is then sent to the user's device.

[0282] The terminal displays the received 3D information using a dedicated application, allowing users to virtually try out interior layouts within a living space using AR or VR technology. During this process, users can review the layout options in real time and select the optimal interior plan.

[0283] With this platform, users can effectively select interior designs considering space and budget constraints, maximizing the appeal of their living spaces.

[0284] The flow of the specific process in Example 1 will be described using FIG. 11.

[0285] Step 1:

[0286] The user uses the terminal to take pictures of their living space and inputs the image information into a dedicated application in the terminal. At this time, the user also inputs desired information such as the interior style and budget they hope for. The input data is initially processed by the application and prepared to be sent to the server. The output is the image information and desired information for sending to the server.

[0287] Step 2:

[0288] The server analyzes the image information received from the terminal. Specifically, using image recognition software such as OpenCV, physical features such as the dimensions and shape of the space are extracted from the image. Through this data processing, the characteristics of the user's living space can be grasped. The analysis result is output as space feature data that can be used to identify the interior style.

[0289] Step 3:

[0290] The server utilizes the generative AI model to generate a prompt sentence based on the desired information. This is an instruction sentence for determining the optimal interior style based on the user's wishes. This model processes the input desired information as text and outputs it as a prompt sentence.

[0291] Step 4:

[0292] The server uses a generative AI model to generate suggestion information based on the prompt text and spatial feature data. This suggestion information includes furniture types and placement suggestions based on an interior style that matches the user's requests. The generated suggestion information is then prepared as input for the next step.

[0293] Step 5:

[0294] The server uses the proposed information to generate 3D display information. Using 3D modeling software such as Blender or Unity, it creates data that visualizes the proposed furniture and arrangement in 3D space. This 3D display information is output and sent to the terminal.

[0295] Step 6:

[0296] The terminal displays 3D information received from the server within a dedicated application, providing an environment where users can virtually experience interior layouts using AR or VR technology. Users can use the virtually displayed interior to check and compare layout options in real time and select the optimal plan. The output is the interior plan selected by the user, and this data is passed on to subsequent processing.

[0297] (Application Example 1)

[0298] 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."

[0299] The goal is to efficiently simulate interior layouts and provide users with a means to visually confirm them before purchase. Furthermore, utilizing virtual simulations is required to improve the in-store experience while simplifying the purchase process. Traditional methods carry the risk of users realizing after purchase that the design doesn't suit them; therefore, it's necessary to prevent this and facilitate smooth purchasing.

[0300] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means.

[0301] In this invention, the server includes means for receiving spatial image data and request data from a user, means for analyzing the received spatial image data and request data to generate proposal data, and means for generating three-dimensional space display data using the proposal data. As a result, the user can virtually confirm the arrangement of articles and automatically perform an electronic transaction procedure.

[0302] "Spatial image data" is data in image format including visual information of the user's room or space.

[0303] "Request data" is data including information on the interior style or budget desired by the user.

[0304] "Proposal data" is data for article arrangement plans and product selection generated based on the analyzed spatial image data and request data.

[0305] "Three-dimensional space display data" is data generated based on the proposal data, which enables the user to virtually visualize the arrangement of articles.

[0306] "Display device" is an electronic device for the user to check the three-dimensional space display data, including smartphones, tablets, etc.

[0307] "Virtual arrangement" is a digital display that virtually reproduces the arrangement of articles in the real space.

[0308] "Electronic transaction procedure" is a process that automatically and electronically performs procedures related to the purchase of articles.

[0309] "Transportation procedure" is a process that automates the arrangements and management for delivering the articles selected by the user to the designated location.

[0310] The system that realizes this application allows users to efficiently simulate interior layouts and facilitate the purchase process. First, the user uses a display device such as a smartphone or tablet to input spatial image data of the room and request data. This request data includes the desired interior style and budget.

[0311] Next, the user's device sends the input data to the server. The server analyzes the received spatial image data to understand the physical characteristics of the room. Based on this, the server generates appropriate suggestion data while considering the requested data. This process utilizes image analysis libraries such as OpenCV and machine learning frameworks such as TensorFlow.

[0312] Subsequently, the server generates three-dimensional spatial display data using the proposed data and sends it to the user's display device. This data visualizes the placement of objects in a virtual reality space using AR technologies such as Unity and ARCore. The user can virtually check the placement of objects in the real space and select them from the virtual array.

[0313] Furthermore, the purchase process for the items selected by the user is automated through electronic transaction procedures handled by the server. This process utilizes electronic payment APIs (such as the Stripe API). The selected items are then delivered to the user's specified location via appropriate transportation procedures.

[0314] For example, if a user requests a Scandinavian-style interior and inputs spatial image data, the server will suggest furniture primarily made of wood. The user can virtually check the placement via AR display and make a purchase decision on the spot. An example of a prompt to the generating AI model would be, "Analyze the photo of the room and suggest a natural-style furniture arrangement."

[0315] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0316] Step 1:

[0317] Users take spatial image data of their room using their smartphone or tablet and input their desired interior style and budget. This data is prepared and optimized for transmission by the device.

[0318] Step 2:

[0319] The terminal sends prepared spatial image data and request data to the server. The input includes image files and text data, which the server receives. Here, the data format is checked, and appropriate processing preparations are made.

[0320] Step 3:

[0321] The server uses tools such as OpenCV and TensorFlow to analyze the received spatial image data. It recognizes the physical features and layout of the room from the input data and obtains the analysis results as output. The analysis results include information on the dimensions and shape of the room.

[0322] Step 4:

[0323] The server generates proposal data based on the analysis results, taking the requested data into consideration. This process utilizes a generation AI model to assemble interior layout plans that suit the user's style. The output includes specific furniture types and placement suggestions.

[0324] Step 5:

[0325] The server uses Unity or ARCore to convert the proposed data into 3D spatial display data. The proposed data is used as input, and the output is data in a format that can be displayed in AR.

[0326] Step 6:

[0327] Three-dimensional spatial display data is transmitted to the terminal, and the user can see the virtual placement of objects in the actual space via the display device. Here, the terminal uses AR technology to display the data, resulting in a visual experience where reality and virtuality overlap.

[0328] Step 7:

[0329] The user uses a display device to view and select items in a virtual environment. In this step, they confirm their selected layout using intuitive touch controls or voice input.

[0330] Step 8:

[0331] The server automates the purchase process via an electronic payment API based on the user's selections. It uses the selected data as input and generates purchase confirmation and payment completion data as output.

[0332] Step 9:

[0333] For the selected items, the server arranges transportation procedures and manages delivery to the user's specified location. It processes logistics information and manages the transportation status.

[0334] 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.

[0335] This invention further enhances the user experience by combining an emotion engine with a system that allows users to efficiently select and arrange their ideal interior. The system consists of a user, a terminal, a server, and an emotion engine.

[0336] The user takes a picture of their room through the device and inputs data such as their desired interior style and budget. The device incorporates sensors to detect the user's emotions, such as facial expressions and tone of voice, and this data is sent to the emotion engine in real time.

[0337] The server analyzes the received image data and request data, but also refers to the user's emotional data analyzed by the emotion engine. This makes it possible to determine which interior styles the user has a positive emotional response to.

[0338] Based on sentiment data, the server generates multiple suggestion data tailored to the user's preferences. In this process, the sentiment engine particularly considers the styles and colors that the user finds appealing and adjusts the suggestions accordingly. Furthermore, it generates three-dimensional spatial display data to prepare for the user to visually confirm.

[0339] The device receives the generated 3D spatial display data and simulates furniture placement. Through this simulation, users can virtually place furniture in a room and try out different arrangements in real time. This makes it possible for even first-time users to select the optimal interior plan that resonates with their feelings.

[0340] For example, if a user prefers vibrant colors, the emotion engine analyzes this emotion data and prioritizes suggesting interior plans that include the user's preferred colors and designs. The user can review the selected plan and, if they like it, proceed to purchase. The server automatically arranges the purchase, delivery, and installation of the selected furniture.

[0341] This embodiment of the invention enables the provision of personalized interior plans based on the user's emotions and prompt service, thereby increasing user satisfaction.

[0342] The following describes the processing flow.

[0343] Step 1:

[0344] The user uses the device to take pictures of their room and inputs data such as their desired interior style and budget. The device has sensors that capture the user's facial expressions and voice, recording them in real time as emotional data.

[0345] Step 2:

[0346] The device sends image data of the room it photographed, along with request data and emotion data, to the server. This prepares the server to begin processing the data.

[0347] Step 3:

[0348] The server first analyzes image data to understand the physical characteristics of the room (dimensions, shape). It also uses the request data to confirm the user's desired interior style and budget.

[0349] Step 4:

[0350] The server uses an emotion engine to analyze the user's emotional data. The results of this analysis measure which styles the user responds favorably to.

[0351] Step 5:

[0352] By integrating emotion data and request data, the server generates multiple furniture placement plans. In this process, it reflects the results of the emotion engine and creates suggestion data that takes into account the styles and colors that the user is judged to prefer.

