System

Abstract

A system is provided.SOLUTION: A system comprising: means for accepting user input; means for analyzing text information and illustration information received from a user; means for generating a three dimensional model of an accessory based on the analysis; means for transmitting instructions for producing a physical object based on the generated three dimensional model; means for prompting the user to confirm the generated three dimensional model; and means for accepting a modification request from 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] Conventional accessories often lack the detailed design that users expect, making it difficult to provide a satisfying product experience. Furthermore, some products do not even have accessories available, leaving many users unable to obtain accessories that meet their needs. The present invention aims to solve these problems and provide a system that allows all users to obtain accessories that meet their individual preferences. [Means for solving the problem]

[0005] The present invention comprises a system including means for accepting user input, means for analyzing text information and illustration information received from the user, means for generating a three-dimensional model of an accessory based on the analysis results, means for sending instructions for producing an actual item based on the generated three-dimensional model, means for prompting the user to confirm the generated three-dimensional model, and means for accepting correction requests from the user. The system also includes means for producing accessories using a three-dimensional printer, wood processing equipment, or leather processing equipment, thereby enabling the system to meet a variety of user needs.

[0006] The "means for accepting user input" is a device or software that provides an interface for the user to input detailed textual and / or illustrated information about the accessory they desire.

[0007] The "means for analyzing text information and illustration information" refers to a device or software for analyzing the information received from the user and extracting data necessary for designing the accessory.

[0008] "Means for generating a three-dimensional model" means a device or software that designs and generates a three-dimensional model of the accessory based on the analyzed information.

[0009] "Means for sending instructions to produce an actual object" refers to a device or software that sends the generated 3D model data to a 3D printer or other production device and provides instructions to start production.

[0010] The "means for prompting confirmation of the three-dimensional model" refers to a device or software that displays the generated three-dimensional model to the user and provides an interface for requesting confirmation and correction.

[0011] The "means for accepting a modification request" is a device or software for receiving a modification request from a user and regenerating a three-dimensional model based on the request.

[0012] A "3D printer" is a device that creates physical 3D objects based on digital model data.

[0013] A "wood processing device" is a device that processes wood based on digital model data and produces accessories.

[0014] A "leather processing device" is a device that processes leather based on digital model data and produces accessories. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

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

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then produces it using a three-dimensional printer or other processing device. The purpose of this system is to meet the needs of the user and provide original accessories based on those requests.

[0037] The system operates in the following manner. First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[0038] The device then sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0039] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, based on the size and shape of a camera lens case, it designs a model of a case that fits the lens perfectly.

[0040] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input correction requests as needed. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[0041] When the modification request arrives at the server, the server again modifies and regenerates the model using 3D modeling AI. This modified model is also sent to the device as a preview, and the user is asked for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[0042] The 3D printer or processing device that receives the production instruction will then produce the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is produced that meets the user's specific needs.

[0043] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[0044] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and uploads an illustration of the accessory's desired appearance. The server analyzes this information and uses 3D modeling AI to generate a 3D model of the lens case. This model is previewed to the user, who then inputs a request for revisions, such as "I would like the case to be a little thicker." The server then revises the model and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced and delivered.

[0045] The system of the present invention allows users to obtain accessories that are tailored to their needs, greatly improving the product usage experience.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] Users input detailed information about the accessories they want, including dimensions, shape, material, and other information as text data, and upload illustration data if necessary.

[0049] Step 2:

[0050] The terminal transmits the text information and illustration information input by the user to the server.

[0051] Step 3:

[0052] The server analyzes the received text information using natural language processing technology, extracting specific data such as dimensions, shape, and material from the text.

[0053] Step 4:

[0054] The server uses image analysis technology to analyze the received illustration information, understand the shape and design elements from the illustration, and generate data.

[0055] Step 5:

[0056] The server generates a three-dimensional model of the accessory using three-dimensional modeling AI based on the analyzed text information and illustration information.

[0057] Step 6:

[0058] The server transmits preview information of the generated three-dimensional model to the terminal.

[0059] Step 7:

[0060] The terminal displays the preview information to the user and asks for confirmation.

[0061] Step 8:

[0062] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[0063] Step 9:

[0064] The terminal transmits the user's correction request information to the server again.

[0065] Step 10:

[0066] The server modifies and regenerates the 3D model again using the 3D modeling AI based on the received modification request.

[0067] Step 11:

[0068] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[0069] Step 12:

[0070] The terminal displays the preview information to the user again and asks the user for final confirmation.

[0071] Step 13:

[0072] The user performs a final check and, if satisfied, approves the production.

[0073] Step 14:

[0074] The server sends the data of the final approved three-dimensional model to a three-dimensional printer or other processing device and issues production instructions.

[0075] Step 15:

[0076] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[0077] Step 16:

[0078] The server notifies the user that production is complete and arranges for delivery of the finished product.

[0079] Step 17:

[0080] The user receives the finished product and uses it to check that it meets their requirements.

[0081] Example 1

[0082] 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."

[0083] With conventional accessory manufacturing systems, it was difficult to easily produce custom-made accessories that met specific user requirements. In particular, to quickly and accurately provide products that met the user's desired specifications and designs, advanced design technology and effort were required, which led to challenges such as increased production costs.

[0084] 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.

[0085] In this invention, the server includes means for accepting user input, means for analyzing text data and image data received from the user, means for analyzing the text data using natural language processing technology, means for analyzing the image data using image analysis technology, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing an actual object based on the generated 3D model, means for displaying a preview of the generated 3D model to the user to prompt confirmation, means for accepting a correction request from the user, and means for regenerating the 3D model based on the correction request, thereby enabling users to easily create custom-made accessories.

[0086] The "means for accepting user input" is a mechanism for the user to input their wishes and requests regarding accessories as text data and image data.

[0087] "Means for analyzing text data and image data" refers to technology for analyzing text data and image data entered by a user and extracting information necessary for design.

[0088] "Means for analyzing text data using natural language processing technology" refers to technology for mechanically understanding text data and extracting specific design information such as dimensions and materials.

[0089] "Means for analyzing image data using image analysis technology" refers to technology for analyzing image data (e.g., illustrations) provided by users, understanding their contents, and reflecting them in the design.

[0090] The "means for generating a three-dimensional model of an accessory" is a mechanism for designing a three-dimensional shape of an accessory based on the analyzed text data and image data.

[0091] The "means for sending instructions for producing an entity" is a mechanism for sending production instructions to a production device based on the generated three-dimensional model.

[0092] The "means for displaying a preview of the generated three-dimensional model and prompting confirmation" is a mechanism for visually displaying a preview of the generated three-dimensional model to the user and prompting confirmation and correction requests.

[0093] The "means for accepting correction requests from users" is a mechanism that allows users to request corrections to be made to parts that need to be corrected after checking the preview.

[0094] The "means for regenerating a three-dimensional model based on a modification request" is a mechanism for regenerating a three-dimensional model by reflecting a modification request from a user.

[0095] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then manufactures it using a processing device. The system aims to meet the needs of the user and provide original accessories based on the user's requests.

[0096] This system operates using the following hardware and software: a server, terminals, a 3D printer, and various processing equipment. The analysis and modeling technologies used are natural language processing, image analysis, and 3D modeling AI.

[0097] First, the user uses the device to input detailed requests for the accessories they want. This request includes both text and illustrations. For example, if a user wants a case that fits a lens with a diameter of 70 mm and a height of 150 mm, they can input the size, material, and shape in text format and upload an illustration of the desired shape.

[0098] The device sends the text and illustration information entered by the user to the server. The server receives this information and first analyzes the text information using natural language processing technology. This extracts specific data such as the required dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0099] Based on the analysis results, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, it generates a 3D model of a case that fits a lens with a diameter of 70 mm and a height of 150 mm. This generated model is sent from the server to the device as a preview and displayed to the user.

[0100] The user can check the preview displayed on their device and input correction requests as needed. For example, they can input a specific request for correction, such as "I want the case to be 2mm thicker." The server receives the request and uses the 3D modeling AI to correct and regenerate the model.

[0101] Once the edits are complete, the model is again displayed as a preview to the user. Once the user has given their final approval, the server sends production instructions to a 3D printer or other processing device. The 3D printer then produces a physical accessory based on the model data. For example, it might produce a lens case using the specified material and dimensions.

[0102] Once production is complete, the server notifies the user and arranges for delivery of the finished product. The user receives the finished product at the address they specify and uses it. This system allows users to easily obtain original accessories that perfectly suit their needs.

[0103] As a concrete example, consider a case where a user wants to create a "camera lens case." The user enters the following prompt:

[0104] "I'd like you to design a case that will fit a lens with a diameter of 70mm and a height of 150mm."

[0105] By uploading an illustration of the desired shape, the server analyzes the information and uses 3D modeling AI to generate a 3D model of the accessory. This process is repeated until the final product is produced and delivered to the user.

[0106] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0107] Step 1: User enters request

[0108] The user uses a terminal to enter detailed requests for accessories into a special form. The input includes text information (e.g., "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm") and image information (an illustration of the desired shape). When the user presses the "Submit" button, the request is sent.

[0109] Input: Text and image information entered by the user on the device.

[0110] Output: Input text and image data

[0111] Step 2: The device sends the input information to the server

[0112] The terminal transmits the text and image information input by the user to the server, which converts the data into packets and transmits them to the server via the network.

[0113] Input: Text and image data entered into the device

[0114] Output: Text and image data sent to the server

[0115] Step 3: The server receives the information and parses the text information

[0116] The server receives the text information sent from the device and analyzes it using natural language processing technology. Through this analysis, design data such as specific dimensions and shape is extracted. For example, information such as "diameter 70 mm, height 150 mm" is extracted.

[0117] Input: Text information sent

[0118] Output: Extracted design data such as dimensions and shapes

[0119] Step 4: The server analyzes the image information

[0120] The server receives the image information sent from the device and analyzes it using image analysis technology. For example, it analyzes an illustration uploaded by a user and extracts its shape and design features.

[0121] Input: Image information sent

[0122] Output: Extracted shapes and design features

[0123] Step 5: The server generates the 3D model

[0124] The server uses 3D modeling AI to generate a 3D model based on the analyzed text and image data. The model has the 3D shape of the accessory designed based on the analysis results.

[0125] Input: Parsed text data and image data

[0126] Output: Data of the generated 3D model

[0127] Step 6: Send the generated model to the device

[0128] The server transmits preview information of the generated 3D model to the terminal and displays it to the user. The terminal receives the data and displays the model on the preview screen.

[0129] Input: Data of the generated 3D model

[0130] Output: Preview information of the 3D model displayed on the device

[0131] Step 7: User sees preview

[0132] The user checks the preview of the 3D model displayed on the terminal, checks whether it matches their requirements, and prepares to re-enter any necessary corrections.

[0133] Input: Previewed 3D model

[0134] Output: User's modification request

[0135] Step 8: User Enters Modification Request

[0136] The user inputs the required corrections and sends them to the server, for example, "I want the case thickness to be increased by 2 mm," and presses the submit button.

[0137] Input: User inputs correction request

[0138] Output: Correction request submitted

[0139] Step 9: The server regenerates the 3D model based on the modification request.

[0140] The server receives the modification request sent by the user and again modifies and regenerates the model using the 3D modeling AI.

[0141] Input: The correction request submitted

[0142] Output: Regenerated 3D model data

[0143] Step 10: The server sends the regenerated model to the device

[0144] The server transmits preview information of the regenerated 3D model to the terminal and displays it to the user. The terminal receives the data and redisplays the model on the preview screen.

[0145] Input: Data of the regenerated 3D model

[0146] Output: Preview information of the regenerated 3D model displayed on the device

[0147] Step 11: User performs final confirmation

[0148] The user checks the preview again and makes a final check, and if satisfied, presses the approve button to confirm the model as the final version.

[0149] Input: Redisplayed preview information

[0150] Output: Final user review and approval

[0151] Step 12: The server issues a production command

[0152] The server sends the final 3D model approved by the user as a production instruction to a 3D printer or other processing device.

[0153] Input: User-approved final model

[0154] Output: Production instructions for 3D printers and processing equipment

[0155] Step 13: The 3D printer creates

[0156] A 3D printer or processing device creates a physical accessory based on the transmitted model data, such as a lens case made of the specified material and dimensions.

[0157] Input: 3D model production instructions

[0158] Output: Complete physical attachment

[0159] Step 14: Server arranges delivery

[0160] Once production is complete, the server notifies the user and arranges for delivery of the finished product, which the user can then pick up at the address they specify.

[0161] Input: Notification of production completion

[0162] Output: The finished product delivered to the user

[0163] This allows users to get original accessories that suit their needs.

[0164] (Application example 1)

[0165] 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."

[0166] Today's consumers are increasingly seeking custom-made products that meet their individual needs. However, mass-produced products are sold in general stores, making it difficult for consumers to obtain custom accessories that meet their specific requirements. Furthermore, the process for consumers to create custom products based on their own designs is complicated, and they cannot fully utilize the service unless they are familiar with the tools and technology used. Furthermore, when ordering custom-made products online, consumers cannot see the actual product, which can reduce consumer satisfaction. There is a need for a system that solves these problems and meets consumers' individual needs quickly and easily.

[0167] 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.

[0168] In this invention, the server includes means for accepting user input, means for analyzing the text and illustration information received from the user, and means for generating a three-dimensional model of the accessory based on the analysis results. This enables a system for creating, manufacturing, and selling custom accessories in a physical store. By incorporating this system, consumers can quickly create custom products based on their own designs and requests, and then check and purchase the actual product in a physical store.

[0169] The "means for accepting user input" is an interface that allows the user to input text information and illustration information.

[0170] "Means for analyzing text information and illustration information received from users" refers to the processes and techniques for analyzing text information entered by users and illustrations uploaded by users and extracting the necessary data.

[0171] "Means for generating a three-dimensional model of an accessory based on the analysis results" refers to techniques and tools for designing and creating a three-dimensional model of an accessory based on the analyzed text information and illustration information.

[0172] "Means for sending instructions for producing an actual product based on the generated three-dimensional model" refers to a process or system that sends instructions for producing an actual product based on the generated three-dimensional model to a processing device or manufacturing equipment.

[0173] The "means for prompting the user to check the generated three-dimensional model" refers to a function or interface for displaying a preview of the generated three-dimensional model to the user and requesting confirmation of the model.

[0174] The "means for accepting a modification request from a user" is an interface that allows a user to input a request for modification or change to the generated three-dimensional model.

[0175] "Means for creating, manufacturing, and selling custom accessories in a physical store" refers to equipment or a system for creating, manufacturing, and selling custom accessories in a physical store.

[0176] "Means for producing with a 3D printer" refers to the technology and equipment for producing a product using a 3D printer based on the generated 3D model.

[0177] "Means for producing with woodworking equipment or leatherworking equipment" means equipment or techniques for producing products based on three-dimensional models using wood or leather.

[0178] The present invention relates to a system that generates three-dimensional models of custom accessories based on requests input by users, and then produces and sells them in a physical store. The purpose of this system is to provide original accessories that meet the needs of users.

[0179] A specific embodiment of the system is given below.

[0180] First, the user accesses the application using a smartphone. This application has a text input form and an illustration data upload function as a means of accepting user input. When the user enters text information and uploads illustration data of the desired shape, the requested content is notified to the system.

[0181] Next, the device sends the text and illustration information received from the user to the server. The server analyzes this information using natural language processing technology (e.g., OpenAI GPT-3) and image analysis technology (e.g., OpenCV). The text information is analyzed to extract specific data such as dimensions and shape, and the illustration information is used to extract shape data through image recognition.

[0182] Based on the analyzed data, the server uses 3D modeling AI (e.g., Blender's Python API) to generate a 3D model of the custom accessory. The generated 3D model is sent from the server to the device as preview information and displayed to the user. The user can check this preview and input correction requests as needed. For example, they can input specific requests such as "I want it to be a little thicker."

[0183] When the user inputs a modification request, the server again modifies and regenerates the model using the 3D modeling AI. This modified model is also displayed to the user as a preview again, and the user is asked for final confirmation. Once the user has made the final confirmation and approved, the server sends production instructions to the 3D printer or processing equipment in the physical store.

[0184] The 3D printer receives the production instructions and begins producing the custom accessory based on the model data sent. Once production is complete, the server notifies the user, who then picks up the finished product at a physical store. This allows users to obtain an original accessory that perfectly matches their design.

[0185] As a concrete example, consider the case where a user wants to create a pendant. The user enters text information such as "I want a pendant with a diameter of 50 mm and a height of 100 mm," and uploads an illustration of the desired design. The server analyzes this information and generates a 3D model of the pendant using 3D modeling AI. This model is previewed to the user, who then inputs a correction request, such as "I'd like it to be a little thicker." The server then corrects the model again and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced in a physical store and the user is notified.

[0186] An example of a prompt sentence to input to the generative AI model is as follows:

[0187] Extract dimensions from the text: 'I would like a pendant that is 50mm in diameter and 100mm in height'

[0188]

[0189] Generate a 3D model with dimensions 50mm diameter and 100mm height and based on the recognized shape from the uploaded illustration.

[0190] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0191] Step 1:

[0192] The user accesses the smartphone app and inputs text information and illustration data.

[0193] Input: Text information (e.g., "I want a pendant with a diameter of 50 mm and a height of 100 mm"), illustration data

[0194] Data processing / data calculation: The user uses the application's input form to enter details of the accessory they are requesting in text and upload illustration data.

[0195] Output: The entered text information and illustration data are saved on the device and sent to the server.

[0196] Step 2:

[0197] The terminal transmits the received text information and illustration information to the server.

[0198] Input: Text information and illustration data entered by the user

[0199] Data processing / data calculation: The terminal sends this information to the server via the API.

[0200] Output: Text information and illustration data are received by the server.

[0201] Step 3:

[0202] The server analyzes the text information using natural language processing techniques to extract specific data such as dimensions.

[0203] Input: Text information received by the server

[0204] Data processing / data calculation: The server analyzes the text information using natural language processing technology (e.g., OpenAI GPT-3) and extracts data related to dimensions and shape.

[0205] Output: Extracted dimensional and geometric data

[0206] Step 4:

[0207] The server analyzes the illustration information using image analysis technology and extracts shape data.

[0208] Input: Illustration data received by the server

[0209] Data processing / data calculation: The server uses image analysis technology (e.g., OpenCV) to analyze the illustration information and extract shape data.

[0210] Output: Extracted shape data

[0211] Step 5:

[0212] The server performs three-dimensional modeling based on the extracted dimension data and shape data.

[0213] Input: Extracted dimensional and geometric data

[0214] Data processing / data calculation: The server generates a 3D model using 3D modeling AI (e.g., Blender's Python API).

[0215] Output: Data of the generated 3D model

[0216] Step 6:

[0217] The server transmits the generated three-dimensional model to the terminal as a preview and displays it to the user.

[0218] Input: Data of the generated 3D model

[0219] Data processing / data calculation: The server generates preview data for the 3D model and sends it to the terminal.

[0220] Output: Preview image displayed on the device

[0221] Step 7:

[0222] The user checks the preview and inputs correction requests as necessary.

[0223] Input: Preview image, correction request (e.g. "I'd like it to be a little thicker")

[0224] Data processing / data calculation: The user checks the preview and, if any corrections are necessary, sends a correction request to the server through the application.

[0225] Output: Modified request data

[0226] Step 8:

[0227] The server regenerates the three-dimensional model based on the modification request.

[0228] Input: Correction request data, original 3D model data

[0229] Data processing / data calculation: The server again uses 3D modeling AI (e.g., Blender's Python API) to modify and regenerate the model.

[0230] Output: Corrected 3D model data

[0231] Step 9:

[0232] The server transmits the modified three-dimensional model to the terminal as a re-preview and asks the user for final confirmation.

