System

Abstract

To provide a system for enabling a user to easily customize his or her favorite furniture and efficiently providing a high-quality product.SOLUTION: The system includes means for inputting details of styles, functions, arrangement, and sizes by a user through a client, means for transmitting information input by the client to a server, means for analyzing information received by the server and calling a generation AI, means for generating an optimal furniture design by the generation AI based on user information, means for optimizing materials necessary for the design by the generation AI and creating a design drawing, means for transmitting the design generated by the server to the client, means for confirming the design by the user and performing an order procedure, means for transmitting a final design to a manufacturing department by the server, and means for manufacturing the furniture based on the design received by the manufacturing department and delivering the completed furniture to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the conventional furniture purchasing process, users must choose from a limited number of options, making it difficult to obtain furniture that perfectly suits their needs. Furthermore, ready-made furniture often does not fit the user's installation space or specific requirements, resulting in low satisfaction. Furthermore, material selection and optimization are limited, sometimes resulting in a lack of durability and aesthetic appeal. The objective of this invention is to provide a system that allows users to easily customize furniture to their liking and efficiently delivers high-quality products. [Means for solving the problem]

[0005] The system of the present invention includes the following means.

[0006] 1. A means by which a user inputs details of style, function, placement, and size via a terminal.

[0007] 2. A means by which the terminal transmits the entered information to the server.

[0008] 3. A means for the server to analyze the information received and call the generation AI.

[0009] 4. A means for generative AI to generate optimal furniture designs based on user information.

[0010] 5. A means for generative AI to optimize the materials needed for a design and create a blueprint.

[0011] 6. A means by which the server transmits the generated design to the user terminal.

[0012] 7. How users can view designs and place orders.

[0013] 8. A means by which the server sends the final design to manufacturing.

[0014] 9. A means by which the manufacturing department produces furniture based on the received design and delivers the finished furniture to the user.

[0015] These methods allow users to easily design and order custom furniture according to their tastes and needs through an online platform, and generative AI can optimize materials to provide high-quality furniture that is both durable and beautiful.

[0016] "User" means any individual or entity that utilizes the System to customize and order furniture.

[0017] "Terminal" refers to an electronic device through which a user accesses the system, enters information, and reviews designs.

[0018] "Server" refers to the central computer system that receives data from users, generates furniture designs via generative AI, and manages the final design data.

[0019] "Generative AI" refers to artificial intelligence that automatically generates optimal furniture designs based on user input.

[0020] "Style" refers to the appearance and design theme of the furniture, and includes types such as modern and classic.

[0021] "Function" refers to the specific purpose or function of furniture, such as the number of drawers or the arrangement of shelves.

[0022] "Layout" refers to the location where the furniture is placed and the type of room, including information such as a living room or an office.

[0023] "Size" refers to the specific dimensions of the furniture, including width, depth, and height.

[0024] "Design" refers to the furniture blueprints and 3D models created by generative AI.

[0025] "Materials" refers to the raw materials used to make the furniture, including wood, metal, etc.

[0026] "Manufacturing department" refers to the organization or department that actually manufactures furniture based on the final design data received from the server.

[0027] "Optimization" refers to a method or process for maximizing performance or minimizing cost within given conditions or constraints.

[0028] "Delivery" refers to the act or process of delivering the completed furniture to the address specified by the user. [Brief explanation of the drawings]

[0029] [Figure 1]1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0030] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0031] First, the terms used in the following description will be explained.

[0032] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0033] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0034] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0035] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0036] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0037] [First embodiment]

[0038] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0039] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0040] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0041] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0042] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0043] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0044] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0045] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0046] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0047] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0048] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0049] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0050] System Overview

[0051] This invention is a series of systems that allows users to customize furniture design and size via an online platform, and then generative AI proposes optimal designs based on that, optimizes materials, and finally manufactures and delivers the furniture. Below is an overview of the program processing of this system and a concrete example.

[0052] Program processing flow

[0053] Entering user information

[0054] 1. The user accesses the online platform on their own device (PC or smartphone).

[0055] 2. Through the interface, the user enters details such as preferred style, desired features, furniture arrangement, size, etc. This information is temporarily stored in the device's memory and is ready to be sent.

[0056] Data Transmission and Processing

[0057] 3. The device sends the input information to the server. Specifically, the user's input information is sent as structured data in JSON format or similar.

[0058] 4. The server analyzes the received information, which may include checking the data for integrity and filtering out invalid values.

[0059] Design Generation and Material Optimization

[0060] 5. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[0061] 6. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[0062] Check the design and order

[0063] 7. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[0064] 8. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[0065] Manufacturing and Delivery

[0066] 9. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[0067] 10. Based on the design data received by the manufacturing department, the furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[0068] 11. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[0069] Specific examples

[0070] Case: Customizing your office desk

[0071] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[0072] 2. The device sends this information to the server in JSON format.

[0073] json

[0074] {

[0075] "style": "modern",

[0076] "shape": "L-shaped",

[0077] "features": {

[0078] "drawers": 3

[0079] },

[0080] "dimensions": {

[0081] "width": 150,

[0082] "depth": 70,

[0083] "height": 75

[0084] }

[0085] }

[0086] 3. The server analyzes the received data, checks its integrity and format, and then calls the generation AI.

[0087] 4. Generative AI generates the optimal desk design based on user information and optimizes materials. The final design is generated as a 3D model.

[0088] 5. The server sends the generated 3D model to the user's device.

[0089] 6. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[0090] 7. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[0091] 8. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[0092] 9. The manufacturing department packages the finished desk and delivers it to the address specified by the user.

[0093] This concludes the detailed description of the present invention, which allows users to efficiently obtain custom furniture that meets their tastes and needs.

[0094] The processing flow will be explained below.

[0095] Step 1:

[0096] A user accesses the online platform using their device (PC or smartphone), and the device displays the login screen or homepage.

[0097] Step 2:

[0098] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[0099] Step 3:

[0100] The terminal temporarily stores the entered information in memory and prepares it for transmission.

[0101] Step 4:

[0102] The device sends the input information to the server in a structured format (e.g., JSON format). An example is shown below.

[0103] json

[0104] {

[0105] "style": "modern",

[0106] "shape": "L-shaped",

[0107] "features": {

[0108] "drawers": 3

[0109] },

[0110] "dimensions": {

[0111] "width": 150,

[0112] "depth": 70,

[0113] "height": 75

[0114] }

[0115] }

[0116] Step 5:

[0117] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values.

[0118] Step 6:

[0119] The server calls the generation AI based on the analyzed information, and passes the user data as an argument to the generation AI function.

[0120] Step 7:

[0121] The generative AI generates optimal furniture designs based on user information, specifically using CAD software to create designs based on the specified style and functions.

[0122] Step 8:

[0123] Generative AI generates designs while optimizing materials, selecting the necessary materials (e.g., wood, metal) and determining the optimal materials based on cost, durability, and aesthetics.

[0124] Step 9:

[0125] The generative AI creates the final design as a 3D model or drawing data and returns it to the server.

[0126] Step 10:

[0127] The server sends the generated design to the user's terminal, which displays the received design on a user interface so that the user can check it.

[0128] Step 11:

[0129] The user checks the design and makes further adjustments as necessary. Specifically, they input any corrections or additional requests for the design via the interface.

[0130] Step 12:

[0131] Once the user has decided on a design that satisfies them, they can place an order online, and the terminal will send the entered order information to the server.

[0132] Step 13:

[0133] The server sends the final design to manufacturing, including materials lists, blueprints, and processing instructions.

[0134] Step 14:

[0135] Based on the design data received by the manufacturing department, furniture is manufactured using CNC machines and 3D printers.

[0136] Step 15:

[0137] The manufacturing department packs the completed furniture and delivers it to the specified address. The delivery status is notified to the user's terminal via the server.

[0138] This series of steps allows users to easily design and order custom furniture according to their tastes and needs.

[0139] Example 1

[0140] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0141] Conventional furniture customization and manufacturing systems have problems such as difficulty in efficiently and accurately reflecting a user's desired design, and a large amount of material waste. Furthermore, the process of specifically visualizing and re-adjusting a user's customized design is complicated, which can lead to a poor user experience.

[0142] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0143] In this invention, the server includes a means for a user to input details of the style, function, arrangement, and dimensions of an article via a terminal, a means for the terminal to transmit the input structured data to the server, and a means for the server to analyze the received information, check the consistency of the data, and filter out invalid values, thereby enabling the user to efficiently and accurately reflect their desired design.

[0144] "User" means any individual or entity that utilizes the System to customize and order items.

[0145] "Terminal" refers to an electronic device, such as a computer device or smartphone, that a user uses to access the system.

[0146] "Server" refers to the computer system that analyzes the data received from the terminal and calls the generation AI to generate the design.

[0147] "Structured data" is data that is organized according to a specific format, including JSON and XML formats.

[0148] "Generative AI" refers to an artificial intelligence model that generates optimal designs based on user requirements and selects and optimizes materials.

[0149] "Blueprint" refers to a drawing showing the detailed design of the furniture generated by the generation AI.

[0150] "Automated machines" refers to devices, such as CNC machines and 3D printers, that automatically carry out manufacturing processes based on received design data.

[0151] A "3D model" refers to digital data used to visualize furniture designs in three dimensions.

[0152] "Interface" refers to the system's operation screen that the user uses to input and adjust the design.

[0153] "Materials list" refers to a list showing the types and quantities of materials required based on the design generated by the generation AI.

[0154] "Processing Instructions" refers to data containing specific instructions for the manufacturing department to process materials in accordance with a specified design.

[0155] The present invention is a system in which users customize the design and size of an item, especially furniture, through an online platform, and a generative AI model proposes the optimal design based on that, selects and optimizes materials, and finally manufactures and delivers the item. The program process of this system is described in detail below.

[0156] System Overview

[0157] The system consists of the following main components:

[0158] 1. User terminal: An electronic device such as a PC or smartphone.

[0159] 2. Server: A computer system that analyzes the received data and invokes the generative AI model.

[0160] 3. Generative AI model: Artificial intelligence that optimizes the design and materials based on the user's customization requirements.

[0161] 4. Interface: The operation screen where the user can input and adjust the design.

[0162] 5. Automated Machinery: Automated manufacturing equipment such as CNC machines and 3D printers.

[0163] Processing Details

[0164] 1. Enter your user information:

[0165] Users access the online platform using their devices, enter a URL into the address bar of their web browser, and log in to the site.

[0166] Using the form on the interface, users enter the item's style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm), etc.

[0167] Example: Prompt = "Generate a design for a modern-style L-shaped office desk with three drawers, 150cm wide, 70cm deep, and 75cm high."

[0168] 2. Data transmission and processing:

[0169] The terminal sends the entered information to the server as structured data (JSON format).

[0170] The server analyzes the received information, performs data integrity checks and filters out invalid values.

[0171] 3. Design generation and material optimization:

[0172] The server calls a generative AI model based on the analyzed information, and the generative AI model generates a design that best suits the user's requirements.

[0173] The generative AI model generates the design while simultaneously selecting and optimizing the necessary materials.

[0174] 4. Confirm the design and place your order:

[0175] The server sends the generated 3D model to the user's device, allowing the user to visualize the design.

[0176] The user can review the design through the interface and make any necessary adjustments. Once the final design is confirmed, the user can place the order online.

[0177] 5. Production and Delivery:

[0178] The server sends the final design to the manufacturing department, transferring data including blueprints, material lists, and processing instructions.

[0179] The manufacturing department uses automated machines to create the furniture based on the received design, and finally delivers the finished furniture to the address specified by the user.

[0180] Specific examples

[0181] A user accesses the online platform and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm." The device sends this information in JSON format to the server, which analyzes the received data and calls the generative AI model. The generative AI model generates a design and sends an optimized 3D model to the user's device. The user reviews the design, makes any adjustments or final confirmations, and then completes the order. The final design is sent to the manufacturing department, where the furniture is produced using automated machines and delivered to the user.

[0182] By implementing this invention, users can efficiently obtain custom furniture that meets their tastes and needs.

[0183] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0184] Program processing steps

[0185] Step 1:

[0186] A user accesses an online platform using their device. They enter the platform URL in the address bar of their web browser and log in to the site. As input, the user's authentication information (username, password) is required, and as output, a login session is generated.

[0187] Step 2:

[0188] The user uses a form on the interface to input customization information for the furniture, such as style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm). The user's customization requirements are required as input, and the input data is temporarily stored in the device's memory as output.

[0189] Step 3:

[0190] The information entered on the device is sent to the server as structured data (JSON format). User customization information is required as input, and JSON data is generated as output and sent to the server. The specific operation is to send the data to the server using JavaScript AJAX.

[0191] Step 4:

[0192] The server analyzes the received information. Specifically, it parses the received JSON data and validates its contents. As input, it requires the JSON data sent from the terminal, and as output, it checks the data for consistency and filters out invalid values. This ensures that the data is formatted correctly and does not contain any invalid values.

[0193] Step 5:

[0194] The server calls the generative AI model based on the analyzed information. The analyzed user information is required as input, and a design generation request is sent to the generative AI model as output. Specifically, the analysis data is sent to the API endpoint of the generative AI model.

[0195] Step 6:

[0196] The generative AI model generates product designs based on user information and optimizes materials. It takes a design generation request sent from the server as input, and generates an optimized design and materials list as output. The model uses machine learning algorithms to generate designs that meet the user's requirements.

[0197] Step 7:

[0198] The server sends the generated 3D model data to the user's device. The input requires design data from the generative AI model, and the output is the 3D model sent to the user's device. Specifically, the design data is transferred to the user's device in JSON format, and the 3D model is displayed on a web page.

[0199] Step 8:

[0200] The user reviews the design through an interface and makes any necessary adjustments. As input, the user can visualize the 3D model and input specific modifications through the interface. As output, the adjusted design is generated.

[0201] Step 9:

[0202] The user confirms the design and completes the order online. The input is the reconciled design and payment information, and the output is a notification that the order is complete. Specific actions include adding the design to the cart, entering payment information, and confirming the order.

[0203] Step 10:

[0204] The server sends the final design to the manufacturing department.,The inputs required are the final design data,,design drawings, material lists, and processing instructions, and the output,is the completion of data transfer to the manufacturing department.,Specifically, the design data is sent to the server in the,manufacturing department.

[0205] Step 11:

[0206] The manufacturing department uses automated machines to manufacture furniture based on the design data received. The inputs are a design drawing and a materials list, and the output is the final product. Specific operations include processing materials using CNC machines and 3D printers, and assembling the furniture.

[0207] Step 12:

[0208] The manufacturing department packs the finished furniture and delivers it to the address specified by the user. The input is the finished product and delivery address information, and the output is the shipping of the furniture. Specific operations include printing a shipping label and delivering the furniture to the user via a logistics service.

[0209] (Application example 1)

[0210] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0211] Modern consumers often want to customize furniture to suit their preferences and needs when purchasing it. However, with typical online shopping, users are unable to directly touch the product and visualization is limited, making it difficult to select the furniture they desire. Another issue is that the customization process requires a lot of time and effort. Furthermore, resources can be wasted during the manufacturing process. Therefore, the objective of this invention is to provide a system that allows users to check and adjust furniture designs in real time, and ensures efficient manufacturing and delivery using optimized resources.

[0212] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0213] In this invention, the server includes: means for a user to input details of style, function, layout, and size via an information processing device; means for the information processing device to transmit the input information to a group of information processing devices; means for the group of information processing devices to analyze the received information and call a generative AI model; means for the generative AI model to generate an optimal furniture design based on the user information; means for the generative AI model to optimize resources required for the design and create a blueprint; means for the group of information processing devices to transmit the generated design to the user's information processing device; means for the user to confirm the design through a head-mounted display and complete an order procedure; means for the group of information processing devices to transmit the final design to a manufacturing department; and means for the manufacturing department to manufacture the furniture based on the received design and deliver the completed furniture to the user. This allows the user to confirm and adjust the furniture design in real time in a virtual space, streamlining the ordering process and minimizing resource waste.

[0214] "Means for users to input details of style, function, placement, and size via an information processing device" refers to an interface that allows users to input specific requirements for furniture design using an information processing device such as a computer or smartphone.

[0215] The "means for transmitting information input by an information processing device to a group of information processing devices" is a function for transmitting data input by a user to a cloud server or another information processing system.

[0216] "Means for analyzing information received by a group of information processing devices and invoking a generative AI model" refers to technology that enables a server or cloud system to analyze data received from a user and activate a generative AI model based on that data.

[0217] "Means by which a generative AI model generates optimal furniture designs based on user information" refers to the process by which a pre-trained generative AI model automatically creates the most suitable furniture design based on user input information.

[0218] "Means by which a generative AI model optimizes the resources required for design and creates blueprints" refers to the process by which a generative AI model optimally selects and arranges the materials and parts required for design to form a specific blueprint.

[0219] "Means for transmitting the design generated by the information processing device group to the user information processing device" refers to a function that transmits design data generated by a cloud server or other information processing system to the user's computer or smartphone.

[0220] "Means for users to check the design through a head-mounted display and place an order" refers to an interface that allows users to wear a head-mounted display (HMD), visually check the generated furniture design, and confirm the order if they are satisfied.

[0221] "Means for the information processing device group to send the final design to the manufacturing department" refers to the process by which a cloud server or another information processing system sends finalized design data to the system or equipment in charge of manufacturing.

[0222] "Means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user" refers to the process in which the manufacturing department manufactures furniture using automated equipment according to the received design drawings and then delivers the product to the address specified by the user.

[0223] System Overview

[0224] This invention is a system in which a user uses an information processing device to customize the design and size of furniture through an online platform, and a generative AI model proposes an optimal design based on that, and then optimizes the necessary resources for manufacturing and delivery. Details and specific examples of this system are provided below.

[0225] Hardware and Software

[0226] User information processing device

[0227] Users access the online platform using an information processing device, such as a computer or smartphone, which has a web browser or dedicated application installed, and which provides an interface through which users can input details about their furniture design.

[0228] Servers and information processing devices

[0229] The server, located in the cloud, receives and analyzes the data sent by the user, including checking the data for consistency and filtering outliers. It then invokes a generative AI model to generate the optimal design based on the input data.

[0230] Generative AI Models

[0231] The generative AI model is a pre-trained AI model that generates optimal furniture designs based on user input. Specifically, Hugging Face's GPT-4 model is used. In addition to generating designs, the generative AI model also optimizes resources.

[0232] Program processing explanation

[0233] The program works as follows: First, the user inputs details such as style, function, size, etc. via an information processing device. This input information is sent to the server in JSON format.

[0234] The server analyzes the received data, checks its consistency, and then calls the generative AI model. The generative AI model generates an optimal design based on the received data and optimizes resources. The generated design and blueprint are then sent from the server to the user's information processing device.

[0235] Using a head-mounted display (HMD), users can view and adjust the 3D model generated in real time within the virtual space. Once adjustments are complete, users can view the final design and place an order online.

[0236] The final design is sent from the server to the manufacturing department, where the furniture is manufactured using automated manufacturing equipment based on the received design data. The finished product is then packaged and delivered to the address specified by the user.

[0237] Specific examples

[0238] If a user wants to customize a "dining table" in the "midcentury modern" style, they might input the following prompts into the generative AI model:

[0239] Style: Mid-century modern

[0240] Furniture: Dining table

[0241] Length: 180 cm

[0242] Width: 90cm

[0243] Height: 75 cm

[0244] Features: Expandable, Material: Walnut Wood

[0245] The user can view the generated 3D model through a head-mounted display and confirm their order if they are satisfied, allowing them to efficiently obtain custom furniture.

[0246] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0247] Step 1:

[0248] The user inputs details of the furniture style, function, placement, and size via an information processing device, which involves the user entering specific specifications of the desired furniture into input fields on a computer or smartphone interface. This input information is temporarily stored on the device in JSON format.

[0249] Input: Furniture details regarding style, function, placement, and size

[0250] Output: User input data in JSON format

[0251] Step 2:

[0252] The terminal sends the entered information to the server. In this step, the user-entered data stored in JSON format is sent to the server via an HTTP request. The server receives this data and stores it in a database.