[0353] Step 6:

[0354] The server generates three-dimensional spatial display data based on the proposed data. This data includes 3D models of furniture and suggested placements, which can be visually reviewed by the user.

[0355] Step 7:

[0356] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and starts the simulation for the next stage.

[0357] Step 8:

[0358] The device uses the received 3D spatial display data to perform furniture placement simulations using an AR or VR application. Users can view this in real time and try out different plans.

[0359] Step 9:

[0360] Based on the information obtained from the simulation, the user selects their favorite furniture arrangement plan. Once the selection is complete, they proceed to the next step: purchasing the furniture.

[0361] Step 10:

[0362] The server handles the purchase of furniture and arranges automated delivery and installation based on the user's selected plan. This completes the process, allowing the user to receive their goods quickly.

[0363] (Example 2)

[0364] 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".

[0365] Traditional interior design selection systems have the drawback of failing to adequately reflect users' latent preferences because they offer uniform suggestions without considering the user's feelings. Furthermore, the process from furniture purchase to installation is cumbersome, placing a significant burden on users.

[0366] 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.

[0367] In this invention, the server includes means for receiving image data, request data, and emotion data from the user; means for analyzing the received data and generating proposal data using a generative AI model; and means for generating three-dimensional spatial display data and transmitting it to the user terminal. This enables personalized interior design proposals based on the user's emotions and allows for efficient processing from purchase to installation.

[0368] "Image data" refers to digital data containing visual information of a space captured by a user.

[0369] "Request data" refers to information that users have entered regarding their preferences and requirements for interior design style and budget.

[0370] "Emotional data" refers to information that quantifies or categorizes the psychological state of a user, inferred from their facial expressions, tone of voice, and other factors.

[0371] A "generative AI model" is an algorithm or program that analyzes multiple input data and generates optimal suggested data accordingly.

[0372] "Suggestion data" refers to information that, based on the server's analysis results, presents users with candidate interior designs and layouts.

[0373] "Three-dimensional spatial display data" refers to digital data in a three-dimensional format used to visually represent the layout of an interior space virtually.

[0374] An "information processing device" is a device used by users, such as a computer or smart device, for inputting, processing, and outputting data.

[0375] "Simulation" is a process that allows you to try out actual interior layouts in a virtual environment.

[0376] "Purchase, delivery, and installation procedures" refers to the entire process from arranging for the user to receive the interior items they have selected, to their delivery to the location specified by the user, and their proper placement.

[0377] This invention is a system that helps users efficiently select and arrange their ideal interior, thereby improving their experience. The system's components include a user, a terminal, a server, and an emotion engine.

[0378] Users utilize devices such as smartphones and tablets. They take pictures of their rooms with the device's camera and input their interior design preferences, particularly style and budget, using the device's input function. Furthermore, the devices incorporate facial recognition sensors and microphones, which collect the user's facial expressions and voice tone in real time and transmit this data to the emotion engine.

[0379] The server receives and analyzes image data and request data sent by the user. Image recognition software and natural language processing technology are used for the analysis. The received emotional data is analyzed by an emotion engine, and the user's emotional state is quantified. Based on this data, the server uses a generative AI model to generate interior design suggestions tailored to the user's preferences.

[0380] The proposed data is formed as multiple candidates, particularly emphasizing designs and colors that are likely to evoke positive emotions in users. Based on this data, the server creates three-dimensional spatial display data and sends it to the user's terminal.

[0381] The terminal receives three-dimensional spatial display data using a dedicated application, allowing users to experience virtual interior layouts. A touch-enabled interface allows users to visually simulate furniture placement and interactively change its appearance.

[0382] For example, if a user prefers a bright and lively interior style, the emotion sensor detects this preference and transmits it to the server. The server then uses a generative AI model to prioritize suggestions based on this information. As a result, the user can easily find a plan they like and proceed with the purchase.

[0383] An example of a prompt would be, "I'm looking for a bright and lively style to choose for the interior of my room. Can you use sentiment analysis to give me specific interior design suggestions that suit my preferences?"

[0384] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0385] Step 1:

[0386] The user uses a device to take image data of the room and inputs data such as interior style and budget. The device has a facial recognition sensor and microphone, which captures emotional data from the user's facial expressions and tone of voice. This data (image data, request data, and emotional data) is transmitted to the server in real time. The input data becomes a valuable source of information about the user's preferences and emotional state, and is necessary for the next processing step.

[0387] Step 2:

[0388] The server analyzes the received image data and request data, and uses image recognition software to understand the characteristics of the space. In addition, it uses natural language processing technology to understand the request data. Emotional data is quantified by an emotion engine, and the user's emotional state is determined. Based on the input data (images, requests, emotions), an AI model is created to generate optimal interior design proposals, producing multiple proposal data. The output consists of multiple interior design proposals tailored to the user's preferences.

[0389] Step 3:

[0390] The server creates three-dimensional spatial display data based on the generated proposal data. This data reflects designs and colors that will attract the user's attention and is prepared in a visually verifiable format. For three-dimensional display, rendering is performed in real time and transmitted to the user's terminal. The output data is three-dimensional spatial display data for visualizing the proposed interior in space.

[0391] Step 4:

[0392] The terminal loads received 3D spatial display data into a dedicated application, providing the user with an interactive interior simulation. Users can try out virtual furniture placements using touch controls. The interface is intuitive, allowing users to experiment with different arrangements according to their preferences. Input is 3D display data from the server, and output is the furniture placement in the virtual space that the user can view.

[0393] Step 5:

[0394] Once a user selects an interior design plan, the information is sent back to the server via their device. The server then automates the process from purchasing the furniture to delivery and installation based on the selected plan. This is done using an e-commerce system, with all necessary processing handled in the backend. The final output is the confirmation of the order and delivery schedule for the furniture items selected by the user.

[0395] (Application Example 2)

[0396] 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."

[0397] Conventional interior design systems often lacked optimal suggestions that took user preferences into account, resulting in decreased user satisfaction. Furthermore, it was difficult for users to make interior design choices that reflected their emotions, leading to a less-than-smooth purchase process.

[0398] 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.

[0399] In this invention, the server includes means for receiving image data and request data from the user, means for analyzing the received image data and request data to generate suggestion data, and means for acquiring the user's emotional data, analyzing the emotional data, and adjusting suggestions based on the user's preferences. This makes it possible to propose personalized interior plans based on the user's emotions.

[0400] "Image data" refers to digital information that visually records the user's environment and serves as the basis for the system to analyze the layout of the interior.

[0401] "Request data" refers to information that describes individual requirements, such as the interior style and budget desired by the user.

[0402] "Suggestion data" refers to candidate information for interior plans and items generated based on the user's image data, request data, and emotion data.

[0403] "Three-dimensional spatial display data" refers to three-dimensional visual information used to virtually simulate the placement of interior items on a user's device.

[0404] "Emotional data" refers to information used to analyze a user's feelings and sensations, and is data obtained based on changes in facial expressions and tone of voice.

[0405] "User preferences" refer to the personal tastes and preferences that users have for specific interior styles, colors, and designs.

[0406] A "virtual environment" is a digital space that mimics and reproduces the real world, allowing users to simulate actual placement of interior items.

[0407] To implement this invention, the user first takes a picture of their room using a device such as a smartphone or smart glasses. The captured image data and the user's request data are sent from the device to a server. The server receives this data and analyzes the image data and request data in order to suggest an interior layout.

[0408] The server uses an emotion engine to acquire and analyze the user's emotional data. Smartphones and smart glasses utilize sensors to determine emotions, generating emotional data while monitoring the user's facial expressions and tone of voice. Based on the analyzed emotional data, the server generates suggested data tailored to the user's preferred interior style.

[0409] Next, the server generates three-dimensional spatial display data based on the adjusted proposal data and sends it to the user's terminal. The terminal can then use the received three-dimensional spatial display data to simulate furniture placement in a virtual space.

[0410] For example, if a user prefers vibrant colors, the emotion engine will take this into account and suggest an interior design plan that emphasizes those colors and designs. The user can review the suggestion and, if they like it, proceed with the purchase. The server will then automatically handle the process from purchase to delivery and installation.

[0411] An example of a prompt message is as follows: "Based on the user's emotional data and photos of their interior style, please suggest interior items that this user might like. Also, please perform a 3D simulation to show how those items would fit into the room."

[0412] The system of the present invention enables interior design selection based on the user's emotions, thereby significantly improving the user experience.

[0413] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0414] Step 1:

[0415] The user takes a picture of the room using the device and inputs request data into the interface. During this process, the device's built-in camera and microphone are used to acquire emotional data from facial expressions and tone of voice. This process prepares image data, request data, and emotional data.

[0416] Step 2:

[0417] The device sends captured image data, request data, and acquired emotion data to the server. Based on this input data, the server begins analyzing the data using image processing algorithms and natural language processing. The analysis utilizes data processing services such as Google Cloud Platform to extract basic elements that match the user's requests and preferences.

[0418] Step 3:

[0419] The server generates suggestion data based on the received data. Here, the emotion engine refers to the user's emotion data and prioritizes selecting designs and colors that the user has responded positively to. Using an AI model, the system provides suggestions that reflect the user's preferences, utilizing prompt text.