[0233] Input: Data of the corrected 3D model

[0234] Data processing / data calculation: The server generates data for re-preview and sends it to the terminal.

[0235] Output: Preview image displayed on the device

[0236] Step 10:

[0237] Once the user has made a final confirmation and approved it, the server sends production instructions to the 3D printer or processing equipment at the physical store.

[0238] Input: Final confirmation and approval, corrected 3D model data

[0239] Data processing / data calculation: The server generates production instruction data and sends it to the 3D printer in the physical store.

[0240] Output: Production instruction data sent to the 3D printer and processing equipment in the physical store

[0241] Step 11:

[0242] In the physical store, a 3D printer creates custom accessories based on production instructions.

[0243] Input: Manufacturing instruction data, corrected 3D model data

[0244] Data processing / data calculation: The 3D printer produces custom accessories according to the production instructions.

[0245] Output: Finished custom accessories

[0246] Step 12:

[0247] Once production is complete, the server notifies the user and arranges for them to pick up the accessory at a designated physical store.

[0248] Input: Completed custom accessory information

[0249] Data processing / data calculation: The server generates a production completion notification and sends it to the user. It also arranges for the item to be picked up at the designated physical store.

[0250] Output: Notification to users and physical stores

[0251] 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.

[0252] The present invention relates to a system that generates a three-dimensional model of an accessory based on requests input by the user and then produces it using a three-dimensional printer or other processing device.The purpose of the present invention is to provide a higher user experience by combining it with an "emotion engine" that recognizes the user's emotions and reflects that information.

[0253] This system works as follows: First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[0254] The device sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0255] Furthermore, the system includes an emotion engine for recognizing the user's emotions. This emotion engine analyzes emotions from facial expressions, voice, and text when the user inputs information. For example, it recognizes whether the user's facial expression is happy or confused while inputting information. It also analyzes emotional expressions contained in the text.

[0256] Based on the analyzed text, illustration, and emotion information, the server uses 3D modeling AI to generate a 3D model of the accessory. Emotional information is reflected in the generation and modification of the 3D model. For example, if the user has a confused expression, the server can provide more detailed guidance on the model or ask a simple question.

[0257] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input any necessary correction requests. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[0258] When the modification request arrives at the server, the server again uses the 3D modeling AI to modify and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the modification request and providing appropriate support and guidance. This modified model is again sent to the device as a preview, prompting the user for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[0259] The 3D printer or processing device that receives the production instructions will then create the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is created that meets the user's specific requests and emotional information.

[0260] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[0261] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and also uploads an illustration of the accessory's desired appearance. The emotion engine analyzes the user's emotions as they input, and if it detects, for example, a "confused expression," the server provides additional support. The server analyzes the information and uses 3D modeling AI to generate a 3D model of the lens case. This model is then previewed for the user, who can then input any final revision requests. Once the model is finally approved, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[0262] The system of the present invention allows users to get accessories that are tailored to their needs and emotions, thus greatly improving the product usage experience.

[0263] The processing flow will be explained below.

[0264] Step 1:

[0265] Users input detailed information about the accessories they want. Specifically, they input information such as dimensions, shape, and material as text data, and upload illustration data if necessary. The emotion engine also analyzes the user's facial expressions and voice while they are entering information.

[0266] Step 2:

[0267] The terminal transmits the text information, illustration information, and emotion information received from the user to the server.

[0268] Step 3:

[0269] The server uses natural language processing technology to analyze the text information and extract specific data such as dimensions, shape, and material. It also uses image analysis technology to analyze the illustration information and understand its content.

[0270] Step 4:

[0271] The server uses an emotion engine to analyze the user's emotions from their facial expressions and voice. The emotion data is reflected in the generation and modification of models.

[0272] Step 5:

[0273] The server uses 3D modeling AI to generate a 3D model of the accessory based on the analyzed text information, illustration information, and emotion information.

[0274] Step 6:

[0275] The server transmits preview information of the generated three-dimensional model to the terminal.

[0276] Step 7:

[0277] The device displays preview information to the user and asks for their confirmation. The emotion engine analyzes the user's reaction in real time and provides appropriate guidance and support.

[0278] Step 8:

[0279] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[0280] Step 9:

[0281] The terminal transmits the user's correction request information to the server again.

[0282] Step 10:

[0283] The server then uses the 3D modeling AI to modify and regenerate the 3D model based on the received modification request and emotion information. During this process, the emotion engine analyzes the user's emotions and provides appropriate support.

[0284] Step 11:

[0285] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[0286] Step 12:

[0287] The terminal displays the preview information to the user again and asks the user for final confirmation.

[0288] Step 13:

[0289] The user then makes a final check and, if satisfied, approves the production. At this point, the emotion engine analyzes the user's emotions and provides final feedback.

[0290] Step 14:

[0291] The server sends the final approved 3D model data to a 3D printer or other processing device and issues production instructions.

[0292] Step 15:

[0293] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[0294] Step 16:

[0295] The server notifies the user that production is complete and arranges for the finished product to be delivered to the specified address.

[0296] Step 17:

[0297] The user receives the finished product and uses it to check that it meets their requirements.

[0298] Example 2

[0299] 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."

[0300] The purpose of this invention is to efficiently produce custom-made accessories based on user input. However, conventional systems have difficulty in properly analyzing and incorporating vague user requests and feelings. Furthermore, the process of repeatedly incorporating revision requests into the design of the final product desired by the user must also be made more efficient. There is a need for a system that can address these challenges.

[0301] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0302] In this invention, the server includes: means for inputting a user's request; means for analyzing text information and image information received from the user; means for analyzing the text information and image information using natural language processing technology and image analysis technology; means including an emotion recognition engine for recognizing and analyzing the user's emotions; means including a generative AI model for generating a 3D model of the accessory based on the analysis result and the emotion information; means for sending instructions for producing the actual product based on the generated 3D model; means for sending preview information of the generated 3D model to the user and prompting confirmation; and means for accepting correction requests from the user. This enables the rapid production of sophisticated, custom-made accessories that reflect the user's detailed requests and emotion information.

[0303] The "means for inputting user requests" is an interface that allows the user to input information about the accessories they want in text or image format.

[0304] The "means for analyzing text information and image information" refers to a processing device that analyzes the content of input text or images and extracts specific instructions or data from that information.

[0305] "Natural language processing technology" is a technology that analyzes text data, understands human language, and processes it as meaningful information.

[0306] "Image analysis technology" is a technology that analyzes image data and recognizes objects and features within it.

[0307] An "emotion recognition engine" is a device that analyzes and detects emotions from input such as a user's facial expressions, voice, and text.

[0308] A "generative AI model" is a system that has an artificial intelligence algorithm for automatically generating three-dimensional models based on analysis results and emotional information.

[0309] The "means for transmitting instructions for producing an actual product" is a communication device for sending production instructions to a processing machine or other production device based on the generated three-dimensional model.

[0310] The "means for sending preview information of the generated three-dimensional model to the user and prompting confirmation" is a device for sending a visual preview of the generated three-dimensional model to the user's terminal and prompting confirmation or correction requests.

[0311] The "means for accepting a modification request from a user" refers to an interface that allows a user to input a modification request for a three-dimensional model, and a device that transmits that information to the server.

[0312] The present invention relates to a system for efficiently generating and manufacturing custom accessories based on a user's specific needs. The system analyzes information entered by the user, generates a 3D model, and then automatically performs a series of steps to manufacture the accessory based on that model.

[0313] First, the user inputs information about the accessory they want using a dedicated application on their device or a web interface. Specifically, they can input text and image information. This text information can include detailed instructions about the accessory's dimensions, material, and shape. For image information, they can upload illustrations or photos showing the desired shape of the accessory.

[0314] Next, the terminal receives the text and image information entered by the user and transmits it to the server using a secure communication method using the HTTPS protocol.

[0315] The server is equipped with various technologies for analyzing the received text and image information. To analyze the text information, it uses natural language processing technology (such as SpaCy or BERT) to extract specific dimensional and shape data. To analyze the image information, it uses image processing technology (such as OpenCV or TensorFlow) to recognize shape and design information.

[0316] Furthermore, the server uses an emotion recognition engine to analyze the user's emotions from facial expressions, voice, and text while the user is entering information. It uses facial recognition and voice analysis technologies to understand the user's emotional state (e.g., confusion, joy, etc.). This emotional information plays an important role in subsequent processing.

[0317] Based on the analyzed information and emotion data, the server uses a generative AI model to generate a 3D model of the accessory, for example, by utilizing Blender or Autodesk Fusion 360 APIs to generate a specific 3D model, which is then optimized by taking emotion information into account.

[0318] The generated 3D model is sent from the server to the device in a preview format. The user can check this preview and, if necessary, input a correction request from the device. The server receives the user's correction request and uses the 3D modeling AI to correct and regenerate the model. This process is repeated until the user is satisfied.

[0319] Once the user finally reviews and approves the 3D model, the server sends production instructions to a 3D printer or other production device, which then produces the actual accessory. For example, a 3D printer begins producing the camera lens case specified by the user. Once production is complete, the server notifies the user and arranges for the finished product to be promptly delivered to the specified address.

[0320] Specific examples

[0321] For example, if a user inputs text information such as "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," along with an illustration of the case's shape, the server analyzes that information and generates a 3D model of the lens case using 3D modeling AI. If the user then checks the preview and inputs a request for revision, such as "I'd like the case to be a little thicker," the server will reflect that request and regenerate the model. This process is repeated several times, and once the final model is approved, a 3D printer will produce the case and deliver it to the customer.

[0322] Prompt Sentence Examples

[0323] "I'd like a camera lens case. Please model a case that fits a lens with a diameter of 70mm and a height of 150mm. I'll also upload an illustration."

[0324] Through this system, users can quickly obtain custom-made accessories that perfectly match their needs and emotions.

[0325] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0326] Step 1:

[0327] The user inputs information about the accessory they want into the device using a dedicated application or a web interface. The input information includes text specifications (e.g., "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm.") and illustrations in the form of images. This information is then imported into the device as input data.

[0328] Step 2:

[0329] The terminal sends the text and image information entered by the user to the server using the HTTPS protocol. For transmission, the text data and image data are packaged in JSON format and a secure communication channel is used. The input is JSON-formatted data, and the output is a successful transmission notification to the server.

[0330] Step 3:

[0331] The server analyzes the received text information using natural language processing technology (for example, SpaCy or BERT). Through analysis, specific dimension, material, and shape data is extracted from the input text information. The input is text data in JSON format, and the output is analyzed dimension and material data.

[0332] Step 4:

[0333] The server analyzes the received image information using image analysis technology (e.g., OpenCV or TensorFlow). Through the analysis, information about the shape and design is extracted from the image. The input is image data in JSON format, and the output is analyzed shape data and design data.

[0334] Step 5:

[0335] The server's emotion recognition engine analyzes facial expressions and voice data in real time while the user is entering information. It uses facial recognition and voice analysis technologies to analyze the user's emotional state (e.g., confusion, joy, etc.). The input is facial expression data and voice data, and the output is analyzed emotional information.

[0336] Step 6:

[0337] The server generates a 3D model using a generative AI model (e.g., Blender or Autodesk Fusion 360 API) based on the analysis results of natural language processing and image analysis technologies, as well as emotional information. The inputs are dimensional data, shape data, and emotional information, and the output is the generated 3D model data.

[0338] Step 7:

[0339] The server sends the generated 3D model in a preview format to the terminal. The user checks the preview on the terminal and inputs correction requests as necessary. The input is the generated 3D model data, and the output is the user's confirmation and correction request information.

[0340] Step 8:

[0341] The terminal receives the user's modification request and sends it back to the server. The server modifies and regenerates the model using 3D modeling AI based on the modification request information. The input is the modification request information, and the output is the modified 3D model data.

[0342] Step 9:

[0343] Once the user has finally reviewed and approved the 3D model, the server sends production instructions to a 3D printer or other processing device. The input is the final approved 3D model data, and the output is the production instructions.

[0344] Step 10:

[0345] The 3D printer or other processing device receives the production instructions and produces the specified accessory. When production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The input is the production instructions and status data of the 3D printer (or processing device), and the output is a production completion notification and delivery instructions.

[0346] (Application example 2)

[0347] 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."

[0348] Conventional customized product generation systems do not take user emotions into account, making it difficult to effectively provide original products that satisfy users. Furthermore, there is a lack of means to provide a better user experience by reflecting user emotions and needs in real time. Therefore, there is a growing need for a more personalized customized product generation system that includes user emotion analysis.

[0349] 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.

[0350] In this invention, the server includes means for accepting user input, means for analyzing text information and illustration information received from the user, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing the actual product based on the generated 3D model, means for prompting the user to confirm the generated 3D model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the 3D model, thereby enabling the generation and production of a 3D model based on the user's emotions and specific needs.

[0351] The "means for accepting user input" is an interface that allows the user to input their wishes and requirements in text or image format.

[0352] The "means for analyzing text information and illustration information received from the user" is a system for analyzing the content of the text and illustrations provided by the user and extracting the necessary data.

[0353] The "means for generating a three-dimensional model of the accessory based on the analysis results" is a system that creates a detailed three-dimensional model of the accessory based on the analyzed information.

[0354] The "means for transmitting instructions for producing an actual product based on the generated three-dimensional model" is a system that transmits data on the generated three-dimensional model to a device that actually produces the product.

[0355] The "means for prompting the user to check the generated three-dimensional model" is an interface that presents the generated three-dimensional model to the user and requests feedback.

[0356] The "means for accepting a modification request from a user" is a system in which a user inputs a request for modification of a generated three-dimensional model.

[0357] "Means for analyzing emotions" refers to technology for analyzing a user's emotions from their facial expressions, voice, and text.

[0358] "Means for reflecting the results of emotion analysis in the generation of 3D models" refers to a system that adjusts the design and guide of 3D models based on the analyzed emotion information.

[0359] A "three-dimensional manufacturing device" is a device that physically produces accessories based on three-dimensional model data.

[0360] A "wood processing machine" is a machine that processes wood into a specified shape.

[0361] A "leather processing device" is a device that processes leather material into a specified shape.

[0362] This invention relates to a system that accepts user input and generates original accessories based on that information. It also analyzes the user's emotions and reflects the results in the generation of a 3D model, providing a more personalized experience.

[0363] This system includes means for accepting user input, means for analyzing text information and illustration information, means for generating a three-dimensional model of the accessory based on the analysis results, means for sending instructions for producing the actual item based on the generated three-dimensional model, means for prompting the user to confirm the generated three-dimensional model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the three-dimensional model.

[0364] To explain the embodiment in detail, the operation is as follows:

[0365] 1. The user provides input

[0366] Users enter detailed information about the accessories they want using text and illustrations. For example, if they are ordering a camera lens case, they would enter the lens size, shape, and material requirements in text, and upload the desired shape as illustration data.

[0367] 2. Analysis of text and illustration information

[0368] The server analyzes the text and illustration information received from the user. The text information is interpreted using natural language processing technology to extract specific data on dimensions and shape. The illustration information is also analyzed using image analysis technology. The natural language processing technology used includes Huggingface transformers, and the image analysis technology used is OpenCV.

[0369] 3. 3D Model Generation

[0370] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. In this step, OpenAI's API is used to generate the 3D model. For example, a model of a camera lens case with the required shape and dimensions is generated based on the information entered by the user and the analysis results.

[0371] 4. User sentiment analysis and feedback

[0372] The system analyzes the user's facial expressions and voice while they are typing to collect emotional information. An emotion recognition model using Keras and TensorFlow is used for the emotion analysis. The results are reflected in the model generation process, providing detailed guidance if the user is confused, and incorporating positive emotions into the model design.

[0373] 5. Preview and correction requests

[0374] The server sends a preview of the generated 3D model to the user's device and displays it to them. The user can then review the preview and input correction requests as needed. For example, they could request to increase the thickness of the case or slightly change its shape.

[0375] 6. Final confirmation and production instructions

[0376] Based on the revision request, the server again uses the 3D modeling AI to revise and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the revision request and providing appropriate support and guidance. The revised model is previewed again, and once the user gives their final confirmation and approval, the server sends production instructions to the 3D manufacturing equipment.

[0377] 7. Production and Delivery

[0378] The 3D manufacturing equipment then produces the accessory based on the model data. For example, a 3D printer starts producing a camera lens case. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[0379] As a specific use case, consider a case where a user inputs "I want a camera lens case with a diameter of 70 mm and a height of 150 mm" and uploads their own image. If the emotion engine detects a "confused expression," the server provides additional support. The server then analyzes the information and generates a 3D model of the lens case using 3D modeling AI. This model is previewed to the user, who can then input any final revision requests. After final confirmation, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[0380] An example prompt is:

[0381] "I want a camera lens case that is 70mm in diameter and 150mm in height. User sentiment is confused."

[0382] This makes it possible to provide high-quality original accessories that meet the needs and feelings of users.

[0383] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0384] Step 1:

[0385] The user provides input

[0386] The user inputs detailed information about the accessory they want into the terminal. The input includes text information (e.g., "I want a camera lens case with a diameter of 70 mm and a height of 150 mm") and illustration information. The input data is sent to the server.

[0387] Input: Text information, illustration information

[0388] Output: User request data sent to the server

[0389] Step 2:

[0390] Analysis of text and illustration information

[0391] The server analyzes the received text using natural language processing technology (e.g., Huggingface's transformers), extracting specific dimensions and shape data from the text. At the same time, the illustration information is analyzed using image analysis technology (e.g., OpenCV) to obtain shape and design information.

[0392] Input: User's text information, illustration information

[0393] Output: Extracted dimension data and shape data

[0394] Step 3:

[0395] 3D model generation

[0396] The server uses a 3D modeling AI (e.g., OpenAI's API) to generate a 3D model of the accessory based on the analyzed data. The AI ​​model uses prompts to guide the generation process.

[0397] Input: Extracted dimension data, shape data, prompt statement (e.g., "I would like a camera lens case with a diameter of 70 mm and a height of 150 mm.")

[0398] Output: Generated 3D model

[0399] Step 4:

[0400] Emotion analysis

[0401] While the user is inputting, the user's facial expression and voice data are collected and emotion analysis is performed on the server. Keras and TensorFlow are used for emotion analysis to identify the type of emotion (e.g., "confusion") from the user's facial image and voice. Emotional information is also reflected in the generation of the 3D model.

[0402] Input: User's face image, voice data

[0403] Output: Parsed emotion information

[0404] Step 5:

[0405] Model modification based on user sentiment

[0406] Based on the analyzed emotion information, the server provides feedback to the 3D model generation process: if the emotion is "confused," additional support or detailed guidance is provided.

[0407] Input: Analyzed emotion information, generated 3D model

[0408] Output: Corrected 3D model, supporting information

[0409] Step 6:

[0410] Preview and correction requests accepted

[0411] The server sends a preview of the generated 3D model to the terminal and displays it to the user. The user checks the preview and re-enters any parts they want to modify. The modification request is then sent back to the server.

[0412] Input: Generated 3D model, user modification request

[0413] Output: User feedback, correction requests

[0414] Step 7:

[0415] Final confirmation and production instructions

[0416] Based on the modification request, the server again modifies and regenerates the model using the 3D modeling AI. Once final confirmation is received from the user, the server issues a manufacturing instruction to the 3D manufacturing equipment.

[0417] Input: User's final confirmation, modified 3D model

[0418] Output: Production instructions for 3D manufacturing equipment

[0419] Step 8:

[0420] Production and Delivery

[0421] The 3D manufacturing equipment creates the actual product based on the model data sent from the server. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[0422] Input: Modified 3D model, fabrication instructions

[0423] Output: Finished product, notification to user and delivery arrangements

[0424] 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.

[0425] 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.

[0426] 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.