[0253] Input: User-supplied data in JSON format

[0254] Output: User-entered data sent to the server

[0255] Step 3:

[0256] The server analyzes the received information and calls the generative AI model. Specifically, the server checks the data for consistency and filters out invalid values ​​and missing data. Then, based on the data whose consistency has been confirmed, it calls the generative AI model (e.g., GPT-4) via an API request.

[0257] Input: User-entered data stored on the server

[0258] Output: The prompt sent to the generative AI model

[0259] Step 4:

[0260] The generative AI model generates the optimal furniture design based on user information. The generative AI model (GPT-4) analyzes the user's input data and generates the optimal design based on it. This design is output as a drawing or 3D model and returned to the server.

[0261] Input: The prompt sent to the generative AI model

[0262] Output: 3D design data of the generated furniture

[0263] Step 5:

[0264] The generative AI model optimizes the resources required for the design and creates a blueprint. The generative AI model selects the optimal combination of resources (materials, parts, etc.) required for the design and creates a blueprint based on that. This blueprint is optimized to minimize resource waste.

[0265] Input: 3D design data of the generated furniture

[0266] Output: Resource-optimized blueprint

[0267] Step 6:

[0268] The server sends the generated design to the user's information processing device, and the server sends the generated 3D model and optimized blueprint to the user's information processing device, allowing the user to check the design in real time.

[0269] Input: Resource-optimized blueprint

[0270] Output: 3D design data sent to the user's device

[0271] Step 7:

[0272] The user checks the design through a head-mounted display and places an order. The user wears a head-mounted display (HMD) and checks the 3D model generated in the virtual space. If satisfied, the user confirms the order through the interface.

[0273] Input: 3D design data sent to the user's device

[0274] Output: Confirmed order data

[0275] Step 8:

[0276] The server sends the final design to the manufacturing department. The server sends the finalized design drawings and order data to the manufacturing department, which then starts the manufacturing process.

[0277] Input: Confirmed order data and design drawings

[0278] Output: Final design data sent to manufacturing

[0279] Step 9:

[0280] The manufacturing department manufactures the furniture based on the received design and delivers the finished furniture to the user. The manufacturing department uses the received design data to manufacture the furniture using automated manufacturing equipment (CNC machines, 3D printers, etc.). Once manufacturing is complete, the furniture is packaged and delivered to the address specified by the user.

[0281] Input: Final design data sent to manufacturing

[0282] Output: Finished furniture delivered to the user

[0283] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0284] System Overview

[0285] This system allows users to customize furniture design and size through an online platform, and then generative AI proposes optimal designs based on the customization, optimizes materials, and uses an emotion engine to recognize and reflect the user's emotions, thereby improving user satisfaction and enabling more personalized recommendations.

[0286] Program processing flow

[0287] User information input and emotion recognition

[0288] 1. A user accesses the online platform using their device (PC or smartphone). The device displays the login screen or homepage.

[0289] 2. Through the interface, the user inputs detailed information such as the preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and size (e.g., 150 cm width, 70 cm depth, 75 cm height).

[0290] 3. An emotion engine built into the device recognizes emotions from the user's facial expressions, input, interactions, etc. For example, a camera can be used to analyze the user's facial expressions and emotions can be extracted from voice input.

[0291] Data Transmission and Processing

[0292] 4. The device temporarily stores the input information and emotion data in memory and prepares it for transmission.

[0293] 5. The device sends the input information and emotion data to the server in a structured format (e.g., JSON format).

[0294] json

[0295] {

[0296] "style": "modern",

[0297] "shape": "L-shaped",

[0298] "features": {

[0299] "drawers": 3

[0300] },

[0301] "dimensions": {

[0302] "width": 150,

[0303] "depth": 70,

[0304] "height": 75

[0305] },

[0306] "emotions": {

[0307] "happiness": 0.8,

[0308] "neutral": 0.2

[0309] }

[0310] }

[0311] 6. The server analyzes the received information, checks the data for consistency, and filters out invalid values.

[0312] Design Generation and Material Optimization

[0313] 7. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[0314] 8. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[0315] 9. Based on the emotional data obtained from the emotion engine, the generative AI will reflect this in the design and material selection. For example, if the user expresses a high level of happiness, it will suggest a more enthusiastic design.

[0316] Check the design and order

[0317] 10. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[0318] 11. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place their order online.

[0319] Manufacturing and Delivery

[0320] 12. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[0321] 13. Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[0322] 14. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[0323] Specific examples

[0324] Case: Office desk customization and emotion recognition

[0325] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[0326] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[0327] 3. The device sends this information to the server in JSON format.

[0328] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[0329] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[0330] 6. The server sends the generated 3D model to the user's device.

[0331] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[0332] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[0333] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[0334] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[0335] This process allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their sentiments.

[0336] The processing flow will be explained below.

[0337] Step 1:

[0338] A user accesses the online platform on their device (PC or smartphone). The device displays a login screen, and the user enters their account information to log in.

[0339] Step 2:

[0340] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[0341] Step 3:

[0342] The emotion engine built into the device recognizes emotions through the user's facial expressions and voice input. For example, a camera can be used to analyze the user's facial expressions in real time and extract emotional states (e.g., happiness, impatience, satisfaction, etc.).

[0343] Step 4:

[0344] The device temporarily stores the input information and recognized emotion data in memory and prepares for transmission.

[0345] Step 5:

[0346] The device sends input information and emotion data to the server in a structured format (e.g., JSON format). An example is shown below.

[0347] json

[0348] {

[0349] "style": "modern",

[0350] "shape": "L-shaped",

[0351] "features": {

[0352] "drawers": 3

[0353] },

[0354] "dimensions": {

[0355] "width": 150,

[0356] "depth": 70,

[0357] "height": 75

[0358] },

[0359] "emotions": {

[0360] "happiness": 0.8,

[0361] "neutral": 0.2

[0362] }

[0363] }

[0364] Step 6:

[0365] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values. Emotional data is also analyzed.

[0366] Step 7:

[0367] The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[0368] Step 8:

[0369] The generative AI generates furniture designs that match the style and functionality specified by the user. It also adjusts the design by taking into account emotional data. For example, if the user expresses a high level of happiness, it will make more proactive design suggestions.

[0370] Step 9:

[0371] The generative AI simultaneously generates the design and selects and optimizes materials, taking into account cost, durability, and aesthetics.

[0372] Step 10:

[0373] The generative AI creates the final design as a 3D model or drawing data and returns it to the server. The generative AI creates a visually appealing 3D model based on the emotion data.

[0374] Step 11:

[0375] The server sends the generated design to the user's device, which launches a 3D model viewer so the user can view the design.

[0376] Step 12:

[0377] The user checks the design and makes further adjustments if necessary. The user again inputs any corrections or additions via the interface.

[0378] Step 13:

[0379] Once the user has decided on a design that satisfies them, they can place an order online, with the terminal sending the order information to the server.

[0380] Step 14:

[0381] The server sends the final design to the manufacturing department, including materials lists, blueprints, and processing instructions.

[0382] Step 15:

[0383] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[0384] Step 16:

[0385] The manufacturing department packs the completed furniture and delivers it to the address specified by the user. The delivery status is notified to the user's terminal via the server.

[0386] This series of steps allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their emotions.

[0387] Example 2

[0388] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0389] Conventional furniture design and manufacturing systems do not take into account the user's emotions when customizing a product to suit their preferences and needs, making it difficult to provide personalized suggestions. Furthermore, there is a lack of a way for users to see in real time the design that reflects their own emotions and experiences. These issues make it difficult to increase user satisfaction.

[0390] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input details of style, function, layout, and size via a terminal; a means for the terminal to transmit the input information and user emotion data to the server; a means for the server to analyze the received information and emotion data and call a generation AI; a means for the generation AI to generate an optimal furniture design based on the user information and emotion data; a means for the generation AI to optimize materials required for the design and create a blueprint; a means for the server to transmit the generated design to the user terminal; a means for the user to confirm the design and complete an order procedure; a means for the server to transmit the final design to a manufacturing department; and a means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user. This enables personalized furniture designs and proposals that reflect the user's emotions.

[0391] A "terminal" is an electronic device that allows a user to input, send, and receive information.

[0392] The "server" is a central computer that analyzes the information received from the terminal, calls the generation AI, generates furniture designs, and sends the received designs to the manufacturing department.

[0393] "Generative AI" is an artificial intelligence model that generates optimal furniture designs based on user input and emotional data, and optimizes the necessary materials.

[0394] "Emotion data" is numerical or text data that represents emotions extracted from the user's facial expressions or voice input.

[0395] "Blueprints" are drawings or documents that show the detailed design and construction of furniture created by the generative AI.

[0396] "Online Platform" means a web-based system that users access via a terminal to input details of their furniture designs.

[0397] An "interface" is a screen or operation panel that allows a user to input information and check the design.

[0398] "Manufacturing" refers to the factory or department that receives the final design and produces the furniture using automated manufacturing equipment such as CNC machines and 3D printers.

[0399] The "design readjustment interface" is an operation panel that allows the user to review the generated design and make changes as needed.

[0400] The present invention is a system that allows users to access an online platform using their devices and input details of their furniture design, such as style, function, placement, and size, and then uses a generative AI model to suggest optimal designs and materials, and furthermore, uses an emotion engine to recognize and reflect the user's emotions, allowing users to receive more personalized suggestions.

[0401] Hardware and Software Configuration

[0402] Terminal

[0403] A terminal is an electronic device such as a PC or smartphone that allows users to input information. The terminal is equipped with a browser and an emotion engine. The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice.

[0404] server

[0405] The server is a central computer that analyzes the information received from the device, calls the generative AI, and generates the optimal design. It also sends the generated design to the user's device and sends the final design to the manufacturing department.

[0406] Generative AI Models

[0407] The generative AI model is an artificial intelligence that generates optimal furniture designs based on user input and emotional data. Because the model is trained in advance using a large design dataset, it can automatically generate designs that meet user requirements.

[0408] manufacturing department

[0409] The manufacturing department uses automated manufacturing equipment such as CNC machines and 3D printers to produce the furniture based on the final design sent from the server, and the finished furniture is then properly packaged and delivered to the user.

[0410] Data processing and calculation

[0411] Collecting input information and emotional data from devices

[0412] Users access the online platform and enter details such as their preferred style, placement, size, etc. The emotion engine built into the device uses the camera and microphone to collect the user's emotional data.

[0413] Data analysis by server and calling of generation AI

[0414] The server receives the information sent from the device and checks the consistency of the data. After checking the consistency, the server calls the generative AI model and generates the optimal design based on the user's requests. The generative AI also reflects the user's emotional data and makes personalized suggestions.

[0415] Design generation and material optimization using generative AI

[0416] The generative AI model generates designs based on user information and emotional data, optimizing the necessary materials, resulting in efficient and high-quality designs.

[0417] Design submission and order processing by the server

[0418] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they are satisfied with the final design, they can place their order online.

[0419] Furniture production and delivery by the manufacturing department

[0420] The final design is sent from the server to the manufacturing department, which produces the furniture using CNC machines, 3D printers, etc. The finished furniture is then properly packaged and delivered to the address specified by the user.

[0421] Specific cases and examples of prompts

[0422] Case: Office desk customization and emotion recognition

[0423] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[0424] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[0425] 3. The device sends this information to the server in JSON format.

[0426] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[0427] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[0428] 6. The server sends the generated 3D model to the user's device.

[0429] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[0430] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[0431] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[0432] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[0433] Prompt Sentence Examples

[0434] "I want to design a modern style sofa that will fit in my living room. It should be 200cm wide, 90cm deep, and 85cm high."

[0435] "I want a bookshelf with a classic design. It's 180cm high, 80cm wide, and 30cm deep. I'd also like it to have three drawers."

[0436] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0437] Step 1:

[0438] The user accesses the online platform on their device and logs in. The user enters detailed information about the furniture design, such as style, function, placement, and size.

[0439] Input: Information on style, function, position, size, etc.

[0440] Output: The terminal stores the input information and prepares it for transmission.

[0441] What happens: The user fills in the form and clicks the "Submit" button.

[0442] Step 2:

[0443] The device collects input information and the user's emotional data. The emotional data is acquired by an emotion engine built into the device using the camera and microphone.

[0444] Input: User input information, facial and vocal emotion data

[0445] Output: Structured data (JSON format)

[0446] How it works: The device captures the user's facial expressions with a camera, and the emotion engine analyzes them in real time. It also extracts emotions from voice input.

[0447] Step 3:

[0448] The device converts the collected information into JSON format and sends it to the server.

[0449] Input: Structured data (JSON format)

[0450] Output: Data sent to the server

[0451] What happens: Structured data is sent to the server using an HTTPS request.

[0452] Step 4:

[0453] The server analyzes the information it receives, checks the integrity of the data, and filters out invalid values.

[0454] Input: JSON data sent from the terminal

[0455] Output: Parsed and consistent data

[0456] Specific behavior: The server parses the received JSON data, performs schema validation, and filters out any invalid values.

[0457] Step 5:

[0458] The server calls up a generative AI model based on the analyzed information, which then generates a furniture design that best suits the user's requirements.

[0459] Input: Analyzed and consistent data

[0460] Output: Generated design and optimized materials list

[0461] Specific operation: Sends API calls to the generative AI model to generate a design based on the input data.

[0462] Step 6:

[0463] The generative AI model generates the design, while simultaneously selecting and optimizing the necessary materials and creating the blueprint.

[0464] Input: User information, emotion data

[0465] Output: Designs, blueprints, material lists

[0466] What it does: Generate blueprints, create materials lists, and calculate the optimal combination of materials needed.

[0467] Step 7:

[0468] The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[0469] Input: Generated design, blueprint, material list

[0470] Output: 3D model data sent to the user's device

[0471] Specific operation: The blueprint is converted into a 3D model and the data is sent to the device, where it is displayed in a dedicated viewer.

[0472] Step 8:

[0473] The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[0474] Input: 3D model data

[0475] Output: Final design and order information

[0476] Specific operation: Rotate, zoom in and out to check the 3D model, then re-edit the form. When you are satisfied, click the "Order" button.

[0477] Step 9:

[0478] The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[0479] Input: Final design and order information

[0480] Output: Blueprints, material lists, and processing instructions sent to the manufacturing department

[0481] Specific operation: Send design data to the manufacturing API.

[0482] Step 10:

[0483] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[0484] Input: Design drawings, material lists, processing instructions

[0485] Output: Manufactured furniture

[0486] How it works: Based on the blueprint, a CNC machine cuts and processes the wood as specified. A 3D printer prints the parts.

[0487] Step 11:

[0488] The manufacturing department packs the finished furniture and delivers it to the address specified by the user.

[0489] Input: Manufactured furniture, user address

[0490] Output: Fully assembled furniture delivered to the user's address

[0491] Specific operations: Pack the finished product, enter the user's address into the delivery instruction system, and hand it over to the delivery company.

[0492] (Application example 2)

[0493] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0494] Currently, when users customize furniture online, the proposed designs often do not adequately reflect the user's emotions or specific needs. Furthermore, there is no function that takes user emotions into account when optimizing the design or selecting materials, leaving a lack of means to improve user satisfaction. Therefore, there is a need for a system that can improve the user experience and provide more personalized suggestions that reflect emotions.

[0495] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0496] In this invention, the server includes a means for a user to input details of style, function, layout, and size via a terminal, a means for an emotion recognition engine built into the terminal to acquire the user's emotion data and send it to the server, and a means for a generation AI to generate an optimal furniture design based on the user information, thereby enabling design proposals that take emotions into consideration.

[0497] "Terminal" means a computing device through which a User accesses and inputs information into the online platform.

[0498] "Input information" refers to detailed information about style, function, layout, and size input by the user via the terminal.

[0499] The "server" is a remote computer system that receives input information, analyzes it, and invokes the generating AI.

[0500] "Generative AI" is an artificial intelligence technology that generates optimal furniture designs based on user input, optimizes materials, and creates blueprints.

[0501] An "emotion recognition engine" is software that acquires and analyzes emotional data from a user's facial expressions, voice, etc.

[0502] "Emotion data" is data that quantifies or categorizes the user's current emotional state.

[0503] "Design adjustment" refers to the process in which the generative AI modifies and improves the design based on the acquired emotional data.

[0504] "Design confirmation" is the process by which the user visually checks the generated design and makes any necessary adjustments.

[0505] "Ordering process" refers to the process in which the user finally decides on a design that satisfies them and places their purchase / order online.

[0506] "Manufacturing department" refers to the department or facility that actually manufactures furniture based on the final design sent from the server.

[0507] System Overview

[0508] This invention is a system in which users customize furniture design and size via a terminal, and a generative AI proposes optimal designs based on that. Furthermore, by using an emotion engine to recognize and reflect the user's emotions, more personalized design proposals are realized.

[0509] Hardware and software used

[0510] Hardware:

[0511] Devices: PC, smartphone, tablet, etc.

[0512] Camera: Built-in or external camera for capturing user facial expressions

[0513] software:

[0514] Emotion recognition engine: A library or algorithm for extracting emotional data from a user's facial expressions and voice. A specific example is the "EmotionRecognition Library."

[0515] Generative AI: An AI model that generates optimal furniture designs based on user information. A specific example is "DesignGenerator."

[0516] Server and communication protocol: A server and communication protocol for sending, receiving, and analyzing data. A specific example is an HTTP POST request.

[0517] Processing flow and specific examples

[0518] 1. User Input and Emotion Recognition

[0519] Users input information such as their preferred style, desired functions, furniture layout, and size via a terminal. For example, they input detailed information such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm."

[0520] 2. Acquiring Emotion Data

[0521] The device's built-in emotion recognition engine captures the user's facial expressions and voice via a camera and microphone, extracting emotional data, which is then converted into a numerical value, such as "Happiness 0.8" or "Neutrality 0.2."

[0522] 3. Data transmission and analysis

[0523] This input information and emotion data are temporarily stored in memory and sent to the server in a structured data format (e.g., JSON format). The server analyzes the received data, checks its consistency, and filters out invalid values.

[0524] 4. Design generation and adjustment

[0525] The server then calls the generation AI based on the analyzed information. The generation AI generates the optimal design based on the user's input information and emotional data, optimizing the necessary materials to create a blueprint. The generation AI takes the emotional data into account, and suggests a more ambitious design if, for example, the user is expressing a high level of happiness.

[0526] 5. Confirm the design and place your order

[0527] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they have decided on a design they are satisfied with, they can place an order online.

[0528] Prompt Sentence Examples

[0529] An example of a prompt given to a generative AI model might look something like this:

[0530] Create a modern L-shaped office desk with 3 drawers. Dimensions: width 150cm, depth 70cm, height 75cm. Optimize the materials based on user happiness level of 0.8.

[0531] Based on this example, the system can efficiently design, propose, and accept orders for custom furniture that reflects the user's preferences and feelings.

[0532] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0533] Step 1:

[0534] The user inputs detailed information about the furniture's style, function, layout, and size via the terminal. The input information is temporarily stored in the terminal's memory. Specifically, data such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm" are input.

[0535] Step 2:

[0536] The emotion recognition engine built into the device captures the user's facial expressions and voice via the camera and microphone. The emotion recognition engine analyzes the user's emotional data and generates numerical emotional data. For example, it can obtain data such as "Happiness 0.8" or "Neutrality 0.2."

[0537] Step 3:

[0538] The device converts the input information and emotion data into a structured data format (JSON format) and sends it to the server, where preprocessing is also performed to check the data for consistency and filter out invalid values.

[0539] Step 4:

[0540] The server analyzes the received information and checks the data integrity and format. Valid data is obtained as a result of the analysis. For example, user information and emotion data are stored in an organized format on the server.

[0541] Step 5:

[0542] The server then calls a generative AI based on the analyzed information. The generative AI uses a pre-trained model to generate the optimal furniture design for the user. The input is user information and emotional data, and the output is an optimal design that reflects the user's needs.