[0420] Step 4:

[0421] The server uses the generated proposal data to create three-dimensional spatial display data. This display data is designed to allow the user to visually confirm the proposed interior items. At this stage, a digital simulation is performed using a 3D graphics engine.

[0422] Step 5:

[0423] The server sends three-dimensional spatial display data to the user's terminal. The terminal receives this data and provides the user with the ability to try out interior placement in a virtual space. This allows the user to visually confirm how the furniture will actually be placed.

[0424] Step 6:

[0425] When a user selects a specific interior design plan, that selection is sent from the terminal to the server. The server can then automatically arrange the purchase, delivery, and installation processes for the selected items. In this step, the system integrates with transaction management and logistics systems to prepare for the completion of service delivery.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] [Third Embodiment]

[0430] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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".

[0442] This invention is a system that allows users to achieve their ideal interior layout with minimal effort. The system consists of a user, a terminal, and a server.

[0443] First, the user takes image data of their room using a device and inputs data such as their desired interior style and budget. The device then sends this data to the server, and the process begins.

[0444] The server analyzes the received image data to understand the physical characteristics of the room, such as its size and shape. Furthermore, it uses the request data to identify the interior style desired by the user and generates suggestion data. This suggestion data includes furniture types and arrangement ideas that match the user's requirements.

[0445] Next, the server creates three-dimensional spatial display data based on the generated proposal data. This data is designed to allow the user to visually confirm the image of the furniture being placed in real space with accurate size and position. At this stage, the server generates multiple furniture combination options for the user to select from.

[0446] The terminal receives 3D spatial display data transmitted from the server and uses a dedicated application to simulate furniture placement. Using the terminal, users can utilize AR or VR technology to virtually display furniture in their real room and check its placement and design in real time. As a result, they can select the optimal interior plan from multiple proposals.

[0447] For example, if a user desires a natural style for an 8-tatami mat room, the server might suggest wood-grain tables and sofas. By performing an AR simulation on their device, the user can instantly check how the placement and design match. If the user is satisfied with the simulation results, they can confirm the purchase, and the server will automatically handle the furniture delivery and installation procedures.

[0448] This process allows users to efficiently select the optimal interior design within limited space and budget, and to make effective use of the space.

[0449] The following describes the processing flow.

[0450] Step 1:

[0451] The user uses a device to take pictures of their room and inputs data such as their desired interior style and budget. The device then prepares to send this data to the server.

[0452] Step 2:

[0453] The terminal sends the created data package (image data and request data) to the server. Once the server receives this data, the next process begins.

[0454] Step 3:

[0455] The server analyzes image data to determine the room dimensions and layout. It also uses the requested data to confirm the user's preferred interior style and budget.

[0456] Step 4:

[0457] The server generates multiple furniture placement plans based on the analysis results. It selects furniture that meets the criteria from the database and compiles it as suggested data.

[0458] Step 5:

[0459] The server uses the proposed data to generate three-dimensional spatial display data. This data includes information for AR or VR to simulate furniture placement.

[0460] Step 6:

[0461] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and prepares for the next processing step.

[0462] Step 7:

[0463] The device uses the received three-dimensional spatial display data to start a furniture placement simulation using AR or VR. Through this simulation, the user can virtually place furniture in the room and visually confirm its placement.

[0464] Step 8:

[0465] The user reviews the simulation results and selects the plan they deem best from among the proposed furniture arrangement options. Once the user confirms their selection, the process proceeds.

[0466] Step 9:

[0467] The server generates information for purchasing furniture based on the user's selected interior design plan. It also automatically arranges furniture delivery and installation, enabling rapid service delivery.

[0468] (Example 1)

[0469] 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."

[0470] In modern society, efficiently and effectively planning the interior layout of living spaces is a time-consuming and laborious task for many people. In particular, achieving an ideal layout within limited space and budget is a significant challenge. This invention aims to solve these problems and provide a system that allows users to easily arrange the optimal interior for their own space.

[0471] 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.

[0472] In this invention, the server includes means for receiving image information and request information from the user, means for analyzing the received image information and extracting spatial features, and means for utilizing a generation AI model based on the request information to generate suggestion information. This enables the user to automatically and intuitively plan complex interior layouts.

[0473] A "user" is a person who uses the system and is the entity that provides information regarding interior design.

[0474] "Image information" refers to visual data of the living space provided by the user, which is used to analyze the dimensions and characteristics of the room.

[0475] "Request information" refers to data about the user's desired interior style and budget, and serves as the basis for proposing interior layouts.

[0476] A "generative AI model" is an artificial intelligence technology that generates interior layout suggestions from given information, and is an algorithm that derives the optimal solution based on the user's requests.

[0477] "Suggested information" refers to data on interior layout plans and options that match the user's requests, generated by a generative AI model.

[0478] "Three-dimensional display information" refers to visually three-dimensional data created based on proposed information, and serves as the foundation for users to confirm interior layouts in a virtual space.

[0479] An "information processing terminal" is an electronic device used by users to operate a system, and is a device used for capturing image information and confirming virtualized interior layouts.

[0480] "Arrangement of items" refers to the act or plan of specifically placing furniture and decorative items as interior furnishings within a space.

[0481] "Acquisition and Transfer Procedures" refers to all necessary procedures for delivering the selected items to the user, encompassing the entire process from purchase to delivery.

[0482] This invention is a system for efficiently planning the interior layout of a living space. The system consists of a user, a terminal, and a server. The user first uses the terminal to capture images of their living space and inputs desired information such as their preferred interior style and budget. A dedicated application is installed on the terminal, and data is transmitted to the server via this application.

[0483] The server uses image recognition software (e.g., OpenCV) to analyze the received image information and identify physical features such as spatial dimensions and shape. Next, the server uses a generative AI model (e.g., a large-scale language model) to generate prompts based on the user's request information and identify an appropriate interior style. An example of such a prompt is: "Please suggest a natural style interior layout suitable for an 8-tatami mat room. The budget is 200,000 yen, and the preferred furniture is a wood-grain table and sofa."

[0484] Based on this information, the server generates suggestion data, including furniture types and placement options that meet the user's requirements. The server then uses 3D modeling software (e.g., Blender or Unity) to visualize this suggestion data as a 3D display. This display data is then sent to the user's device.

[0485] The terminal displays the received 3D information using a dedicated application, allowing users to virtually try out interior layouts within a living space using AR or VR technology. During this process, users can review the layout options in real time and select the optimal interior plan.

[0486] This platform allows users to effectively select interior design elements while taking space and budget constraints into consideration, maximizing the appeal of their living spaces.

[0487] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0488] Step 1:

[0489] Users use a device to photograph their living space and input the image information into a dedicated application on the device. At this time, users also input information such as their desired interior style and budget. The input data is initially processed by the application and prepared for transmission to the server. The output consists of the image information and request information ready for transmission to the server.

[0490] Step 2:

[0491] The server analyzes the image information received from the terminal. Specifically, it uses image recognition software such as OpenCV to extract physical features such as spatial dimensions and shape from the image. This data processing allows for an understanding of the characteristics of the user's living space. The analysis results are output as spatial feature data that can be used to identify interior styles.

[0492] Step 3:

[0493] The server utilizes a generative AI model to generate prompt messages based on the request information. These are instructions to determine the optimal interior style based on the user's preferences. This model processes the input request information as text and outputs it as prompt messages.

[0494] Step 4:

[0495] The server uses a generative AI model to generate suggestion information based on the prompt text and spatial feature data. This suggestion information includes furniture types and placement suggestions based on an interior style that matches the user's requests. The generated suggestion information is then prepared as input for the next step.

[0496] Step 5:

[0497] The server uses the proposed information to generate 3D display information. Using 3D modeling software such as Blender or Unity, it creates data that visualizes the proposed furniture and arrangement in 3D space. This 3D display information is output and sent to the terminal.

[0498] Step 6:

[0499] The terminal displays 3D information received from the server within a dedicated application, providing an environment where users can virtually experience interior layouts using AR or VR technology. Users can use the virtually displayed interior to check and compare layout options in real time and select the optimal plan. The output is the interior plan selected by the user, and this data is passed on to subsequent processing.

[0500] (Application Example 1)

[0501] 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."

[0502] The goal is to efficiently simulate interior layouts and provide users with a means to visually confirm them before purchase. Furthermore, utilizing virtual simulations is required to improve the in-store experience while simplifying the purchase process. Traditional methods carry the risk of users realizing after purchase that the design doesn't suit them; therefore, it's necessary to prevent this and facilitate smooth purchasing.

[0503] 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.

[0504] In this invention, the server includes means for receiving spatial image data and request data from a user, means for analyzing the received spatial image data and request data to generate proposal data, and means for generating three-dimensional spatial display data using the proposal data. This enables the user to virtually confirm the arrangement of items and automatically perform electronic transaction procedures.

[0505] "Spatial image data" refers to image data containing visual information about a user's room or space.

[0506] "Request data" refers to data that includes information about the user's desired interior style and budget.