[0427] [Second embodiment]

[0428] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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).

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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."

[0440] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then produces it using a three-dimensional printer or other processing device. The purpose of this system is to meet the needs of the user and provide original accessories based on those requests.

[0441] The system operates in the following manner. First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[0442] The device then sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0443] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, based on the size and shape of a camera lens case, it designs a model of a case that fits the lens perfectly.

[0444] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input correction requests as needed. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[0445] When the modification request arrives at the server, the server again modifies and regenerates the model using 3D modeling AI. This modified model is also sent to the device as a preview, and the user is asked for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[0446] The 3D printer or processing device that receives the production instruction will then produce the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is produced that meets the user's specific needs.

[0447] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[0448] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and uploads an illustration of the accessory's desired appearance. The server analyzes this information and uses 3D modeling AI to generate a 3D model of the lens case. This model is previewed to the user, who then inputs a request for revisions, such as "I would like the case to be a little thicker." The server then revises the model and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced and delivered.

[0449] The system of the present invention allows users to obtain accessories that are tailored to their needs, greatly improving the product usage experience.

[0450] The processing flow will be explained below.

[0451] Step 1:

[0452] Users input detailed information about the accessories they want, including dimensions, shape, material, and other information as text data, and upload illustration data if necessary.

[0453] Step 2:

[0454] The terminal transmits the text information and illustration information input by the user to the server.

[0455] Step 3:

[0456] The server analyzes the received text information using natural language processing technology, extracting specific data such as dimensions, shape, and material from the text.

[0457] Step 4:

[0458] The server uses image analysis technology to analyze the received illustration information, understand the shape and design elements from the illustration, and generate data.

[0459] Step 5:

[0460] The server generates a three-dimensional model of the accessory using three-dimensional modeling AI based on the analyzed text information and illustration information.

[0461] Step 6:

[0462] The server transmits preview information of the generated three-dimensional model to the terminal.

[0463] Step 7:

[0464] The terminal displays the preview information to the user and asks for confirmation.

[0465] Step 8:

[0466] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[0467] Step 9:

[0468] The terminal transmits the user's correction request information to the server again.

[0469] Step 10:

[0470] The server modifies and regenerates the 3D model again using the 3D modeling AI based on the received modification request.

[0471] Step 11:

[0472] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[0473] Step 12:

[0474] The terminal displays the preview information to the user again and asks the user for final confirmation.

[0475] Step 13:

[0476] The user performs a final check and, if satisfied, approves the production.

[0477] Step 14:

[0478] The server sends the data of the final approved three-dimensional model to a three-dimensional printer or other processing device and issues production instructions.

[0479] Step 15:

[0480] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[0481] Step 16:

[0482] The server notifies the user that production is complete and arranges for delivery of the finished product.

[0483] Step 17:

[0484] The user receives the finished product and uses it to check that it meets their requirements.

[0485] Example 1

[0486] 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."

[0487] With conventional accessory manufacturing systems, it was difficult to easily produce custom-made accessories that met specific user requirements. In particular, to quickly and accurately provide products that met the user's desired specifications and designs, advanced design technology and effort were required, which led to challenges such as increased production costs.

[0488] 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.

[0489] In this invention, the server includes means for accepting user input, means for analyzing text data and image data received from the user, means for analyzing the text data using natural language processing technology, means for analyzing the image data using image analysis technology, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing an actual object based on the generated 3D model, means for displaying a preview of the generated 3D model to the user to prompt confirmation, means for accepting a correction request from the user, and means for regenerating the 3D model based on the correction request, thereby enabling users to easily create custom-made accessories.

[0490] The "means for accepting user input" is a mechanism for the user to input their wishes and requests regarding accessories as text data and image data.

[0491] "Means for analyzing text data and image data" refers to technology for analyzing text data and image data entered by a user and extracting information necessary for design.

[0492] "Means for analyzing text data using natural language processing technology" refers to technology for mechanically understanding text data and extracting specific design information such as dimensions and materials.

[0493] "Means for analyzing image data using image analysis technology" refers to technology for analyzing image data (e.g., illustrations) provided by users, understanding their contents, and reflecting them in the design.

[0494] The "means for generating a three-dimensional model of an accessory" is a mechanism for designing a three-dimensional shape of an accessory based on the analyzed text data and image data.

[0495] The "means for sending instructions for producing an entity" is a mechanism for sending production instructions to a production device based on the generated three-dimensional model.

[0496] The "means for displaying a preview of the generated three-dimensional model and prompting confirmation" is a mechanism for visually displaying a preview of the generated three-dimensional model to the user and prompting confirmation and correction requests.

[0497] The "means for accepting correction requests from users" is a mechanism that allows users to request corrections to be made to parts that need to be corrected after checking the preview.

[0498] The "means for regenerating a three-dimensional model based on a modification request" is a mechanism for regenerating a three-dimensional model by reflecting a modification request from a user.

[0499] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then manufactures it using a processing device. The system aims to meet the needs of the user and provide original accessories based on the user's requests.

[0500] This system operates using the following hardware and software: a server, terminals, a 3D printer, and various processing equipment. The analysis and modeling technologies used are natural language processing, image analysis, and 3D modeling AI.

[0501] First, the user uses the device to input detailed requests for the accessories they want. This request includes both text and illustrations. For example, if a user wants a case that fits a lens with a diameter of 70 mm and a height of 150 mm, they can input the size, material, and shape in text format and upload an illustration of the desired shape.

[0502] The device sends the text and illustration information entered by the user to the server. The server receives this information and first analyzes the text information using natural language processing technology. This extracts specific data such as the required dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0503] Based on the analysis results, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, it generates a 3D model of a case that fits a lens with a diameter of 70 mm and a height of 150 mm. This generated model is sent from the server to the device as a preview and displayed to the user.

[0504] The user can check the preview displayed on their device and input correction requests as needed. For example, they can input a specific request for correction, such as "I want the case to be 2mm thicker." The server receives the request and uses the 3D modeling AI to correct and regenerate the model.

[0505] Once the edits are complete, the model is again displayed as a preview to the user. Once the user has given their final approval, the server sends production instructions to a 3D printer or other processing device. The 3D printer then produces a physical accessory based on the model data. For example, it might produce a lens case using the specified material and dimensions.

[0506] Once production is complete, the server notifies the user and arranges for delivery of the finished product. The user receives the finished product at the address they specify and uses it. This system allows users to easily obtain original accessories that perfectly suit their needs.

[0507] As a concrete example, consider a case where a user wants to create a "camera lens case." The user enters the following prompt:

[0508] "I'd like you to design a case that will fit a lens with a diameter of 70mm and a height of 150mm."

[0509] By uploading an illustration of the desired shape, the server analyzes the information and uses 3D modeling AI to generate a 3D model of the accessory. This process is repeated until the final product is produced and delivered to the user.

[0510] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0511] Step 1: User enters request

[0512] The user uses a terminal to enter detailed requests for accessories into a special form. The input includes text information (e.g., "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm") and image information (an illustration of the desired shape). When the user presses the "Submit" button, the request is sent.

[0513] Input: Text and image information entered by the user on the device.

[0514] Output: Input text and image data

[0515] Step 2: The device sends the input information to the server

[0516] The terminal transmits the text and image information input by the user to the server, which converts the data into packets and transmits them to the server via the network.

[0517] Input: Text and image data entered into the device

[0518] Output: Text and image data sent to the server

[0519] Step 3: The server receives the information and parses the text information

[0520] The server receives the text information sent from the device and analyzes it using natural language processing technology. Through this analysis, design data such as specific dimensions and shape is extracted. For example, information such as "diameter 70 mm, height 150 mm" is extracted.

[0521] Input: Text information sent

[0522] Output: Extracted design data such as dimensions and shapes

[0523] Step 4: The server analyzes the image information

[0524] The server receives the image information sent from the device and analyzes it using image analysis technology. For example, it analyzes an illustration uploaded by a user and extracts its shape and design features.

[0525] Input: Image information sent

[0526] Output: Extracted shapes and design features

[0527] Step 5: The server generates the 3D model

[0528] The server uses 3D modeling AI to generate a 3D model based on the analyzed text and image data. The model has the 3D shape of the accessory designed based on the analysis results.

[0529] Input: Parsed text data and image data

[0530] Output: Data of the generated 3D model

[0531] Step 6: Send the generated model to the device

[0532] The server transmits preview information of the generated 3D model to the terminal and displays it to the user. The terminal receives the data and displays the model on the preview screen.

[0533] Input: Data of the generated 3D model

[0534] Output: Preview information of the 3D model displayed on the device

[0535] Step 7: User sees preview

[0536] The user checks the preview of the 3D model displayed on the terminal, checks whether it matches their requirements, and prepares to re-enter any necessary corrections.

[0537] Input: Previewed 3D model

[0538] Output: User's modification request

[0539] Step 8: User Enters Modification Request

[0540] The user inputs the required corrections and sends them to the server, for example, "I want the case thickness to be increased by 2 mm," and presses the submit button.

[0541] Input: User inputs correction request

[0542] Output: Correction request submitted

[0543] Step 9: The server regenerates the 3D model based on the modification request.

[0544] The server receives the modification request sent by the user and again modifies and regenerates the model using the 3D modeling AI.

[0545] Input: The correction request submitted

[0546] Output: Regenerated 3D model data

[0547] Step 10: The server sends the regenerated model to the device

[0548] The server transmits preview information of the regenerated 3D model to the terminal and displays it to the user. The terminal receives the data and redisplays the model on the preview screen.

[0549] Input: Data of the regenerated 3D model

[0550] Output: Preview information of the regenerated 3D model displayed on the device

[0551] Step 11: User performs final confirmation

[0552] The user checks the preview again and makes a final check, and if satisfied, presses the approve button to confirm the model as the final version.

[0553] Input: Redisplayed preview information

[0554] Output: Final user review and approval

[0555] Step 12: The server issues a production command

[0556] The server sends the final 3D model approved by the user as a production instruction to a 3D printer or other processing device.

[0557] Input: User-approved final model

[0558] Output: Production instructions for 3D printers and processing equipment

[0559] Step 13: The 3D printer creates

[0560] A 3D printer or processing device creates a physical accessory based on the transmitted model data, such as a lens case made of the specified material and dimensions.

[0561] Input: 3D model production instructions

[0562] Output: Complete physical attachment

[0563] Step 14: Server arranges delivery

[0564] Once production is complete, the server notifies the user and arranges for delivery of the finished product, which the user can then pick up at the address they specify.

[0565] Input: Notification of production completion

[0566] Output: The finished product delivered to the user

[0567] This allows users to get original accessories that suit their needs.

[0568] (Application example 1)

[0569] 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."

[0570] Today's consumers are increasingly seeking custom-made products that meet their individual needs. However, mass-produced products are sold in general stores, making it difficult for consumers to obtain custom accessories that meet their specific requirements. Furthermore, the process for consumers to create custom products based on their own designs is complicated, and they cannot fully utilize the service unless they are familiar with the tools and technology used. Furthermore, when ordering custom-made products online, consumers cannot see the actual product, which can reduce consumer satisfaction. There is a need for a system that solves these problems and meets consumers' individual needs quickly and easily.

[0571] 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.

[0572] In this invention, the server includes means for accepting user input, means for analyzing the text and illustration information received from the user, and means for generating a three-dimensional model of the accessory based on the analysis results. This enables a system for creating, manufacturing, and selling custom accessories in a physical store. By incorporating this system, consumers can quickly create custom products based on their own designs and requests, and then check and purchase the actual product in a physical store.

[0573] The "means for accepting user input" is an interface that allows the user to input text information and illustration information.

[0574] "Means for analyzing text information and illustration information received from users" refers to the processes and techniques for analyzing text information entered by users and illustrations uploaded by users and extracting the necessary data.

[0575] "Means for generating a three-dimensional model of an accessory based on the analysis results" refers to techniques and tools for designing and creating a three-dimensional model of an accessory based on the analyzed text information and illustration information.

[0576] "Means for sending instructions for producing an actual product based on the generated three-dimensional model" refers to a process or system that sends instructions for producing an actual product based on the generated three-dimensional model to a processing device or manufacturing equipment.

[0577] The "means for prompting the user to check the generated three-dimensional model" refers to a function or interface for displaying a preview of the generated three-dimensional model to the user and requesting confirmation of the model.

[0578] The "means for accepting a modification request from a user" is an interface that allows a user to input a request for modification or change to the generated three-dimensional model.

[0579] "Means for creating, manufacturing, and selling custom accessories in a physical store" refers to equipment or a system for creating, manufacturing, and selling custom accessories in a physical store.

[0580] "Means for producing with a 3D printer" refers to the technology and equipment for producing a product using a 3D printer based on the generated 3D model.

[0581] "Means for producing with woodworking equipment or leatherworking equipment" means equipment or techniques for producing products based on three-dimensional models using wood or leather.

[0582] The present invention relates to a system that generates three-dimensional models of custom accessories based on requests input by users, and then produces and sells them in a physical store. The purpose of this system is to provide original accessories that meet the needs of users.

[0583] A specific embodiment of the system is given below.

[0584] First, the user accesses the application using a smartphone. This application has a text input form and an illustration data upload function as a means of accepting user input. When the user enters text information and uploads illustration data of the desired shape, the requested content is notified to the system.

[0585] Next, the device sends the text and illustration information received from the user to the server. The server analyzes this information using natural language processing technology (e.g., OpenAI GPT-3) and image analysis technology (e.g., OpenCV). The text information is analyzed to extract specific data such as dimensions and shape, and the illustration information is used to extract shape data through image recognition.

[0586] Based on the analyzed data, the server uses 3D modeling AI (e.g., Blender's Python API) to generate a 3D model of the custom accessory. The generated 3D model is sent from the server to the device as preview information and displayed to the user. The user can check this preview and input correction requests as needed. For example, they can input specific requests such as "I want it to be a little thicker."

[0587] When the user inputs a modification request, the server again modifies and regenerates the model using the 3D modeling AI. This modified model is also displayed to the user as a preview again, and the user is asked for final confirmation. Once the user has made the final confirmation and approved, the server sends production instructions to the 3D printer or processing equipment in the physical store.

[0588] The 3D printer receives the production instructions and begins producing the custom accessory based on the model data sent. Once production is complete, the server notifies the user, who then picks up the finished product at a physical store. This allows users to obtain an original accessory that perfectly matches their design.

[0589] As a concrete example, consider the case where a user wants to create a pendant. The user enters text information such as "I want a pendant with a diameter of 50 mm and a height of 100 mm," and uploads an illustration of the desired design. The server analyzes this information and generates a 3D model of the pendant using 3D modeling AI. This model is previewed to the user, who then inputs a correction request, such as "I'd like it to be a little thicker." The server then corrects the model again and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced in a physical store and the user is notified.

[0590] An example of a prompt sentence to input to the generative AI model is as follows:

[0591] Extract dimensions from the text: 'I would like a pendant that is 50mm in diameter and 100mm in height'

[0592]

[0593] Generate a 3D model with dimensions 50mm diameter and 100mm height and based on the recognized shape from the uploaded illustration.

[0594] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0595] Step 1:

[0596] The user accesses the smartphone app and inputs text information and illustration data.

[0597] Input: Text information (e.g., "I want a pendant with a diameter of 50 mm and a height of 100 mm"), illustration data

[0598] Data processing / data calculation: The user uses the application's input form to enter details of the accessory they are requesting in text and upload illustration data.

[0599] Output: The entered text information and illustration data are saved on the device and sent to the server.

[0600] Step 2:

[0601] The terminal transmits the received text information and illustration information to the server.

[0602] Input: Text information and illustration data entered by the user

[0603] Data processing / data calculation: The terminal sends this information to the server via the API.

[0604] Output: Text information and illustration data are received by the server.

[0605] Step 3:

[0606] The server analyzes the text information using natural language processing techniques to extract specific data such as dimensions.

[0607] Input: Text information received by the server

[0608] Data processing / data calculation: The server analyzes the text information using natural language processing technology (e.g., OpenAI GPT-3) and extracts data related to dimensions and shape.

[0609] Output: Extracted dimensional and geometric data

[0610] Step 4:

[0611] The server analyzes the illustration information using image analysis technology and extracts shape data.

[0612] Input: Illustration data received by the server

[0613] Data processing / data calculation: The server uses image analysis technology (e.g., OpenCV) to analyze the illustration information and extract shape data.

[0614] Output: Extracted shape data

[0615] Step 5:

[0616] The server performs three-dimensional modeling based on the extracted dimension data and shape data.

[0617] Input: Extracted dimensional and geometric data

[0618] Data processing / data calculation: The server generates a 3D model using 3D modeling AI (e.g., Blender's Python API).

[0619] Output: Data of the generated 3D model

[0620] Step 6:

[0621] The server transmits the generated three-dimensional model to the terminal as a preview and displays it to the user.

[0622] Input: Data of the generated 3D model

[0623] Data processing / data calculation: The server generates preview data for the 3D model and sends it to the terminal.

[0624] Output: Preview image displayed on the device

[0625] Step 7:

[0626] The user checks the preview and inputs correction requests as necessary.

[0627] Input: Preview image, correction request (e.g. "I'd like it to be a little thicker")

[0628] Data processing / data calculation: The user checks the preview and, if any corrections are necessary, sends a correction request to the server through the application.

[0629] Output: Modified request data

[0630] Step 8:

[0631] The server regenerates the three-dimensional model based on the modification request.

[0632] Input: Correction request data, original 3D model data

[0633] Data processing / data calculation: The server again uses 3D modeling AI (e.g., Blender's Python API) to modify and regenerate the model.

[0634] Output: Corrected 3D model data

[0635] Step 9:

[0636] The server transmits the modified three-dimensional model to the terminal as a re-preview and asks the user for final confirmation.

[0637] Input: Data of the corrected 3D model

[0638] Data processing / data calculation: The server generates data for re-preview and sends it to the terminal.

[0639] Output: Preview image displayed on the device

[0640] Step 10:

[0641] Once the user has made a final confirmation and approved it, the server sends production instructions to the 3D printer or processing equipment at the physical store.

[0642] Input: Final confirmation and approval, corrected 3D model data

[0643] Data processing / data calculation: The server generates production instruction data and sends it to the 3D printer in the physical store.

[0644] Output: Production instruction data sent to the 3D printer and processing equipment in the physical store

[0645] Step 11:

[0646] In the physical store, a 3D printer creates custom accessories based on production instructions.

[0647] Input: Manufacturing instruction data, corrected 3D model data

[0648] Data processing / data calculation: The 3D printer produces custom accessories according to the production instructions.

[0649] Output: Finished custom accessories

[0650] Step 12:

[0651] Once production is complete, the server notifies the user and arranges for them to pick up the accessory at a designated physical store.

[0652] Input: Completed custom accessory information

[0653] Data processing / data calculation: The server generates a production completion notification and sends it to the user. It also arranges for the item to be picked up at the designated physical store.

[0654] Output: Notification to users and physical stores

[0655] 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.

[0656] The present invention relates to a system that generates a three-dimensional model of an accessory based on requests input by the user and then produces it using a three-dimensional printer or other processing device.The purpose of the present invention is to provide a higher user experience by combining it with an "emotion engine" that recognizes the user's emotions and reflects that information.

[0657] This system works as follows: First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[0658] The device sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0659] Furthermore, the system includes an emotion engine for recognizing the user's emotions. This emotion engine analyzes emotions from facial expressions, voice, and text when the user inputs information. For example, it recognizes whether the user's facial expression is happy or confused while inputting information. It also analyzes emotional expressions contained in the text.

[0660] Based on the analyzed text, illustration, and emotion information, the server uses 3D modeling AI to generate a 3D model of the accessory. Emotional information is reflected in the generation and modification of the 3D model. For example, if the user has a confused expression, the server can provide more detailed guidance on the model or ask a simple question.