[0543] Step 6:

[0544] The generative AI simultaneously generates the design and selects and optimizes the necessary materials. Based on emotional data, the design and material selection are fine-tuned. For example, if the user expresses a high level of happiness, a bright color scheme will be suggested.

[0545] Step 7:

[0546] The generated design and material information are sent from the server to the user's device. The device displays the received design as a 3D model for the user to confirm. The input here is the generated design data, and the output is the 3D model display.

[0547] Step 8:

[0548] The user checks the 3D model and makes any necessary adjustments. Once they are satisfied with the design, they place their order online. The terminal sends the order information and the final design to the server.

[0549] Step 9:

[0550] The server sends the received order data and final design to the manufacturing department, which uses automated machines to produce the furniture. The resulting output is specific manufacturing instructions and blueprints.

[0551] Step 10:

[0552] The manufactured furniture is then packaged and delivered to the address specified by the user, where the user can receive their custom furniture order.

[0553] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0554] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0555] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0556] [Second embodiment]

[0557] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0558] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0559] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0560] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0561] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0562] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0563] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0564] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0565] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0566] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0567] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0568] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0569] System Overview

[0570] This invention is a series of systems that allows users to customize furniture design and size via an online platform, and then generative AI proposes optimal designs based on that, optimizes materials, and finally manufactures and delivers the furniture. Below is an overview of the program processing of this system and a concrete example.

[0571] Program processing flow

[0572] Entering user information

[0573] 1. The user accesses the online platform on their own device (PC or smartphone).

[0574] 2. Through the interface, the user enters details such as preferred style, desired features, furniture arrangement, size, etc. This information is temporarily stored in the device's memory and is ready to be sent.

[0575] Data Transmission and Processing

[0576] 3. The device sends the input information to the server. Specifically, the user's input information is sent as structured data in JSON format or similar.

[0577] 4. The server analyzes the received information, which may include checking the data for integrity and filtering out invalid values.

[0578] Design Generation and Material Optimization

[0579] 5. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[0580] 6. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[0581] Check the design and order

[0582] 7. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[0583] 8. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[0584] Manufacturing and Delivery

[0585] 9. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[0586] 10. Based on the design data received by the manufacturing department, the furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[0587] 11. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[0588] Specific examples

[0589] Case: Customizing your office desk

[0590] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[0591] 2. The device sends this information to the server in JSON format.

[0592] json

[0593] {

[0594] "style": "modern",

[0595] "shape": "L-shaped",

[0596] "features": {

[0597] "drawers": 3

[0598] },

[0599] "dimensions": {

[0600] "width": 150,

[0601] "depth": 70,

[0602] "height": 75

[0603] }

[0604] }

[0605] 3. The server analyzes the received data, checks its integrity and format, and then calls the generation AI.

[0606] 4. Generative AI generates the optimal desk design based on user information and optimizes materials. The final design is generated as a 3D model.

[0607] 5. The server sends the generated 3D model to the user's device.

[0608] 6. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[0609] 7. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[0610] 8. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[0611] 9. The manufacturing department packages the finished desk and delivers it to the address specified by the user.

[0612] This concludes the detailed description of the present invention, which allows users to efficiently obtain custom furniture that meets their tastes and needs.

[0613] The processing flow will be explained below.

[0614] Step 1:

[0615] A user accesses the online platform using their device (PC or smartphone), and the device displays the login screen or homepage.

[0616] Step 2:

[0617] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[0618] Step 3:

[0619] The terminal temporarily stores the entered information in memory and prepares it for transmission.

[0620] Step 4:

[0621] The device sends the input information to the server in a structured format (e.g., JSON format). An example is shown below.

[0622] json

[0623] {

[0624] "style": "modern",

[0625] "shape": "L-shaped",

[0626] "features": {

[0627] "drawers": 3

[0628] },

[0629] "dimensions": {

[0630] "width": 150,

[0631] "depth": 70,

[0632] "height": 75

[0633] }

[0634] }

[0635] Step 5:

[0636] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values.

[0637] Step 6:

[0638] The server calls the generation AI based on the analyzed information, and passes the user data as an argument to the generation AI function.

[0639] Step 7:

[0640] The generative AI generates optimal furniture designs based on user information, specifically using CAD software to create designs based on the specified style and functions.

[0641] Step 8:

[0642] Generative AI generates designs while optimizing materials, selecting the necessary materials (e.g., wood, metal) and determining the optimal materials based on cost, durability, and aesthetics.

[0643] Step 9:

[0644] The generative AI creates the final design as a 3D model or drawing data and returns it to the server.

[0645] Step 10:

[0646] The server sends the generated design to the user's terminal, which displays the received design on a user interface so that the user can check it.

[0647] Step 11:

[0648] The user checks the design and makes further adjustments as necessary. Specifically, they input any corrections or additional requests for the design via the interface.

[0649] Step 12:

[0650] Once the user has decided on a design that satisfies them, they can place an order online, and the terminal will send the entered order information to the server.

[0651] Step 13:

[0652] The server sends the final design to manufacturing, including materials lists, blueprints, and processing instructions.

[0653] Step 14:

[0654] Based on the design data received by the manufacturing department, furniture is manufactured using CNC machines and 3D printers.

[0655] Step 15:

[0656] The manufacturing department packs the completed furniture and delivers it to the specified address. The delivery status is notified to the user's terminal via the server.

[0657] This series of steps allows users to easily design and order custom furniture according to their tastes and needs.

[0658] Example 1

[0659] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0660] Conventional furniture customization and manufacturing systems have problems such as difficulty in efficiently and accurately reflecting a user's desired design, and a large amount of material waste. Furthermore, the process of specifically visualizing and re-adjusting a user's customized design is complicated, which can lead to a poor user experience.

[0661] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0662] In this invention, the server includes a means for a user to input details of the style, function, arrangement, and dimensions of an article via a terminal, a means for the terminal to transmit the input structured data to the server, and a means for the server to analyze the received information, check the consistency of the data, and filter out invalid values, thereby enabling the user to efficiently and accurately reflect their desired design.

[0663] "User" means any individual or entity that utilizes the System to customize and order items.

[0664] "Terminal" refers to an electronic device, such as a computer device or smartphone, that a user uses to access the system.

[0665] "Server" refers to the computer system that analyzes the data received from the terminal and calls the generation AI to generate the design.

[0666] "Structured data" is data that is organized according to a specific format, including JSON and XML formats.

[0667] "Generative AI" refers to an artificial intelligence model that generates optimal designs based on user requirements and selects and optimizes materials.

[0668] "Blueprint" refers to a drawing showing the detailed design of the furniture generated by the generation AI.

[0669] "Automated machines" refers to devices, such as CNC machines and 3D printers, that automatically carry out manufacturing processes based on received design data.

[0670] A "3D model" refers to digital data used to visualize furniture designs in three dimensions.

[0671] "Interface" refers to the system's operation screen that the user uses to input and adjust the design.

[0672] "Materials list" refers to a list showing the types and quantities of materials required based on the design generated by the generation AI.

[0673] "Processing Instructions" refers to data containing specific instructions for the manufacturing department to process materials in accordance with a specified design.

[0674] The present invention is a system in which users customize the design and size of an item, especially furniture, through an online platform, and a generative AI model proposes the optimal design based on that, selects and optimizes materials, and finally manufactures and delivers the item. The program process of this system is described in detail below.

[0675] System Overview

[0676] The system consists of the following main components:

[0677] 1. User terminal: An electronic device such as a PC or smartphone.

[0678] 2. Server: A computer system that analyzes the received data and invokes the generative AI model.

[0679] 3. Generative AI model: Artificial intelligence that optimizes the design and materials based on the user's customization requirements.

[0680] 4. Interface: The operation screen where the user can input and adjust the design.

[0681] 5. Automated Machinery: Automated manufacturing equipment such as CNC machines and 3D printers.

[0682] Processing Details

[0683] 1. Enter your user information:

[0684] Users access the online platform using their devices, enter a URL into the address bar of their web browser, and log in to the site.

[0685] Using the form on the interface, users enter the item's style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm), etc.

[0686] Example: Prompt = "Generate a design for a modern-style L-shaped office desk with three drawers, 150cm wide, 70cm deep, and 75cm high."

[0687] 2. Data transmission and processing:

[0688] The terminal sends the entered information to the server as structured data (JSON format).

[0689] The server analyzes the received information, performs data integrity checks and filters out invalid values.

[0690] 3. Design generation and material optimization:

[0691] The server calls a generative AI model based on the analyzed information, and the generative AI model generates a design that best suits the user's requirements.

[0692] The generative AI model generates the design while simultaneously selecting and optimizing the necessary materials.

[0693] 4. Confirm the design and place your order:

[0694] The server sends the generated 3D model to the user's device, allowing the user to visualize the design.

[0695] The user can review the design through the interface and make any necessary adjustments. Once the final design is confirmed, the user can place the order online.

[0696] 5. Production and Delivery:

[0697] The server sends the final design to the manufacturing department, transferring data including blueprints, material lists, and processing instructions.

[0698] The manufacturing department uses automated machines to create the furniture based on the received design, and finally delivers the finished furniture to the address specified by the user.

[0699] Specific examples

[0700] A user accesses the online platform and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm." The device sends this information in JSON format to the server, which analyzes the received data and calls the generative AI model. The generative AI model generates a design and sends an optimized 3D model to the user's device. The user reviews the design, makes any adjustments or final confirmations, and then completes the order. The final design is sent to the manufacturing department, where the furniture is produced using automated machines and delivered to the user.

[0701] By implementing this invention, users can efficiently obtain custom furniture that meets their tastes and needs.

[0702] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0703] Program processing steps

[0704] Step 1:

[0705] A user accesses an online platform using their device. They enter the platform URL in the address bar of their web browser and log in to the site. As input, the user's authentication information (username, password) is required, and as output, a login session is generated.

[0706] Step 2:

[0707] The user uses a form on the interface to input customization information for the furniture, such as style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm). The user's customization requirements are required as input, and the input data is temporarily stored in the device's memory as output.

[0708] Step 3:

[0709] The information entered on the device is sent to the server as structured data (JSON format). User customization information is required as input, and JSON data is generated as output and sent to the server. The specific operation is to send the data to the server using JavaScript AJAX.

[0710] Step 4:

[0711] The server analyzes the received information. Specifically, it parses the received JSON data and validates its contents. As input, it requires the JSON data sent from the terminal, and as output, it checks the data for consistency and filters out invalid values. This ensures that the data is formatted correctly and does not contain any invalid values.

[0712] Step 5:

[0713] The server calls the generative AI model based on the analyzed information. The analyzed user information is required as input, and a design generation request is sent to the generative AI model as output. Specifically, the analysis data is sent to the API endpoint of the generative AI model.

[0714] Step 6:

[0715] The generative AI model generates product designs based on user information and optimizes materials. It takes a design generation request sent from the server as input, and generates an optimized design and materials list as output. The model uses machine learning algorithms to generate designs that meet the user's requirements.

[0716] Step 7:

[0717] The server sends the generated 3D model data to the user's device. The input requires design data from the generative AI model, and the output is the 3D model sent to the user's device. Specifically, the design data is transferred to the user's device in JSON format, and the 3D model is displayed on a web page.

[0718] Step 8:

[0719] The user reviews the design through an interface and makes any necessary adjustments. As input, the user can visualize the 3D model and input specific modifications through the interface. As output, the adjusted design is generated.

[0720] Step 9:

[0721] The user confirms the design and completes the order online. The input is the reconciled design and payment information, and the output is a notification that the order is complete. Specific actions include adding the design to the cart, entering payment information, and confirming the order.

[0722] Step 10:

[0723] The server sends the final design to the manufacturing department.,The inputs required are the final design data,,design drawings, material lists, and processing instructions, and the output,is the completion of data transfer to the manufacturing department.,Specifically, the design data is sent to the server in the,manufacturing department.

[0724] Step 11:

[0725] The manufacturing department uses automated machines to manufacture furniture based on the design data received. The inputs are a design drawing and a materials list, and the output is the final product. Specific operations include processing materials using CNC machines and 3D printers, and assembling the furniture.

[0726] Step 12:

[0727] The manufacturing department packs the finished furniture and delivers it to the address specified by the user. The input is the finished product and delivery address information, and the output is the shipping of the furniture. Specific operations include printing a shipping label and delivering the furniture to the user via a logistics service.

[0728] (Application example 1)

[0729] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0730] Modern consumers often want to customize furniture to suit their preferences and needs when purchasing it. However, with typical online shopping, users are unable to directly touch the product and visualization is limited, making it difficult to select the furniture they desire. Another issue is that the customization process requires a lot of time and effort. Furthermore, resources can be wasted during the manufacturing process. Therefore, the objective of this invention is to provide a system that allows users to check and adjust furniture designs in real time, and ensures efficient manufacturing and delivery using optimized resources.

[0731] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0732] In this invention, the server includes: means for a user to input details of style, function, layout, and size via an information processing device; means for the information processing device to transmit the input information to a group of information processing devices; means for the group of information processing devices to analyze the received information and call a generative AI model; means for the generative AI model to generate an optimal furniture design based on the user information; means for the generative AI model to optimize resources required for the design and create a blueprint; means for the group of information processing devices to transmit the generated design to the user's information processing device; means for the user to confirm the design through a head-mounted display and complete an order procedure; means for the group of information processing devices to transmit the final design to a manufacturing department; and means for the manufacturing department to manufacture the furniture based on the received design and deliver the completed furniture to the user. This allows the user to confirm and adjust the furniture design in real time in a virtual space, streamlining the ordering process and minimizing resource waste.

[0733] "Means for users to input details of style, function, placement, and size via an information processing device" refers to an interface that allows users to input specific requirements for furniture design using an information processing device such as a computer or smartphone.

[0734] The "means for transmitting information input by an information processing device to a group of information processing devices" is a function for transmitting data input by a user to a cloud server or another information processing system.

[0735] "Means for analyzing information received by a group of information processing devices and invoking a generative AI model" refers to technology that enables a server or cloud system to analyze data received from a user and activate a generative AI model based on that data.

[0736] "Means by which a generative AI model generates optimal furniture designs based on user information" refers to the process by which a pre-trained generative AI model automatically creates the most suitable furniture design based on user input information.

[0737] "Means by which a generative AI model optimizes the resources required for design and creates blueprints" refers to the process by which a generative AI model optimally selects and arranges the materials and parts required for design to form a specific blueprint.

[0738] "Means for transmitting the design generated by the information processing device group to the user information processing device" refers to a function that transmits design data generated by a cloud server or other information processing system to the user's computer or smartphone.

[0739] "Means for users to check the design through a head-mounted display and place an order" refers to an interface that allows users to wear a head-mounted display (HMD), visually check the generated furniture design, and confirm the order if they are satisfied.

[0740] "Means for the information processing device group to send the final design to the manufacturing department" refers to the process by which a cloud server or another information processing system sends finalized design data to the system or equipment in charge of manufacturing.

[0741] "Means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user" refers to the process in which the manufacturing department manufactures furniture using automated equipment according to the received design drawings and then delivers the product to the address specified by the user.

[0742] System Overview

[0743] This invention is a system in which a user uses an information processing device to customize the design and size of furniture through an online platform, and a generative AI model proposes an optimal design based on that, and then optimizes the necessary resources for manufacturing and delivery. Details and specific examples of this system are provided below.

[0744] Hardware and Software

[0745] User information processing device

[0746] Users access the online platform using an information processing device, such as a computer or smartphone, which has a web browser or dedicated application installed, and which provides an interface through which users can input details about their furniture design.

[0747] Servers and information processing devices

[0748] The server, located in the cloud, receives and analyzes the data sent by the user, including checking the data for consistency and filtering outliers. It then invokes a generative AI model to generate the optimal design based on the input data.

[0749] Generative AI Models

[0750] The generative AI model is a pre-trained AI model that generates optimal furniture designs based on user input. Specifically, Hugging Face's GPT-4 model is used. In addition to generating designs, the generative AI model also optimizes resources.

[0751] Program processing explanation

[0752] The program works as follows: First, the user inputs details such as style, function, size, etc. via an information processing device. This input information is sent to the server in JSON format.

[0753] The server analyzes the received data, checks its consistency, and then calls the generative AI model. The generative AI model generates an optimal design based on the received data and optimizes resources. The generated design and blueprint are then sent from the server to the user's information processing device.

[0754] Using a head-mounted display (HMD), users can view and adjust the 3D model generated in real time within the virtual space. Once adjustments are complete, users can view the final design and place an order online.

[0755] The final design is sent from the server to the manufacturing department, where the furniture is manufactured using automated manufacturing equipment based on the received design data. The finished product is then packaged and delivered to the address specified by the user.

[0756] Specific examples

[0757] If a user wants to customize a "dining table" in the "midcentury modern" style, they might input the following prompts into the generative AI model:

[0758] Style: Mid-century modern

[0759] Furniture: Dining table

[0760] Length: 180 cm

[0761] Width: 90cm

[0762] Height: 75 cm

[0763] Features: Expandable, Material: Walnut Wood

[0764] The user can view the generated 3D model through a head-mounted display and confirm their order if they are satisfied, allowing them to efficiently obtain custom furniture.

[0765] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0766] Step 1:

[0767] The user inputs details of the furniture style, function, placement, and size via an information processing device, which involves the user entering specific specifications of the desired furniture into input fields on a computer or smartphone interface. This input information is temporarily stored on the device in JSON format.

[0768] Input: Furniture details regarding style, function, placement, and size

[0769] Output: User input data in JSON format

[0770] Step 2:

[0771] The terminal sends the entered information to the server. In this step, the user-entered data stored in JSON format is sent to the server via an HTTP request. The server receives this data and stores it in a database.

[0772] Input: User-supplied data in JSON format

[0773] Output: User-entered data sent to the server

[0774] Step 3:

[0775] The server analyzes the received information and calls the generative AI model. Specifically, the server checks the data for consistency and filters out invalid values ​​and missing data. Then, based on the data whose consistency has been confirmed, it calls the generative AI model (e.g., GPT-4) via an API request.

[0776] Input: User-entered data stored on the server

[0777] Output: The prompt sent to the generative AI model

[0778] Step 4:

[0779] The generative AI model generates the optimal furniture design based on user information. The generative AI model (GPT-4) analyzes the user's input data and generates the optimal design based on it. This design is output as a drawing or 3D model and returned to the server.

[0780] Input: The prompt sent to the generative AI model

[0781] Output: 3D design data of the generated furniture

[0782] Step 5:

[0783] The generative AI model optimizes the resources required for the design and creates a blueprint. The generative AI model selects the optimal combination of resources (materials, parts, etc.) required for the design and creates a blueprint based on that. This blueprint is optimized to minimize resource waste.

[0784] Input: 3D design data of the generated furniture

[0785] Output: Resource-optimized blueprint

[0786] Step 6:

[0787] The server sends the generated design to the user's information processing device, and the server sends the generated 3D model and optimized blueprint to the user's information processing device, allowing the user to check the design in real time.

[0788] Input: Resource-optimized blueprint

[0789] Output: 3D design data sent to the user's device

[0790] Step 7:

[0791] The user checks the design through a head-mounted display and places an order. The user wears a head-mounted display (HMD) and checks the 3D model generated in the virtual space. If satisfied, the user confirms the order through the interface.

[0792] Input: 3D design data sent to the user's device

[0793] Output: Confirmed order data

[0794] Step 8:

[0795] The server sends the final design to the manufacturing department. The server sends the finalized design drawings and order data to the manufacturing department, which then starts the manufacturing process.

[0796] Input: Confirmed order data and design drawings

[0797] Output: Final design data sent to manufacturing

[0798] Step 9:

[0799] The manufacturing department manufactures the furniture based on the received design and delivers the finished furniture to the user. The manufacturing department uses the received design data to manufacture the furniture using automated manufacturing equipment (CNC machines, 3D printers, etc.). Once manufacturing is complete, the furniture is packaged and delivered to the address specified by the user.