[0507] "Proposal data" refers to data generated based on analyzed spatial image data and request data, used for item placement plans and product selection.

[0508] "Three-dimensional spatial display data" refers to data generated based on proposed data that allows users to virtually visualize the placement of items.

[0509] A "display device" is an electronic device used by users to view three-dimensional spatial display data, and includes smartphones and tablets.

[0510] A "virtual arrangement" is a digital display that virtually reproduces the arrangement of objects in a real-world space.

[0511] "Electronic transaction procedures" refer to the process of automatically carrying out procedures related to the purchase of goods electronically.

[0512] "Transportation procedures" refer to the automated process of arranging and managing the delivery of items selected by the user to a specified location.

[0513] The system that realizes this application allows users to efficiently simulate interior layouts and facilitate the purchase process. First, the user uses a display device such as a smartphone or tablet to input spatial image data of the room and request data. This request data includes the desired interior style and budget.

[0514] Next, the user's device sends the input data to the server. The server analyzes the received spatial image data to understand the physical characteristics of the room. Based on this, the server generates appropriate suggestion data while considering the requested data. This process utilizes image analysis libraries such as OpenCV and machine learning frameworks such as TensorFlow.

[0515] Subsequently, the server generates three-dimensional spatial display data using the proposed data and sends it to the user's display device. This data visualizes the placement of objects in a virtual reality space using AR technologies such as Unity and ARCore. The user can virtually check the placement of objects in the real space and select them from the virtual array.

[0516] Furthermore, the purchase process for the items selected by the user is automated through electronic transaction procedures handled by the server. This process utilizes electronic payment APIs (such as the Stripe API). The selected items are then delivered to the user's specified location via appropriate transportation procedures.

[0517] For example, if a user requests a Scandinavian-style interior and inputs spatial image data, the server will suggest furniture primarily made of wood. The user can virtually check the placement via AR display and make a purchase decision on the spot. An example of a prompt to the generating AI model would be, "Analyze the photo of the room and suggest a natural-style furniture arrangement."

[0518] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0519] Step 1:

[0520] Users take spatial image data of their room using their smartphone or tablet and input their desired interior style and budget. This data is prepared and optimized for transmission by the device.

[0521] Step 2:

[0522] The terminal sends prepared spatial image data and request data to the server. The input includes image files and text data, which the server receives. Here, the data format is checked, and appropriate processing preparations are made.

[0523] Step 3:

[0524] The server uses tools such as OpenCV and TensorFlow to analyze the received spatial image data. It recognizes the physical features and layout of the room from the input data and obtains the analysis results as output. The analysis results include information on the dimensions and shape of the room.

[0525] Step 4:

[0526] The server generates proposal data based on the analysis results, taking the requested data into consideration. This process utilizes a generation AI model to assemble interior layout plans that suit the user's style. The output includes specific furniture types and placement suggestions.

[0527] Step 5:

[0528] The server uses Unity or ARCore to convert the proposed data into 3D spatial display data. The proposed data is used as input, and the output is data in a format that can be displayed in AR.

[0529] Step 6:

[0530] Three-dimensional spatial display data is transmitted to the terminal, and the user can see the virtual placement of objects in the actual space via the display device. Here, the terminal uses AR technology to display the data, resulting in a visual experience where reality and virtuality overlap.

[0531] Step 7:

[0532] The user uses a display device to view and select items in a virtual environment. In this step, they confirm their selected layout using intuitive touch controls or voice input.

[0533] Step 8:

[0534] The server automates the purchase process via an electronic payment API based on the user's selections. It uses the selected data as input and generates purchase confirmation and payment completion data as output.

[0535] Step 9:

[0536] For the selected items, the server arranges transportation procedures and manages delivery to the user's specified location. It processes logistics information and manages the transportation status.

[0537] 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.

[0538] This invention further enhances the user experience by combining an emotion engine with a system that allows users to efficiently select and arrange their ideal interior. The system consists of a user, a terminal, a server, and an emotion engine.

[0539] The user takes a picture of their room through the device and inputs data such as their desired interior style and budget. The device incorporates sensors to detect the user's emotions, such as facial expressions and tone of voice, and this data is sent to the emotion engine in real time.

[0540] The server analyzes the received image data and request data, but also refers to the user's emotional data analyzed by the emotion engine. This makes it possible to determine which interior styles the user has a positive emotional response to.

[0541] Based on sentiment data, the server generates multiple suggestion data tailored to the user's preferences. In this process, the sentiment engine particularly considers the styles and colors that the user finds appealing and adjusts the suggestions accordingly. Furthermore, it generates three-dimensional spatial display data to prepare for the user to visually confirm.

[0542] The device receives the generated 3D spatial display data and simulates furniture placement. Through this simulation, users can virtually place furniture in a room and try out different arrangements in real time. This makes it possible for even first-time users to select the optimal interior plan that resonates with their feelings.

[0543] For example, if a user prefers vibrant colors, the emotion engine analyzes this emotion data and prioritizes suggesting interior plans that include the user's preferred colors and designs. The user can review the selected plan and, if they like it, proceed to purchase. The server automatically arranges the purchase, delivery, and installation of the selected furniture.

[0544] This embodiment of the invention enables the provision of personalized interior plans based on the user's emotions and prompt service, thereby increasing user satisfaction.

[0545] The following describes the processing flow.

[0546] Step 1:

[0547] The user uses the device to take pictures of their room and inputs data such as their desired interior style and budget. The device has sensors that capture the user's facial expressions and voice, recording them in real time as emotional data.

[0548] Step 2:

[0549] The device sends image data of the room it photographed, along with request data and emotion data, to the server. This prepares the server to begin processing the data.

[0550] Step 3:

[0551] The server first analyzes image data to understand the physical characteristics of the room (dimensions, shape). It also uses the request data to confirm the user's desired interior style and budget.

[0552] Step 4:

[0553] The server uses an emotion engine to analyze the user's emotional data. The results of this analysis measure which styles the user responds favorably to.

[0554] Step 5:

[0555] By integrating emotion data and request data, the server generates multiple furniture placement plans. In this process, it reflects the results of the emotion engine and creates suggestion data that takes into account the styles and colors that the user is judged to prefer.

[0556] Step 6:

[0557] The server generates three-dimensional spatial display data based on the proposed data. This data includes 3D models of furniture and suggested placements, which can be visually reviewed by the user.

[0558] Step 7:

[0559] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and starts the simulation for the next stage.

[0560] Step 8:

[0561] The device uses the received 3D spatial display data to perform furniture placement simulations using an AR or VR application. Users can view this in real time and try out different plans.

[0562] Step 9:

[0563] Based on the information obtained from the simulation, the user selects their favorite furniture arrangement plan. Once the selection is complete, they proceed to the next step: purchasing the furniture.

[0564] Step 10:

[0565] The server handles the purchase of furniture and arranges automated delivery and installation based on the user's selected plan. This completes the process, allowing the user to receive their goods quickly.

[0566] (Example 2)

[0567] 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."

[0568] Traditional interior design selection systems have the drawback of failing to adequately reflect users' latent preferences because they offer uniform suggestions without considering the user's feelings. Furthermore, the process from furniture purchase to installation is cumbersome, placing a significant burden on users.

[0569] 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.

[0570] In this invention, the server includes means for receiving image data, request data, and emotion data from the user; means for analyzing the received data and generating proposal data using a generative AI model; and means for generating three-dimensional spatial display data and transmitting it to the user terminal. This enables personalized interior design proposals based on the user's emotions and allows for efficient processing from purchase to installation.

[0571] "Image data" refers to digital data containing visual information of a space captured by a user.

[0572] "Request data" refers to information that users have entered regarding their preferences and requirements for interior design style and budget.

[0573] "Emotional data" refers to information that quantifies or categorizes the psychological state of a user, inferred from their facial expressions, tone of voice, and other factors.

[0574] A "generative AI model" is an algorithm or program that analyzes multiple input data and generates optimal suggested data accordingly.

[0575] "Suggestion data" refers to information that, based on the server's analysis results, presents users with candidate interior designs and layouts.

[0576] "Three-dimensional spatial display data" refers to digital data in a three-dimensional format used to visually represent the layout of an interior space virtually.

[0577] An "information processing device" is a device used by users, such as a computer or smart device, for inputting, processing, and outputting data.

[0578] "Simulation" is a process that allows you to try out actual interior layouts in a virtual environment.

[0579] "Purchase, delivery, and installation procedures" refers to the entire process from arranging for the user to receive the interior items they have selected, to their delivery to the location specified by the user, and their proper placement.

[0580] This invention is a system that helps users efficiently select and arrange their ideal interior, thereby improving their experience. The system's components include a user, a terminal, a server, and an emotion engine.

[0581] Users utilize devices such as smartphones and tablets. They take pictures of their rooms with the device's camera and input their interior design preferences, particularly style and budget, using the device's input function. Furthermore, the devices incorporate facial recognition sensors and microphones, which collect the user's facial expressions and voice tone in real time and transmit this data to the emotion engine.