[0661] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input any necessary correction requests. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[0662] When the modification request arrives at the server, the server again uses the 3D modeling AI to modify and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the modification request and providing appropriate support and guidance. This modified model is again sent to the device as a preview, prompting the user for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[0663] The 3D printer or processing device that receives the production instructions will then create the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is created that meets the user's specific requests and emotional information.

[0664] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[0665] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and also uploads an illustration of the accessory's desired appearance. The emotion engine analyzes the user's emotions as they input, and if it detects, for example, a "confused expression," the server provides additional support. The server analyzes the information and uses 3D modeling AI to generate a 3D model of the lens case. This model is then previewed for the user, who can then input any final revision requests. Once the model is finally approved, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[0666] The system of the present invention allows users to get accessories that are tailored to their needs and emotions, thus greatly improving the product usage experience.

[0667] The processing flow will be explained below.

[0668] Step 1:

[0669] Users input detailed information about the accessories they want. Specifically, they input information such as dimensions, shape, and material as text data, and upload illustration data if necessary. The emotion engine also analyzes the user's facial expressions and voice while they are entering information.

[0670] Step 2:

[0671] The terminal transmits the text information, illustration information, and emotion information received from the user to the server.

[0672] Step 3:

[0673] The server uses natural language processing technology to analyze the text information and extract specific data such as dimensions, shape, and material. It also uses image analysis technology to analyze the illustration information and understand its content.

[0674] Step 4:

[0675] The server uses an emotion engine to analyze the user's emotions from their facial expressions and voice. The emotion data is reflected in the generation and modification of models.

[0676] Step 5:

[0677] The server uses 3D modeling AI to generate a 3D model of the accessory based on the analyzed text information, illustration information, and emotion information.

[0678] Step 6:

[0679] The server transmits preview information of the generated three-dimensional model to the terminal.

[0680] Step 7:

[0681] The device displays preview information to the user and asks for their confirmation. The emotion engine analyzes the user's reaction in real time and provides appropriate guidance and support.

[0682] Step 8:

[0683] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[0684] Step 9:

[0685] The terminal transmits the user's correction request information to the server again.

[0686] Step 10:

[0687] The server then uses the 3D modeling AI to modify and regenerate the 3D model based on the received modification request and emotion information. During this process, the emotion engine analyzes the user's emotions and provides appropriate support.

[0688] Step 11:

[0689] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[0690] Step 12:

[0691] The terminal displays the preview information to the user again and asks the user for final confirmation.

[0692] Step 13:

[0693] The user then makes a final check and, if satisfied, approves the production. At this point, the emotion engine analyzes the user's emotions and provides final feedback.

[0694] Step 14:

[0695] The server sends the final approved 3D model data to a 3D printer or other processing device and issues production instructions.

[0696] Step 15:

[0697] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[0698] Step 16:

[0699] The server notifies the user that production is complete and arranges for the finished product to be delivered to the specified address.

[0700] Step 17:

[0701] The user receives the finished product and uses it to check that it meets their requirements.

[0702] Example 2

[0703] 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."

[0704] The purpose of this invention is to efficiently produce custom-made accessories based on user input. However, conventional systems have difficulty in properly analyzing and incorporating vague user requests and feelings. Furthermore, the process of repeatedly incorporating revision requests into the design of the final product desired by the user must also be made more efficient. There is a need for a system that can address these challenges.

[0705] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0706] In this invention, the server includes: means for inputting a user's request; means for analyzing text information and image information received from the user; means for analyzing the text information and image information using natural language processing technology and image analysis technology; means including an emotion recognition engine for recognizing and analyzing the user's emotions; means including a generative AI model for generating a 3D model of the accessory based on the analysis result and the emotion information; means for sending instructions for producing the actual product based on the generated 3D model; means for sending preview information of the generated 3D model to the user and prompting confirmation; and means for accepting correction requests from the user. This enables the rapid production of sophisticated, custom-made accessories that reflect the user's detailed requests and emotion information.

[0707] The "means for inputting user requests" is an interface that allows the user to input information about the accessories they want in text or image format.

[0708] The "means for analyzing text information and image information" refers to a processing device that analyzes the content of input text or images and extracts specific instructions or data from that information.

[0709] "Natural language processing technology" is a technology that analyzes text data, understands human language, and processes it as meaningful information.

[0710] "Image analysis technology" is a technology that analyzes image data and recognizes objects and features within it.

[0711] An "emotion recognition engine" is a device that analyzes and detects emotions from input such as a user's facial expressions, voice, and text.

[0712] A "generative AI model" is a system that has an artificial intelligence algorithm for automatically generating three-dimensional models based on analysis results and emotional information.

[0713] The "means for transmitting instructions for producing an actual product" is a communication device for sending production instructions to a processing machine or other production device based on the generated three-dimensional model.

[0714] The "means for sending preview information of the generated three-dimensional model to the user and prompting confirmation" is a device for sending a visual preview of the generated three-dimensional model to the user's terminal and prompting confirmation or correction requests.

[0715] The "means for accepting a modification request from a user" refers to an interface that allows a user to input a modification request for a three-dimensional model, and a device that transmits that information to the server.

[0716] The present invention relates to a system for efficiently generating and manufacturing custom accessories based on a user's specific needs. The system analyzes information entered by the user, generates a 3D model, and then automatically performs a series of steps to manufacture the accessory based on that model.

[0717] First, the user inputs information about the accessory they want using a dedicated application on their device or a web interface. Specifically, they can input text and image information. This text information can include detailed instructions about the accessory's dimensions, material, and shape. For image information, they can upload illustrations or photos showing the desired shape of the accessory.

[0718] Next, the terminal receives the text and image information entered by the user and transmits it to the server using a secure communication method using the HTTPS protocol.

[0719] The server is equipped with various technologies for analyzing the received text and image information. To analyze the text information, it uses natural language processing technology (such as SpaCy or BERT) to extract specific dimensional and shape data. To analyze the image information, it uses image processing technology (such as OpenCV or TensorFlow) to recognize shape and design information.

[0720] Furthermore, the server uses an emotion recognition engine to analyze the user's emotions from facial expressions, voice, and text while the user is entering information. It uses facial recognition and voice analysis technologies to understand the user's emotional state (e.g., confusion, joy, etc.). This emotional information plays an important role in subsequent processing.

[0721] Based on the analyzed information and emotion data, the server uses a generative AI model to generate a 3D model of the accessory, for example, by utilizing Blender or Autodesk Fusion 360 APIs to generate a specific 3D model, which is then optimized by taking emotion information into account.

[0722] The generated 3D model is sent from the server to the device in a preview format. The user can check this preview and, if necessary, input a correction request from the device. The server receives the user's correction request and uses the 3D modeling AI to correct and regenerate the model. This process is repeated until the user is satisfied.

[0723] Once the user finally reviews and approves the 3D model, the server sends production instructions to a 3D printer or other production device, which then produces the actual accessory. For example, a 3D printer begins producing the camera lens case specified by the user. Once production is complete, the server notifies the user and arranges for the finished product to be promptly delivered to the specified address.

[0724] Specific examples

[0725] For example, if a user inputs text information such as "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," along with an illustration of the case's shape, the server analyzes that information and generates a 3D model of the lens case using 3D modeling AI. If the user then checks the preview and inputs a request for revision, such as "I'd like the case to be a little thicker," the server will reflect that request and regenerate the model. This process is repeated several times, and once the final model is approved, a 3D printer will produce the case and deliver it to the customer.

[0726] Prompt Sentence Examples

[0727] "I'd like a camera lens case. Please model a case that fits a lens with a diameter of 70mm and a height of 150mm. I'll also upload an illustration."

[0728] Through this system, users can quickly obtain custom-made accessories that perfectly match their needs and emotions.

[0729] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0730] Step 1:

[0731] The user inputs information about the accessory they want into the device using a dedicated application or a web interface. The input information includes text specifications (e.g., "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm.") and illustrations in the form of images. This information is then imported into the device as input data.

[0732] Step 2:

[0733] The terminal sends the text and image information entered by the user to the server using the HTTPS protocol. For transmission, the text data and image data are packaged in JSON format and a secure communication channel is used. The input is JSON-formatted data, and the output is a successful transmission notification to the server.

[0734] Step 3:

[0735] The server analyzes the received text information using natural language processing technology (for example, SpaCy or BERT). Through analysis, specific dimension, material, and shape data is extracted from the input text information. The input is text data in JSON format, and the output is analyzed dimension and material data.

[0736] Step 4:

[0737] The server analyzes the received image information using image analysis technology (e.g., OpenCV or TensorFlow). Through the analysis, information about the shape and design is extracted from the image. The input is image data in JSON format, and the output is analyzed shape data and design data.

[0738] Step 5:

[0739] The server's emotion recognition engine analyzes facial expressions and voice data in real time while the user is entering information. It uses facial recognition and voice analysis technologies to analyze the user's emotional state (e.g., confusion, joy, etc.). The input is facial expression data and voice data, and the output is analyzed emotional information.

[0740] Step 6:

[0741] The server generates a 3D model using a generative AI model (e.g., Blender or Autodesk Fusion 360 API) based on the analysis results of natural language processing and image analysis technologies, as well as emotional information. The inputs are dimensional data, shape data, and emotional information, and the output is the generated 3D model data.

[0742] Step 7:

[0743] The server sends the generated 3D model in a preview format to the terminal. The user checks the preview on the terminal and inputs correction requests as necessary. The input is the generated 3D model data, and the output is the user's confirmation and correction request information.

[0744] Step 8:

[0745] The terminal receives the user's modification request and sends it back to the server. The server modifies and regenerates the model using 3D modeling AI based on the modification request information. The input is the modification request information, and the output is the modified 3D model data.

[0746] Step 9:

[0747] Once the user has finally reviewed and approved the 3D model, the server sends production instructions to a 3D printer or other processing device. The input is the final approved 3D model data, and the output is the production instructions.

[0748] Step 10:

[0749] The 3D printer or other processing device receives the production instructions and produces the specified accessory. When production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The input is the production instructions and status data of the 3D printer (or processing device), and the output is a production completion notification and delivery instructions.

[0750] (Application example 2)

[0751] 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."

[0752] Conventional customized product generation systems do not take user emotions into account, making it difficult to effectively provide original products that satisfy users. Furthermore, there is a lack of means to provide a better user experience by reflecting user emotions and needs in real time. Therefore, there is a growing need for a more personalized customized product generation system that includes user emotion analysis.

[0753] 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.

[0754] In this invention, the server includes means for accepting user input, means for analyzing text information and illustration information received from the user, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing the actual product based on the generated 3D model, means for prompting the user to confirm the generated 3D model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the 3D model, thereby enabling the generation and production of a 3D model based on the user's emotions and specific needs.

[0755] The "means for accepting user input" is an interface that allows the user to input their wishes and requirements in text or image format.

[0756] The "means for analyzing text information and illustration information received from the user" is a system for analyzing the content of the text and illustrations provided by the user and extracting the necessary data.

[0757] The "means for generating a three-dimensional model of the accessory based on the analysis results" is a system that creates a detailed three-dimensional model of the accessory based on the analyzed information.

[0758] The "means for transmitting instructions for producing an actual product based on the generated three-dimensional model" is a system that transmits data on the generated three-dimensional model to a device that actually produces the product.

[0759] The "means for prompting the user to check the generated three-dimensional model" is an interface that presents the generated three-dimensional model to the user and requests feedback.

[0760] The "means for accepting a modification request from a user" is a system in which a user inputs a request for modification of a generated three-dimensional model.

[0761] "Means for analyzing emotions" refers to technology for analyzing a user's emotions from their facial expressions, voice, and text.

[0762] "Means for reflecting the results of emotion analysis in the generation of 3D models" refers to a system that adjusts the design and guide of 3D models based on the analyzed emotion information.

[0763] A "three-dimensional manufacturing device" is a device that physically produces accessories based on three-dimensional model data.

[0764] A "wood processing machine" is a machine that processes wood into a specified shape.

[0765] A "leather processing device" is a device that processes leather material into a specified shape.

[0766] This invention relates to a system that accepts user input and generates original accessories based on that information. It also analyzes the user's emotions and reflects the results in the generation of a 3D model, providing a more personalized experience.

[0767] This system includes means for accepting user input, means for analyzing text information and illustration information, means for generating a three-dimensional model of the accessory based on the analysis results, means for sending instructions for producing the actual item based on the generated three-dimensional model, means for prompting the user to confirm the generated three-dimensional model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the three-dimensional model.

[0768] To explain the embodiment in detail, the operation is as follows:

[0769] 1. The user provides input

[0770] Users enter detailed information about the accessories they want using text and illustrations. For example, if they are ordering a camera lens case, they would enter the lens size, shape, and material requirements in text, and upload the desired shape as illustration data.

[0771] 2. Analysis of text and illustration information

[0772] The server analyzes the text and illustration information received from the user. The text information is interpreted using natural language processing technology to extract specific data on dimensions and shape. The illustration information is also analyzed using image analysis technology. The natural language processing technology used includes Huggingface transformers, and the image analysis technology used is OpenCV.

[0773] 3. 3D Model Generation

[0774] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. In this step, OpenAI's API is used to generate the 3D model. For example, a model of a camera lens case with the required shape and dimensions is generated based on the information entered by the user and the analysis results.

[0775] 4. User sentiment analysis and feedback

[0776] The system analyzes the user's facial expressions and voice while they are typing to collect emotional information. An emotion recognition model using Keras and TensorFlow is used for the emotion analysis. The results are reflected in the model generation process, providing detailed guidance if the user is confused, and incorporating positive emotions into the model design.

[0777] 5. Preview and correction requests

[0778] The server sends a preview of the generated 3D model to the user's device and displays it to them. The user can then review the preview and input correction requests as needed. For example, they could request to increase the thickness of the case or slightly change its shape.

[0779] 6. Final confirmation and production instructions

[0780] Based on the revision request, the server again uses the 3D modeling AI to revise and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the revision request and providing appropriate support and guidance. The revised model is previewed again, and once the user gives their final confirmation and approval, the server sends production instructions to the 3D manufacturing equipment.

[0781] 7. Production and Delivery

[0782] The 3D manufacturing equipment then produces the accessory based on the model data. For example, a 3D printer starts producing a camera lens case. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[0783] As a specific use case, consider a case where a user inputs "I want a camera lens case with a diameter of 70 mm and a height of 150 mm" and uploads their own image. If the emotion engine detects a "confused expression," the server provides additional support. The server then analyzes the information and generates a 3D model of the lens case using 3D modeling AI. This model is previewed to the user, who can then input any final revision requests. After final confirmation, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[0784] An example prompt is:

[0785] "I want a camera lens case that is 70mm in diameter and 150mm in height. User sentiment is confused."

[0786] This makes it possible to provide high-quality original accessories that meet the needs and feelings of users.

[0787] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0788] Step 1:

[0789] The user provides input

[0790] The user inputs detailed information about the accessory they want into the terminal. The input includes text information (e.g., "I want a camera lens case with a diameter of 70 mm and a height of 150 mm") and illustration information. The input data is sent to the server.

[0791] Input: Text information, illustration information

[0792] Output: User request data sent to the server

[0793] Step 2:

[0794] Analysis of text and illustration information

[0795] The server analyzes the received text using natural language processing technology (e.g., Huggingface's transformers), extracting specific dimensions and shape data from the text. At the same time, the illustration information is analyzed using image analysis technology (e.g., OpenCV) to obtain shape and design information.

[0796] Input: User's text information, illustration information

[0797] Output: Extracted dimension data and shape data

[0798] Step 3:

[0799] 3D model generation

[0800] The server uses a 3D modeling AI (e.g., OpenAI's API) to generate a 3D model of the accessory based on the analyzed data. The AI ​​model uses prompts to guide the generation process.

[0801] Input: Extracted dimension data, shape data, prompt statement (e.g., "I would like a camera lens case with a diameter of 70 mm and a height of 150 mm.")

[0802] Output: Generated 3D model

[0803] Step 4:

[0804] Emotion analysis

[0805] While the user is inputting, the user's facial expression and voice data are collected and emotion analysis is performed on the server. Keras and TensorFlow are used for emotion analysis to identify the type of emotion (e.g., "confusion") from the user's facial image and voice. Emotional information is also reflected in the generation of the 3D model.

[0806] Input: User's face image, voice data

[0807] Output: Parsed emotion information

[0808] Step 5:

[0809] Model modification based on user sentiment

[0810] Based on the analyzed emotion information, the server provides feedback to the 3D model generation process: if the emotion is "confused," additional support or detailed guidance is provided.

[0811] Input: Analyzed emotion information, generated 3D model

[0812] Output: Corrected 3D model, supporting information

[0813] Step 6:

[0814] Preview and correction requests accepted

[0815] The server sends a preview of the generated 3D model to the terminal and displays it to the user. The user checks the preview and re-enters any parts they want to modify. The modification request is then sent back to the server.

[0816] Input: Generated 3D model, user modification request

[0817] Output: User feedback, correction requests

[0818] Step 7:

[0819] Final confirmation and production instructions

[0820] Based on the modification request, the server again modifies and regenerates the model using the 3D modeling AI. Once final confirmation is received from the user, the server issues a manufacturing instruction to the 3D manufacturing equipment.

[0821] Input: User's final confirmation, modified 3D model

[0822] Output: Production instructions for 3D manufacturing equipment

[0823] Step 8:

[0824] Production and Delivery

[0825] The 3D manufacturing equipment creates the actual product based on the model data sent from the server. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[0826] Input: Modified 3D model, fabrication instructions

[0827] Output: Finished product, notification to user and delivery arrangements

[0828] 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.

[0829] 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.

[0830] 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.

[0831] [Third embodiment]

[0832] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0833] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0834] 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).

[0835] 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.

[0836] 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.

[0837] 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).

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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."

[0844] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then produces it using a three-dimensional printer or other processing device. The purpose of this system is to meet the needs of the user and provide original accessories based on those requests.

[0845] The system operates in the following manner. First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[0846] The device then sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0847] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, based on the size and shape of a camera lens case, it designs a model of a case that fits the lens perfectly.

[0848] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input correction requests as needed. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[0849] When the modification request arrives at the server, the server again modifies and regenerates the model using 3D modeling AI. This modified model is also sent to the device as a preview, and the user is asked for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[0850] The 3D printer or processing device that receives the production instruction will then produce the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is produced that meets the user's specific needs.

[0851] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[0852] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and uploads an illustration of the accessory's desired appearance. The server analyzes this information and uses 3D modeling AI to generate a 3D model of the lens case. This model is previewed to the user, who then inputs a request for revisions, such as "I would like the case to be a little thicker." The server then revises the model and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced and delivered.

[0853] The system of the present invention allows users to obtain accessories that are tailored to their needs, greatly improving the product usage experience.

[0854] The processing flow will be explained below.

[0855] Step 1:

[0856] Users input detailed information about the accessories they want, including dimensions, shape, material, and other information as text data, and upload illustration data if necessary.

[0857] Step 2:

[0858] The terminal transmits the text information and illustration information input by the user to the server.

[0859] Step 3:

[0860] The server analyzes the received text information using natural language processing technology, extracting specific data such as dimensions, shape, and material from the text.

[0861] Step 4:

[0862] The server uses image analysis technology to analyze the received illustration information, understand the shape and design elements from the illustration, and generate data.

[0863] Step 5:

[0864] The server generates a three-dimensional model of the accessory using three-dimensional modeling AI based on the analyzed text information and illustration information.

[0865] Step 6:

[0866] The server transmits preview information of the generated three-dimensional model to the terminal.

[0867] Step 7:

[0868] The terminal displays the preview information to the user and asks for confirmation.