[0800] Input: Final design data sent to manufacturing

[0801] Output: Finished furniture delivered to the user

[0802] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0803] System Overview

[0804] This system allows users to customize furniture design and size through an online platform, and then generative AI proposes optimal designs based on the customization, optimizes materials, and uses an emotion engine to recognize and reflect the user's emotions, thereby improving user satisfaction and enabling more personalized recommendations.

[0805] Program processing flow

[0806] User information input and emotion recognition

[0807] 1. A user accesses the online platform using their device (PC or smartphone). The device displays the login screen or homepage.

[0808] 2. Through the interface, the user inputs detailed information such as the preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and size (e.g., 150 cm width, 70 cm depth, 75 cm height).

[0809] 3. An emotion engine built into the device recognizes emotions from the user's facial expressions, input, interactions, etc. For example, a camera can be used to analyze the user's facial expressions and emotions can be extracted from voice input.

[0810] Data Transmission and Processing

[0811] 4. The device temporarily stores the input information and emotion data in memory and prepares it for transmission.

[0812] 5. The device sends the input information and emotion data to the server in a structured format (e.g., JSON format).

[0813] json

[0814] {

[0815] "style": "modern",

[0816] "shape": "L-shaped",

[0817] "features": {

[0818] "drawers": 3

[0819] },

[0820] "dimensions": {

[0821] "width": 150,

[0822] "depth": 70,

[0823] "height": 75

[0824] },

[0825] "emotions": {

[0826] "happiness": 0.8,

[0827] "neutral": 0.2

[0828] }

[0829] }

[0830] 6. The server analyzes the received information, checks the data for consistency, and filters out invalid values.

[0831] Design Generation and Material Optimization

[0832] 7. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[0833] 8. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[0834] 9. Based on the emotional data obtained from the emotion engine, the generative AI will reflect this in the design and material selection. For example, if the user expresses a high level of happiness, it will suggest a more enthusiastic design.

[0835] Check the design and order

[0836] 10. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[0837] 11. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place their order online.

[0838] Manufacturing and Delivery

[0839] 12. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[0840] 13. Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[0841] 14. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[0842] Specific examples

[0843] Case: Office desk customization and emotion recognition

[0844] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[0845] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[0846] 3. The device sends this information to the server in JSON format.

[0847] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[0848] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[0849] 6. The server sends the generated 3D model to the user's device.

[0850] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[0851] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[0852] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[0853] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[0854] This process allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their sentiments.

[0855] The processing flow will be explained below.

[0856] Step 1:

[0857] A user accesses the online platform on their device (PC or smartphone). The device displays a login screen, and the user enters their account information to log in.

[0858] Step 2:

[0859] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[0860] Step 3:

[0861] The emotion engine built into the device recognizes emotions through the user's facial expressions and voice input. For example, a camera can be used to analyze the user's facial expressions in real time and extract emotional states (e.g., happiness, impatience, satisfaction, etc.).

[0862] Step 4:

[0863] The device temporarily stores the input information and recognized emotion data in memory and prepares for transmission.

[0864] Step 5:

[0865] The device sends input information and emotion data to the server in a structured format (e.g., JSON format). An example is shown below.

[0866] json

[0867] {

[0868] "style": "modern",

[0869] "shape": "L-shaped",

[0870] "features": {

[0871] "drawers": 3

[0872] },

[0873] "dimensions": {

[0874] "width": 150,

[0875] "depth": 70,

[0876] "height": 75

[0877] },

[0878] "emotions": {

[0879] "happiness": 0.8,

[0880] "neutral": 0.2

[0881] }

[0882] }

[0883] Step 6:

[0884] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values. Emotional data is also analyzed.

[0885] Step 7:

[0886] The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[0887] Step 8:

[0888] The generative AI generates furniture designs that match the style and functionality specified by the user. It also adjusts the design by taking into account emotional data. For example, if the user expresses a high level of happiness, it will make more proactive design suggestions.

[0889] Step 9:

[0890] The generative AI simultaneously generates the design and selects and optimizes materials, taking into account cost, durability, and aesthetics.

[0891] Step 10:

[0892] The generative AI creates the final design as a 3D model or drawing data and returns it to the server. The generative AI creates a visually appealing 3D model based on the emotion data.

[0893] Step 11:

[0894] The server sends the generated design to the user's device, which launches a 3D model viewer so the user can view the design.

[0895] Step 12:

[0896] The user checks the design and makes further adjustments if necessary. The user again inputs any corrections or additions via the interface.

[0897] Step 13:

[0898] Once the user has decided on a design that satisfies them, they can place an order online, with the terminal sending the order information to the server.

[0899] Step 14:

[0900] The server sends the final design to the manufacturing department, including materials lists, blueprints, and processing instructions.

[0901] Step 15:

[0902] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[0903] Step 16:

[0904] The manufacturing department packs the completed furniture and delivers it to the address specified by the user. The delivery status is notified to the user's terminal via the server.

[0905] This series of steps allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their emotions.

[0906] Example 2

[0907] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0908] Conventional furniture design and manufacturing systems do not take into account the user's emotions when customizing a product to suit their preferences and needs, making it difficult to provide personalized suggestions. Furthermore, there is a lack of a way for users to see in real time the design that reflects their own emotions and experiences. These issues make it difficult to increase user satisfaction.

[0909] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input details of style, function, layout, and size via a terminal; a means for the terminal to transmit the input information and user emotion data to the server; a means for the server to analyze the received information and emotion data and call a generation AI; a means for the generation AI to generate an optimal furniture design based on the user information and emotion data; a means for the generation AI to optimize materials required for the design and create a blueprint; a means for the server to transmit the generated design to the user terminal; a means for the user to confirm the design and complete an order procedure; a means for the server to transmit the final design to a manufacturing department; and a means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user. This enables personalized furniture designs and proposals that reflect the user's emotions.

[0910] A "terminal" is an electronic device that allows a user to input, send, and receive information.

[0911] The "server" is a central computer that analyzes the information received from the terminal, calls the generation AI, generates furniture designs, and sends the received designs to the manufacturing department.

[0912] "Generative AI" is an artificial intelligence model that generates optimal furniture designs based on user input and emotional data, and optimizes the necessary materials.

[0913] "Emotion data" is numerical or text data that represents emotions extracted from the user's facial expressions or voice input.

[0914] "Blueprints" are drawings or documents that show the detailed design and construction of furniture created by the generative AI.

[0915] "Online Platform" means a web-based system that users access via a terminal to input details of their furniture designs.

[0916] An "interface" is a screen or operation panel that allows a user to input information and check the design.

[0917] "Manufacturing" refers to the factory or department that receives the final design and produces the furniture using automated manufacturing equipment such as CNC machines and 3D printers.

[0918] The "design readjustment interface" is an operation panel that allows the user to review the generated design and make changes as needed.

[0919] The present invention is a system that allows users to access an online platform using their devices and input details of their furniture design, such as style, function, placement, and size, and then uses a generative AI model to suggest optimal designs and materials, and furthermore, uses an emotion engine to recognize and reflect the user's emotions, allowing users to receive more personalized suggestions.

[0920] Hardware and Software Configuration

[0921] Terminal

[0922] A terminal is an electronic device such as a PC or smartphone that allows users to input information. The terminal is equipped with a browser and an emotion engine. The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice.

[0923] server

[0924] The server is a central computer that analyzes the information received from the device, calls the generative AI, and generates the optimal design. It also sends the generated design to the user's device and sends the final design to the manufacturing department.

[0925] Generative AI Models

[0926] The generative AI model is an artificial intelligence that generates optimal furniture designs based on user input and emotional data. Because the model is trained in advance using a large design dataset, it can automatically generate designs that meet user requirements.

[0927] manufacturing department

[0928] The manufacturing department uses automated manufacturing equipment such as CNC machines and 3D printers to produce the furniture based on the final design sent from the server, and the finished furniture is then properly packaged and delivered to the user.

[0929] Data processing and calculation

[0930] Collecting input information and emotional data from devices

[0931] Users access the online platform and enter details such as their preferred style, placement, size, etc. The emotion engine built into the device uses the camera and microphone to collect the user's emotional data.

[0932] Data analysis by server and calling of generation AI

[0933] The server receives the information sent from the device and checks the consistency of the data. After checking the consistency, the server calls the generative AI model and generates the optimal design based on the user's requests. The generative AI also reflects the user's emotional data and makes personalized suggestions.

[0934] Design generation and material optimization using generative AI

[0935] The generative AI model generates designs based on user information and emotional data, optimizing the necessary materials, resulting in efficient and high-quality designs.

[0936] Design submission and order processing by the server

[0937] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they are satisfied with the final design, they can place their order online.

[0938] Furniture production and delivery by the manufacturing department

[0939] The final design is sent from the server to the manufacturing department, which produces the furniture using CNC machines, 3D printers, etc. The finished furniture is then properly packaged and delivered to the address specified by the user.

[0940] Specific cases and examples of prompts

[0941] Case: Office desk customization and emotion recognition

[0942] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[0943] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[0944] 3. The device sends this information to the server in JSON format.

[0945] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[0946] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[0947] 6. The server sends the generated 3D model to the user's device.

[0948] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[0949] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[0950] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[0951] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[0952] Prompt Sentence Examples

[0953] "I want to design a modern style sofa that will fit in my living room. It should be 200cm wide, 90cm deep, and 85cm high."

[0954] "I want a bookshelf with a classic design. It's 180cm high, 80cm wide, and 30cm deep. I'd also like it to have three drawers."

[0955] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0956] Step 1:

[0957] The user accesses the online platform on their device and logs in. The user enters detailed information about the furniture design, such as style, function, placement, and size.

[0958] Input: Information on style, function, position, size, etc.

[0959] Output: The terminal stores the input information and prepares it for transmission.

[0960] What happens: The user fills in the form and clicks the "Submit" button.

[0961] Step 2:

[0962] The device collects input information and the user's emotional data. The emotional data is acquired by an emotion engine built into the device using the camera and microphone.

[0963] Input: User input information, facial and vocal emotion data

[0964] Output: Structured data (JSON format)

[0965] How it works: The device captures the user's facial expressions with a camera, and the emotion engine analyzes them in real time. It also extracts emotions from voice input.

[0966] Step 3:

[0967] The device converts the collected information into JSON format and sends it to the server.

[0968] Input: Structured data (JSON format)

[0969] Output: Data sent to the server

[0970] What happens: Structured data is sent to the server using an HTTPS request.

[0971] Step 4:

[0972] The server analyzes the information it receives, checks the integrity of the data, and filters out invalid values.

[0973] Input: JSON data sent from the terminal

[0974] Output: Parsed and consistent data

[0975] Specific behavior: The server parses the received JSON data, performs schema validation, and filters out any invalid values.

[0976] Step 5:

[0977] The server calls up a generative AI model based on the analyzed information, which then generates a furniture design that best suits the user's requirements.

[0978] Input: Analyzed and consistent data

[0979] Output: Generated design and optimized materials list

[0980] Specific operation: Sends API calls to the generative AI model to generate a design based on the input data.

[0981] Step 6:

[0982] The generative AI model generates the design, while simultaneously selecting and optimizing the necessary materials and creating the blueprint.

[0983] Input: User information, emotion data

[0984] Output: Designs, blueprints, material lists

[0985] What it does: Generate blueprints, create materials lists, and calculate the optimal combination of materials needed.

[0986] Step 7:

[0987] The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[0988] Input: Generated design, blueprint, material list

[0989] Output: 3D model data sent to the user's device

[0990] Specific operation: The blueprint is converted into a 3D model and the data is sent to the device, where it is displayed in a dedicated viewer.

[0991] Step 8:

[0992] The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[0993] Input: 3D model data

[0994] Output: Final design and order information

[0995] Specific operation: Rotate, zoom in and out to check the 3D model, then re-edit the form. When you are satisfied, click the "Order" button.

[0996] Step 9:

[0997] The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[0998] Input: Final design and order information

[0999] Output: Blueprints, material lists, and processing instructions sent to the manufacturing department

[1000] Specific operation: Send design data to the manufacturing API.

[1001] Step 10:

[1002] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1003] Input: Design drawings, material lists, processing instructions

[1004] Output: Manufactured furniture

[1005] How it works: Based on the blueprint, a CNC machine cuts and processes the wood as specified. A 3D printer prints the parts.

[1006] Step 11:

[1007] The manufacturing department packs the finished furniture and delivers it to the address specified by the user.

[1008] Input: Manufactured furniture, user address

[1009] Output: Fully assembled furniture delivered to the user's address

[1010] Specific operations: Pack the finished product, enter the user's address into the delivery instruction system, and hand it over to the delivery company.

[1011] (Application example 2)

[1012] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1013] Currently, when users customize furniture online, the proposed designs often do not adequately reflect the user's emotions or specific needs. Furthermore, there is no function that takes user emotions into account when optimizing the design or selecting materials, leaving a lack of means to improve user satisfaction. Therefore, there is a need for a system that can improve the user experience and provide more personalized suggestions that reflect emotions.

[1014] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1015] In this invention, the server includes a means for a user to input details of style, function, layout, and size via a terminal, a means for an emotion recognition engine built into the terminal to acquire the user's emotion data and send it to the server, and a means for a generation AI to generate an optimal furniture design based on the user information, thereby enabling design proposals that take emotions into consideration.

[1016] "Terminal" means a computing device through which a User accesses and inputs information into the online platform.

[1017] "Input information" refers to detailed information about style, function, layout, and size input by the user via the terminal.

[1018] The "server" is a remote computer system that receives input information, analyzes it, and invokes the generating AI.

[1019] "Generative AI" is an artificial intelligence technology that generates optimal furniture designs based on user input, optimizes materials, and creates blueprints.

[1020] An "emotion recognition engine" is software that acquires and analyzes emotional data from a user's facial expressions, voice, etc.

[1021] "Emotion data" is data that quantifies or categorizes the user's current emotional state.

[1022] "Design adjustment" refers to the process in which the generative AI modifies and improves the design based on the acquired emotional data.

[1023] "Design confirmation" is the process by which the user visually checks the generated design and makes any necessary adjustments.

[1024] "Ordering process" refers to the process in which the user finally decides on a design that satisfies them and places their purchase / order online.

[1025] "Manufacturing department" refers to the department or facility that actually manufactures furniture based on the final design sent from the server.

[1026] System Overview

[1027] This invention is a system in which users customize furniture design and size via a terminal, and a generative AI proposes optimal designs based on that. Furthermore, by using an emotion engine to recognize and reflect the user's emotions, more personalized design proposals are realized.

[1028] Hardware and software used

[1029] Hardware:

[1030] Devices: PC, smartphone, tablet, etc.

[1031] Camera: Built-in or external camera for capturing user facial expressions

[1032] software:

[1033] Emotion recognition engine: A library or algorithm for extracting emotional data from a user's facial expressions and voice. A specific example is the "EmotionRecognition Library."

[1034] Generative AI: An AI model that generates optimal furniture designs based on user information. A specific example is "DesignGenerator."

[1035] Server and communication protocol: A server and communication protocol for sending, receiving, and analyzing data. A specific example is an HTTP POST request.

[1036] Processing flow and specific examples

[1037] 1. User Input and Emotion Recognition

[1038] Users input information such as their preferred style, desired functions, furniture layout, and size via a terminal. For example, they input detailed information such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm."

[1039] 2. Acquiring Emotion Data

[1040] The device's built-in emotion recognition engine captures the user's facial expressions and voice via a camera and microphone, extracting emotional data, which is then converted into a numerical value, such as "Happiness 0.8" or "Neutrality 0.2."

[1041] 3. Data transmission and analysis

[1042] This input information and emotion data are temporarily stored in memory and sent to the server in a structured data format (e.g., JSON format). The server analyzes the received data, checks its consistency, and filters out invalid values.

[1043] 4. Design generation and adjustment

[1044] The server then calls the generation AI based on the analyzed information. The generation AI generates the optimal design based on the user's input information and emotional data, optimizing the necessary materials to create a blueprint. The generation AI takes the emotional data into account, and suggests a more ambitious design if, for example, the user is expressing a high level of happiness.

[1045] 5. Confirm the design and place your order

[1046] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they have decided on a design they are satisfied with, they can place an order online.

[1047] Prompt Sentence Examples

[1048] An example of a prompt given to a generative AI model might look something like this:

[1049] Create a modern L-shaped office desk with 3 drawers. Dimensions: width 150cm, depth 70cm, height 75cm. Optimize the materials based on user happiness level of 0.8.

[1050] Based on this example, the system can efficiently design, propose, and accept orders for custom furniture that reflects the user's preferences and feelings.

[1051] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1052] Step 1:

[1053] The user inputs detailed information about the furniture's style, function, layout, and size via the terminal. The input information is temporarily stored in the terminal's memory. Specifically, data such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm" are input.

[1054] Step 2:

[1055] The emotion recognition engine built into the device captures the user's facial expressions and voice via the camera and microphone. The emotion recognition engine analyzes the user's emotional data and generates numerical emotional data. For example, it can obtain data such as "Happiness 0.8" or "Neutrality 0.2."

[1056] Step 3:

[1057] The device converts the input information and emotion data into a structured data format (JSON format) and sends it to the server, where preprocessing is also performed to check the data for consistency and filter out invalid values.

[1058] Step 4:

[1059] The server analyzes the received information and checks the data integrity and format. Valid data is obtained as a result of the analysis. For example, user information and emotion data are stored in an organized format on the server.

[1060] Step 5:

[1061] The server then calls a generative AI based on the analyzed information. The generative AI uses a pre-trained model to generate the optimal furniture design for the user. The input is user information and emotional data, and the output is an optimal design that reflects the user's needs.

[1062] Step 6:

[1063] The generative AI simultaneously generates the design and selects and optimizes the necessary materials. Based on emotional data, the design and material selection are fine-tuned. For example, if the user expresses a high level of happiness, a bright color scheme will be suggested.

[1064] Step 7:

[1065] The generated design and material information are sent from the server to the user's device. The device displays the received design as a 3D model for the user to confirm. The input here is the generated design data, and the output is the 3D model display.

[1066] Step 8:

[1067] The user checks the 3D model and makes any necessary adjustments. Once they are satisfied with the design, they place their order online. The terminal sends the order information and the final design to the server.

[1068] Step 9:

[1069] The server sends the received order data and final design to the manufacturing department, which uses automated machines to produce the furniture. The resulting output is specific manufacturing instructions and blueprints.

[1070] Step 10:

[1071] The manufactured furniture is then packaged and delivered to the address specified by the user, where the user can receive their custom furniture order.

[1072] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1073] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1074] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1075] [Third embodiment]

[1076] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1077] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1078] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1079] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1080] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1081] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1082] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1083] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1084] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1085] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1086] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1087] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1088] System Overview

[1089] This invention is a series of systems that allows users to customize furniture design and size via an online platform, and then generative AI proposes optimal designs based on that, optimizes materials, and finally manufactures and delivers the furniture. Below is an overview of the program processing of this system and a concrete example.

[1090] Program processing flow

[1091] Entering user information

[1092] 1. The user accesses the online platform on their own device (PC or smartphone).

[1093] 2. Through the interface, the user enters details such as preferred style, desired features, furniture arrangement, size, etc. This information is temporarily stored in the device's memory and is ready to be sent.

[1094] Data Transmission and Processing

[1095] 3. The device sends the input information to the server. Specifically, the user's input information is sent as structured data in JSON format or similar.

[1096] 4. The server analyzes the received information, which may include checking the data for integrity and filtering out invalid values.

[1097] Design Generation and Material Optimization

[1098] 5. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[1099] 6. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[1100] Check the design and order

[1101] 7. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[1102] 8. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[1103] Manufacturing and Delivery

[1104] 9. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[1105] 10. Based on the design data received by the manufacturing department, the furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1106] 11. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[1107] Specific examples

[1108] Case: Customizing your office desk

[1109] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[1110] 2. The device sends this information to the server in JSON format.