[0582] The server receives and analyzes image data and request data sent by the user. Image recognition software and natural language processing technology are used for the analysis. The received emotional data is analyzed by an emotion engine, and the user's emotional state is quantified. Based on this data, the server uses a generative AI model to generate interior design suggestions tailored to the user's preferences.

[0583] The proposed data is formed as multiple candidates, particularly emphasizing designs and colors that are likely to evoke positive emotions in users. Based on this data, the server creates three-dimensional spatial display data and sends it to the user's terminal.

[0584] The terminal receives three-dimensional spatial display data using a dedicated application, allowing users to experience virtual interior layouts. A touch-enabled interface allows users to visually simulate furniture placement and interactively change its appearance.

[0585] For example, if a user prefers a bright and lively interior style, the emotion sensor detects this preference and transmits it to the server. The server then uses a generative AI model to prioritize suggestions based on this information. As a result, the user can easily find a plan they like and proceed with the purchase.

[0586] An example of a prompt would be, "I'm looking for a bright and lively style to choose for the interior of my room. Can you use sentiment analysis to give me specific interior design suggestions that suit my preferences?"

[0587] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0588] Step 1:

[0589] The user uses a device to take image data of the room and inputs data such as interior style and budget. The device has a facial recognition sensor and microphone, which captures emotional data from the user's facial expressions and tone of voice. This data (image data, request data, and emotional data) is transmitted to the server in real time. The input data becomes a valuable source of information about the user's preferences and emotional state, and is necessary for the next processing step.

[0590] Step 2:

[0591] The server analyzes the received image data and request data, and uses image recognition software to understand the characteristics of the space. In addition, it uses natural language processing technology to understand the request data. Emotional data is quantified by an emotion engine, and the user's emotional state is determined. Based on the input data (images, requests, emotions), an AI model is created to generate optimal interior design proposals, producing multiple proposal data. The output consists of multiple interior design proposals tailored to the user's preferences.

[0592] Step 3:

[0593] The server creates three-dimensional spatial display data based on the generated proposal data. This data reflects designs and colors that will attract the user's attention and is prepared in a visually verifiable format. For three-dimensional display, rendering is performed in real time and transmitted to the user's terminal. The output data is three-dimensional spatial display data for visualizing the proposed interior in space.

[0594] Step 4:

[0595] The terminal loads received 3D spatial display data into a dedicated application, providing the user with an interactive interior simulation. Users can try out virtual furniture placements using touch controls. The interface is intuitive, allowing users to experiment with different arrangements according to their preferences. Input is 3D display data from the server, and output is the furniture placement in the virtual space that the user can view.

[0596] Step 5:

[0597] Once a user selects an interior design plan, the information is sent back to the server via their device. The server then automates the process from purchasing the furniture to delivery and installation based on the selected plan. This is done using an e-commerce system, with all necessary processing handled in the backend. The final output is the confirmation of the order and delivery schedule for the furniture items selected by the user.

[0598] (Application Example 2)

[0599] 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."

[0600] Conventional interior design systems often lacked optimal suggestions that took user preferences into account, resulting in decreased user satisfaction. Furthermore, it was difficult for users to make interior design choices that reflected their emotions, leading to a less-than-smooth purchase process.

[0601] 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.

[0602] In this invention, the server includes means for receiving image data and request data from the user, means for analyzing the received image data and request data to generate suggestion data, and means for acquiring the user's emotional data, analyzing the emotional data, and adjusting suggestions based on the user's preferences. This makes it possible to propose personalized interior plans based on the user's emotions.

[0603] "Image data" refers to digital information that visually records the user's environment and serves as the basis for the system to analyze the layout of the interior.

[0604] "Request data" refers to information that describes individual requirements, such as the interior style and budget desired by the user.

[0605] "Suggestion data" refers to candidate information for interior plans and items generated based on the user's image data, request data, and emotion data.

[0606] "Three-dimensional spatial display data" refers to three-dimensional visual information used to virtually simulate the placement of interior items on a user's device.

[0607] "Emotional data" refers to information used to analyze a user's feelings and sensations, and is data obtained based on changes in facial expressions and tone of voice.

[0608] "User preferences" refer to the personal tastes and preferences that users have for specific interior styles, colors, and designs.

[0609] A "virtual environment" is a digital space that mimics and reproduces the real world, allowing users to simulate actual placement of interior items.

[0610] To implement this invention, the user first takes a picture of their room using a device such as a smartphone or smart glasses. The captured image data and the user's request data are sent from the device to a server. The server receives this data and analyzes the image data and request data in order to suggest an interior layout.

[0611] The server uses an emotion engine to acquire and analyze the user's emotional data. Smartphones and smart glasses utilize sensors to determine emotions, generating emotional data while monitoring the user's facial expressions and tone of voice. Based on the analyzed emotional data, the server generates suggested data tailored to the user's preferred interior style.

[0612] Next, the server generates three-dimensional spatial display data based on the adjusted proposal data and sends it to the user's terminal. The terminal can then use the received three-dimensional spatial display data to simulate furniture placement in a virtual space.

[0613] For example, if a user prefers vibrant colors, the emotion engine will take this into account and suggest an interior design plan that emphasizes those colors and designs. The user can review the suggestion and, if they like it, proceed with the purchase. The server will then automatically handle the process from purchase to delivery and installation.

[0614] An example of a prompt message is as follows: "Based on the user's emotional data and photos of their interior style, please suggest interior items that this user might like. Also, please perform a 3D simulation to show how those items would fit into the room."

[0615] The system of the present invention enables interior design selection based on the user's emotions, thereby significantly improving the user experience.

[0616] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0617] Step 1:

[0618] The user takes a picture of the room using the device and inputs request data into the interface. During this process, the device's built-in camera and microphone are used to acquire emotional data from facial expressions and tone of voice. This process prepares image data, request data, and emotional data.

[0619] Step 2:

[0620] The device sends captured image data, request data, and acquired emotion data to the server. Based on this input data, the server begins analyzing the data using image processing algorithms and natural language processing. The analysis utilizes data processing services such as Google Cloud Platform to extract basic elements that match the user's requests and preferences.

[0621] Step 3:

[0622] The server generates suggestion data based on the received data. Here, the emotion engine refers to the user's emotion data and prioritizes selecting designs and colors that the user has responded positively to. Using an AI model, the system provides suggestions that reflect the user's preferences, utilizing prompt text.

[0623] Step 4:

[0624] The server uses the generated proposal data to create three-dimensional spatial display data. This display data is designed to allow the user to visually confirm the proposed interior items. At this stage, a digital simulation is performed using a 3D graphics engine.

[0625] Step 5:

[0626] The server sends three-dimensional spatial display data to the user's terminal. The terminal receives this data and provides the user with the ability to try out interior placement in a virtual space. This allows the user to visually confirm how the furniture will actually be placed.

[0627] Step 6:

[0628] When a user selects a specific interior design plan, that selection is sent from the terminal to the server. The server can then automatically arrange the purchase, delivery, and installation processes for the selected items. In this step, the system integrates with transaction management and logistics systems to prepare for the completion of service delivery.

[0629] 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.

[0630] 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.

[0631] 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.

[0632] [Fourth Embodiment]

[0633] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0634] 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.

[0635] 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).

[0636] 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.

[0637] 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.

[0638] 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).

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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.

[0645] 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".

[0646] This invention is a system that allows users to achieve their ideal interior layout with minimal effort. The system consists of a user, a terminal, and a server.

[0647] First, the user takes image data of their room using a device and inputs data such as their desired interior style and budget. The device then sends this data to the server, and the process begins.

[0648] The server analyzes the received image data to understand the physical characteristics of the room, such as its size and shape. Furthermore, it uses the request data to identify the interior style desired by the user and generates suggestion data. This suggestion data includes furniture types and arrangement ideas that match the user's requirements.

[0649] Next, the server creates three-dimensional spatial display data based on the generated proposal data. This data is designed to allow the user to visually confirm the image of the furniture being placed in real space with accurate size and position. At this stage, the server generates multiple furniture combination options for the user to select from.

[0650] The terminal receives 3D spatial display data transmitted from the server and uses a dedicated application to simulate furniture placement. Using the terminal, users can utilize AR or VR technology to virtually display furniture in their real room and check its placement and design in real time. As a result, they can select the optimal interior plan from multiple proposals.

[0651] For example, if a user desires a natural style for an 8-tatami mat room, the server might suggest wood-grain tables and sofas. By performing an AR simulation on their device, the user can instantly check how the placement and design match. If the user is satisfied with the simulation results, they can confirm the purchase, and the server will automatically handle the furniture delivery and installation procedures.

[0652] This process allows users to efficiently select the optimal interior design within limited space and budget, and to make effective use of the space.

[0653] The following describes the processing flow.

[0654] Step 1:

[0655] The user uses a device to take pictures of their room and inputs data such as their desired interior style and budget. The device then prepares to send this data to the server.

[0656] Step 2:

[0657] The terminal sends the created data package (image data and request data) to the server. Once the server receives this data, the next process begins.

[0658] Step 3:

[0659] The server analyzes image data to determine the room dimensions and layout. It also uses the requested data to confirm the user's preferred interior style and budget.