[0869] Step 8:

[0870] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[0871] Step 9:

[0872] The terminal transmits the user's correction request information to the server again.

[0873] Step 10:

[0874] The server modifies and regenerates the 3D model again using the 3D modeling AI based on the received modification request.

[0875] Step 11:

[0876] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[0877] Step 12:

[0878] The terminal displays the preview information to the user again and asks the user for final confirmation.

[0879] Step 13:

[0880] The user performs a final check and, if satisfied, approves the production.

[0881] Step 14:

[0882] The server sends the data of the final approved three-dimensional model to a three-dimensional printer or other processing device and issues production instructions.

[0883] Step 15:

[0884] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[0885] Step 16:

[0886] The server notifies the user that production is complete and arranges for delivery of the finished product.

[0887] Step 17:

[0888] The user receives the finished product and uses it to check that it meets their requirements.

[0889] Example 1

[0890] 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."

[0891] With conventional accessory manufacturing systems, it was difficult to easily produce custom-made accessories that met specific user requirements. In particular, to quickly and accurately provide products that met the user's desired specifications and designs, advanced design technology and effort were required, which led to challenges such as increased production costs.

[0892] 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.

[0893] In this invention, the server includes means for accepting user input, means for analyzing text data and image data received from the user, means for analyzing the text data using natural language processing technology, means for analyzing the image data using image analysis technology, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing an actual object based on the generated 3D model, means for displaying a preview of the generated 3D model to the user to prompt confirmation, means for accepting a correction request from the user, and means for regenerating the 3D model based on the correction request, thereby enabling users to easily create custom-made accessories.

[0894] The "means for accepting user input" is a mechanism for the user to input their wishes and requests regarding accessories as text data and image data.

[0895] "Means for analyzing text data and image data" refers to technology for analyzing text data and image data entered by a user and extracting information necessary for design.

[0896] "Means for analyzing text data using natural language processing technology" refers to technology for mechanically understanding text data and extracting specific design information such as dimensions and materials.

[0897] "Means for analyzing image data using image analysis technology" refers to technology for analyzing image data (e.g., illustrations) provided by users, understanding their contents, and reflecting them in the design.

[0898] The "means for generating a three-dimensional model of an accessory" is a mechanism for designing a three-dimensional shape of an accessory based on the analyzed text data and image data.

[0899] The "means for sending instructions for producing an entity" is a mechanism for sending production instructions to a production device based on the generated three-dimensional model.

[0900] The "means for displaying a preview of the generated three-dimensional model and prompting confirmation" is a mechanism for visually displaying a preview of the generated three-dimensional model to the user and prompting confirmation and correction requests.

[0901] The "means for accepting correction requests from users" is a mechanism that allows users to request corrections to be made to parts that need to be corrected after checking the preview.

[0902] The "means for regenerating a three-dimensional model based on a modification request" is a mechanism for regenerating a three-dimensional model by reflecting a modification request from a user.

[0903] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then manufactures it using a processing device. The system aims to meet the needs of the user and provide original accessories based on the user's requests.

[0904] This system operates using the following hardware and software: a server, terminals, a 3D printer, and various processing equipment. The analysis and modeling technologies used are natural language processing, image analysis, and 3D modeling AI.

[0905] First, the user uses the device to input detailed requests for the accessories they want. This request includes both text and illustrations. For example, if a user wants a case that fits a lens with a diameter of 70 mm and a height of 150 mm, they can input the size, material, and shape in text format and upload an illustration of the desired shape.

[0906] The device sends the text and illustration information entered by the user to the server. The server receives this information and first analyzes the text information using natural language processing technology. This extracts specific data such as the required dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[0907] Based on the analysis results, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, it generates a 3D model of a case that fits a lens with a diameter of 70 mm and a height of 150 mm. This generated model is sent from the server to the device as a preview and displayed to the user.

[0908] The user can check the preview displayed on their device and input correction requests as needed. For example, they can input a specific request for correction, such as "I want the case to be 2mm thicker." The server receives the request and uses the 3D modeling AI to correct and regenerate the model.

[0909] Once the edits are complete, the model is again displayed as a preview to the user. Once the user has given their final approval, the server sends production instructions to a 3D printer or other processing device. The 3D printer then produces a physical accessory based on the model data. For example, it might produce a lens case using the specified material and dimensions.

[0910] Once production is complete, the server notifies the user and arranges for delivery of the finished product. The user receives the finished product at the address they specify and uses it. This system allows users to easily obtain original accessories that perfectly suit their needs.

[0911] As a concrete example, consider a case where a user wants to create a "camera lens case." The user enters the following prompt:

[0912] "I'd like you to design a case that will fit a lens with a diameter of 70mm and a height of 150mm."

[0913] By uploading an illustration of the desired shape, the server analyzes the information and uses 3D modeling AI to generate a 3D model of the accessory. This process is repeated until the final product is produced and delivered to the user.

[0914] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0915] Step 1: User enters request

[0916] The user uses a terminal to enter detailed requests for accessories into a special form. The input includes text information (e.g., "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm") and image information (an illustration of the desired shape). When the user presses the "Submit" button, the request is sent.

[0917] Input: Text and image information entered by the user on the device.

[0918] Output: Input text and image data

[0919] Step 2: The device sends the input information to the server

[0920] The terminal transmits the text and image information input by the user to the server, which converts the data into packets and transmits them to the server via the network.

[0921] Input: Text and image data entered into the device

[0922] Output: Text and image data sent to the server

[0923] Step 3: The server receives the information and parses the text information

[0924] The server receives the text information sent from the device and analyzes it using natural language processing technology. Through this analysis, design data such as specific dimensions and shape is extracted. For example, information such as "diameter 70 mm, height 150 mm" is extracted.

[0925] Input: Text information sent

[0926] Output: Extracted design data such as dimensions and shapes

[0927] Step 4: The server analyzes the image information

[0928] The server receives the image information sent from the device and analyzes it using image analysis technology. For example, it analyzes an illustration uploaded by a user and extracts its shape and design features.

[0929] Input: Image information sent

[0930] Output: Extracted shapes and design features

[0931] Step 5: The server generates the 3D model

[0932] The server uses 3D modeling AI to generate a 3D model based on the analyzed text and image data. The model has the 3D shape of the accessory designed based on the analysis results.

[0933] Input: Parsed text data and image data

[0934] Output: Data of the generated 3D model

[0935] Step 6: Send the generated model to the device

[0936] The server transmits preview information of the generated 3D model to the terminal and displays it to the user. The terminal receives the data and displays the model on the preview screen.

[0937] Input: Data of the generated 3D model

[0938] Output: Preview information of the 3D model displayed on the device

[0939] Step 7: User sees preview

[0940] The user checks the preview of the 3D model displayed on the terminal, checks whether it matches their requirements, and prepares to re-enter any necessary corrections.

[0941] Input: Previewed 3D model

[0942] Output: User's modification request

[0943] Step 8: User Enters Modification Request

[0944] The user inputs the required corrections and sends them to the server, for example, "I want the case thickness to be increased by 2 mm," and presses the submit button.

[0945] Input: User inputs correction request

[0946] Output: Correction request submitted

[0947] Step 9: The server regenerates the 3D model based on the modification request.

[0948] The server receives the modification request sent by the user and again modifies and regenerates the model using the 3D modeling AI.

[0949] Input: The correction request submitted

[0950] Output: Regenerated 3D model data

[0951] Step 10: The server sends the regenerated model to the device

[0952] The server transmits preview information of the regenerated 3D model to the terminal and displays it to the user. The terminal receives the data and redisplays the model on the preview screen.

[0953] Input: Data of the regenerated 3D model

[0954] Output: Preview information of the regenerated 3D model displayed on the device

[0955] Step 11: User performs final confirmation

[0956] The user checks the preview again and makes a final check, and if satisfied, presses the approve button to confirm the model as the final version.

[0957] Input: Redisplayed preview information

[0958] Output: Final user review and approval

[0959] Step 12: The server issues a production command

[0960] The server sends the final 3D model approved by the user as a production instruction to a 3D printer or other processing device.

[0961] Input: User-approved final model

[0962] Output: Production instructions for 3D printers and processing equipment

[0963] Step 13: The 3D printer creates

[0964] A 3D printer or processing device creates a physical accessory based on the transmitted model data, such as a lens case made of the specified material and dimensions.

[0965] Input: 3D model production instructions

[0966] Output: Complete physical attachment

[0967] Step 14: Server arranges delivery

[0968] Once production is complete, the server notifies the user and arranges for delivery of the finished product, which the user can then pick up at the address they specify.

[0969] Input: Notification of production completion

[0970] Output: The finished product delivered to the user

[0971] This allows users to get original accessories that suit their needs.

[0972] (Application example 1)

[0973] 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."

[0974] Today's consumers are increasingly seeking custom-made products that meet their individual needs. However, mass-produced products are sold in general stores, making it difficult for consumers to obtain custom accessories that meet their specific requirements. Furthermore, the process for consumers to create custom products based on their own designs is complicated, and they cannot fully utilize the service unless they are familiar with the tools and technology used. Furthermore, when ordering custom-made products online, consumers cannot see the actual product, which can reduce consumer satisfaction. There is a need for a system that solves these problems and meets consumers' individual needs quickly and easily.

[0975] 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.

[0976] In this invention, the server includes means for accepting user input, means for analyzing the text and illustration information received from the user, and means for generating a three-dimensional model of the accessory based on the analysis results. This enables a system for creating, manufacturing, and selling custom accessories in a physical store. By incorporating this system, consumers can quickly create custom products based on their own designs and requests, and then check and purchase the actual product in a physical store.

[0977] The "means for accepting user input" is an interface that allows the user to input text information and illustration information.

[0978] "Means for analyzing text information and illustration information received from users" refers to the processes and techniques for analyzing text information entered by users and illustrations uploaded by users and extracting the necessary data.

[0979] "Means for generating a three-dimensional model of an accessory based on the analysis results" refers to techniques and tools for designing and creating a three-dimensional model of an accessory based on the analyzed text information and illustration information.

[0980] "Means for sending instructions for producing an actual product based on the generated three-dimensional model" refers to a process or system that sends instructions for producing an actual product based on the generated three-dimensional model to a processing device or manufacturing equipment.

[0981] The "means for prompting the user to check the generated three-dimensional model" refers to a function or interface for displaying a preview of the generated three-dimensional model to the user and requesting confirmation of the model.

[0982] The "means for accepting a modification request from a user" is an interface that allows a user to input a request for modification or change to the generated three-dimensional model.

[0983] "Means for creating, manufacturing, and selling custom accessories in a physical store" refers to equipment or a system for creating, manufacturing, and selling custom accessories in a physical store.

[0984] "Means for producing with a 3D printer" refers to the technology and equipment for producing a product using a 3D printer based on the generated 3D model.

[0985] "Means for producing with woodworking equipment or leatherworking equipment" means equipment or techniques for producing products based on three-dimensional models using wood or leather.

[0986] The present invention relates to a system that generates three-dimensional models of custom accessories based on requests input by users, and then produces and sells them in a physical store. The purpose of this system is to provide original accessories that meet the needs of users.

[0987] A specific embodiment of the system is given below.

[0988] First, the user accesses the application using a smartphone. This application has a text input form and an illustration data upload function as a means of accepting user input. When the user enters text information and uploads illustration data of the desired shape, the requested content is notified to the system.

[0989] Next, the device sends the text and illustration information received from the user to the server. The server analyzes this information using natural language processing technology (e.g., OpenAI GPT-3) and image analysis technology (e.g., OpenCV). The text information is analyzed to extract specific data such as dimensions and shape, and the illustration information is used to extract shape data through image recognition.

[0990] Based on the analyzed data, the server uses 3D modeling AI (e.g., Blender's Python API) to generate a 3D model of the custom accessory. The generated 3D model is sent from the server to the device as preview information and displayed to the user. The user can check this preview and input correction requests as needed. For example, they can input specific requests such as "I want it to be a little thicker."

[0991] When the user inputs a modification request, the server again modifies and regenerates the model using the 3D modeling AI. This modified model is also displayed to the user as a preview again, and the user is asked for final confirmation. Once the user has made the final confirmation and approved, the server sends production instructions to the 3D printer or processing equipment in the physical store.

[0992] The 3D printer receives the production instructions and begins producing the custom accessory based on the model data sent. Once production is complete, the server notifies the user, who then picks up the finished product at a physical store. This allows users to obtain an original accessory that perfectly matches their design.

[0993] As a concrete example, consider the case where a user wants to create a pendant. The user enters text information such as "I want a pendant with a diameter of 50 mm and a height of 100 mm," and uploads an illustration of the desired design. The server analyzes this information and generates a 3D model of the pendant using 3D modeling AI. This model is previewed to the user, who then inputs a correction request, such as "I'd like it to be a little thicker." The server then corrects the model again and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced in a physical store and the user is notified.

[0994] An example of a prompt sentence to input to the generative AI model is as follows:

[0995] Extract dimensions from the text: 'I would like a pendant that is 50mm in diameter and 100mm in height'

[0996]

[0997] Generate a 3D model with dimensions 50mm diameter and 100mm height and based on the recognized shape from the uploaded illustration.

[0998] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0999] Step 1:

[1000] The user accesses the smartphone app and inputs text information and illustration data.

[1001] Input: Text information (e.g., "I want a pendant with a diameter of 50 mm and a height of 100 mm"), illustration data

[1002] Data processing / data calculation: The user uses the application's input form to enter details of the accessory they are requesting in text and upload illustration data.

[1003] Output: The entered text information and illustration data are saved on the device and sent to the server.

[1004] Step 2:

[1005] The terminal transmits the received text information and illustration information to the server.

[1006] Input: Text information and illustration data entered by the user

[1007] Data processing / data calculation: The terminal sends this information to the server via the API.

[1008] Output: Text information and illustration data are received by the server.

[1009] Step 3:

[1010] The server analyzes the text information using natural language processing techniques to extract specific data such as dimensions.

[1011] Input: Text information received by the server

[1012] Data processing / data calculation: The server analyzes the text information using natural language processing technology (e.g., OpenAI GPT-3) and extracts data related to dimensions and shape.

[1013] Output: Extracted dimensional and geometric data

[1014] Step 4:

[1015] The server analyzes the illustration information using image analysis technology and extracts shape data.

[1016] Input: Illustration data received by the server

[1017] Data processing / data calculation: The server uses image analysis technology (e.g., OpenCV) to analyze the illustration information and extract shape data.

[1018] Output: Extracted shape data

[1019] Step 5:

[1020] The server performs three-dimensional modeling based on the extracted dimension data and shape data.

[1021] Input: Extracted dimensional and geometric data

[1022] Data processing / data calculation: The server generates a 3D model using 3D modeling AI (e.g., Blender's Python API).

[1023] Output: Data of the generated 3D model

[1024] Step 6:

[1025] The server transmits the generated three-dimensional model to the terminal as a preview and displays it to the user.

[1026] Input: Data of the generated 3D model

[1027] Data processing / data calculation: The server generates preview data for the 3D model and sends it to the terminal.

[1028] Output: Preview image displayed on the device

[1029] Step 7:

[1030] The user checks the preview and inputs correction requests as necessary.

[1031] Input: Preview image, correction request (e.g. "I'd like it to be a little thicker")

[1032] Data processing / data calculation: The user checks the preview and, if any corrections are necessary, sends a correction request to the server through the application.

[1033] Output: Modified request data

[1034] Step 8:

[1035] The server regenerates the three-dimensional model based on the modification request.

[1036] Input: Correction request data, original 3D model data

[1037] Data processing / data calculation: The server again uses 3D modeling AI (e.g., Blender's Python API) to modify and regenerate the model.

[1038] Output: Corrected 3D model data

[1039] Step 9:

[1040] The server transmits the modified three-dimensional model to the terminal as a re-preview and asks the user for final confirmation.

[1041] Input: Data of the corrected 3D model

[1042] Data processing / data calculation: The server generates data for re-preview and sends it to the terminal.

[1043] Output: Preview image displayed on the device

[1044] Step 10:

[1045] Once the user has made a final confirmation and approved it, the server sends production instructions to the 3D printer or processing equipment at the physical store.

[1046] Input: Final confirmation and approval, corrected 3D model data

[1047] Data processing / data calculation: The server generates production instruction data and sends it to the 3D printer in the physical store.

[1048] Output: Production instruction data sent to the 3D printer and processing equipment in the physical store

[1049] Step 11:

[1050] In the physical store, a 3D printer creates custom accessories based on production instructions.

[1051] Input: Manufacturing instruction data, corrected 3D model data

[1052] Data processing / data calculation: The 3D printer produces custom accessories according to the production instructions.

[1053] Output: Finished custom accessories

[1054] Step 12:

[1055] Once production is complete, the server notifies the user and arranges for them to pick up the accessory at a designated physical store.

[1056] Input: Completed custom accessory information

[1057] Data processing / data calculation: The server generates a production completion notification and sends it to the user. It also arranges for the item to be picked up at the designated physical store.

[1058] Output: Notification to users and physical stores

[1059] 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.

[1060] The present invention relates to a system that generates a three-dimensional model of an accessory based on requests input by the user and then produces it using a three-dimensional printer or other processing device.The purpose of the present invention is to provide a higher user experience by combining it with an "emotion engine" that recognizes the user's emotions and reflects that information.

[1061] This system works as follows: First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[1062] The device sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[1063] Furthermore, the system includes an emotion engine for recognizing the user's emotions. This emotion engine analyzes emotions from facial expressions, voice, and text when the user inputs information. For example, it recognizes whether the user's facial expression is happy or confused while inputting information. It also analyzes emotional expressions contained in the text.

[1064] Based on the analyzed text, illustration, and emotion information, the server uses 3D modeling AI to generate a 3D model of the accessory. Emotional information is reflected in the generation and modification of the 3D model. For example, if the user has a confused expression, the server can provide more detailed guidance on the model or ask a simple question.

[1065] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input any necessary correction requests. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[1066] When the modification request arrives at the server, the server again uses the 3D modeling AI to modify and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the modification request and providing appropriate support and guidance. This modified model is again sent to the device as a preview, prompting the user for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[1067] The 3D printer or processing device that receives the production instructions will then create the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is created that meets the user's specific requests and emotional information.

[1068] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[1069] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and also uploads an illustration of the accessory's desired appearance. The emotion engine analyzes the user's emotions as they input, and if it detects, for example, a "confused expression," the server provides additional support. The server analyzes the information and uses 3D modeling AI to generate a 3D model of the lens case. This model is then previewed for the user, who can then input any final revision requests. Once the model is finally approved, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[1070] The system of the present invention allows users to get accessories that are tailored to their needs and emotions, thus greatly improving the product usage experience.

[1071] The processing flow will be explained below.

[1072] Step 1:

[1073] Users input detailed information about the accessories they want. Specifically, they input information such as dimensions, shape, and material as text data, and upload illustration data if necessary. The emotion engine also analyzes the user's facial expressions and voice while they are entering information.

[1074] Step 2:

[1075] The terminal transmits the text information, illustration information, and emotion information received from the user to the server.

[1076] Step 3:

[1077] The server uses natural language processing technology to analyze the text information and extract specific data such as dimensions, shape, and material. It also uses image analysis technology to analyze the illustration information and understand its content.

[1078] Step 4:

[1079] The server uses an emotion engine to analyze the user's emotions from their facial expressions and voice. The emotion data is reflected in the generation and modification of models.

[1080] Step 5:

[1081] The server uses 3D modeling AI to generate a 3D model of the accessory based on the analyzed text information, illustration information, and emotion information.

[1082] Step 6:

[1083] The server transmits preview information of the generated three-dimensional model to the terminal.

[1084] Step 7:

[1085] The device displays preview information to the user and asks for their confirmation. The emotion engine analyzes the user's reaction in real time and provides appropriate guidance and support.