[1111] json

[1112] {

[1113] "style": "modern",

[1114] "shape": "L-shaped",

[1115] "features": {

[1116] "drawers": 3

[1117] },

[1118] "dimensions": {

[1119] "width": 150,

[1120] "depth": 70,

[1121] "height": 75

[1122] }

[1123] }

[1124] 3. The server analyzes the received data, checks its integrity and format, and then calls the generation AI.

[1125] 4. Generative AI generates the optimal desk design based on user information and optimizes materials. The final design is generated as a 3D model.

[1126] 5. The server sends the generated 3D model to the user's device.

[1127] 6. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[1128] 7. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[1129] 8. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[1130] 9. The manufacturing department packages the finished desk and delivers it to the address specified by the user.

[1131] This concludes the detailed description of the present invention, which allows users to efficiently obtain custom furniture that meets their tastes and needs.

[1132] The processing flow will be explained below.

[1133] Step 1:

[1134] A user accesses the online platform using their device (PC or smartphone), and the device displays the login screen or homepage.

[1135] Step 2:

[1136] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[1137] Step 3:

[1138] The terminal temporarily stores the entered information in memory and prepares it for transmission.

[1139] Step 4:

[1140] The device sends the input information to the server in a structured format (e.g., JSON format). An example is shown below.

[1141] json

[1142] {

[1143] "style": "modern",

[1144] "shape": "L-shaped",

[1145] "features": {

[1146] "drawers": 3

[1147] },

[1148] "dimensions": {

[1149] "width": 150,

[1150] "depth": 70,

[1151] "height": 75

[1152] }

[1153] }

[1154] Step 5:

[1155] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values.

[1156] Step 6:

[1157] The server calls the generation AI based on the analyzed information, and passes the user data as an argument to the generation AI function.

[1158] Step 7:

[1159] The generative AI generates optimal furniture designs based on user information, specifically using CAD software to create designs based on the specified style and functions.

[1160] Step 8:

[1161] Generative AI generates designs while optimizing materials, selecting the necessary materials (e.g., wood, metal) and determining the optimal materials based on cost, durability, and aesthetics.

[1162] Step 9:

[1163] The generative AI creates the final design as a 3D model or drawing data and returns it to the server.

[1164] Step 10:

[1165] The server sends the generated design to the user's terminal, which displays the received design on a user interface so that the user can check it.

[1166] Step 11:

[1167] The user checks the design and makes further adjustments as necessary. Specifically, they input any corrections or additional requests for the design via the interface.

[1168] Step 12:

[1169] Once the user has decided on a design that satisfies them, they can place an order online, and the terminal will send the entered order information to the server.

[1170] Step 13:

[1171] The server sends the final design to manufacturing, including materials lists, blueprints, and processing instructions.

[1172] Step 14:

[1173] Based on the design data received by the manufacturing department, furniture is manufactured using CNC machines and 3D printers.

[1174] Step 15:

[1175] The manufacturing department packs the completed furniture and delivers it to the specified address. The delivery status is notified to the user's terminal via the server.

[1176] This series of steps allows users to easily design and order custom furniture according to their tastes and needs.

[1177] Example 1

[1178] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1179] Conventional furniture customization and manufacturing systems have problems such as difficulty in efficiently and accurately reflecting a user's desired design, and a large amount of material waste. Furthermore, the process of specifically visualizing and re-adjusting a user's customized design is complicated, which can lead to a poor user experience.

[1180] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1181] In this invention, the server includes a means for a user to input details of the style, function, arrangement, and dimensions of an article via a terminal, a means for the terminal to transmit the input structured data to the server, and a means for the server to analyze the received information, check the consistency of the data, and filter out invalid values, thereby enabling the user to efficiently and accurately reflect their desired design.

[1182] "User" means any individual or entity that utilizes the System to customize and order items.

[1183] "Terminal" refers to an electronic device, such as a computer device or smartphone, that a user uses to access the system.

[1184] "Server" refers to the computer system that analyzes the data received from the terminal and calls the generation AI to generate the design.

[1185] "Structured data" is data that is organized according to a specific format, including JSON and XML formats.

[1186] "Generative AI" refers to an artificial intelligence model that generates optimal designs based on user requirements and selects and optimizes materials.

[1187] "Blueprint" refers to a drawing showing the detailed design of the furniture generated by the generation AI.

[1188] "Automated machines" refers to devices, such as CNC machines and 3D printers, that automatically carry out manufacturing processes based on received design data.

[1189] A "3D model" refers to digital data used to visualize furniture designs in three dimensions.

[1190] "Interface" refers to the system's operation screen that the user uses to input and adjust the design.

[1191] "Materials list" refers to a list showing the types and quantities of materials required based on the design generated by the generation AI.

[1192] "Processing Instructions" refers to data containing specific instructions for the manufacturing department to process materials in accordance with a specified design.

[1193] The present invention is a system in which users customize the design and size of an item, especially furniture, through an online platform, and a generative AI model proposes the optimal design based on that, selects and optimizes materials, and finally manufactures and delivers the item. The program process of this system is described in detail below.

[1194] System Overview

[1195] The system consists of the following main components:

[1196] 1. User terminal: An electronic device such as a PC or smartphone.

[1197] 2. Server: A computer system that analyzes the received data and invokes the generative AI model.

[1198] 3. Generative AI model: Artificial intelligence that optimizes the design and materials based on the user's customization requirements.

[1199] 4. Interface: The operation screen where the user can input and adjust the design.

[1200] 5. Automated Machinery: Automated manufacturing equipment such as CNC machines and 3D printers.

[1201] Processing Details

[1202] 1. Enter your user information:

[1203] Users access the online platform using their devices, enter a URL into the address bar of their web browser, and log in to the site.

[1204] Using the form on the interface, users enter the item's style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm), etc.

[1205] Example: Prompt = "Generate a design for a modern-style L-shaped office desk with three drawers, 150cm wide, 70cm deep, and 75cm high."

[1206] 2. Data transmission and processing:

[1207] The terminal sends the entered information to the server as structured data (JSON format).

[1208] The server analyzes the received information, performs data integrity checks and filters out invalid values.

[1209] 3. Design generation and material optimization:

[1210] The server calls a generative AI model based on the analyzed information, and the generative AI model generates a design that best suits the user's requirements.

[1211] The generative AI model generates the design while simultaneously selecting and optimizing the necessary materials.

[1212] 4. Confirm the design and place your order:

[1213] The server sends the generated 3D model to the user's device, allowing the user to visualize the design.

[1214] The user can review the design through the interface and make any necessary adjustments. Once the final design is confirmed, the user can place the order online.

[1215] 5. Production and Delivery:

[1216] The server sends the final design to the manufacturing department, transferring data including blueprints, material lists, and processing instructions.

[1217] The manufacturing department uses automated machines to create the furniture based on the received design, and finally delivers the finished furniture to the address specified by the user.

[1218] Specific examples

[1219] A user accesses the online platform and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm." The device sends this information in JSON format to the server, which analyzes the received data and calls the generative AI model. The generative AI model generates a design and sends an optimized 3D model to the user's device. The user reviews the design, makes any adjustments or final confirmations, and then completes the order. The final design is sent to the manufacturing department, where the furniture is produced using automated machines and delivered to the user.

[1220] By implementing this invention, users can efficiently obtain custom furniture that meets their tastes and needs.

[1221] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1222] Program processing steps

[1223] Step 1:

[1224] A user accesses an online platform using their device. They enter the platform URL in the address bar of their web browser and log in to the site. As input, the user's authentication information (username, password) is required, and as output, a login session is generated.

[1225] Step 2:

[1226] The user uses a form on the interface to input customization information for the furniture, such as style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm). The user's customization requirements are required as input, and the input data is temporarily stored in the device's memory as output.

[1227] Step 3:

[1228] The information entered on the device is sent to the server as structured data (JSON format). User customization information is required as input, and JSON data is generated as output and sent to the server. The specific operation is to send the data to the server using JavaScript AJAX.

[1229] Step 4:

[1230] The server analyzes the received information. Specifically, it parses the received JSON data and validates its contents. As input, it requires the JSON data sent from the terminal, and as output, it checks the data for consistency and filters out invalid values. This ensures that the data is formatted correctly and does not contain any invalid values.

[1231] Step 5:

[1232] The server calls the generative AI model based on the analyzed information. The analyzed user information is required as input, and a design generation request is sent to the generative AI model as output. Specifically, the analysis data is sent to the API endpoint of the generative AI model.

[1233] Step 6:

[1234] The generative AI model generates product designs based on user information and optimizes materials. It takes a design generation request sent from the server as input, and generates an optimized design and materials list as output. The model uses machine learning algorithms to generate designs that meet the user's requirements.

[1235] Step 7:

[1236] The server sends the generated 3D model data to the user's device. The input requires design data from the generative AI model, and the output is the 3D model sent to the user's device. Specifically, the design data is transferred to the user's device in JSON format, and the 3D model is displayed on a web page.

[1237] Step 8:

[1238] The user reviews the design through an interface and makes any necessary adjustments. As input, the user can visualize the 3D model and input specific modifications through the interface. As output, the adjusted design is generated.

[1239] Step 9:

[1240] The user confirms the design and completes the order online. The input is the reconciled design and payment information, and the output is a notification that the order is complete. Specific actions include adding the design to the cart, entering payment information, and confirming the order.

[1241] Step 10:

[1242] The server sends the final design to the manufacturing department.,The inputs required are the final design data,,design drawings, material lists, and processing instructions, and the output,is the completion of data transfer to the manufacturing department.,Specifically, the design data is sent to the server in the,manufacturing department.

[1243] Step 11:

[1244] The manufacturing department uses automated machines to manufacture furniture based on the design data received. The inputs are a design drawing and a materials list, and the output is the final product. Specific operations include processing materials using CNC machines and 3D printers, and assembling the furniture.

[1245] Step 12:

[1246] The manufacturing department packs the finished furniture and delivers it to the address specified by the user. The input is the finished product and delivery address information, and the output is the shipping of the furniture. Specific operations include printing a shipping label and delivering the furniture to the user via a logistics service.

[1247] (Application example 1)

[1248] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1249] Modern consumers often want to customize furniture to suit their preferences and needs when purchasing it. However, with typical online shopping, users are unable to directly touch the product and visualization is limited, making it difficult to select the furniture they desire. Another issue is that the customization process requires a lot of time and effort. Furthermore, resources can be wasted during the manufacturing process. Therefore, the objective of this invention is to provide a system that allows users to check and adjust furniture designs in real time, and ensures efficient manufacturing and delivery using optimized resources.

[1250] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1251] In this invention, the server includes: means for a user to input details of style, function, layout, and size via an information processing device; means for the information processing device to transmit the input information to a group of information processing devices; means for the group of information processing devices to analyze the received information and call a generative AI model; means for the generative AI model to generate an optimal furniture design based on the user information; means for the generative AI model to optimize resources required for the design and create a blueprint; means for the group of information processing devices to transmit the generated design to the user's information processing device; means for the user to confirm the design through a head-mounted display and complete an order procedure; means for the group of information processing devices to transmit the final design to a manufacturing department; and means for the manufacturing department to manufacture the furniture based on the received design and deliver the completed furniture to the user. This allows the user to confirm and adjust the furniture design in real time in a virtual space, streamlining the ordering process and minimizing resource waste.

[1252] "Means for users to input details of style, function, placement, and size via an information processing device" refers to an interface that allows users to input specific requirements for furniture design using an information processing device such as a computer or smartphone.

[1253] The "means for transmitting information input by an information processing device to a group of information processing devices" is a function for transmitting data input by a user to a cloud server or another information processing system.

[1254] "Means for analyzing information received by a group of information processing devices and invoking a generative AI model" refers to technology that enables a server or cloud system to analyze data received from a user and activate a generative AI model based on that data.

[1255] "Means by which a generative AI model generates optimal furniture designs based on user information" refers to the process by which a pre-trained generative AI model automatically creates the most suitable furniture design based on user input information.

[1256] "Means by which a generative AI model optimizes the resources required for design and creates blueprints" refers to the process by which a generative AI model optimally selects and arranges the materials and parts required for design to form a specific blueprint.

[1257] "Means for transmitting the design generated by the information processing device group to the user information processing device" refers to a function that transmits design data generated by a cloud server or other information processing system to the user's computer or smartphone.

[1258] "Means for users to check the design through a head-mounted display and place an order" refers to an interface that allows users to wear a head-mounted display (HMD), visually check the generated furniture design, and confirm the order if they are satisfied.

[1259] "Means for the information processing device group to send the final design to the manufacturing department" refers to the process by which a cloud server or another information processing system sends finalized design data to the system or equipment in charge of manufacturing.

[1260] "Means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user" refers to the process in which the manufacturing department manufactures furniture using automated equipment according to the received design drawings and then delivers the product to the address specified by the user.

[1261] System Overview

[1262] This invention is a system in which a user uses an information processing device to customize the design and size of furniture through an online platform, and a generative AI model proposes an optimal design based on that, and then optimizes the necessary resources for manufacturing and delivery. Details and specific examples of this system are provided below.

[1263] Hardware and Software

[1264] User information processing device

[1265] Users access the online platform using an information processing device, such as a computer or smartphone, which has a web browser or dedicated application installed, and which provides an interface through which users can input details about their furniture design.

[1266] Servers and information processing devices

[1267] The server, located in the cloud, receives and analyzes the data sent by the user, including checking the data for consistency and filtering outliers. It then invokes a generative AI model to generate the optimal design based on the input data.

[1268] Generative AI Models

[1269] The generative AI model is a pre-trained AI model that generates optimal furniture designs based on user input. Specifically, Hugging Face's GPT-4 model is used. In addition to generating designs, the generative AI model also optimizes resources.

[1270] Program processing explanation

[1271] The program works as follows: First, the user inputs details such as style, function, size, etc. via an information processing device. This input information is sent to the server in JSON format.

[1272] The server analyzes the received data, checks its consistency, and then calls the generative AI model. The generative AI model generates an optimal design based on the received data and optimizes resources. The generated design and blueprint are then sent from the server to the user's information processing device.

[1273] Using a head-mounted display (HMD), users can view and adjust the 3D model generated in real time within the virtual space. Once adjustments are complete, users can view the final design and place an order online.

[1274] The final design is sent from the server to the manufacturing department, where the furniture is manufactured using automated manufacturing equipment based on the received design data. The finished product is then packaged and delivered to the address specified by the user.

[1275] Specific examples

[1276] If a user wants to customize a "dining table" in the "midcentury modern" style, they might input the following prompts into the generative AI model:

[1277] Style: Mid-century modern

[1278] Furniture: Dining table

[1279] Length: 180 cm

[1280] Width: 90cm

[1281] Height: 75 cm

[1282] Features: Expandable, Material: Walnut Wood

[1283] The user can view the generated 3D model through a head-mounted display and confirm their order if they are satisfied, allowing them to efficiently obtain custom furniture.

[1284] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1285] Step 1:

[1286] The user inputs details of the furniture style, function, placement, and size via an information processing device, which involves the user entering specific specifications of the desired furniture into input fields on a computer or smartphone interface. This input information is temporarily stored on the device in JSON format.

[1287] Input: Furniture details regarding style, function, placement, and size

[1288] Output: User input data in JSON format

[1289] Step 2:

[1290] The terminal sends the entered information to the server. In this step, the user-entered data stored in JSON format is sent to the server via an HTTP request. The server receives this data and stores it in a database.

[1291] Input: User-supplied data in JSON format

[1292] Output: User-entered data sent to the server

[1293] Step 3:

[1294] The server analyzes the received information and calls the generative AI model. Specifically, the server checks the data for consistency and filters out invalid values ​​and missing data. Then, based on the data whose consistency has been confirmed, it calls the generative AI model (e.g., GPT-4) via an API request.

[1295] Input: User-entered data stored on the server

[1296] Output: The prompt sent to the generative AI model

[1297] Step 4:

[1298] The generative AI model generates the optimal furniture design based on user information. The generative AI model (GPT-4) analyzes the user's input data and generates the optimal design based on it. This design is output as a drawing or 3D model and returned to the server.

[1299] Input: The prompt sent to the generative AI model

[1300] Output: 3D design data of the generated furniture

[1301] Step 5:

[1302] The generative AI model optimizes the resources required for the design and creates a blueprint. The generative AI model selects the optimal combination of resources (materials, parts, etc.) required for the design and creates a blueprint based on that. This blueprint is optimized to minimize resource waste.

[1303] Input: 3D design data of the generated furniture

[1304] Output: Resource-optimized blueprint

[1305] Step 6:

[1306] The server sends the generated design to the user's information processing device, and the server sends the generated 3D model and optimized blueprint to the user's information processing device, allowing the user to check the design in real time.

[1307] Input: Resource-optimized blueprint

[1308] Output: 3D design data sent to the user's device

[1309] Step 7:

[1310] The user checks the design through a head-mounted display and places an order. The user wears a head-mounted display (HMD) and checks the 3D model generated in the virtual space. If satisfied, the user confirms the order through the interface.

[1311] Input: 3D design data sent to the user's device

[1312] Output: Confirmed order data

[1313] Step 8:

[1314] The server sends the final design to the manufacturing department. The server sends the finalized design drawings and order data to the manufacturing department, which then starts the manufacturing process.

[1315] Input: Confirmed order data and design drawings

[1316] Output: Final design data sent to manufacturing

[1317] Step 9:

[1318] The manufacturing department manufactures the furniture based on the received design and delivers the finished furniture to the user. The manufacturing department uses the received design data to manufacture the furniture using automated manufacturing equipment (CNC machines, 3D printers, etc.). Once manufacturing is complete, the furniture is packaged and delivered to the address specified by the user.

[1319] Input: Final design data sent to manufacturing

[1320] Output: Finished furniture delivered to the user

[1321] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1322] System Overview

[1323] This system allows users to customize furniture design and size through an online platform, and then generative AI proposes optimal designs based on the customization, optimizes materials, and uses an emotion engine to recognize and reflect the user's emotions, thereby improving user satisfaction and enabling more personalized recommendations.

[1324] Program processing flow

[1325] User information input and emotion recognition

[1326] 1. A user accesses the online platform using their device (PC or smartphone). The device displays the login screen or homepage.

[1327] 2. Through the interface, the user inputs detailed information such as the preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and size (e.g., 150 cm width, 70 cm depth, 75 cm height).

[1328] 3. An emotion engine built into the device recognizes emotions from the user's facial expressions, input, interactions, etc. For example, a camera can be used to analyze the user's facial expressions and emotions can be extracted from voice input.

[1329] Data Transmission and Processing

[1330] 4. The device temporarily stores the input information and emotion data in memory and prepares it for transmission.

[1331] 5. The device sends the input information and emotion data to the server in a structured format (e.g., JSON format).

[1332] json

[1333] {

[1334] "style": "modern",

[1335] "shape": "L-shaped",

[1336] "features": {

[1337] "drawers": 3

[1338] },

[1339] "dimensions": {

[1340] "width": 150,

[1341] "depth": 70,

[1342] "height": 75

[1343] },

[1344] "emotions": {

[1345] "happiness": 0.8,

[1346] "neutral": 0.2

[1347] }

[1348] }

[1349] 6. The server analyzes the received information, checks the data for consistency, and filters out invalid values.

[1350] Design Generation and Material Optimization

[1351] 7. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[1352] 8. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[1353] 9. Based on the emotional data obtained from the emotion engine, the generative AI will reflect this in the design and material selection. For example, if the user expresses a high level of happiness, it will suggest a more enthusiastic design.

[1354] Check the design and order

[1355] 10. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[1356] 11. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place their order online.

[1357] Manufacturing and Delivery

[1358] 12. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[1359] 13. Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1360] 14. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[1361] Specific examples

[1362] Case: Office desk customization and emotion recognition

[1363] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[1364] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[1365] 3. The device sends this information to the server in JSON format.

[1366] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[1367] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[1368] 6. The server sends the generated 3D model to the user's device.

[1369] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[1370] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[1371] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[1372] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[1373] This process allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their sentiments.

[1374] The processing flow will be explained below.