[0660] Step 4:

[0661] The server generates multiple furniture placement plans based on the analysis results. It selects furniture that meets the criteria from the database and compiles it as suggested data.

[0662] Step 5:

[0663] The server uses the proposed data to generate three-dimensional spatial display data. This data includes information for AR or VR to simulate furniture placement.

[0664] Step 6:

[0665] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and prepares for the next processing step.

[0666] Step 7:

[0667] The device uses the received three-dimensional spatial display data to start a furniture placement simulation using AR or VR. Through this simulation, the user can virtually place furniture in the room and visually confirm its placement.

[0668] Step 8:

[0669] The user reviews the simulation results and selects the plan they deem best from among the proposed furniture arrangement options. Once the user confirms their selection, the process proceeds.

[0670] Step 9:

[0671] The server generates information for purchasing furniture based on the user's selected interior design plan. It also automatically arranges furniture delivery and installation, enabling rapid service delivery.

[0672] (Example 1)

[0673] 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".

[0674] In modern society, efficiently and effectively planning the interior layout of living spaces is a time-consuming and laborious task for many people. In particular, achieving an ideal layout within limited space and budget is a significant challenge. This invention aims to solve these problems and provide a system that allows users to easily arrange the optimal interior for their own space.

[0675] 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.

[0676] In this invention, the server includes means for receiving image information and request information from the user, means for analyzing the received image information and extracting spatial features, and means for utilizing a generation AI model based on the request information to generate suggestion information. This enables the user to automatically and intuitively plan complex interior layouts.

[0677] A "user" is a person who uses the system and is the entity that provides information regarding interior design.

[0678] "Image information" refers to visual data of the living space provided by the user, which is used to analyze the dimensions and characteristics of the room.

[0679] "Request information" refers to data about the user's desired interior style and budget, and serves as the basis for proposing interior layouts.

[0680] A "generative AI model" is an artificial intelligence technology that generates interior layout suggestions from given information, and is an algorithm that derives the optimal solution based on the user's requests.

[0681] "Suggested information" refers to data on interior layout plans and options that match the user's requests, generated by a generative AI model.

[0682] "Three-dimensional display information" refers to visually three-dimensional data created based on proposed information, and serves as the foundation for users to confirm interior layouts in a virtual space.

[0683] An "information processing terminal" is an electronic device used by users to operate a system, and is a device used for capturing image information and confirming virtualized interior layouts.

[0684] "Arrangement of items" refers to the act or plan of specifically placing furniture and decorative items as interior furnishings within a space.

[0685] "Acquisition and Transfer Procedures" refers to all necessary procedures for delivering the selected items to the user, encompassing the entire process from purchase to delivery.

[0686] This invention is a system for efficiently planning the interior layout of a living space. The system consists of a user, a terminal, and a server. The user first uses the terminal to capture images of their living space and inputs desired information such as their preferred interior style and budget. A dedicated application is installed on the terminal, and data is transmitted to the server via this application.

[0687] The server uses image recognition software (e.g., OpenCV) to analyze the received image information and identify physical features such as spatial dimensions and shape. Next, the server uses a generative AI model (e.g., a large-scale language model) to generate prompts based on the user's request information and identify an appropriate interior style. An example of such a prompt is: "Please suggest a natural style interior layout suitable for an 8-tatami mat room. The budget is 200,000 yen, and the preferred furniture is a wood-grain table and sofa."

[0688] Based on this information, the server generates suggestion data, including furniture types and placement options that meet the user's requirements. The server then uses 3D modeling software (e.g., Blender or Unity) to visualize this suggestion data as a 3D display. This display data is then sent to the user's device.

[0689] The terminal displays the received 3D information using a dedicated application, allowing users to virtually try out interior layouts within a living space using AR or VR technology. During this process, users can review the layout options in real time and select the optimal interior plan.

[0690] This platform allows users to effectively select interior design elements while taking space and budget constraints into consideration, maximizing the appeal of their living spaces.

[0691] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0692] Step 1:

[0693] Users use a device to photograph their living space and input the image information into a dedicated application on the device. At this time, users also input information such as their desired interior style and budget. The input data is initially processed by the application and prepared for transmission to the server. The output consists of the image information and request information ready for transmission to the server.

[0694] Step 2:

[0695] The server analyzes the image information received from the terminal. Specifically, it uses image recognition software such as OpenCV to extract physical features such as spatial dimensions and shape from the image. This data processing allows for an understanding of the characteristics of the user's living space. The analysis results are output as spatial feature data that can be used to identify interior styles.

[0696] Step 3:

[0697] The server utilizes a generative AI model to generate prompt messages based on the request information. These are instructions to determine the optimal interior style based on the user's preferences. This model processes the input request information as text and outputs it as prompt messages.

[0698] Step 4:

[0699] The server uses a generative AI model to generate suggestion information based on the prompt text and spatial feature data. This suggestion information includes furniture types and placement suggestions based on an interior style that matches the user's requests. The generated suggestion information is then prepared as input for the next step.

[0700] Step 5:

[0701] The server uses the proposed information to generate 3D display information. Using 3D modeling software such as Blender or Unity, it creates data that visualizes the proposed furniture and arrangement in 3D space. This 3D display information is output and sent to the terminal.

[0702] Step 6:

[0703] The terminal displays 3D information received from the server within a dedicated application, providing an environment where users can virtually experience interior layouts using AR or VR technology. Users can use the virtually displayed interior to check and compare layout options in real time and select the optimal plan. The output is the interior plan selected by the user, and this data is passed on to subsequent processing.

[0704] (Application Example 1)

[0705] 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".

[0706] The goal is to efficiently simulate interior layouts and provide users with a means to visually confirm them before purchase. Furthermore, utilizing virtual simulations is required to improve the in-store experience while simplifying the purchase process. Traditional methods carry the risk of users realizing after purchase that the design doesn't suit them; therefore, it's necessary to prevent this and facilitate smooth purchasing.

[0707] 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.

[0708] In this invention, the server includes means for receiving spatial image data and request data from a user, means for analyzing the received spatial image data and request data to generate proposal data, and means for generating three-dimensional spatial display data using the proposal data. This enables the user to virtually confirm the arrangement of items and automatically perform electronic transaction procedures.

[0709] "Spatial image data" refers to image data containing visual information about a user's room or space.

[0710] "Request data" refers to data that includes information about the user's desired interior style and budget.

[0711] "Proposal data" refers to data generated based on analyzed spatial image data and request data, used for item placement plans and product selection.

[0712] "Three-dimensional spatial display data" refers to data generated based on proposed data that allows users to virtually visualize the placement of items.

[0713] A "display device" is an electronic device used by users to view three-dimensional spatial display data, and includes smartphones and tablets.

[0714] A "virtual arrangement" is a digital display that virtually reproduces the arrangement of objects in a real-world space.

[0715] "Electronic transaction procedures" refer to the process of automatically carrying out procedures related to the purchase of goods electronically.

[0716] "Transportation procedures" refer to the automated process of arranging and managing the delivery of items selected by the user to a specified location.

[0717] The system that realizes this application allows users to efficiently simulate interior layouts and facilitate the purchase process. First, the user uses a display device such as a smartphone or tablet to input spatial image data of the room and request data. This request data includes the desired interior style and budget.

[0718] Next, the user's device sends the input data to the server. The server analyzes the received spatial image data to understand the physical characteristics of the room. Based on this, the server generates appropriate suggestion data while considering the requested data. This process utilizes image analysis libraries such as OpenCV and machine learning frameworks such as TensorFlow.

[0719] Subsequently, the server generates three-dimensional spatial display data using the proposed data and sends it to the user's display device. This data visualizes the placement of objects in a virtual reality space using AR technologies such as Unity and ARCore. The user can virtually check the placement of objects in the real space and select them from the virtual array.

[0720] Furthermore, the purchase process for the items selected by the user is automated through electronic transaction procedures handled by the server. This process utilizes electronic payment APIs (such as the Stripe API). The selected items are then delivered to the user's specified location via appropriate transportation procedures.

[0721] For example, if a user requests a Scandinavian-style interior and inputs spatial image data, the server will suggest furniture primarily made of wood. The user can virtually check the placement via AR display and make a purchase decision on the spot. An example of a prompt to the generating AI model would be, "Analyze the photo of the room and suggest a natural-style furniture arrangement."

[0722] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0723] Step 1:

[0724] Users take spatial image data of their room using their smartphone or tablet and input their desired interior style and budget. This data is prepared and optimized for transmission by the device.

[0725] Step 2:

[0726] The terminal sends prepared spatial image data and request data to the server. The input includes image files and text data, which the server receives. Here, the data format is checked, and appropriate processing preparations are made.

[0727] Step 3:

[0728] The server uses tools such as OpenCV and TensorFlow to analyze the received spatial image data. It recognizes the physical features and layout of the room from the input data and obtains the analysis results as output. The analysis results include information on the dimensions and shape of the room.

[0729] Step 4:

[0730] The server generates proposal data based on the analysis results, taking the requested data into consideration. This process utilizes a generation AI model to assemble interior layout plans that suit the user's style. The output includes specific furniture types and placement suggestions.