[1086] Step 8:

[1087] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[1088] Step 9:

[1089] The terminal transmits the user's correction request information to the server again.

[1090] Step 10:

[1091] The server then uses the 3D modeling AI to modify and regenerate the 3D model based on the received modification request and emotion information. During this process, the emotion engine analyzes the user's emotions and provides appropriate support.

[1092] Step 11:

[1093] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[1094] Step 12:

[1095] The terminal displays the preview information to the user again and asks the user for final confirmation.

[1096] Step 13:

[1097] The user then makes a final check and, if satisfied, approves the production. At this point, the emotion engine analyzes the user's emotions and provides final feedback.

[1098] Step 14:

[1099] The server sends the final approved 3D model data to a 3D printer or other processing device and issues production instructions.

[1100] Step 15:

[1101] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[1102] Step 16:

[1103] The server notifies the user that production is complete and arranges for the finished product to be delivered to the specified address.

[1104] Step 17:

[1105] The user receives the finished product and uses it to check that it meets their requirements.

[1106] Example 2

[1107] 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."

[1108] The purpose of this invention is to efficiently produce custom-made accessories based on user input. However, conventional systems have difficulty in properly analyzing and incorporating vague user requests and feelings. Furthermore, the process of repeatedly incorporating revision requests into the design of the final product desired by the user must also be made more efficient. There is a need for a system that can address these challenges.

[1109] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1110] In this invention, the server includes: means for inputting a user's request; means for analyzing text information and image information received from the user; means for analyzing the text information and image information using natural language processing technology and image analysis technology; means including an emotion recognition engine for recognizing and analyzing the user's emotions; means including a generative AI model for generating a 3D model of the accessory based on the analysis result and the emotion information; means for sending instructions for producing the actual product based on the generated 3D model; means for sending preview information of the generated 3D model to the user and prompting confirmation; and means for accepting correction requests from the user. This enables the rapid production of sophisticated, custom-made accessories that reflect the user's detailed requests and emotion information.

[1111] The "means for inputting user requests" is an interface that allows the user to input information about the accessories they want in text or image format.

[1112] The "means for analyzing text information and image information" refers to a processing device that analyzes the content of input text or images and extracts specific instructions or data from that information.

[1113] "Natural language processing technology" is a technology that analyzes text data, understands human language, and processes it as meaningful information.

[1114] "Image analysis technology" is a technology that analyzes image data and recognizes objects and features within it.

[1115] An "emotion recognition engine" is a device that analyzes and detects emotions from input such as a user's facial expressions, voice, and text.

[1116] A "generative AI model" is a system that has an artificial intelligence algorithm for automatically generating three-dimensional models based on analysis results and emotional information.

[1117] The "means for transmitting instructions for producing an actual product" is a communication device for sending production instructions to a processing machine or other production device based on the generated three-dimensional model.

[1118] The "means for sending preview information of the generated three-dimensional model to the user and prompting confirmation" is a device for sending a visual preview of the generated three-dimensional model to the user's terminal and prompting confirmation or correction requests.

[1119] The "means for accepting a modification request from a user" refers to an interface that allows a user to input a modification request for a three-dimensional model, and a device that transmits that information to the server.

[1120] The present invention relates to a system for efficiently generating and manufacturing custom accessories based on a user's specific needs. The system analyzes information entered by the user, generates a 3D model, and then automatically performs a series of steps to manufacture the accessory based on that model.

[1121] First, the user inputs information about the accessory they want using a dedicated application on their device or a web interface. Specifically, they can input text and image information. This text information can include detailed instructions about the accessory's dimensions, material, and shape. For image information, they can upload illustrations or photos showing the desired shape of the accessory.

[1122] Next, the terminal receives the text and image information entered by the user and transmits it to the server using a secure communication method using the HTTPS protocol.

[1123] The server is equipped with various technologies for analyzing the received text and image information. To analyze the text information, it uses natural language processing technology (such as SpaCy or BERT) to extract specific dimensional and shape data. To analyze the image information, it uses image processing technology (such as OpenCV or TensorFlow) to recognize shape and design information.

[1124] Furthermore, the server uses an emotion recognition engine to analyze the user's emotions from facial expressions, voice, and text while the user is entering information. It uses facial recognition and voice analysis technologies to understand the user's emotional state (e.g., confusion, joy, etc.). This emotional information plays an important role in subsequent processing.

[1125] Based on the analyzed information and emotion data, the server uses a generative AI model to generate a 3D model of the accessory, for example, by utilizing Blender or Autodesk Fusion 360 APIs to generate a specific 3D model, which is then optimized by taking emotion information into account.

[1126] The generated 3D model is sent from the server to the device in a preview format. The user can check this preview and, if necessary, input a correction request from the device. The server receives the user's correction request and uses the 3D modeling AI to correct and regenerate the model. This process is repeated until the user is satisfied.

[1127] Once the user finally reviews and approves the 3D model, the server sends production instructions to a 3D printer or other production device, which then produces the actual accessory. For example, a 3D printer begins producing the camera lens case specified by the user. Once production is complete, the server notifies the user and arranges for the finished product to be promptly delivered to the specified address.

[1128] Specific examples

[1129] For example, if a user inputs text information such as "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," along with an illustration of the case's shape, the server analyzes that information and generates a 3D model of the lens case using 3D modeling AI. If the user then checks the preview and inputs a request for revision, such as "I'd like the case to be a little thicker," the server will reflect that request and regenerate the model. This process is repeated several times, and once the final model is approved, a 3D printer will produce the case and deliver it to the customer.

[1130] Prompt Sentence Examples

[1131] "I'd like a camera lens case. Please model a case that fits a lens with a diameter of 70mm and a height of 150mm. I'll also upload an illustration."

[1132] Through this system, users can quickly obtain custom-made accessories that perfectly match their needs and emotions.

[1133] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1134] Step 1:

[1135] The user inputs information about the accessory they want into the device using a dedicated application or a web interface. The input information includes text specifications (e.g., "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm.") and illustrations in the form of images. This information is then imported into the device as input data.

[1136] Step 2:

[1137] The terminal sends the text and image information entered by the user to the server using the HTTPS protocol. For transmission, the text data and image data are packaged in JSON format and a secure communication channel is used. The input is JSON-formatted data, and the output is a successful transmission notification to the server.

[1138] Step 3:

[1139] The server analyzes the received text information using natural language processing technology (for example, SpaCy or BERT). Through analysis, specific dimension, material, and shape data is extracted from the input text information. The input is text data in JSON format, and the output is analyzed dimension and material data.

[1140] Step 4:

[1141] The server analyzes the received image information using image analysis technology (e.g., OpenCV or TensorFlow). Through the analysis, information about the shape and design is extracted from the image. The input is image data in JSON format, and the output is analyzed shape data and design data.

[1142] Step 5:

[1143] The server's emotion recognition engine analyzes facial expressions and voice data in real time while the user is entering information. It uses facial recognition and voice analysis technologies to analyze the user's emotional state (e.g., confusion, joy, etc.). The input is facial expression data and voice data, and the output is analyzed emotional information.

[1144] Step 6:

[1145] The server generates a 3D model using a generative AI model (e.g., Blender or Autodesk Fusion 360 API) based on the analysis results of natural language processing and image analysis technologies, as well as emotional information. The inputs are dimensional data, shape data, and emotional information, and the output is the generated 3D model data.

[1146] Step 7:

[1147] The server sends the generated 3D model in a preview format to the terminal. The user checks the preview on the terminal and inputs correction requests as necessary. The input is the generated 3D model data, and the output is the user's confirmation and correction request information.

[1148] Step 8:

[1149] The terminal receives the user's modification request and sends it back to the server. The server modifies and regenerates the model using 3D modeling AI based on the modification request information. The input is the modification request information, and the output is the modified 3D model data.

[1150] Step 9:

[1151] Once the user has finally reviewed and approved the 3D model, the server sends production instructions to a 3D printer or other processing device. The input is the final approved 3D model data, and the output is the production instructions.

[1152] Step 10:

[1153] The 3D printer or other processing device receives the production instructions and produces the specified accessory. When production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The input is the production instructions and status data of the 3D printer (or processing device), and the output is a production completion notification and delivery instructions.

[1154] (Application example 2)

[1155] 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."

[1156] Conventional customized product generation systems do not take user emotions into account, making it difficult to effectively provide original products that satisfy users. Furthermore, there is a lack of means to provide a better user experience by reflecting user emotions and needs in real time. Therefore, there is a growing need for a more personalized customized product generation system that includes user emotion analysis.

[1157] 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.

[1158] In this invention, the server includes means for accepting user input, means for analyzing text information and illustration information received from the user, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing the actual product based on the generated 3D model, means for prompting the user to confirm the generated 3D model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the 3D model, thereby enabling the generation and production of a 3D model based on the user's emotions and specific needs.

[1159] The "means for accepting user input" is an interface that allows the user to input their wishes and requirements in text or image format.

[1160] The "means for analyzing text information and illustration information received from the user" is a system for analyzing the content of the text and illustrations provided by the user and extracting the necessary data.

[1161] The "means for generating a three-dimensional model of the accessory based on the analysis results" is a system that creates a detailed three-dimensional model of the accessory based on the analyzed information.

[1162] The "means for transmitting instructions for producing an actual product based on the generated three-dimensional model" is a system that transmits data on the generated three-dimensional model to a device that actually produces the product.

[1163] The "means for prompting the user to check the generated three-dimensional model" is an interface that presents the generated three-dimensional model to the user and requests feedback.

[1164] The "means for accepting a modification request from a user" is a system in which a user inputs a request for modification of a generated three-dimensional model.

[1165] "Means for analyzing emotions" refers to technology for analyzing a user's emotions from their facial expressions, voice, and text.

[1166] "Means for reflecting the results of emotion analysis in the generation of 3D models" refers to a system that adjusts the design and guide of 3D models based on the analyzed emotion information.

[1167] A "three-dimensional manufacturing device" is a device that physically produces accessories based on three-dimensional model data.

[1168] A "wood processing machine" is a machine that processes wood into a specified shape.

[1169] A "leather processing device" is a device that processes leather material into a specified shape.

[1170] This invention relates to a system that accepts user input and generates original accessories based on that information. It also analyzes the user's emotions and reflects the results in the generation of a 3D model, providing a more personalized experience.

[1171] This system includes means for accepting user input, means for analyzing text information and illustration information, means for generating a three-dimensional model of the accessory based on the analysis results, means for sending instructions for producing the actual item based on the generated three-dimensional model, means for prompting the user to confirm the generated three-dimensional model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the three-dimensional model.

[1172] To explain the embodiment in detail, the operation is as follows:

[1173] 1. The user provides input

[1174] Users enter detailed information about the accessories they want using text and illustrations. For example, if they are ordering a camera lens case, they would enter the lens size, shape, and material requirements in text, and upload the desired shape as illustration data.

[1175] 2. Analysis of text and illustration information

[1176] The server analyzes the text and illustration information received from the user. The text information is interpreted using natural language processing technology to extract specific data on dimensions and shape. The illustration information is also analyzed using image analysis technology. The natural language processing technology used includes Huggingface transformers, and the image analysis technology used is OpenCV.

[1177] 3. 3D Model Generation

[1178] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. In this step, OpenAI's API is used to generate the 3D model. For example, a model of a camera lens case with the required shape and dimensions is generated based on the information entered by the user and the analysis results.

[1179] 4. User sentiment analysis and feedback

[1180] The system analyzes the user's facial expressions and voice while they are typing to collect emotional information. An emotion recognition model using Keras and TensorFlow is used for the emotion analysis. The results are reflected in the model generation process, providing detailed guidance if the user is confused, and incorporating positive emotions into the model design.

[1181] 5. Preview and correction requests

[1182] The server sends a preview of the generated 3D model to the user's device and displays it to them. The user can then review the preview and input correction requests as needed. For example, they could request to increase the thickness of the case or slightly change its shape.

[1183] 6. Final confirmation and production instructions

[1184] Based on the revision request, the server again uses the 3D modeling AI to revise and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the revision request and providing appropriate support and guidance. The revised model is previewed again, and once the user gives their final confirmation and approval, the server sends production instructions to the 3D manufacturing equipment.

[1185] 7. Production and Delivery

[1186] The 3D manufacturing equipment then produces the accessory based on the model data. For example, a 3D printer starts producing a camera lens case. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[1187] As a specific use case, consider a case where a user inputs "I want a camera lens case with a diameter of 70 mm and a height of 150 mm" and uploads their own image. If the emotion engine detects a "confused expression," the server provides additional support. The server then analyzes the information and generates a 3D model of the lens case using 3D modeling AI. This model is previewed to the user, who can then input any final revision requests. After final confirmation, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[1188] An example prompt is:

[1189] "I want a camera lens case that is 70mm in diameter and 150mm in height. User sentiment is confused."

[1190] This makes it possible to provide high-quality original accessories that meet the needs and feelings of users.

[1191] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1192] Step 1:

[1193] The user provides input

[1194] The user inputs detailed information about the accessory they want into the terminal. The input includes text information (e.g., "I want a camera lens case with a diameter of 70 mm and a height of 150 mm") and illustration information. The input data is sent to the server.

[1195] Input: Text information, illustration information

[1196] Output: User request data sent to the server

[1197] Step 2:

[1198] Analysis of text and illustration information

[1199] The server analyzes the received text using natural language processing technology (e.g., Huggingface's transformers), extracting specific dimensions and shape data from the text. At the same time, the illustration information is analyzed using image analysis technology (e.g., OpenCV) to obtain shape and design information.

[1200] Input: User's text information, illustration information

[1201] Output: Extracted dimension data and shape data

[1202] Step 3:

[1203] 3D model generation

[1204] The server uses a 3D modeling AI (e.g., OpenAI's API) to generate a 3D model of the accessory based on the analyzed data. The AI ​​model uses prompts to guide the generation process.

[1205] Input: Extracted dimension data, shape data, prompt statement (e.g., "I would like a camera lens case with a diameter of 70 mm and a height of 150 mm.")

[1206] Output: Generated 3D model

[1207] Step 4:

[1208] Emotion analysis

[1209] While the user is inputting, the user's facial expression and voice data are collected and emotion analysis is performed on the server. Keras and TensorFlow are used for emotion analysis to identify the type of emotion (e.g., "confusion") from the user's facial image and voice. Emotional information is also reflected in the generation of the 3D model.

[1210] Input: User's face image, voice data

[1211] Output: Parsed emotion information

[1212] Step 5:

[1213] Model modification based on user sentiment

[1214] Based on the analyzed emotion information, the server provides feedback to the 3D model generation process: if the emotion is "confused," additional support or detailed guidance is provided.

[1215] Input: Analyzed emotion information, generated 3D model

[1216] Output: Corrected 3D model, supporting information

[1217] Step 6:

[1218] Preview and correction requests accepted

[1219] The server sends a preview of the generated 3D model to the terminal and displays it to the user. The user checks the preview and re-enters any parts they want to modify. The modification request is then sent back to the server.

[1220] Input: Generated 3D model, user modification request

[1221] Output: User feedback, correction requests

[1222] Step 7:

[1223] Final confirmation and production instructions

[1224] Based on the modification request, the server again modifies and regenerates the model using the 3D modeling AI. Once final confirmation is received from the user, the server issues a manufacturing instruction to the 3D manufacturing equipment.

[1225] Input: User's final confirmation, modified 3D model

[1226] Output: Production instructions for 3D manufacturing equipment

[1227] Step 8:

[1228] Production and Delivery

[1229] The 3D manufacturing equipment creates the actual product based on the model data sent from the server. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[1230] Input: Modified 3D model, fabrication instructions

[1231] Output: Finished product, notification to user and delivery arrangements

[1232] 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.

[1233] 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.

[1234] 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.

[1235] [Fourth embodiment]

[1236] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1237] 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.

[1238] 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).

[1239] 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.

[1240] 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.

[1241] 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).

[1242] 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.

[1243] 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.

[1244] 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.

[1245] 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.

[1246] 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.

[1247] 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.

[1248] 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."

[1249] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then produces it using a three-dimensional printer or other processing device. The purpose of this system is to meet the needs of the user and provide original accessories based on those requests.

[1250] The system operates in the following manner. First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[1251] The device then sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[1252] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, based on the size and shape of a camera lens case, it designs a model of a case that fits the lens perfectly.

[1253] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input correction requests as needed. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[1254] When the modification request arrives at the server, the server again modifies and regenerates the model using 3D modeling AI. This modified model is also sent to the device as a preview, and the user is asked for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[1255] The 3D printer or processing device that receives the production instruction will then produce the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is produced that meets the user's specific needs.

[1256] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[1257] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and uploads an illustration of the accessory's desired appearance. The server analyzes this information and uses 3D modeling AI to generate a 3D model of the lens case. This model is previewed to the user, who then inputs a request for revisions, such as "I would like the case to be a little thicker." The server then revises the model and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced and delivered.

[1258] The system of the present invention allows users to obtain accessories that are tailored to their needs, greatly improving the product usage experience.

[1259] The processing flow will be explained below.

[1260] Step 1:

[1261] Users input detailed information about the accessories they want, including dimensions, shape, material, and other information as text data, and upload illustration data if necessary.

[1262] Step 2:

[1263] The terminal transmits the text information and illustration information input by the user to the server.

[1264] Step 3:

[1265] The server analyzes the received text information using natural language processing technology, extracting specific data such as dimensions, shape, and material from the text.

[1266] Step 4:

[1267] The server uses image analysis technology to analyze the received illustration information, understand the shape and design elements from the illustration, and generate data.

[1268] Step 5:

[1269] The server generates a three-dimensional model of the accessory using three-dimensional modeling AI based on the analyzed text information and illustration information.

[1270] Step 6:

[1271] The server transmits preview information of the generated three-dimensional model to the terminal.

[1272] Step 7:

[1273] The terminal displays the preview information to the user and asks for confirmation.

[1274] Step 8:

[1275] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[1276] Step 9:

[1277] The terminal transmits the user's correction request information to the server again.

[1278] Step 10:

[1279] The server modifies and regenerates the 3D model again using the 3D modeling AI based on the received modification request.

[1280] Step 11:

[1281] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[1282] Step 12:

[1283] The terminal displays the preview information to the user again and asks the user for final confirmation.

[1284] Step 13:

[1285] The user performs a final check and, if satisfied, approves the production.

[1286] Step 14:

[1287] The server sends the data of the final approved three-dimensional model to a three-dimensional printer or other processing device and issues production instructions.

[1288] Step 15:

[1289] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[1290] Step 16:

[1291] The server notifies the user that production is complete and arranges for delivery of the finished product.

[1292] Step 17:

[1293] The user receives the finished product and uses it to check that it meets their requirements.

[1294] Example 1

[1295] 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."

[1296] With conventional accessory manufacturing systems, it was difficult to easily produce custom-made accessories that met specific user requirements. In particular, to quickly and accurately provide products that met the user's desired specifications and designs, advanced design technology and effort were required, which led to challenges such as increased production costs.

[1297] 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.

[1298] In this invention, the server includes means for accepting user input, means for analyzing text data and image data received from the user, means for analyzing the text data using natural language processing technology, means for analyzing the image data using image analysis technology, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing an actual object based on the generated 3D model, means for displaying a preview of the generated 3D model to the user to prompt confirmation, means for accepting a correction request from the user, and means for regenerating the 3D model based on the correction request, thereby enabling users to easily create custom-made accessories.

[1299] The "means for accepting user input" is a mechanism for the user to input their wishes and requests regarding accessories as text data and image data.

[1300] "Means for analyzing text data and image data" refers to technology for analyzing text data and image data entered by a user and extracting information necessary for design.

[1301] "Means for analyzing text data using natural language processing technology" refers to technology for mechanically understanding text data and extracting specific design information such as dimensions and materials.