[1375] Step 1:

[1376] A user accesses the online platform on their device (PC or smartphone). The device displays a login screen, and the user enters their account information to log in.

[1377] Step 2:

[1378] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[1379] Step 3:

[1380] The emotion engine built into the device recognizes emotions through the user's facial expressions and voice input. For example, a camera can be used to analyze the user's facial expressions in real time and extract emotional states (e.g., happiness, impatience, satisfaction, etc.).

[1381] Step 4:

[1382] The device temporarily stores the input information and recognized emotion data in memory and prepares for transmission.

[1383] Step 5:

[1384] The device sends input information and emotion data to the server in a structured format (e.g., JSON format). An example is shown below.

[1385] json

[1386] {

[1387] "style": "modern",

[1388] "shape": "L-shaped",

[1389] "features": {

[1390] "drawers": 3

[1391] },

[1392] "dimensions": {

[1393] "width": 150,

[1394] "depth": 70,

[1395] "height": 75

[1396] },

[1397] "emotions": {

[1398] "happiness": 0.8,

[1399] "neutral": 0.2

[1400] }

[1401] }

[1402] Step 6:

[1403] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values. Emotional data is also analyzed.

[1404] Step 7:

[1405] The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[1406] Step 8:

[1407] The generative AI generates furniture designs that match the style and functionality specified by the user. It also adjusts the design by taking into account emotional data. For example, if the user expresses a high level of happiness, it will make more proactive design suggestions.

[1408] Step 9:

[1409] The generative AI simultaneously generates the design and selects and optimizes materials, taking into account cost, durability, and aesthetics.

[1410] Step 10:

[1411] The generative AI creates the final design as a 3D model or drawing data and returns it to the server. The generative AI creates a visually appealing 3D model based on the emotion data.

[1412] Step 11:

[1413] The server sends the generated design to the user's device, which launches a 3D model viewer so the user can view the design.

[1414] Step 12:

[1415] The user checks the design and makes further adjustments if necessary. The user again inputs any corrections or additions via the interface.

[1416] Step 13:

[1417] Once the user has decided on a design that satisfies them, they can place an order online, with the terminal sending the order information to the server.

[1418] Step 14:

[1419] The server sends the final design to the manufacturing department, including materials lists, blueprints, and processing instructions.

[1420] Step 15:

[1421] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1422] Step 16:

[1423] The manufacturing department packs the completed furniture and delivers it to the address specified by the user. The delivery status is notified to the user's terminal via the server.

[1424] This series of steps allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their emotions.

[1425] Example 2

[1426] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1427] Conventional furniture design and manufacturing systems do not take into account the user's emotions when customizing a product to suit their preferences and needs, making it difficult to provide personalized suggestions. Furthermore, there is a lack of a way for users to see in real time the design that reflects their own emotions and experiences. These issues make it difficult to increase user satisfaction.

[1428] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input details of style, function, layout, and size via a terminal; a means for the terminal to transmit the input information and user emotion data to the server; a means for the server to analyze the received information and emotion data and call a generation AI; a means for the generation AI to generate an optimal furniture design based on the user information and emotion data; a means for the generation AI to optimize materials required for the design and create a blueprint; a means for the server to transmit the generated design to the user terminal; a means for the user to confirm the design and complete an order procedure; a means for the server to transmit the final design to a manufacturing department; and a means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user. This enables personalized furniture designs and proposals that reflect the user's emotions.

[1429] A "terminal" is an electronic device that allows a user to input, send, and receive information.

[1430] The "server" is a central computer that analyzes the information received from the terminal, calls the generation AI, generates furniture designs, and sends the received designs to the manufacturing department.

[1431] "Generative AI" is an artificial intelligence model that generates optimal furniture designs based on user input and emotional data, and optimizes the necessary materials.

[1432] "Emotion data" is numerical or text data that represents emotions extracted from the user's facial expressions or voice input.

[1433] "Blueprints" are drawings or documents that show the detailed design and construction of furniture created by the generative AI.

[1434] "Online Platform" means a web-based system that users access via a terminal to input details of their furniture designs.

[1435] An "interface" is a screen or operation panel that allows a user to input information and check the design.

[1436] "Manufacturing" refers to the factory or department that receives the final design and produces the furniture using automated manufacturing equipment such as CNC machines and 3D printers.

[1437] The "design readjustment interface" is an operation panel that allows the user to review the generated design and make changes as needed.

[1438] The present invention is a system that allows users to access an online platform using their devices and input details of their furniture design, such as style, function, placement, and size, and then uses a generative AI model to suggest optimal designs and materials, and furthermore, uses an emotion engine to recognize and reflect the user's emotions, allowing users to receive more personalized suggestions.

[1439] Hardware and Software Configuration

[1440] Terminal

[1441] A terminal is an electronic device such as a PC or smartphone that allows users to input information. The terminal is equipped with a browser and an emotion engine. The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice.

[1442] server

[1443] The server is a central computer that analyzes the information received from the device, calls the generative AI, and generates the optimal design. It also sends the generated design to the user's device and sends the final design to the manufacturing department.

[1444] Generative AI Models

[1445] The generative AI model is an artificial intelligence that generates optimal furniture designs based on user input and emotional data. Because the model is trained in advance using a large design dataset, it can automatically generate designs that meet user requirements.

[1446] manufacturing department

[1447] The manufacturing department uses automated manufacturing equipment such as CNC machines and 3D printers to produce the furniture based on the final design sent from the server, and the finished furniture is then properly packaged and delivered to the user.

[1448] Data processing and calculation

[1449] Collecting input information and emotional data from devices

[1450] Users access the online platform and enter details such as their preferred style, placement, size, etc. The emotion engine built into the device uses the camera and microphone to collect the user's emotional data.

[1451] Data analysis by server and calling of generation AI

[1452] The server receives the information sent from the device and checks the consistency of the data. After checking the consistency, the server calls the generative AI model and generates the optimal design based on the user's requests. The generative AI also reflects the user's emotional data and makes personalized suggestions.

[1453] Design generation and material optimization using generative AI

[1454] The generative AI model generates designs based on user information and emotional data, optimizing the necessary materials, resulting in efficient and high-quality designs.

[1455] Design submission and order processing by the server

[1456] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they are satisfied with the final design, they can place their order online.

[1457] Furniture production and delivery by the manufacturing department

[1458] The final design is sent from the server to the manufacturing department, which produces the furniture using CNC machines, 3D printers, etc. The finished furniture is then properly packaged and delivered to the address specified by the user.

[1459] Specific cases and examples of prompts

[1460] Case: Office desk customization and emotion recognition

[1461] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[1462] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[1463] 3. The device sends this information to the server in JSON format.

[1464] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[1465] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[1466] 6. The server sends the generated 3D model to the user's device.

[1467] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[1468] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[1469] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[1470] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[1471] Prompt Sentence Examples

[1472] "I want to design a modern style sofa that will fit in my living room. It should be 200cm wide, 90cm deep, and 85cm high."

[1473] "I want a bookshelf with a classic design. It's 180cm high, 80cm wide, and 30cm deep. I'd also like it to have three drawers."

[1474] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1475] Step 1:

[1476] The user accesses the online platform on their device and logs in. The user enters detailed information about the furniture design, such as style, function, placement, and size.

[1477] Input: Information on style, function, position, size, etc.

[1478] Output: The terminal stores the input information and prepares it for transmission.

[1479] What happens: The user fills in the form and clicks the "Submit" button.

[1480] Step 2:

[1481] The device collects input information and the user's emotional data. The emotional data is acquired by an emotion engine built into the device using the camera and microphone.

[1482] Input: User input information, facial and vocal emotion data

[1483] Output: Structured data (JSON format)

[1484] How it works: The device captures the user's facial expressions with a camera, and the emotion engine analyzes them in real time. It also extracts emotions from voice input.

[1485] Step 3:

[1486] The device converts the collected information into JSON format and sends it to the server.

[1487] Input: Structured data (JSON format)

[1488] Output: Data sent to the server

[1489] What happens: Structured data is sent to the server using an HTTPS request.

[1490] Step 4:

[1491] The server analyzes the information it receives, checks the integrity of the data, and filters out invalid values.

[1492] Input: JSON data sent from the terminal

[1493] Output: Parsed and consistent data

[1494] Specific behavior: The server parses the received JSON data, performs schema validation, and filters out any invalid values.

[1495] Step 5:

[1496] The server calls up a generative AI model based on the analyzed information, which then generates a furniture design that best suits the user's requirements.

[1497] Input: Analyzed and consistent data

[1498] Output: Generated design and optimized materials list

[1499] Specific operation: Sends API calls to the generative AI model to generate a design based on the input data.

[1500] Step 6:

[1501] The generative AI model generates the design, while simultaneously selecting and optimizing the necessary materials and creating the blueprint.

[1502] Input: User information, emotion data

[1503] Output: Designs, blueprints, material lists

[1504] What it does: Generate blueprints, create materials lists, and calculate the optimal combination of materials needed.

[1505] Step 7:

[1506] The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[1507] Input: Generated design, blueprint, material list

[1508] Output: 3D model data sent to the user's device

[1509] Specific operation: The blueprint is converted into a 3D model and the data is sent to the device, where it is displayed in a dedicated viewer.

[1510] Step 8:

[1511] The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[1512] Input: 3D model data

[1513] Output: Final design and order information

[1514] Specific operation: Rotate, zoom in and out to check the 3D model, then re-edit the form. When you are satisfied, click the "Order" button.

[1515] Step 9:

[1516] The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[1517] Input: Final design and order information

[1518] Output: Blueprints, material lists, and processing instructions sent to the manufacturing department

[1519] Specific operation: Send design data to the manufacturing API.

[1520] Step 10:

[1521] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1522] Input: Design drawings, material lists, processing instructions

[1523] Output: Manufactured furniture

[1524] How it works: Based on the blueprint, a CNC machine cuts and processes the wood as specified. A 3D printer prints the parts.

[1525] Step 11:

[1526] The manufacturing department packs the finished furniture and delivers it to the address specified by the user.

[1527] Input: Manufactured furniture, user address

[1528] Output: Fully assembled furniture delivered to the user's address

[1529] Specific operations: Pack the finished product, enter the user's address into the delivery instruction system, and hand it over to the delivery company.

[1530] (Application example 2)

[1531] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1532] Currently, when users customize furniture online, the proposed designs often do not adequately reflect the user's emotions or specific needs. Furthermore, there is no function that takes user emotions into account when optimizing the design or selecting materials, leaving a lack of means to improve user satisfaction. Therefore, there is a need for a system that can improve the user experience and provide more personalized suggestions that reflect emotions.

[1533] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1534] In this invention, the server includes a means for a user to input details of style, function, layout, and size via a terminal, a means for an emotion recognition engine built into the terminal to acquire the user's emotion data and send it to the server, and a means for a generation AI to generate an optimal furniture design based on the user information, thereby enabling design proposals that take emotions into consideration.

[1535] "Terminal" means a computing device through which a User accesses and inputs information into the online platform.

[1536] "Input information" refers to detailed information about style, function, layout, and size input by the user via the terminal.

[1537] The "server" is a remote computer system that receives input information, analyzes it, and invokes the generating AI.

[1538] "Generative AI" is an artificial intelligence technology that generates optimal furniture designs based on user input, optimizes materials, and creates blueprints.

[1539] An "emotion recognition engine" is software that acquires and analyzes emotional data from a user's facial expressions, voice, etc.

[1540] "Emotion data" is data that quantifies or categorizes the user's current emotional state.

[1541] "Design adjustment" refers to the process in which the generative AI modifies and improves the design based on the acquired emotional data.

[1542] "Design confirmation" is the process by which the user visually checks the generated design and makes any necessary adjustments.

[1543] "Ordering process" refers to the process in which the user finally decides on a design that satisfies them and places their purchase / order online.

[1544] "Manufacturing department" refers to the department or facility that actually manufactures furniture based on the final design sent from the server.

[1545] System Overview

[1546] This invention is a system in which users customize furniture design and size via a terminal, and a generative AI proposes optimal designs based on that. Furthermore, by using an emotion engine to recognize and reflect the user's emotions, more personalized design proposals are realized.

[1547] Hardware and software used

[1548] Hardware:

[1549] Devices: PC, smartphone, tablet, etc.

[1550] Camera: Built-in or external camera for capturing user facial expressions

[1551] software:

[1552] Emotion recognition engine: A library or algorithm for extracting emotional data from a user's facial expressions and voice. A specific example is the "EmotionRecognition Library."

[1553] Generative AI: An AI model that generates optimal furniture designs based on user information. A specific example is "DesignGenerator."

[1554] Server and communication protocol: A server and communication protocol for sending, receiving, and analyzing data. A specific example is an HTTP POST request.

[1555] Processing flow and specific examples

[1556] 1. User Input and Emotion Recognition

[1557] Users input information such as their preferred style, desired functions, furniture layout, and size via a terminal. For example, they input detailed information such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm."

[1558] 2. Acquiring Emotion Data

[1559] The device's built-in emotion recognition engine captures the user's facial expressions and voice via a camera and microphone, extracting emotional data, which is then converted into a numerical value, such as "Happiness 0.8" or "Neutrality 0.2."

[1560] 3. Data transmission and analysis

[1561] This input information and emotion data are temporarily stored in memory and sent to the server in a structured data format (e.g., JSON format). The server analyzes the received data, checks its consistency, and filters out invalid values.

[1562] 4. Design generation and adjustment

[1563] The server then calls the generation AI based on the analyzed information. The generation AI generates the optimal design based on the user's input information and emotional data, optimizing the necessary materials to create a blueprint. The generation AI takes the emotional data into account, and suggests a more ambitious design if, for example, the user is expressing a high level of happiness.

[1564] 5. Confirm the design and place your order

[1565] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they have decided on a design they are satisfied with, they can place an order online.

[1566] Prompt Sentence Examples

[1567] An example of a prompt given to a generative AI model might look something like this:

[1568] Create a modern L-shaped office desk with 3 drawers. Dimensions: width 150cm, depth 70cm, height 75cm. Optimize the materials based on user happiness level of 0.8.

[1569] Based on this example, the system can efficiently design, propose, and accept orders for custom furniture that reflects the user's preferences and feelings.

[1570] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1571] Step 1:

[1572] The user inputs detailed information about the furniture's style, function, layout, and size via the terminal. The input information is temporarily stored in the terminal's memory. Specifically, data such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm" are input.

[1573] Step 2:

[1574] The emotion recognition engine built into the device captures the user's facial expressions and voice via the camera and microphone. The emotion recognition engine analyzes the user's emotional data and generates numerical emotional data. For example, it can obtain data such as "Happiness 0.8" or "Neutrality 0.2."

[1575] Step 3:

[1576] The device converts the input information and emotion data into a structured data format (JSON format) and sends it to the server, where preprocessing is also performed to check the data for consistency and filter out invalid values.

[1577] Step 4:

[1578] The server analyzes the received information and checks the data integrity and format. Valid data is obtained as a result of the analysis. For example, user information and emotion data are stored in an organized format on the server.

[1579] Step 5:

[1580] The server then calls a generative AI based on the analyzed information. The generative AI uses a pre-trained model to generate the optimal furniture design for the user. The input is user information and emotional data, and the output is an optimal design that reflects the user's needs.

[1581] Step 6:

[1582] The generative AI simultaneously generates the design and selects and optimizes the necessary materials. Based on emotional data, the design and material selection are fine-tuned. For example, if the user expresses a high level of happiness, a bright color scheme will be suggested.

[1583] Step 7:

[1584] The generated design and material information are sent from the server to the user's device. The device displays the received design as a 3D model for the user to confirm. The input here is the generated design data, and the output is the 3D model display.

[1585] Step 8:

[1586] The user checks the 3D model and makes any necessary adjustments. Once they are satisfied with the design, they place their order online. The terminal sends the order information and the final design to the server.

[1587] Step 9:

[1588] The server sends the received order data and final design to the manufacturing department, which uses automated machines to produce the furniture. The resulting output is specific manufacturing instructions and blueprints.

[1589] Step 10:

[1590] The manufactured furniture is then packaged and delivered to the address specified by the user, where the user can receive their custom furniture order.

[1591] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1592] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1593] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1594] [Fourth embodiment]

[1595] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1596] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1597] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1598] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1599] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1600] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1601] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1602] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1603] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1604] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1605] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1606] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1607] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1608] System Overview

[1609] This invention is a series of systems that allows users to customize furniture design and size via an online platform, and then generative AI proposes optimal designs based on that, optimizes materials, and finally manufactures and delivers the furniture. Below is an overview of the program processing of this system and a concrete example.

[1610] Program processing flow

[1611] Entering user information

[1612] 1. The user accesses the online platform on their own device (PC or smartphone).

[1613] 2. Through the interface, the user enters details such as preferred style, desired features, furniture arrangement, size, etc. This information is temporarily stored in the device's memory and is ready to be sent.

[1614] Data Transmission and Processing

[1615] 3. The device sends the input information to the server. Specifically, the user's input information is sent as structured data in JSON format or similar.

[1616] 4. The server analyzes the received information, which may include checking the data for integrity and filtering out invalid values.

[1617] Design Generation and Material Optimization

[1618] 5. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[1619] 6. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[1620] Check the design and order

[1621] 7. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[1622] 8. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[1623] Manufacturing and Delivery

[1624] 9. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[1625] 10. Based on the design data received by the manufacturing department, the furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1626] 11. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[1627] Specific examples

[1628] Case: Customizing your office desk

[1629] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[1630] 2. The device sends this information to the server in JSON format.

[1631] json

[1632] {

[1633] "style": "modern",

[1634] "shape": "L-shaped",

[1635] "features": {

[1636] "drawers": 3

[1637] },

[1638] "dimensions": {

[1639] "width": 150,

[1640] "depth": 70,

[1641] "height": 75

[1642] }

[1643] }

[1644] 3. The server analyzes the received data, checks its integrity and format, and then calls the generation AI.

[1645] 4. Generative AI generates the optimal desk design based on user information and optimizes materials. The final design is generated as a 3D model.

[1646] 5. The server sends the generated 3D model to the user's device.

[1647] 6. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[1648] 7. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[1649] 8. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[1650] 9. The manufacturing department packages the finished desk and delivers it to the address specified by the user.

[1651] This concludes the detailed description of the present invention, which allows users to efficiently obtain custom furniture that meets their tastes and needs.

[1652] The processing flow will be explained below.

[1653] Step 1:

[1654] A user accesses the online platform using their device (PC or smartphone), and the device displays the login screen or homepage.

[1655] Step 2:

[1656] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[1657] Step 3:

[1658] The terminal temporarily stores the entered information in memory and prepares it for transmission.

[1659] Step 4:

[1660] The device sends the input information to the server in a structured format (e.g., JSON format). An example is shown below.

[1661] json

[1662] {

[1663] "style": "modern",

[1664] "shape": "L-shaped",

[1665] "features": {

[1666] "drawers": 3

[1667] },

[1668] "dimensions": {

[1669] "width": 150,

[1670] "depth": 70,

[1671] "height": 75

[1672] }

[1673] }

[1674] Step 5:

[1675] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values.

[1676] Step 6:

[1677] The server calls the generation AI based on the analyzed information, and passes the user data as an argument to the generation AI function.

[1678] Step 7:

[1679] The generative AI generates optimal furniture designs based on user information, specifically using CAD software to create designs based on the specified style and functions.

[1680] Step 8:

[1681] Generative AI generates designs while optimizing materials, selecting the necessary materials (e.g., wood, metal) and determining the optimal materials based on cost, durability, and aesthetics.

[1682] Step 9:

[1683] The generative AI creates the final design as a 3D model or drawing data and returns it to the server.

[1684] Step 10:

[1685] The server sends the generated design to the user's terminal, which displays the received design on a user interface so that the user can check it.

[1686] Step 11:

[1687] The user checks the design and makes further adjustments as necessary. Specifically, they input any corrections or additional requests for the design via the interface.