[0731] Step 5:

[0732] The server uses Unity or ARCore to convert the proposed data into 3D spatial display data. The proposed data is used as input, and the output is data in a format that can be displayed in AR.

[0733] Step 6:

[0734] Three-dimensional spatial display data is transmitted to the terminal, and the user can see the virtual placement of objects in the actual space via the display device. Here, the terminal uses AR technology to display the data, resulting in a visual experience where reality and virtuality overlap.

[0735] Step 7:

[0736] The user uses a display device to view and select items in a virtual environment. In this step, they confirm their selected layout using intuitive touch controls or voice input.

[0737] Step 8:

[0738] The server automates the purchase process via an electronic payment API based on the user's selections. It uses the selected data as input and generates purchase confirmation and payment completion data as output.

[0739] Step 9:

[0740] For the selected items, the server arranges transportation procedures and manages delivery to the user's specified location. It processes logistics information and manages the transportation status.

[0741] 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.

[0742] This invention further enhances the user experience by combining an emotion engine with a system that allows users to efficiently select and arrange their ideal interior. The system consists of a user, a terminal, a server, and an emotion engine.

[0743] The user takes a picture of their room through the device and inputs data such as their desired interior style and budget. The device incorporates sensors to detect the user's emotions, such as facial expressions and tone of voice, and this data is sent to the emotion engine in real time.

[0744] The server analyzes the received image data and request data, but also refers to the user's emotional data analyzed by the emotion engine. This makes it possible to determine which interior styles the user has a positive emotional response to.

[0745] Based on sentiment data, the server generates multiple suggestion data tailored to the user's preferences. In this process, the sentiment engine particularly considers the styles and colors that the user finds appealing and adjusts the suggestions accordingly. Furthermore, it generates three-dimensional spatial display data to prepare for the user to visually confirm.

[0746] The device receives the generated 3D spatial display data and simulates furniture placement. Through this simulation, users can virtually place furniture in a room and try out different arrangements in real time. This makes it possible for even first-time users to select the optimal interior plan that resonates with their feelings.

[0747] For example, if a user prefers vibrant colors, the emotion engine analyzes this emotion data and prioritizes suggesting interior plans that include the user's preferred colors and designs. The user can review the selected plan and, if they like it, proceed to purchase. The server automatically arranges the purchase, delivery, and installation of the selected furniture.

[0748] This embodiment of the invention enables the provision of personalized interior plans based on the user's emotions and prompt service, thereby increasing user satisfaction.

[0749] The following describes the processing flow.

[0750] Step 1:

[0751] The user uses the device to take pictures of their room and inputs data such as their desired interior style and budget. The device has sensors that capture the user's facial expressions and voice, recording them in real time as emotional data.

[0752] Step 2:

[0753] The device sends image data of the room it photographed, along with request data and emotion data, to the server. This prepares the server to begin processing the data.

[0754] Step 3:

[0755] The server first analyzes image data to understand the physical characteristics of the room (dimensions, shape). It also uses the request data to confirm the user's desired interior style and budget.

[0756] Step 4:

[0757] The server uses an emotion engine to analyze the user's emotional data. The results of this analysis measure which styles the user responds favorably to.

[0758] Step 5:

[0759] By integrating emotion data and request data, the server generates multiple furniture placement plans. In this process, it reflects the results of the emotion engine and creates suggestion data that takes into account the styles and colors that the user is judged to prefer.

[0760] Step 6:

[0761] The server generates three-dimensional spatial display data based on the proposed data. This data includes 3D models of furniture and suggested placements, which can be visually reviewed by the user.

[0762] Step 7:

[0763] The server sends the generated three-dimensional spatial display data to the terminal. The terminal receives this data and starts the simulation for the next stage.

[0764] Step 8:

[0765] The device uses the received 3D spatial display data to perform furniture placement simulations using an AR or VR application. Users can view this in real time and try out different plans.

[0766] Step 9:

[0767] Based on the information obtained from the simulation, the user selects their favorite furniture arrangement plan. Once the selection is complete, they proceed to the next step: purchasing the furniture.

[0768] Step 10:

[0769] The server handles the purchase of furniture and arranges automated delivery and installation based on the user's selected plan. This completes the process, allowing the user to receive their goods quickly.

[0770] (Example 2)

[0771] 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".

[0772] Traditional interior design selection systems have the drawback of failing to adequately reflect users' latent preferences because they offer uniform suggestions without considering the user's feelings. Furthermore, the process from furniture purchase to installation is cumbersome, placing a significant burden on users.

[0773] 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.

[0774] In this invention, the server includes means for receiving image data, request data, and emotion data from the user; means for analyzing the received data and generating proposal data using a generative AI model; and means for generating three-dimensional spatial display data and transmitting it to the user terminal. This enables personalized interior design proposals based on the user's emotions and allows for efficient processing from purchase to installation.

[0775] "Image data" refers to digital data containing visual information of a space captured by a user.

[0776] "Request data" refers to information that users have entered regarding their preferences and requirements for interior design style and budget.

[0777] "Emotional data" refers to information that quantifies or categorizes the psychological state of a user, inferred from their facial expressions, tone of voice, and other factors.

[0778] A "generative AI model" is an algorithm or program that analyzes multiple input data and generates optimal suggested data accordingly.

[0779] "Suggestion data" refers to information that, based on the server's analysis results, presents users with candidate interior designs and layouts.

[0780] "Three-dimensional spatial display data" refers to digital data in a three-dimensional format used to visually represent the layout of an interior space virtually.

[0781] An "information processing device" is a device used by users, such as a computer or smart device, for inputting, processing, and outputting data.

[0782] "Simulation" is a process that allows you to try out actual interior layouts in a virtual environment.

[0783] "Purchase, delivery, and installation procedures" refers to the entire process from arranging for the user to receive the interior items they have selected, to their delivery to the location specified by the user, and their proper placement.

[0784] This invention is a system that helps users efficiently select and arrange their ideal interior, thereby improving their experience. The system's components include a user, a terminal, a server, and an emotion engine.

[0785] Users utilize devices such as smartphones and tablets. They take pictures of their rooms with the device's camera and input their interior design preferences, particularly style and budget, using the device's input function. Furthermore, the devices incorporate facial recognition sensors and microphones, which collect the user's facial expressions and voice tone in real time and transmit this data to the emotion engine.

[0786] The server receives and analyzes image data and request data sent by the user. Image recognition software and natural language processing technology are used for the analysis. The received emotional data is analyzed by an emotion engine, and the user's emotional state is quantified. Based on this data, the server uses a generative AI model to generate interior design suggestions tailored to the user's preferences.

[0787] The proposed data is formed as multiple candidates, particularly emphasizing designs and colors that are likely to evoke positive emotions in users. Based on this data, the server creates three-dimensional spatial display data and sends it to the user's terminal.

[0788] The terminal receives three-dimensional spatial display data using a dedicated application, allowing users to experience virtual interior layouts. A touch-enabled interface allows users to visually simulate furniture placement and interactively change its appearance.

[0789] For example, if a user prefers a bright and lively interior style, the emotion sensor detects this preference and transmits it to the server. The server then uses a generative AI model to prioritize suggestions based on this information. As a result, the user can easily find a plan they like and proceed with the purchase.

[0790] An example of a prompt would be, "I'm looking for a bright and lively style to choose for the interior of my room. Can you use sentiment analysis to give me specific interior design suggestions that suit my preferences?"

[0791] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0792] Step 1:

[0793] The user uses a device to take image data of the room and inputs data such as interior style and budget. The device has a facial recognition sensor and microphone, which captures emotional data from the user's facial expressions and tone of voice. This data (image data, request data, and emotional data) is transmitted to the server in real time. The input data becomes a valuable source of information about the user's preferences and emotional state, and is necessary for the next processing step.

[0794] Step 2:

[0795] The server analyzes the received image data and request data, and uses image recognition software to understand the characteristics of the space. In addition, it uses natural language processing technology to understand the request data. Emotional data is quantified by an emotion engine, and the user's emotional state is determined. Based on the input data (images, requests, emotions), an AI model is created to generate optimal interior design proposals, producing multiple proposal data. The output consists of multiple interior design proposals tailored to the user's preferences.

[0796] Step 3:

[0797] The server creates three-dimensional spatial display data based on the generated proposal data. This data reflects designs and colors that will attract the user's attention and is prepared in a visually verifiable format. For three-dimensional display, rendering is performed in real time and transmitted to the user's terminal. The output data is three-dimensional spatial display data for visualizing the proposed interior in space.

[0798] Step 4:

[0799] The terminal loads received 3D spatial display data into a dedicated application, providing the user with an interactive interior simulation. Users can try out virtual furniture placements using touch controls. The interface is intuitive, allowing users to experiment with different arrangements according to their preferences. Input is 3D display data from the server, and output is the furniture placement in the virtual space that the user can view.

[0800] Step 5:

[0801] Once a user selects an interior design plan, the information is sent back to the server via their device. The server then automates the process from purchasing the furniture to delivery and installation based on the selected plan. This is done using an e-commerce system, with all necessary processing handled in the backend. The final output is the confirmation of the order and delivery schedule for the furniture items selected by the user.