[1302] "Means for analyzing image data using image analysis technology" refers to technology for analyzing image data (e.g., illustrations) provided by users, understanding their contents, and reflecting them in the design.

[1303] The "means for generating a three-dimensional model of an accessory" is a mechanism for designing a three-dimensional shape of an accessory based on the analyzed text data and image data.

[1304] The "means for sending instructions for producing an entity" is a mechanism for sending production instructions to a production device based on the generated three-dimensional model.

[1305] The "means for displaying a preview of the generated three-dimensional model and prompting confirmation" is a mechanism for visually displaying a preview of the generated three-dimensional model to the user and prompting confirmation and correction requests.

[1306] The "means for accepting correction requests from users" is a mechanism that allows users to request corrections to be made to parts that need to be corrected after checking the preview.

[1307] The "means for regenerating a three-dimensional model based on a modification request" is a mechanism for regenerating a three-dimensional model by reflecting a modification request from a user.

[1308] The present invention relates to a system that generates a three-dimensional model of an accessory based on a request input by a user and then manufactures it using a processing device. The system aims to meet the needs of the user and provide original accessories based on the user's requests.

[1309] This system operates using the following hardware and software: a server, terminals, a 3D printer, and various processing equipment. The analysis and modeling technologies used are natural language processing, image analysis, and 3D modeling AI.

[1310] First, the user uses the device to input detailed requests for the accessories they want. This request includes both text and illustrations. For example, if a user wants a case that fits a lens with a diameter of 70 mm and a height of 150 mm, they can input the size, material, and shape in text format and upload an illustration of the desired shape.

[1311] The device sends the text and illustration information entered by the user to the server. The server receives this information and first analyzes the text information using natural language processing technology. This extracts specific data such as the required dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[1312] Based on the analysis results, the server uses 3D modeling AI to generate a 3D model of the accessory. For example, it generates a 3D model of a case that fits a lens with a diameter of 70 mm and a height of 150 mm. This generated model is sent from the server to the device as a preview and displayed to the user.

[1313] The user can check the preview displayed on their device and input correction requests as needed. For example, they can input a specific request for correction, such as "I want the case to be 2mm thicker." The server receives the request and uses the 3D modeling AI to correct and regenerate the model.

[1314] Once the edits are complete, the model is again displayed as a preview to the user. Once the user has given their final approval, the server sends production instructions to a 3D printer or other processing device. The 3D printer then produces a physical accessory based on the model data. For example, it might produce a lens case using the specified material and dimensions.

[1315] Once production is complete, the server notifies the user and arranges for delivery of the finished product. The user receives the finished product at the address they specify and uses it. This system allows users to easily obtain original accessories that perfectly suit their needs.

[1316] As a concrete example, consider a case where a user wants to create a "camera lens case." The user enters the following prompt:

[1317] "I'd like you to design a case that will fit a lens with a diameter of 70mm and a height of 150mm."

[1318] By uploading an illustration of the desired shape, the server analyzes the information and uses 3D modeling AI to generate a 3D model of the accessory. This process is repeated until the final product is produced and delivered to the user.

[1319] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1320] Step 1: User enters request

[1321] The user uses a terminal to enter detailed requests for accessories into a special form. The input includes text information (e.g., "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm") and image information (an illustration of the desired shape). When the user presses the "Submit" button, the request is sent.

[1322] Input: Text and image information entered by the user on the device.

[1323] Output: Input text and image data

[1324] Step 2: The device sends the input information to the server

[1325] The terminal transmits the text and image information input by the user to the server, which converts the data into packets and transmits them to the server via the network.

[1326] Input: Text and image data entered into the device

[1327] Output: Text and image data sent to the server

[1328] Step 3: The server receives the information and parses the text information

[1329] The server receives the text information sent from the device and analyzes it using natural language processing technology. Through this analysis, design data such as specific dimensions and shape is extracted. For example, information such as "diameter 70 mm, height 150 mm" is extracted.

[1330] Input: Text information sent

[1331] Output: Extracted design data such as dimensions and shapes

[1332] Step 4: The server analyzes the image information

[1333] The server receives the image information sent from the device and analyzes it using image analysis technology. For example, it analyzes an illustration uploaded by a user and extracts its shape and design features.

[1334] Input: Image information sent

[1335] Output: Extracted shapes and design features

[1336] Step 5: The server generates the 3D model

[1337] The server uses 3D modeling AI to generate a 3D model based on the analyzed text and image data. The model has the 3D shape of the accessory designed based on the analysis results.

[1338] Input: Parsed text data and image data

[1339] Output: Data of the generated 3D model

[1340] Step 6: Send the generated model to the device

[1341] The server transmits preview information of the generated 3D model to the terminal and displays it to the user. The terminal receives the data and displays the model on the preview screen.

[1342] Input: Data of the generated 3D model

[1343] Output: Preview information of the 3D model displayed on the device

[1344] Step 7: User sees preview

[1345] The user checks the preview of the 3D model displayed on the terminal, checks whether it matches their requirements, and prepares to re-enter any necessary corrections.

[1346] Input: Previewed 3D model

[1347] Output: User's modification request

[1348] Step 8: User Enters Modification Request

[1349] The user inputs the required corrections and sends them to the server, for example, "I want the case thickness to be increased by 2 mm," and presses the submit button.

[1350] Input: User inputs correction request

[1351] Output: Correction request submitted

[1352] Step 9: The server regenerates the 3D model based on the modification request.

[1353] The server receives the modification request sent by the user and again modifies and regenerates the model using the 3D modeling AI.

[1354] Input: The correction request submitted

[1355] Output: Regenerated 3D model data

[1356] Step 10: The server sends the regenerated model to the device

[1357] The server transmits preview information of the regenerated 3D model to the terminal and displays it to the user. The terminal receives the data and redisplays the model on the preview screen.

[1358] Input: Data of the regenerated 3D model

[1359] Output: Preview information of the regenerated 3D model displayed on the device

[1360] Step 11: User performs final confirmation

[1361] The user checks the preview again and makes a final check, and if satisfied, presses the approve button to confirm the model as the final version.

[1362] Input: Redisplayed preview information

[1363] Output: Final user review and approval

[1364] Step 12: The server issues a production command

[1365] The server sends the final 3D model approved by the user as a production instruction to a 3D printer or other processing device.

[1366] Input: User-approved final model

[1367] Output: Production instructions for 3D printers and processing equipment

[1368] Step 13: The 3D printer creates

[1369] A 3D printer or processing device creates a physical accessory based on the transmitted model data, such as a lens case made of the specified material and dimensions.

[1370] Input: 3D model production instructions

[1371] Output: Complete physical attachment

[1372] Step 14: Server arranges delivery

[1373] Once production is complete, the server notifies the user and arranges for delivery of the finished product, which the user can then pick up at the address they specify.

[1374] Input: Notification of production completion

[1375] Output: The finished product delivered to the user

[1376] This allows users to get original accessories that suit their needs.

[1377] (Application example 1)

[1378] 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."

[1379] Today's consumers are increasingly seeking custom-made products that meet their individual needs. However, mass-produced products are sold in general stores, making it difficult for consumers to obtain custom accessories that meet their specific requirements. Furthermore, the process for consumers to create custom products based on their own designs is complicated, and they cannot fully utilize the service unless they are familiar with the tools and technology used. Furthermore, when ordering custom-made products online, consumers cannot see the actual product, which can reduce consumer satisfaction. There is a need for a system that solves these problems and meets consumers' individual needs quickly and easily.

[1380] 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.

[1381] In this invention, the server includes means for accepting user input, means for analyzing the text and illustration information received from the user, and means for generating a three-dimensional model of the accessory based on the analysis results. This enables a system for creating, manufacturing, and selling custom accessories in a physical store. By incorporating this system, consumers can quickly create custom products based on their own designs and requests, and then check and purchase the actual product in a physical store.

[1382] The "means for accepting user input" is an interface that allows the user to input text information and illustration information.

[1383] "Means for analyzing text information and illustration information received from users" refers to the processes and techniques for analyzing text information entered by users and illustrations uploaded by users and extracting the necessary data.

[1384] "Means for generating a three-dimensional model of an accessory based on the analysis results" refers to techniques and tools for designing and creating a three-dimensional model of an accessory based on the analyzed text information and illustration information.

[1385] "Means for sending instructions for producing an actual product based on the generated three-dimensional model" refers to a process or system that sends instructions for producing an actual product based on the generated three-dimensional model to a processing device or manufacturing equipment.

[1386] The "means for prompting the user to check the generated three-dimensional model" refers to a function or interface for displaying a preview of the generated three-dimensional model to the user and requesting confirmation of the model.

[1387] The "means for accepting a modification request from a user" is an interface that allows a user to input a request for modification or change to the generated three-dimensional model.

[1388] "Means for creating, manufacturing, and selling custom accessories in a physical store" refers to equipment or a system for creating, manufacturing, and selling custom accessories in a physical store.

[1389] "Means for producing with a 3D printer" refers to the technology and equipment for producing a product using a 3D printer based on the generated 3D model.

[1390] "Means for producing with woodworking equipment or leatherworking equipment" means equipment or techniques for producing products based on three-dimensional models using wood or leather.

[1391] The present invention relates to a system that generates three-dimensional models of custom accessories based on requests input by users, and then produces and sells them in a physical store. The purpose of this system is to provide original accessories that meet the needs of users.

[1392] A specific embodiment of the system is given below.

[1393] First, the user accesses the application using a smartphone. This application has a text input form and an illustration data upload function as a means of accepting user input. When the user enters text information and uploads illustration data of the desired shape, the requested content is notified to the system.

[1394] Next, the device sends the text and illustration information received from the user to the server. The server analyzes this information using natural language processing technology (e.g., OpenAI GPT-3) and image analysis technology (e.g., OpenCV). The text information is analyzed to extract specific data such as dimensions and shape, and the illustration information is used to extract shape data through image recognition.

[1395] Based on the analyzed data, the server uses 3D modeling AI (e.g., Blender's Python API) to generate a 3D model of the custom accessory. The generated 3D model is sent from the server to the device as preview information and displayed to the user. The user can check this preview and input correction requests as needed. For example, they can input specific requests such as "I want it to be a little thicker."

[1396] When the user inputs a modification request, the server again modifies and regenerates the model using the 3D modeling AI. This modified model is also displayed to the user as a preview again, and the user is asked for final confirmation. Once the user has made the final confirmation and approved, the server sends production instructions to the 3D printer or processing equipment in the physical store.

[1397] The 3D printer receives the production instructions and begins producing the custom accessory based on the model data sent. Once production is complete, the server notifies the user, who then picks up the finished product at a physical store. This allows users to obtain an original accessory that perfectly matches their design.

[1398] As a concrete example, consider the case where a user wants to create a pendant. The user enters text information such as "I want a pendant with a diameter of 50 mm and a height of 100 mm," and uploads an illustration of the desired design. The server analyzes this information and generates a 3D model of the pendant using 3D modeling AI. This model is previewed to the user, who then inputs a correction request, such as "I'd like it to be a little thicker." The server then corrects the model again and resends it for final confirmation, repeating this process until the user is satisfied. After final confirmation, production instructions are sent to the 3D printer, and the finished product is produced in a physical store and the user is notified.

[1399] An example of a prompt sentence to input to the generative AI model is as follows:

[1400] Extract dimensions from the text: 'I would like a pendant that is 50mm in diameter and 100mm in height'

[1401]

[1402] Generate a 3D model with dimensions 50mm diameter and 100mm height and based on the recognized shape from the uploaded illustration.

[1403] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1404] Step 1:

[1405] The user accesses the smartphone app and inputs text information and illustration data.

[1406] Input: Text information (e.g., "I want a pendant with a diameter of 50 mm and a height of 100 mm"), illustration data

[1407] Data processing / data calculation: The user uses the application's input form to enter details of the accessory they are requesting in text and upload illustration data.

[1408] Output: The entered text information and illustration data are saved on the device and sent to the server.

[1409] Step 2:

[1410] The terminal transmits the received text information and illustration information to the server.

[1411] Input: Text information and illustration data entered by the user

[1412] Data processing / data calculation: The terminal sends this information to the server via the API.

[1413] Output: Text information and illustration data are received by the server.

[1414] Step 3:

[1415] The server analyzes the text information using natural language processing techniques to extract specific data such as dimensions.

[1416] Input: Text information received by the server

[1417] Data processing / data calculation: The server analyzes the text information using natural language processing technology (e.g., OpenAI GPT-3) and extracts data related to dimensions and shape.

[1418] Output: Extracted dimensional and geometric data

[1419] Step 4:

[1420] The server analyzes the illustration information using image analysis technology and extracts shape data.

[1421] Input: Illustration data received by the server

[1422] Data processing / data calculation: The server uses image analysis technology (e.g., OpenCV) to analyze the illustration information and extract shape data.

[1423] Output: Extracted shape data

[1424] Step 5:

[1425] The server performs three-dimensional modeling based on the extracted dimension data and shape data.

[1426] Input: Extracted dimensional and geometric data

[1427] Data processing / data calculation: The server generates a 3D model using 3D modeling AI (e.g., Blender's Python API).

[1428] Output: Data of the generated 3D model

[1429] Step 6:

[1430] The server transmits the generated three-dimensional model to the terminal as a preview and displays it to the user.

[1431] Input: Data of the generated 3D model

[1432] Data processing / data calculation: The server generates preview data for the 3D model and sends it to the terminal.

[1433] Output: Preview image displayed on the device

[1434] Step 7:

[1435] The user checks the preview and inputs correction requests as necessary.

[1436] Input: Preview image, correction request (e.g. "I'd like it to be a little thicker")

[1437] Data processing / data calculation: The user checks the preview and, if any corrections are necessary, sends a correction request to the server through the application.

[1438] Output: Modified request data

[1439] Step 8:

[1440] The server regenerates the three-dimensional model based on the modification request.

[1441] Input: Correction request data, original 3D model data

[1442] Data processing / data calculation: The server again uses 3D modeling AI (e.g., Blender's Python API) to modify and regenerate the model.

[1443] Output: Corrected 3D model data

[1444] Step 9:

[1445] The server transmits the modified three-dimensional model to the terminal as a re-preview and asks the user for final confirmation.

[1446] Input: Data of the corrected 3D model

[1447] Data processing / data calculation: The server generates data for re-preview and sends it to the terminal.

[1448] Output: Preview image displayed on the device

[1449] Step 10:

[1450] Once the user has made a final confirmation and approved it, the server sends production instructions to the 3D printer or processing equipment at the physical store.

[1451] Input: Final confirmation and approval, corrected 3D model data

[1452] Data processing / data calculation: The server generates production instruction data and sends it to the 3D printer in the physical store.

[1453] Output: Production instruction data sent to the 3D printer and processing equipment in the physical store

[1454] Step 11:

[1455] In the physical store, a 3D printer creates custom accessories based on production instructions.

[1456] Input: Manufacturing instruction data, corrected 3D model data

[1457] Data processing / data calculation: The 3D printer produces custom accessories according to the production instructions.

[1458] Output: Finished custom accessories

[1459] Step 12:

[1460] Once production is complete, the server notifies the user and arranges for them to pick up the accessory at a designated physical store.

[1461] Input: Completed custom accessory information

[1462] Data processing / data calculation: The server generates a production completion notification and sends it to the user. It also arranges for the item to be picked up at the designated physical store.

[1463] Output: Notification to users and physical stores

[1464] 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.

[1465] The present invention relates to a system that generates a three-dimensional model of an accessory based on requests input by the user and then produces it using a three-dimensional printer or other processing device.The purpose of the present invention is to provide a higher user experience by combining it with an "emotion engine" that recognizes the user's emotions and reflects that information.

[1466] This system works as follows: First, the user enters detailed information about the accessory they are looking for. This information includes text and illustrations. For example, if a user wants a camera lens case, they can enter the lens size, shape, material, and other requirements in text, and upload the desired shape as illustration data.

[1467] The device sends the text and illustration information received from the user to the server. The server analyzes this information and extracts detailed design data for the accessory. Specifically, it analyzes the text information using natural language processing technology to extract specific data such as dimensions and shape. It also analyzes the illustration information using image analysis technology to understand its content.

[1468] Furthermore, the system includes an emotion engine for recognizing the user's emotions. This emotion engine analyzes emotions from facial expressions, voice, and text when the user inputs information. For example, it recognizes whether the user's facial expression is happy or confused while inputting information. It also analyzes emotional expressions contained in the text.

[1469] Based on the analyzed text, illustration, and emotion information, the server uses 3D modeling AI to generate a 3D model of the accessory. Emotional information is reflected in the generation and modification of the 3D model. For example, if the user has a confused expression, the server can provide more detailed guidance on the model or ask a simple question.

[1470] The generated 3D model preview is sent from the server to the user's device and displayed. The user can review the preview and input any necessary correction requests. For example, they can enter specific requests, such as increasing the thickness of the case or slightly changing the shape.

[1471] When the modification request arrives at the server, the server again uses the 3D modeling AI to modify and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the modification request and providing appropriate support and guidance. This modified model is again sent to the device as a preview, prompting the user for final confirmation. Once the user has completed the final confirmation and approved, the server sends production instructions to a 3D printer or other processing device.

[1472] The 3D printer or processing device that receives the production instructions will then create the accessory based on the transmitted model data. For example, the 3D printer will begin producing a camera lens case. In this way, an original accessory is created that meets the user's specific requests and emotional information.

[1473] Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The user receives and uses the finished product, allowing the user to obtain an accessory that perfectly matches their preferences.

[1474] As a concrete example, consider the case where a user wants to create a "camera lens case." The user enters text information such as "I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," and also uploads an illustration of the accessory's desired appearance. The emotion engine analyzes the user's emotions as they input, and if it detects, for example, a "confused expression," the server provides additional support. The server analyzes the information and uses 3D modeling AI to generate a 3D model of the lens case. This model is then previewed for the user, who can then input any final revision requests. Once the model is finally approved, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[1475] The system of the present invention allows users to get accessories that are tailored to their needs and emotions, thus greatly improving the product usage experience.

[1476] The processing flow will be explained below.

[1477] Step 1:

[1478] Users input detailed information about the accessories they want. Specifically, they input information such as dimensions, shape, and material as text data, and upload illustration data if necessary. The emotion engine also analyzes the user's facial expressions and voice while they are entering information.

[1479] Step 2:

[1480] The terminal transmits the text information, illustration information, and emotion information received from the user to the server.

[1481] Step 3:

[1482] The server uses natural language processing technology to analyze the text information and extract specific data such as dimensions, shape, and material. It also uses image analysis technology to analyze the illustration information and understand its content.

[1483] Step 4:

[1484] The server uses an emotion engine to analyze the user's emotions from their facial expressions and voice. The emotion data is reflected in the generation and modification of models.

[1485] Step 5:

[1486] The server uses 3D modeling AI to generate a 3D model of the accessory based on the analyzed text information, illustration information, and emotion information.

[1487] Step 6:

[1488] The server transmits preview information of the generated three-dimensional model to the terminal.

[1489] Step 7:

[1490] The device displays preview information to the user and asks for their confirmation. The emotion engine analyzes the user's reaction in real time and provides appropriate guidance and support.

[1491] Step 8:

[1492] The user checks the preview and inputs any necessary correction requests, such as "I would like the case to be a little thicker."

[1493] Step 9:

[1494] The terminal transmits the user's correction request information to the server again.

[1495] Step 10:

[1496] The server then uses the 3D modeling AI to modify and regenerate the 3D model based on the received modification request and emotion information. During this process, the emotion engine analyzes the user's emotions and provides appropriate support.

[1497] Step 11:

[1498] The server retransmits the preview information of the modified three-dimensional model to the terminal.