[1688] Step 12:

[1689] Once the user has decided on a design that satisfies them, they can place an order online, and the terminal will send the entered order information to the server.

[1690] Step 13:

[1691] The server sends the final design to manufacturing, including materials lists, blueprints, and processing instructions.

[1692] Step 14:

[1693] Based on the design data received by the manufacturing department, furniture is manufactured using CNC machines and 3D printers.

[1694] Step 15:

[1695] The manufacturing department packs the completed furniture and delivers it to the specified address. The delivery status is notified to the user's terminal via the server.

[1696] This series of steps allows users to easily design and order custom furniture according to their tastes and needs.

[1697] Example 1

[1698] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1699] Conventional furniture customization and manufacturing systems have problems such as difficulty in efficiently and accurately reflecting a user's desired design, and a large amount of material waste. Furthermore, the process of specifically visualizing and re-adjusting a user's customized design is complicated, which can lead to a poor user experience.

[1700] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1701] In this invention, the server includes a means for a user to input details of the style, function, arrangement, and dimensions of an article via a terminal, a means for the terminal to transmit the input structured data to the server, and a means for the server to analyze the received information, check the consistency of the data, and filter out invalid values, thereby enabling the user to efficiently and accurately reflect their desired design.

[1702] "User" means any individual or entity that utilizes the System to customize and order items.

[1703] "Terminal" refers to an electronic device, such as a computer device or smartphone, that a user uses to access the system.

[1704] "Server" refers to the computer system that analyzes the data received from the terminal and calls the generation AI to generate the design.

[1705] "Structured data" is data that is organized according to a specific format, including JSON and XML formats.

[1706] "Generative AI" refers to an artificial intelligence model that generates optimal designs based on user requirements and selects and optimizes materials.

[1707] "Blueprint" refers to a drawing showing the detailed design of the furniture generated by the generation AI.

[1708] "Automated machines" refers to devices, such as CNC machines and 3D printers, that automatically carry out manufacturing processes based on received design data.

[1709] A "3D model" refers to digital data used to visualize furniture designs in three dimensions.

[1710] "Interface" refers to the system's operation screen that the user uses to input and adjust the design.

[1711] "Materials list" refers to a list showing the types and quantities of materials required based on the design generated by the generation AI.

[1712] "Processing Instructions" refers to data containing specific instructions for the manufacturing department to process materials in accordance with a specified design.

[1713] The present invention is a system in which users customize the design and size of an item, especially furniture, through an online platform, and a generative AI model proposes the optimal design based on that, selects and optimizes materials, and finally manufactures and delivers the item. The program process of this system is described in detail below.

[1714] System Overview

[1715] The system consists of the following main components:

[1716] 1. User terminal: An electronic device such as a PC or smartphone.

[1717] 2. Server: A computer system that analyzes the received data and invokes the generative AI model.

[1718] 3. Generative AI model: Artificial intelligence that optimizes the design and materials based on the user's customization requirements.

[1719] 4. Interface: The operation screen where the user can input and adjust the design.

[1720] 5. Automated Machinery: Automated manufacturing equipment such as CNC machines and 3D printers.

[1721] Processing Details

[1722] 1. Enter your user information:

[1723] Users access the online platform using their devices, enter a URL into the address bar of their web browser, and log in to the site.

[1724] Using the form on the interface, users enter the item's style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm), etc.

[1725] Example: Prompt = "Generate a design for a modern-style L-shaped office desk with three drawers, 150cm wide, 70cm deep, and 75cm high."

[1726] 2. Data transmission and processing:

[1727] The terminal sends the entered information to the server as structured data (JSON format).

[1728] The server analyzes the received information, performs data integrity checks and filters out invalid values.

[1729] 3. Design generation and material optimization:

[1730] The server calls a generative AI model based on the analyzed information, and the generative AI model generates a design that best suits the user's requirements.

[1731] The generative AI model generates the design while simultaneously selecting and optimizing the necessary materials.

[1732] 4. Confirm the design and place your order:

[1733] The server sends the generated 3D model to the user's device, allowing the user to visualize the design.

[1734] The user can review the design through the interface and make any necessary adjustments. Once the final design is confirmed, the user can place the order online.

[1735] 5. Production and Delivery:

[1736] The server sends the final design to the manufacturing department, transferring data including blueprints, material lists, and processing instructions.

[1737] The manufacturing department uses automated machines to create the furniture based on the received design, and finally delivers the finished furniture to the address specified by the user.

[1738] Specific examples

[1739] A user accesses the online platform and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm." The device sends this information in JSON format to the server, which analyzes the received data and calls the generative AI model. The generative AI model generates a design and sends an optimized 3D model to the user's device. The user reviews the design, makes any adjustments or final confirmations, and then completes the order. The final design is sent to the manufacturing department, where the furniture is produced using automated machines and delivered to the user.

[1740] By implementing this invention, users can efficiently obtain custom furniture that meets their tastes and needs.

[1741] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1742] Program processing steps

[1743] Step 1:

[1744] A user accesses an online platform using their device. They enter the platform URL in the address bar of their web browser and log in to the site. As input, the user's authentication information (username, password) is required, and as output, a login session is generated.

[1745] Step 2:

[1746] The user uses a form on the interface to input customization information for the furniture, such as style (e.g., modern style), shape (e.g., L-shaped), function (e.g., three drawers), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm). The user's customization requirements are required as input, and the input data is temporarily stored in the device's memory as output.

[1747] Step 3:

[1748] The information entered on the device is sent to the server as structured data (JSON format). User customization information is required as input, and JSON data is generated as output and sent to the server. The specific operation is to send the data to the server using JavaScript AJAX.

[1749] Step 4:

[1750] The server analyzes the received information. Specifically, it parses the received JSON data and validates its contents. As input, it requires the JSON data sent from the terminal, and as output, it checks the data for consistency and filters out invalid values. This ensures that the data is formatted correctly and does not contain any invalid values.

[1751] Step 5:

[1752] The server calls the generative AI model based on the analyzed information. The analyzed user information is required as input, and a design generation request is sent to the generative AI model as output. Specifically, the analysis data is sent to the API endpoint of the generative AI model.

[1753] Step 6:

[1754] The generative AI model generates product designs based on user information and optimizes materials. It takes a design generation request sent from the server as input, and generates an optimized design and materials list as output. The model uses machine learning algorithms to generate designs that meet the user's requirements.

[1755] Step 7:

[1756] The server sends the generated 3D model data to the user's device. The input requires design data from the generative AI model, and the output is the 3D model sent to the user's device. Specifically, the design data is transferred to the user's device in JSON format, and the 3D model is displayed on a web page.

[1757] Step 8:

[1758] The user reviews the design through an interface and makes any necessary adjustments. As input, the user can visualize the 3D model and input specific modifications through the interface. As output, the adjusted design is generated.

[1759] Step 9:

[1760] The user confirms the design and completes the order online. The input is the reconciled design and payment information, and the output is a notification that the order is complete. Specific actions include adding the design to the cart, entering payment information, and confirming the order.

[1761] Step 10:

[1762] The server sends the final design to the manufacturing department.,The inputs required are the final design data,,design drawings, material lists, and processing instructions, and the output,is the completion of data transfer to the manufacturing department.,Specifically, the design data is sent to the server in the,manufacturing department.

[1763] Step 11:

[1764] The manufacturing department uses automated machines to manufacture furniture based on the design data received. The inputs are a design drawing and a materials list, and the output is the final product. Specific operations include processing materials using CNC machines and 3D printers, and assembling the furniture.

[1765] Step 12:

[1766] The manufacturing department packs the finished furniture and delivers it to the address specified by the user. The input is the finished product and delivery address information, and the output is the shipping of the furniture. Specific operations include printing a shipping label and delivering the furniture to the user via a logistics service.

[1767] (Application example 1)

[1768] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1769] Modern consumers often want to customize furniture to suit their preferences and needs when purchasing it. However, with typical online shopping, users are unable to directly touch the product and visualization is limited, making it difficult to select the furniture they desire. Another issue is that the customization process requires a lot of time and effort. Furthermore, resources can be wasted during the manufacturing process. Therefore, the objective of this invention is to provide a system that allows users to check and adjust furniture designs in real time, and ensures efficient manufacturing and delivery using optimized resources.

[1770] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1771] In this invention, the server includes: means for a user to input details of style, function, layout, and size via an information processing device; means for the information processing device to transmit the input information to a group of information processing devices; means for the group of information processing devices to analyze the received information and call a generative AI model; means for the generative AI model to generate an optimal furniture design based on the user information; means for the generative AI model to optimize resources required for the design and create a blueprint; means for the group of information processing devices to transmit the generated design to the user's information processing device; means for the user to confirm the design through a head-mounted display and complete an order procedure; means for the group of information processing devices to transmit the final design to a manufacturing department; and means for the manufacturing department to manufacture the furniture based on the received design and deliver the completed furniture to the user. This allows the user to confirm and adjust the furniture design in real time in a virtual space, streamlining the ordering process and minimizing resource waste.

[1772] "Means for users to input details of style, function, placement, and size via an information processing device" refers to an interface that allows users to input specific requirements for furniture design using an information processing device such as a computer or smartphone.

[1773] The "means for transmitting information input by an information processing device to a group of information processing devices" is a function for transmitting data input by a user to a cloud server or another information processing system.

[1774] "Means for analyzing information received by a group of information processing devices and invoking a generative AI model" refers to technology that enables a server or cloud system to analyze data received from a user and activate a generative AI model based on that data.

[1775] "Means by which a generative AI model generates optimal furniture designs based on user information" refers to the process by which a pre-trained generative AI model automatically creates the most suitable furniture design based on user input information.

[1776] "Means by which a generative AI model optimizes the resources required for design and creates blueprints" refers to the process by which a generative AI model optimally selects and arranges the materials and parts required for design to form a specific blueprint.

[1777] "Means for transmitting the design generated by the information processing device group to the user information processing device" refers to a function that transmits design data generated by a cloud server or other information processing system to the user's computer or smartphone.

[1778] "Means for users to check the design through a head-mounted display and place an order" refers to an interface that allows users to wear a head-mounted display (HMD), visually check the generated furniture design, and confirm the order if they are satisfied.

[1779] "Means for the information processing device group to send the final design to the manufacturing department" refers to the process by which a cloud server or another information processing system sends finalized design data to the system or equipment in charge of manufacturing.

[1780] "Means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user" refers to the process in which the manufacturing department manufactures furniture using automated equipment according to the received design drawings and then delivers the product to the address specified by the user.

[1781] System Overview

[1782] This invention is a system in which a user uses an information processing device to customize the design and size of furniture through an online platform, and a generative AI model proposes an optimal design based on that, and then optimizes the necessary resources for manufacturing and delivery. Details and specific examples of this system are provided below.

[1783] Hardware and Software

[1784] User information processing device

[1785] Users access the online platform using an information processing device, such as a computer or smartphone, which has a web browser or dedicated application installed, and which provides an interface through which users can input details about their furniture design.

[1786] Servers and information processing devices

[1787] The server, located in the cloud, receives and analyzes the data sent by the user, including checking the data for consistency and filtering outliers. It then invokes a generative AI model to generate the optimal design based on the input data.

[1788] Generative AI Models

[1789] The generative AI model is a pre-trained AI model that generates optimal furniture designs based on user input. Specifically, Hugging Face's GPT-4 model is used. In addition to generating designs, the generative AI model also optimizes resources.

[1790] Program processing explanation

[1791] The program works as follows: First, the user inputs details such as style, function, size, etc. via an information processing device. This input information is sent to the server in JSON format.

[1792] The server analyzes the received data, checks its consistency, and then calls the generative AI model. The generative AI model generates an optimal design based on the received data and optimizes resources. The generated design and blueprint are then sent from the server to the user's information processing device.

[1793] Using a head-mounted display (HMD), users can view and adjust the 3D model generated in real time within the virtual space. Once adjustments are complete, users can view the final design and place an order online.

[1794] The final design is sent from the server to the manufacturing department, where the furniture is manufactured using automated manufacturing equipment based on the received design data. The finished product is then packaged and delivered to the address specified by the user.

[1795] Specific examples

[1796] If a user wants to customize a "dining table" in the "midcentury modern" style, they might input the following prompts into the generative AI model:

[1797] Style: Mid-century modern

[1798] Furniture: Dining table

[1799] Length: 180 cm

[1800] Width: 90cm

[1801] Height: 75 cm

[1802] Features: Expandable, Material: Walnut Wood

[1803] The user can view the generated 3D model through a head-mounted display and confirm their order if they are satisfied, allowing them to efficiently obtain custom furniture.

[1804] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1805] Step 1:

[1806] The user inputs details of the furniture style, function, placement, and size via an information processing device, which involves the user entering specific specifications of the desired furniture into input fields on a computer or smartphone interface. This input information is temporarily stored on the device in JSON format.

[1807] Input: Furniture details regarding style, function, placement, and size

[1808] Output: User input data in JSON format

[1809] Step 2:

[1810] The terminal sends the entered information to the server. In this step, the user-entered data stored in JSON format is sent to the server via an HTTP request. The server receives this data and stores it in a database.

[1811] Input: User-supplied data in JSON format

[1812] Output: User-entered data sent to the server

[1813] Step 3:

[1814] The server analyzes the received information and calls the generative AI model. Specifically, the server checks the data for consistency and filters out invalid values ​​and missing data. Then, based on the data whose consistency has been confirmed, it calls the generative AI model (e.g., GPT-4) via an API request.

[1815] Input: User-entered data stored on the server

[1816] Output: The prompt sent to the generative AI model

[1817] Step 4:

[1818] The generative AI model generates the optimal furniture design based on user information. The generative AI model (GPT-4) analyzes the user's input data and generates the optimal design based on it. This design is output as a drawing or 3D model and returned to the server.

[1819] Input: The prompt sent to the generative AI model

[1820] Output: 3D design data of the generated furniture

[1821] Step 5:

[1822] The generative AI model optimizes the resources required for the design and creates a blueprint. The generative AI model selects the optimal combination of resources (materials, parts, etc.) required for the design and creates a blueprint based on that. This blueprint is optimized to minimize resource waste.

[1823] Input: 3D design data of the generated furniture

[1824] Output: Resource-optimized blueprint

[1825] Step 6:

[1826] The server sends the generated design to the user's information processing device, and the server sends the generated 3D model and optimized blueprint to the user's information processing device, allowing the user to check the design in real time.

[1827] Input: Resource-optimized blueprint

[1828] Output: 3D design data sent to the user's device

[1829] Step 7:

[1830] The user checks the design through a head-mounted display and places an order. The user wears a head-mounted display (HMD) and checks the 3D model generated in the virtual space. If satisfied, the user confirms the order through the interface.

[1831] Input: 3D design data sent to the user's device

[1832] Output: Confirmed order data

[1833] Step 8:

[1834] The server sends the final design to the manufacturing department. The server sends the finalized design drawings and order data to the manufacturing department, which then starts the manufacturing process.

[1835] Input: Confirmed order data and design drawings

[1836] Output: Final design data sent to manufacturing

[1837] Step 9:

[1838] The manufacturing department manufactures the furniture based on the received design and delivers the finished furniture to the user. The manufacturing department uses the received design data to manufacture the furniture using automated manufacturing equipment (CNC machines, 3D printers, etc.). Once manufacturing is complete, the furniture is packaged and delivered to the address specified by the user.

[1839] Input: Final design data sent to manufacturing

[1840] Output: Finished furniture delivered to the user

[1841] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1842] System Overview

[1843] This system allows users to customize furniture design and size through an online platform, and then generative AI proposes optimal designs based on the customization, optimizes materials, and uses an emotion engine to recognize and reflect the user's emotions, thereby improving user satisfaction and enabling more personalized recommendations.

[1844] Program processing flow

[1845] User information input and emotion recognition

[1846] 1. A user accesses the online platform using their device (PC or smartphone). The device displays the login screen or homepage.

[1847] 2. Through the interface, the user inputs detailed information such as the preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and size (e.g., 150 cm width, 70 cm depth, 75 cm height).

[1848] 3. An emotion engine built into the device recognizes emotions from the user's facial expressions, input, interactions, etc. For example, a camera can be used to analyze the user's facial expressions and emotions can be extracted from voice input.

[1849] Data Transmission and Processing

[1850] 4. The device temporarily stores the input information and emotion data in memory and prepares it for transmission.

[1851] 5. The device sends the input information and emotion data to the server in a structured format (e.g., JSON format).

[1852] json

[1853] {

[1854] "style": "modern",

[1855] "shape": "L-shaped",

[1856] "features": {

[1857] "drawers": 3

[1858] },

[1859] "dimensions": {

[1860] "width": 150,

[1861] "depth": 70,

[1862] "height": 75

[1863] },

[1864] "emotions": {

[1865] "happiness": 0.8,

[1866] "neutral": 0.2

[1867] }

[1868] }

[1869] 6. The server analyzes the received information, checks the data for consistency, and filters out invalid values.

[1870] Design Generation and Material Optimization

[1871] 7. The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[1872] 8. The generative AI generates the design, while simultaneously selecting and optimizing the necessary materials and creating a blueprint.

[1873] 9. Based on the emotional data obtained from the emotion engine, the generative AI will reflect this in the design and material selection. For example, if the user expresses a high level of happiness, it will suggest a more enthusiastic design.

[1874] Check the design and order

[1875] 10. The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[1876] 11. The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place their order online.

[1877] Manufacturing and Delivery

[1878] 12. The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[1879] 13. Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1880] 14. The completed furniture will be packed according to the prescribed procedures and delivered to the address specified by the user.

[1881] Specific examples

[1882] Case: Office desk customization and emotion recognition

[1883] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[1884] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[1885] 3. The device sends this information to the server in JSON format.

[1886] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[1887] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[1888] 6. The server sends the generated 3D model to the user's device.

[1889] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[1890] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[1891] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[1892] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[1893] This process allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their sentiments.

[1894] The processing flow will be explained below.

[1895] Step 1:

[1896] A user accesses the online platform on their device (PC or smartphone). The device displays a login screen, and the user enters their account information to log in.

[1897] Step 2:

[1898] Through the interface, users input detailed information such as their preferred style (e.g., modern, classic), desired features (e.g., number of drawers, shelf arrangement), furniture placement (e.g., living room, office), and dimensions (e.g., width 150 cm, depth 70 cm, height 75 cm).

[1899] Step 3:

[1900] The emotion engine built into the device recognizes emotions through the user's facial expressions and voice input. For example, a camera can be used to analyze the user's facial expressions in real time and extract emotional states (e.g., happiness, impatience, satisfaction, etc.).

[1901] Step 4:

[1902] The device temporarily stores the input information and recognized emotion data in memory and prepares for transmission.

[1903] Step 5:

[1904] The device sends input information and emotion data to the server in a structured format (e.g., JSON format). An example is shown below.

[1905] json

[1906] {

[1907] "style": "modern",

[1908] "shape": "L-shaped",

[1909] "features": {

[1910] "drawers": 3

[1911] },

[1912] "dimensions": {

[1913] "width": 150,

[1914] "depth": 70,

[1915] "height": 75

[1916] },

[1917] "emotions": {

[1918] "happiness": 0.8,

[1919] "neutral": 0.2

[1920] }

[1921] }

[1922] Step 6:

[1923] The server analyzes the information received, checking data integrity (e.g., whether numbers are correct, whether required fields are filled in), and filtering out invalid values. Emotional data is also analyzed.

[1924] Step 7:

[1925] The server uses the analyzed information to call the generative AI, which uses pre-trained models to generate furniture designs that best fit the user's requirements.

[1926] Step 8:

[1927] The generative AI generates furniture designs that match the style and functionality specified by the user. It also adjusts the design by taking into account emotional data. For example, if the user expresses a high level of happiness, it will make more proactive design suggestions.

[1928] Step 9:

[1929] The generative AI simultaneously generates the design and selects and optimizes materials, taking into account cost, durability, and aesthetics.

[1930] Step 10:

[1931] The generative AI creates the final design as a 3D model or drawing data and returns it to the server. The generative AI creates a visually appealing 3D model based on the emotion data.