[0802] (Application Example 2)

[0803] 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".

[0804] Conventional interior design systems often lacked optimal suggestions that took user preferences into account, resulting in decreased user satisfaction. Furthermore, it was difficult for users to make interior design choices that reflected their emotions, leading to a less-than-smooth purchase process.

[0805] 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.

[0806] In this invention, the server includes means for receiving image data and request data from the user, means for analyzing the received image data and request data to generate suggestion data, and means for acquiring the user's emotional data, analyzing the emotional data, and adjusting suggestions based on the user's preferences. This makes it possible to propose personalized interior plans based on the user's emotions.

[0807] "Image data" refers to digital information that visually records the user's environment and serves as the basis for the system to analyze the layout of the interior.

[0808] "Request data" refers to information that describes individual requirements, such as the interior style and budget desired by the user.

[0809] "Suggestion data" refers to candidate information for interior plans and items generated based on the user's image data, request data, and emotion data.

[0810] "Three-dimensional spatial display data" refers to three-dimensional visual information used to virtually simulate the placement of interior items on a user's device.

[0811] "Emotional data" refers to information used to analyze a user's feelings and sensations, and is data obtained based on changes in facial expressions and tone of voice.

[0812] "User preferences" refer to the personal tastes and preferences that users have for specific interior styles, colors, and designs.

[0813] A "virtual environment" is a digital space that mimics and reproduces the real world, allowing users to simulate actual placement of interior items.

[0814] To implement this invention, the user first takes a picture of their room using a device such as a smartphone or smart glasses. The captured image data and the user's request data are sent from the device to a server. The server receives this data and analyzes the image data and request data in order to suggest an interior layout.

[0815] The server uses an emotion engine to acquire and analyze the user's emotional data. Smartphones and smart glasses utilize sensors to determine emotions, generating emotional data while monitoring the user's facial expressions and tone of voice. Based on the analyzed emotional data, the server generates suggested data tailored to the user's preferred interior style.

[0816] Next, the server generates three-dimensional spatial display data based on the adjusted proposal data and sends it to the user's terminal. The terminal can then use the received three-dimensional spatial display data to simulate furniture placement in a virtual space.

[0817] For example, if a user prefers vibrant colors, the emotion engine will take this into account and suggest an interior design plan that emphasizes those colors and designs. The user can review the suggestion and, if they like it, proceed with the purchase. The server will then automatically handle the process from purchase to delivery and installation.

[0818] An example of a prompt message is as follows: "Based on the user's emotional data and photos of their interior style, please suggest interior items that this user might like. Also, please perform a 3D simulation to show how those items would fit into the room."

[0819] The system of the present invention enables interior design selection based on the user's emotions, thereby significantly improving the user experience.

[0820] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0821] Step 1:

[0822] The user takes a picture of the room using the device and inputs request data into the interface. During this process, the device's built-in camera and microphone are used to acquire emotional data from facial expressions and tone of voice. This process prepares image data, request data, and emotional data.

[0823] Step 2:

[0824] The device sends captured image data, request data, and acquired emotion data to the server. Based on this input data, the server begins analyzing the data using image processing algorithms and natural language processing. The analysis utilizes data processing services such as Google Cloud Platform to extract basic elements that match the user's requests and preferences.

[0825] Step 3:

[0826] The server generates suggestion data based on the received data. Here, the emotion engine refers to the user's emotion data and prioritizes selecting designs and colors that the user has responded positively to. Using an AI model, the system provides suggestions that reflect the user's preferences, utilizing prompt text.

[0827] Step 4:

[0828] The server uses the generated proposal data to create three-dimensional spatial display data. This display data is designed to allow the user to visually confirm the proposed interior items. At this stage, a digital simulation is performed using a 3D graphics engine.

[0829] Step 5:

[0830] The server sends three-dimensional spatial display data to the user's terminal. The terminal receives this data and provides the user with the ability to try out interior placement in a virtual space. This allows the user to visually confirm how the furniture will actually be placed.

[0831] Step 6:

[0832] When a user selects a specific interior design plan, that selection is sent from the terminal to the server. The server can then automatically arrange the purchase, delivery, and installation processes for the selected items. In this step, the system integrates with transaction management and logistics systems to prepare for the completion of service delivery.

[0833] 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.

[0834] 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.

[0835] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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."

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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 to be incorporated by reference.

[0854] The following is further disclosed regarding the embodiments described above.

[0855] (Claim 1)

[0856] A means for receiving image data and request data from the user,

[0857] A means for analyzing received image data and request data to generate proposed data,

[0858] A means for generating three-dimensional spatial display data using the proposed data,

[0859] A means for transmitting three-dimensional spatial display data to the user's terminal,

[0860] A method for simulating furniture placement based on three-dimensional spatial display data on the user's terminal.

[0861] A system that includes this.

[0862] (Claim 2)

[0863] The system according to claim 1, comprising means for generating proposal data as multiple candidates and presenting them to the user for selection.

[0864] (Claim 3)

[0865] The system according to claim 1, comprising means for automatically purchasing and delivering selected furniture after the user has selected a furniture arrangement plan.

[0866] "Example 1"

[0867] (Claim 1)

[0868] Means for receiving image information and request information from the user,

[0869] A means for analyzing received image information and extracting spatial features,

[0870] A means of generating proposal information by utilizing an AI model based on request information,

[0871] A means for generating three-dimensional display information using proposed information,

[0872] A means for transmitting three-dimensional display information to the user's information processing terminal,

[0873] A means of virtualizing the placement of items based on three-dimensional display information on a user's information processing terminal.

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, comprising means for generating proposed information as multiple options and presenting them to the user for selection.

[0877] (Claim 3)

[0878] The system according to claim 1, comprising means for automatically performing the acquisition and transfer procedures for selected items after the user has selected an item placement plan.

[0879] "Application Example 1"

[0880] (Claim 1)

[0881] A means for receiving spatial image data and request data from a user,

[0882] A means for analyzing received spatial image data and request data to generate proposed data,

[0883] A means for generating three-dimensional spatial display data using the proposed data,

[0884] A means for transmitting three-dimensional spatial display data to the user's display device,

[0885] A means for simulating the placement of objects based on three-dimensional spatial display data on the user's display device,

[0886] A means by which the user can view the selected items in a virtual array via a display device,

[0887] A method for automating electronic transaction procedures to facilitate in-store purchases of goods.

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, comprising means for generating proposal data as multiple candidates and presenting them to the user for selection.

[0891] (Claim 3)

[0892] The system according to claim 1, comprising means for automatically purchasing and transporting selected items after the user has selected an item arrangement plan.

[0893] "Example 2 of combining an emotion engine"

[0894] (Claim 1)

[0895] A means for receiving image data, request data, and emotion data from the user,

[0896] A means for analyzing received image data, request data, and emotion data, and generating proposal data using a generative AI model,

[0897] A means for generating three-dimensional spatial display data based on proposed data,

[0898] A means for transmitting three-dimensional spatial display data to a user's information processing device,

[0899] A means of simulating furniture placement based on three-dimensional spatial display data in a user's information processing device.

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, comprising means for generating proposal data as multiple candidates and presenting the preferred one in a selectable manner based on the user's sentiment data.

[0903] (Claim 3)

[0904] The system according to claim 1, comprising means for automatically purchasing, delivering, and installing selected furniture after the user has selected a furniture arrangement plan.

[0905] "Application example 2 when combining with an emotional engine"

[0906] (Claim 1)

[0907] A means for receiving image data and request data from the user,

[0908] A means for analyzing received image data and request data to generate proposed data,

[0909] A means for generating three-dimensional spatial display data using the proposed data,

[0910] A means for transmitting three-dimensional spatial display data to the user's terminal,

[0911] A means of simulating furniture placement based on three-dimensional spatial display data on the user's terminal,

[0912] A means of acquiring user sentiment data, analyzing that sentiment data, and adjusting suggestions based on user preferences,

[0913] A means to visually confirm suggested interior items on the user's terminal and enable their placement in a virtual environment.

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, comprising means for generating proposal data as multiple candidates and presenting them to the user for selection.

[0917] (Claim 3)

[0918] The system according to claim 1, comprising means for automatically purchasing and delivering selected furniture after the user has selected a furniture arrangement plan. [Explanation of symbols]

[0919] 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. A means for receiving spatial image data and request data from a user, A means for analyzing received spatial image data and request data to generate proposed data, A means for generating three-dimensional spatial display data using the proposed data, A means for transmitting three-dimensional spatial display data to the user's display device, A means for simulating the placement of objects based on three-dimensional spatial display data on the user's display device, A means by which the user can view the selected items in a virtual array via a display device, A method for automating electronic transaction procedures to facilitate in-store purchases of goods. A system that includes this.

2. The system according to claim 1, comprising means for generating proposal data as multiple candidates and presenting them to the user for selection.

3. The system according to claim 1, further comprising means for automatically purchasing and transporting selected items after the user has selected an item arrangement plan.

Images