[1499] Step 12:

[1500] The terminal displays the preview information to the user again and asks the user for final confirmation.

[1501] Step 13:

[1502] The user then makes a final check and, if satisfied, approves the production. At this point, the emotion engine analyzes the user's emotions and provides final feedback.

[1503] Step 14:

[1504] The server sends the final approved 3D model data to a 3D printer or other processing device and issues production instructions.

[1505] Step 15:

[1506] The 3D printer / machining device will then create the accessory based on the data sent to it. For example, a 3D printer will create a camera lens case of the specified model.

[1507] Step 16:

[1508] The server notifies the user that production is complete and arranges for the finished product to be delivered to the specified address.

[1509] Step 17:

[1510] The user receives the finished product and uses it to check that it meets their requirements.

[1511] Example 2

[1512] 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."

[1513] The purpose of this invention is to efficiently produce custom-made accessories based on user input. However, conventional systems have difficulty in properly analyzing and incorporating vague user requests and feelings. Furthermore, the process of repeatedly incorporating revision requests into the design of the final product desired by the user must also be made more efficient. There is a need for a system that can address these challenges.

[1514] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1515] In this invention, the server includes: means for inputting a user's request; means for analyzing text information and image information received from the user; means for analyzing the text information and image information using natural language processing technology and image analysis technology; means including an emotion recognition engine for recognizing and analyzing the user's emotions; means including a generative AI model for generating a 3D model of the accessory based on the analysis result and the emotion information; means for sending instructions for producing the actual product based on the generated 3D model; means for sending preview information of the generated 3D model to the user and prompting confirmation; and means for accepting correction requests from the user. This enables the rapid production of sophisticated, custom-made accessories that reflect the user's detailed requests and emotion information.

[1516] The "means for inputting user requests" is an interface that allows the user to input information about the accessories they want in text or image format.

[1517] The "means for analyzing text information and image information" refers to a processing device that analyzes the content of input text or images and extracts specific instructions or data from that information.

[1518] "Natural language processing technology" is a technology that analyzes text data, understands human language, and processes it as meaningful information.

[1519] "Image analysis technology" is a technology that analyzes image data and recognizes objects and features within it.

[1520] An "emotion recognition engine" is a device that analyzes and detects emotions from input such as a user's facial expressions, voice, and text.

[1521] A "generative AI model" is a system that has an artificial intelligence algorithm for automatically generating three-dimensional models based on analysis results and emotional information.

[1522] The "means for transmitting instructions for producing an actual product" is a communication device for sending production instructions to a processing machine or other production device based on the generated three-dimensional model.

[1523] The "means for sending preview information of the generated three-dimensional model to the user and prompting confirmation" is a device for sending a visual preview of the generated three-dimensional model to the user's terminal and prompting confirmation or correction requests.

[1524] The "means for accepting a modification request from a user" refers to an interface that allows a user to input a modification request for a three-dimensional model, and a device that transmits that information to the server.

[1525] The present invention relates to a system for efficiently generating and manufacturing custom accessories based on a user's specific needs. The system analyzes information entered by the user, generates a 3D model, and then automatically performs a series of steps to manufacture the accessory based on that model.

[1526] First, the user inputs information about the accessory they want using a dedicated application on their device or a web interface. Specifically, they can input text and image information. This text information can include detailed instructions about the accessory's dimensions, material, and shape. For image information, they can upload illustrations or photos showing the desired shape of the accessory.

[1527] Next, the terminal receives the text and image information entered by the user and transmits it to the server using a secure communication method using the HTTPS protocol.

[1528] The server is equipped with various technologies for analyzing the received text and image information. To analyze the text information, it uses natural language processing technology (such as SpaCy or BERT) to extract specific dimensional and shape data. To analyze the image information, it uses image processing technology (such as OpenCV or TensorFlow) to recognize shape and design information.

[1529] Furthermore, the server uses an emotion recognition engine to analyze the user's emotions from facial expressions, voice, and text while the user is entering information. It uses facial recognition and voice analysis technologies to understand the user's emotional state (e.g., confusion, joy, etc.). This emotional information plays an important role in subsequent processing.

[1530] Based on the analyzed information and emotion data, the server uses a generative AI model to generate a 3D model of the accessory, for example, by utilizing Blender or Autodesk Fusion 360 APIs to generate a specific 3D model, which is then optimized by taking emotion information into account.

[1531] The generated 3D model is sent from the server to the device in a preview format. The user can check this preview and, if necessary, input a correction request from the device. The server receives the user's correction request and uses the 3D modeling AI to correct and regenerate the model. This process is repeated until the user is satisfied.

[1532] Once the user finally reviews and approves the 3D model, the server sends production instructions to a 3D printer or other production device, which then produces the actual accessory. For example, a 3D printer begins producing the camera lens case specified by the user. Once production is complete, the server notifies the user and arranges for the finished product to be promptly delivered to the specified address.

[1533] Specific examples

[1534] For example, if a user inputs text information such as "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm," along with an illustration of the case's shape, the server analyzes that information and generates a 3D model of the lens case using 3D modeling AI. If the user then checks the preview and inputs a request for revision, such as "I'd like the case to be a little thicker," the server will reflect that request and regenerate the model. This process is repeated several times, and once the final model is approved, a 3D printer will produce the case and deliver it to the customer.

[1535] Prompt Sentence Examples

[1536] "I'd like a camera lens case. Please model a case that fits a lens with a diameter of 70mm and a height of 150mm. I'll also upload an illustration."

[1537] Through this system, users can quickly obtain custom-made accessories that perfectly match their needs and emotions.

[1538] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1539] Step 1:

[1540] The user inputs information about the accessory they want into the device using a dedicated application or a web interface. The input information includes text specifications (e.g., "I want a camera lens case. I want a case that fits a lens with a diameter of 70 mm and a height of 150 mm.") and illustrations in the form of images. This information is then imported into the device as input data.

[1541] Step 2:

[1542] The terminal sends the text and image information entered by the user to the server using the HTTPS protocol. For transmission, the text data and image data are packaged in JSON format and a secure communication channel is used. The input is JSON-formatted data, and the output is a successful transmission notification to the server.

[1543] Step 3:

[1544] The server analyzes the received text information using natural language processing technology (for example, SpaCy or BERT). Through analysis, specific dimension, material, and shape data is extracted from the input text information. The input is text data in JSON format, and the output is analyzed dimension and material data.

[1545] Step 4:

[1546] The server analyzes the received image information using image analysis technology (e.g., OpenCV or TensorFlow). Through the analysis, information about the shape and design is extracted from the image. The input is image data in JSON format, and the output is analyzed shape data and design data.

[1547] Step 5:

[1548] The server's emotion recognition engine analyzes facial expressions and voice data in real time while the user is entering information. It uses facial recognition and voice analysis technologies to analyze the user's emotional state (e.g., confusion, joy, etc.). The input is facial expression data and voice data, and the output is analyzed emotional information.

[1549] Step 6:

[1550] The server generates a 3D model using a generative AI model (e.g., Blender or Autodesk Fusion 360 API) based on the analysis results of natural language processing and image analysis technologies, as well as emotional information. The inputs are dimensional data, shape data, and emotional information, and the output is the generated 3D model data.

[1551] Step 7:

[1552] The server sends the generated 3D model in a preview format to the terminal. The user checks the preview on the terminal and inputs correction requests as necessary. The input is the generated 3D model data, and the output is the user's confirmation and correction request information.

[1553] Step 8:

[1554] The terminal receives the user's modification request and sends it back to the server. The server modifies and regenerates the model using 3D modeling AI based on the modification request information. The input is the modification request information, and the output is the modified 3D model data.

[1555] Step 9:

[1556] Once the user has finally reviewed and approved the 3D model, the server sends production instructions to a 3D printer or other processing device. The input is the final approved 3D model data, and the output is the production instructions.

[1557] Step 10:

[1558] The 3D printer or other processing device receives the production instructions and produces the specified accessory. When production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address. The input is the production instructions and status data of the 3D printer (or processing device), and the output is a production completion notification and delivery instructions.

[1559] (Application example 2)

[1560] 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."

[1561] Conventional customized product generation systems do not take user emotions into account, making it difficult to effectively provide original products that satisfy users. Furthermore, there is a lack of means to provide a better user experience by reflecting user emotions and needs in real time. Therefore, there is a growing need for a more personalized customized product generation system that includes user emotion analysis.

[1562] 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.

[1563] In this invention, the server includes means for accepting user input, means for analyzing text information and illustration information received from the user, means for generating a 3D model of the accessory based on the analysis results, means for sending instructions for producing the actual product based on the generated 3D model, means for prompting the user to confirm the generated 3D model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the 3D model, thereby enabling the generation and production of a 3D model based on the user's emotions and specific needs.

[1564] The "means for accepting user input" is an interface that allows the user to input their wishes and requirements in text or image format.

[1565] The "means for analyzing text information and illustration information received from the user" is a system for analyzing the content of the text and illustrations provided by the user and extracting the necessary data.

[1566] The "means for generating a three-dimensional model of the accessory based on the analysis results" is a system that creates a detailed three-dimensional model of the accessory based on the analyzed information.

[1567] The "means for transmitting instructions for producing an actual product based on the generated three-dimensional model" is a system that transmits data on the generated three-dimensional model to a device that actually produces the product.

[1568] The "means for prompting the user to check the generated three-dimensional model" is an interface that presents the generated three-dimensional model to the user and requests feedback.

[1569] The "means for accepting a modification request from a user" is a system in which a user inputs a request for modification of a generated three-dimensional model.

[1570] "Means for analyzing emotions" refers to technology for analyzing a user's emotions from their facial expressions, voice, and text.

[1571] "Means for reflecting the results of emotion analysis in the generation of 3D models" refers to a system that adjusts the design and guide of 3D models based on the analyzed emotion information.

[1572] A "three-dimensional manufacturing device" is a device that physically produces accessories based on three-dimensional model data.

[1573] A "wood processing machine" is a machine that processes wood into a specified shape.

[1574] A "leather processing device" is a device that processes leather material into a specified shape.

[1575] This invention relates to a system that accepts user input and generates original accessories based on that information. It also analyzes the user's emotions and reflects the results in the generation of a 3D model, providing a more personalized experience.

[1576] This system includes means for accepting user input, means for analyzing text information and illustration information, means for generating a three-dimensional model of the accessory based on the analysis results, means for sending instructions for producing the actual item based on the generated three-dimensional model, means for prompting the user to confirm the generated three-dimensional model, means for accepting correction requests from the user, means for analyzing emotions, and means for reflecting the emotion analysis results in the generation of the three-dimensional model.

[1577] To explain the embodiment in detail, the operation is as follows:

[1578] 1. The user provides input

[1579] Users enter detailed information about the accessories they want using text and illustrations. For example, if they are ordering a camera lens case, they would enter the lens size, shape, and material requirements in text, and upload the desired shape as illustration data.

[1580] 2. Analysis of text and illustration information

[1581] The server analyzes the text and illustration information received from the user. The text information is interpreted using natural language processing technology to extract specific data on dimensions and shape. The illustration information is also analyzed using image analysis technology. The natural language processing technology used includes Huggingface transformers, and the image analysis technology used is OpenCV.

[1582] 3. 3D Model Generation

[1583] Based on the analyzed data, the server uses 3D modeling AI to generate a 3D model of the accessory. In this step, OpenAI's API is used to generate the 3D model. For example, a model of a camera lens case with the required shape and dimensions is generated based on the information entered by the user and the analysis results.

[1584] 4. User sentiment analysis and feedback

[1585] The system analyzes the user's facial expressions and voice while they are typing to collect emotional information. An emotion recognition model using Keras and TensorFlow is used for the emotion analysis. The results are reflected in the model generation process, providing detailed guidance if the user is confused, and incorporating positive emotions into the model design.

[1586] 5. Preview and correction requests

[1587] The server sends a preview of the generated 3D model to the user's device and displays it to them. The user can then review the preview and input correction requests as needed. For example, they could request to increase the thickness of the case or slightly change its shape.

[1588] 6. Final confirmation and production instructions

[1589] Based on the revision request, the server again uses the 3D modeling AI to revise and regenerate the model. The emotion engine also works during this process, analyzing the user's emotions when making the revision request and providing appropriate support and guidance. The revised model is previewed again, and once the user gives their final confirmation and approval, the server sends production instructions to the 3D manufacturing equipment.

[1590] 7. Production and Delivery

[1591] The 3D manufacturing equipment then produces the accessory based on the model data. For example, a 3D printer starts producing a camera lens case. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[1592] As a specific use case, consider a case where a user inputs "I want a camera lens case with a diameter of 70 mm and a height of 150 mm" and uploads their own image. If the emotion engine detects a "confused expression," the server provides additional support. The server then analyzes the information and generates a 3D model of the lens case using 3D modeling AI. This model is previewed to the user, who can then input any final revision requests. After final confirmation, production instructions are sent to a 3D printer, and the finished product is produced and delivered.

[1593] An example prompt is:

[1594] "I want a camera lens case that is 70mm in diameter and 150mm in height. User sentiment is confused."

[1595] This makes it possible to provide high-quality original accessories that meet the needs and feelings of users.

[1596] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1597] Step 1:

[1598] The user provides input

[1599] The user inputs detailed information about the accessory they want into the terminal. The input includes text information (e.g., "I want a camera lens case with a diameter of 70 mm and a height of 150 mm") and illustration information. The input data is sent to the server.

[1600] Input: Text information, illustration information

[1601] Output: User request data sent to the server

[1602] Step 2:

[1603] Analysis of text and illustration information

[1604] The server analyzes the received text using natural language processing technology (e.g., Huggingface's transformers), extracting specific dimensions and shape data from the text. At the same time, the illustration information is analyzed using image analysis technology (e.g., OpenCV) to obtain shape and design information.

[1605] Input: User's text information, illustration information

[1606] Output: Extracted dimension data and shape data

[1607] Step 3:

[1608] 3D model generation

[1609] The server uses a 3D modeling AI (e.g., OpenAI's API) to generate a 3D model of the accessory based on the analyzed data. The AI ​​model uses prompts to guide the generation process.

[1610] Input: Extracted dimension data, shape data, prompt statement (e.g., "I would like a camera lens case with a diameter of 70 mm and a height of 150 mm.")

[1611] Output: Generated 3D model

[1612] Step 4:

[1613] Emotion analysis

[1614] While the user is inputting, the user's facial expression and voice data are collected and emotion analysis is performed on the server. Keras and TensorFlow are used for emotion analysis to identify the type of emotion (e.g., "confusion") from the user's facial image and voice. Emotional information is also reflected in the generation of the 3D model.

[1615] Input: User's face image, voice data

[1616] Output: Parsed emotion information

[1617] Step 5:

[1618] Model modification based on user sentiment

[1619] Based on the analyzed emotion information, the server provides feedback to the 3D model generation process: if the emotion is "confused," additional support or detailed guidance is provided.

[1620] Input: Analyzed emotion information, generated 3D model

[1621] Output: Corrected 3D model, supporting information

[1622] Step 6:

[1623] Preview and correction requests accepted

[1624] The server sends a preview of the generated 3D model to the terminal and displays it to the user. The user checks the preview and re-enters any parts they want to modify. The modification request is then sent back to the server.

[1625] Input: Generated 3D model, user modification request

[1626] Output: User feedback, correction requests

[1627] Step 7:

[1628] Final confirmation and production instructions

[1629] Based on the modification request, the server again modifies and regenerates the model using the 3D modeling AI. Once final confirmation is received from the user, the server issues a manufacturing instruction to the 3D manufacturing equipment.

[1630] Input: User's final confirmation, modified 3D model

[1631] Output: Production instructions for 3D manufacturing equipment

[1632] Step 8:

[1633] Production and Delivery

[1634] The 3D manufacturing equipment creates the actual product based on the model data sent from the server. Once production is complete, the server notifies the user and arranges for the finished product to be delivered to the specified address.

[1635] Input: Modified 3D model, fabrication instructions

[1636] Output: Finished product, notification to user and delivery arrangements

[1637] 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.

[1638] 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.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] 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).

[1644] 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.

[1645] 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."

[1646] 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.

[1647] 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).

[1648] 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.

[1649] 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.

[1650] 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.

[1651] 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.

[1652] 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.

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] 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.

[1658] The following is further disclosed regarding the above embodiment.

[1659] (Claim 1)

[1660] means for accepting user input;

[1661] means for analyzing text information and illustration information received from a user;

[1662] means for generating a three-dimensional model of the accessory based on the analysis results;

[1663] means for transmitting instructions for producing an actual object based on the generated three-dimensional model;

[1664] a means for prompting a user to confirm the generated three-dimensional model;

[1665] The system includes a means for accepting a modification request from a user.

[1666] (Claim 2)

[1667] 10. The system of claim 1, further comprising means for producing the three-dimensional model with a three-dimensional printer.

[1668] (Claim 3)

[1669] 10. The system of claim 1, further comprising means for producing the three-dimensional model in a woodworking or leatherworking machine.

[1670] "Example 1"

[1671] (Claim 1)

[1672] means for accepting user input;

[1673] means for analyzing text data and image data received from a user;

[1674] A means for analyzing text data using natural language processing technology;

[1675] means for analyzing image data using image analysis techniques;

[1676] means for generating a three-dimensional model of the attachment based on the analysis results;

[1677] means for transmitting instructions for fabricating an entity based on the generated three-dimensional model;

[1678] a means for displaying a preview of the generated three-dimensional model to a user to prompt the user to confirm it;

[1679] means for accepting modification requests from users;

[1680] The system includes means for regenerating the three-dimensional model based on the modification request.

[1681] (Claim 2)

[1682] 10. The system of claim 1, further comprising means for producing the three-dimensional model in a three-dimensional printing device.

[1683] (Claim 3)

[1684] 10. The system of claim 1, further comprising means for fabricating the three-dimensional model with various processing equipment.

[1685] "Application Example 1"

[1686] (Claim 1)

[1687] means for accepting user input;

[1688] means for analyzing text information and illustration information received from a user;

[1689] means for generating a three-dimensional model of the accessory based on the analysis results;

[1690] means for transmitting instructions for producing an actual object based on the generated three-dimensional model;

[1691] a means for prompting a user to confirm the generated three-dimensional model;

[1692] means for accepting modification requests from users;

[1693] A system including means for generating, crafting, and selling custom accessories in a brick-and-mortar store.

[1694] (Claim 2)

[1695] 10. The system of claim 1, further comprising means for producing the three-dimensional model with a three-dimensional printer.

[1696] (Claim 3)

[1697] 10. The system of claim 1, further comprising means for producing the three-dimensional model in a woodworking or leatherworking machine.

[1698] "Example 2: Combining Emotion Engines"

[1699] (Claim 1)

[1700] means for inputting a user request;

[1701] means for analyzing text and image information received from a user;

[1702] A means for analyzing text information and image information using natural language processing technology and image analysis technology;

[1703] means including an emotion recognition engine for recognizing and analyzing the emotions of a user;

[1704] means including a generative AI model for generating a three-dimensional model of the accessory based on the analysis result and the emotion information;

[1705] means for transmitting instructions for producing an actual object based on the generated three-dimensional model;

[1706] means for transmitting preview information of the generated three-dimensional mode...

Claims

1. means for accepting user input; means for analyzing text information and illustration information received from a user; means for generating a three-dimensional model of the accessory based on the analysis results; means for transmitting instructions for producing an actual object based on the generated three-dimensional model; a means for prompting a user to confirm the generated three-dimensional model; The system includes a means for accepting a modification request from a user.

2. 10. The system of claim 1, further comprising means for producing the three-dimensional model with a three-dimensional printer.

3. 10. The system of claim 1, further comprising means for producing the three-dimensional model on a woodworking or leatherworking machine.

Images