[1932] Step 11:

[1933] The server sends the generated design to the user's device, which launches a 3D model viewer so the user can view the design.

[1934] Step 12:

[1935] The user checks the design and makes further adjustments if necessary. The user again inputs any corrections or additions via the interface.

[1936] Step 13:

[1937] Once the user has decided on a design that satisfies them, they can place an order online, with the terminal sending the order information to the server.

[1938] Step 14:

[1939] The server sends the final design to the manufacturing department, including materials lists, blueprints, and processing instructions.

[1940] Step 15:

[1941] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[1942] Step 16:

[1943] The manufacturing department packs the completed furniture and delivers it to the address specified by the user. The delivery status is notified to the user's terminal via the server.

[1944] This series of steps allows users to efficiently design and order custom furniture according to their tastes and needs, while also receiving more personalized recommendations that reflect their emotions.

[1945] Example 2

[1946] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1947] Conventional furniture design and manufacturing systems do not take into account the user's emotions when customizing a product to suit their preferences and needs, making it difficult to provide personalized suggestions. Furthermore, there is a lack of a way for users to see in real time the design that reflects their own emotions and experiences. These issues make it difficult to increase user satisfaction.

[1948] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input details of style, function, layout, and size via a terminal; a means for the terminal to transmit the input information and user emotion data to the server; a means for the server to analyze the received information and emotion data and call a generation AI; a means for the generation AI to generate an optimal furniture design based on the user information and emotion data; a means for the generation AI to optimize materials required for the design and create a blueprint; a means for the server to transmit the generated design to the user terminal; a means for the user to confirm the design and complete an order procedure; a means for the server to transmit the final design to a manufacturing department; and a means for the manufacturing department to manufacture furniture based on the received design and deliver the completed furniture to the user. This enables personalized furniture designs and proposals that reflect the user's emotions.

[1949] A "terminal" is an electronic device that allows a user to input, send, and receive information.

[1950] The "server" is a central computer that analyzes the information received from the terminal, calls the generation AI, generates furniture designs, and sends the received designs to the manufacturing department.

[1951] "Generative AI" is an artificial intelligence model that generates optimal furniture designs based on user input and emotional data, and optimizes the necessary materials.

[1952] "Emotion data" is numerical or text data that represents emotions extracted from the user's facial expressions or voice input.

[1953] "Blueprints" are drawings or documents that show the detailed design and construction of furniture created by the generative AI.

[1954] "Online Platform" means a web-based system that users access via a terminal to input details of their furniture designs.

[1955] An "interface" is a screen or operation panel that allows a user to input information and check the design.

[1956] "Manufacturing" refers to the factory or department that receives the final design and produces the furniture using automated manufacturing equipment such as CNC machines and 3D printers.

[1957] The "design readjustment interface" is an operation panel that allows the user to review the generated design and make changes as needed.

[1958] The present invention is a system that allows users to access an online platform using their devices and input details of their furniture design, such as style, function, placement, and size, and then uses a generative AI model to suggest optimal designs and materials, and furthermore, uses an emotion engine to recognize and reflect the user's emotions, allowing users to receive more personalized suggestions.

[1959] Hardware and Software Configuration

[1960] Terminal

[1961] A terminal is an electronic device such as a PC or smartphone that allows users to input information. The terminal is equipped with a browser and an emotion engine. The emotion engine uses a camera and microphone to analyze the user's facial expressions and voice.

[1962] server

[1963] The server is a central computer that analyzes the information received from the device, calls the generative AI, and generates the optimal design. It also sends the generated design to the user's device and sends the final design to the manufacturing department.

[1964] Generative AI Models

[1965] The generative AI model is an artificial intelligence that generates optimal furniture designs based on user input and emotional data. Because the model is trained in advance using a large design dataset, it can automatically generate designs that meet user requirements.

[1966] manufacturing department

[1967] The manufacturing department uses automated manufacturing equipment such as CNC machines and 3D printers to produce the furniture based on the final design sent from the server, and the finished furniture is then properly packaged and delivered to the user.

[1968] Data processing and calculation

[1969] Collecting input information and emotional data from devices

[1970] Users access the online platform and enter details such as their preferred style, placement, size, etc. The emotion engine built into the device uses the camera and microphone to collect the user's emotional data.

[1971] Data analysis by server and calling of generation AI

[1972] The server receives the information sent from the device and checks the consistency of the data. After checking the consistency, the server calls the generative AI model and generates the optimal design based on the user's requests. The generative AI also reflects the user's emotional data and makes personalized suggestions.

[1973] Design generation and material optimization using generative AI

[1974] The generative AI model generates designs based on user information and emotional data, optimizing the necessary materials, resulting in efficient and high-quality designs.

[1975] Design submission and order processing by the server

[1976] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they are satisfied with the final design, they can place their order online.

[1977] Furniture production and delivery by the manufacturing department

[1978] The final design is sent from the server to the manufacturing department, which produces the furniture using CNC machines, 3D printers, etc. The finished furniture is then properly packaged and delivered to the address specified by the user.

[1979] Specific cases and examples of prompts

[1980] Case: Office desk customization and emotion recognition

[1981] 1. The user accesses the online platform on their device and enters information such as "modern style," "L-shaped," "three drawers," "width 150cm, depth 70cm, height 75cm," etc.

[1982] 2. The emotion engine built into the device analyzes the user's facial expressions and input content to extract emotional data.

[1983] 3. The device sends this information to the server in JSON format.

[1984] 4. The server analyzes the received data, checks its integrity and format, and then invokes the generation AI.

[1985] 5. Generative AI generates the optimal desk design based on user information and emotional data, optimizing materials.

[1986] 6. The server sends the generated 3D model to the user's device.

[1987] 7. The user reviews the design and makes any necessary adjustments. Once they are satisfied with the design, they can place their order online.

[1988] 8. The server sends the final design to manufacturing, including the 3D model, materials list, and processing instructions.

[1989] 9. Based on the design received by the manufacturing department, the desks are manufactured using automated machines.

[1990] 10. The manufacturing department packages the completed desk and delivers it to the address specified by the user.

[1991] Prompt Sentence Examples

[1992] "I want to design a modern style sofa that will fit in my living room. It should be 200cm wide, 90cm deep, and 85cm high."

[1993] "I want a bookshelf with a classic design. It's 180cm high, 80cm wide, and 30cm deep. I'd also like it to have three drawers."

[1994] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1995] Step 1:

[1996] The user accesses the online platform on their device and logs in. The user enters detailed information about the furniture design, such as style, function, placement, and size.

[1997] Input: Information on style, function, position, size, etc.

[1998] Output: The terminal stores the input information and prepares it for transmission.

[1999] What happens: The user fills in the form and clicks the "Submit" button.

[2000] Step 2:

[2001] The device collects input information and the user's emotional data. The emotional data is acquired by an emotion engine built into the device using the camera and microphone.

[2002] Input: User input information, facial and vocal emotion data

[2003] Output: Structured data (JSON format)

[2004] How it works: The device captures the user's facial expressions with a camera, and the emotion engine analyzes them in real time. It also extracts emotions from voice input.

[2005] Step 3:

[2006] The device converts the collected information into JSON format and sends it to the server.

[2007] Input: Structured data (JSON format)

[2008] Output: Data sent to the server

[2009] What happens: Structured data is sent to the server using an HTTPS request.

[2010] Step 4:

[2011] The server analyzes the information it receives, checks the integrity of the data, and filters out invalid values.

[2012] Input: JSON data sent from the terminal

[2013] Output: Parsed and consistent data

[2014] Specific behavior: The server parses the received JSON data, performs schema validation, and filters out any invalid values.

[2015] Step 5:

[2016] The server calls up a generative AI model based on the analyzed information, which then generates a furniture design that best suits the user's requirements.

[2017] Input: Analyzed and consistent data

[2018] Output: Generated design and optimized materials list

[2019] Specific operation: Sends API calls to the generative AI model to generate a design based on the input data.

[2020] Step 6:

[2021] The generative AI model generates the design, while simultaneously selecting and optimizing the necessary materials and creating the blueprint.

[2022] Input: User information, emotion data

[2023] Output: Designs, blueprints, material lists

[2024] What it does: Generate blueprints, create materials lists, and calculate the optimal combination of materials needed.

[2025] Step 7:

[2026] The server sends the generated design to the user's device, where the user can view the design as a 3D model.

[2027] Input: Generated design, blueprint, material list

[2028] Output: 3D model data sent to the user's device

[2029] Specific operation: The blueprint is converted into a 3D model and the data is sent to the device, where it is displayed in a dedicated viewer.

[2030] Step 8:

[2031] The user can review the design and make any necessary adjustments. Once the user is satisfied with the design, they can place the order online.

[2032] Input: 3D model data

[2033] Output: Final design and order information

[2034] Specific operation: Rotate, zoom in and out to check the 3D model, then re-edit the form. When you are satisfied, click the "Order" button.

[2035] Step 9:

[2036] The server sends the final design to manufacturing, including blueprints, material lists, and processing instructions.

[2037] Input: Final design and order information

[2038] Output: Blueprints, material lists, and processing instructions sent to the manufacturing department

[2039] Specific operation: Send design data to the manufacturing API.

[2040] Step 10:

[2041] Based on the design data received by the manufacturing department, furniture is manufactured using automated manufacturing equipment such as CNC machines and 3D printers.

[2042] Input: Design drawings, material lists, processing instructions

[2043] Output: Manufactured furniture

[2044] How it works: Based on the blueprint, a CNC machine cuts and processes the wood as specified. A 3D printer prints the parts.

[2045] Step 11:

[2046] The manufacturing department packs the finished furniture and delivers it to the address specified by the user.

[2047] Input: Manufactured furniture, user address

[2048] Output: Fully assembled furniture delivered to the user's address

[2049] Specific operations: Pack the finished product, enter the user's address into the delivery instruction system, and hand it over to the delivery company.

[2050] (Application example 2)

[2051] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2052] Currently, when users customize furniture online, the proposed designs often do not adequately reflect the user's emotions or specific needs. Furthermore, there is no function that takes user emotions into account when optimizing the design or selecting materials, leaving a lack of means to improve user satisfaction. Therefore, there is a need for a system that can improve the user experience and provide more personalized suggestions that reflect emotions.

[2053] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2054] In this invention, the server includes a means for a user to input details of style, function, layout, and size via a terminal, a means for an emotion recognition engine built into the terminal to acquire the user's emotion data and send it to the server, and a means for a generation AI to generate an optimal furniture design based on the user information, thereby enabling design proposals that take emotions into consideration.

[2055] "Terminal" means a computing device through which a User accesses and inputs information into the online platform.

[2056] "Input information" refers to detailed information about style, function, layout, and size input by the user via the terminal.

[2057] The "server" is a remote computer system that receives input information, analyzes it, and invokes the generating AI.

[2058] "Generative AI" is an artificial intelligence technology that generates optimal furniture designs based on user input, optimizes materials, and creates blueprints.

[2059] An "emotion recognition engine" is software that acquires and analyzes emotional data from a user's facial expressions, voice, etc.

[2060] "Emotion data" is data that quantifies or categorizes the user's current emotional state.

[2061] "Design adjustment" refers to the process in which the generative AI modifies and improves the design based on the acquired emotional data.

[2062] "Design confirmation" is the process by which the user visually checks the generated design and makes any necessary adjustments.

[2063] "Ordering process" refers to the process in which the user finally decides on a design that satisfies them and places their purchase / order online.

[2064] "Manufacturing department" refers to the department or facility that actually manufactures furniture based on the final design sent from the server.

[2065] System Overview

[2066] This invention is a system in which users customize furniture design and size via a terminal, and a generative AI proposes optimal designs based on that. Furthermore, by using an emotion engine to recognize and reflect the user's emotions, more personalized design proposals are realized.

[2067] Hardware and software used

[2068] Hardware:

[2069] Devices: PC, smartphone, tablet, etc.

[2070] Camera: Built-in or external camera for capturing user facial expressions

[2071] software:

[2072] Emotion recognition engine: A library or algorithm for extracting emotional data from a user's facial expressions and voice. A specific example is the "EmotionRecognition Library."

[2073] Generative AI: An AI model that generates optimal furniture designs based on user information. A specific example is "DesignGenerator."

[2074] Server and communication protocol: A server and communication protocol for sending, receiving, and analyzing data. A specific example is an HTTP POST request.

[2075] Processing flow and specific examples

[2076] 1. User Input and Emotion Recognition

[2077] Users input information such as their preferred style, desired functions, furniture layout, and size via a terminal. For example, they input detailed information such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm."

[2078] 2. Acquiring Emotion Data

[2079] The device's built-in emotion recognition engine captures the user's facial expressions and voice via a camera and microphone, extracting emotional data, which is then converted into a numerical value, such as "Happiness 0.8" or "Neutrality 0.2."

[2080] 3. Data transmission and analysis

[2081] This input information and emotion data are temporarily stored in memory and sent to the server in a structured data format (e.g., JSON format). The server analyzes the received data, checks its consistency, and filters out invalid values.

[2082] 4. Design generation and adjustment

[2083] The server then calls the generation AI based on the analyzed information. The generation AI generates the optimal design based on the user's input information and emotional data, optimizing the necessary materials to create a blueprint. The generation AI takes the emotional data into account, and suggests a more ambitious design if, for example, the user is expressing a high level of happiness.

[2084] 5. Confirm the design and place your order

[2085] The generated design is sent to the user's device via the server. The user can view the design as a 3D model and make further adjustments as necessary. Once they have decided on a design they are satisfied with, they can place an order online.

[2086] Prompt Sentence Examples

[2087] An example of a prompt given to a generative AI model might look something like this:

[2088] Create a modern L-shaped office desk with 3 drawers. Dimensions: width 150cm, depth 70cm, height 75cm. Optimize the materials based on user happiness level of 0.8.

[2089] Based on this example, the system can efficiently design, propose, and accept orders for custom furniture that reflects the user's preferences and feelings.

[2090] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2091] Step 1:

[2092] The user inputs detailed information about the furniture's style, function, layout, and size via the terminal. The input information is temporarily stored in the terminal's memory. Specifically, data such as "modern style," "L-shaped," "three drawers," "width 150 cm, depth 70 cm, height 75 cm" are input.

[2093] Step 2:

[2094] The emotion recognition engine built into the device captures the user's facial expressions and voice via the camera and microphone. The emotion recognition engine analyzes the user's emotional data and generates numerical emotional data. For example, it can obtain data such as "Happiness 0.8" or "Neutrality 0.2."

[2095] Step 3:

[2096] The device converts the input information and emotion data into a structured data format (JSON format) and sends it to the server, where preprocessing is also performed to check the data for consistency and filter out invalid values.

[2097] Step 4:

[2098] The server analyzes the received information and checks the data integrity and format. Valid data is obtained as a result of the analysis. For example, user information and emotion data are stored in an organized format on the server.

[2099] Step 5:

[2100] The server then calls a generative AI based on the analyzed information. The generative AI uses a pre-trained model to generate the optimal furniture design for the user. The input is user information and emotional data, and the output is an optimal design that reflects the user's needs.

[2101] Step 6:

[2102] The generative AI simultaneously generates the design and selects and optimizes the necessary materials. Based on emotional data, the design and material selection are fine-tuned. For example, if the user expresses a high level of happiness, a bright color scheme will be suggested.

[2103] Step 7:

[2104] The generated design and material information are sent from the server to the user's device. The device displays the received design as a 3D model for the user to confirm. The input here is the generated design data, and the output is the 3D model display.

[2105] Step 8:

[2106] The user checks the 3D model and makes any necessary adjustments. Once they are satisfied with the design, they place their order online. The terminal sends the order information and the final design to the server.

[2107] Step 9:

[2108] The server sends the received order data and final design to the manufacturing department, which uses automated machines to produce the furniture. The resulting output is specific manufacturing instructions and blueprints.

[2109] Step 10:

[2110] The manufactured furniture is then packaged and delivered to the address specified by the user, where the user can receive their custom furniture order.

[2111] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2112] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2113] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2114] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2115] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2116] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2117] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2118] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2119] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2120] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2121] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2122] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2123] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2124] 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.

[2125] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2126] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2127] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2128] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2129] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2130] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2131] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2132] The following is further disclosed regarding the above embodiment.

[2133] (Claim 1)

[2134] means for a user to input style, function, placement, and size details via a terminal;

[2135] A means for transmitting input information from the terminal to a server;

[2136] A means for the server to analyze the received information and call the generation AI;

[2137] A means for the generative AI to generate optimal furniture designs based on user information,

[2138] A means for generative AI to optimize the materials needed for a design and create a blueprint,

[2139] A means for the server to transmit the generated design to a user terminal;

[2140] A means for users to view designs and complete an order process;

[2141] a means for the server to transmit the final design to manufacturing;

[2142] a means for the manufacturing department to manufacture the furniture based on the received design and deliver the completed furniture to the user;

[2143] A system including:

[2144] (Claim 2)

[2145] The system of claim 1, wherein the generative AI performs design generation and material optimization.

[2146] (Claim 3)

[2147] 10. The system of claim 1, further comprising an interface that allows a user to readjust the design.

[2148] "Example 1"

[2149] (Claim 1)

[2150] means for a user to input details of the style, function, arrangement and dimensions of the article via a terminal;

[2151] A means for transmitting the input structured data to a server by the terminal;

[2152] means for analyzing the information received by the server to perform data integrity checks and filter invalid values;

[2153] A means for the server to call a generating artificial intelligence based on the analyzed information;

[2154] A means for the generating artificial intelligence to generate an article design based on user information and select and optimize materials;

[2155] means for the server to transmit the three-dimensional model of the generated design to a user terminal;

[2156] means for the user to review the design, readjust the design if necessary via a readjustable interface, and ultimately complete the order process;

[2157] means for the server to transmit the final design to the manufacturing department and transfer data including blueprints, material lists, and processing instructions;

[2158] a manufacturing department that uses automated machinery to manufacture the furniture based on the received design and delivers the completed furniture to the user;

[2159] A system including:

[2160] (Claim 2)

[2161] 10. The system of claim 1, wherein the generative artificial intelligence generates designs and optimizes materials.

[2162] (Claim 3)

[2163] 10. The system of claim 1, further comprising an interface that allows a user to readjust the design.

[2164] "Application Example 1"

[2165] (Claim 1)

[2166] means for a user to input style, function, placement, and size details via an information processing device;

[2167] a means for transmitting input information to a group of information processing devices;

[2168] A means for analyzing the information received by the information processing device group and calling up the generative AI model;

[2169] A means for the generative AI model to generate optimal furniture designs based on user information;

[2170] A means for a generative AI model to optimize the resources required for design and create blueprints;

[2171] a means for transmitting the design generated by the information processing devices to the user information processing device;

[2172] A means for users to check designs and place orders through a head-mounted display;

[2173] means for the information processing device group to transmit the final design to the manufacturing department;

[2174] a means for the manufacturing department to manufacture the furniture based on the received design and deliver the completed furniture to the user;

[2175] A system including:

[2176] (Claim 2)

[2177] 10. The system of claim 1, wherein the generative AI model performs design generation and resource optimization.

[2178] (Claim 3)

[2179] 10. The system of claim 1, providing an interface that allows a user to readjust the design through a head-mounted display.

[2180] ...

Claims

1. means for a user to input style, function, placement, and size details via a terminal; A means for transmitting input information from the terminal to a server; A means for the server to analyze the received information and call the generation AI; A means for the generative AI to generate optimal furniture designs based on user information, A means for generative AI to optimize the materials needed for a design and create a blueprint, A means for the server to transmit the generated design to a user terminal; A means for users to view designs and complete an order process; a means for the server to transmit the final design to manufacturing; a means for the manufacturing department to manufacture the furniture based on the received design and deliver the completed furniture to the user; A system including:

2. The system of claim 1, wherein the generative AI performs design generation and material optimization.

3. The system of claim 1 , further comprising an interface that allows a user to readjust the design.

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