System

Abstract

A system is provided.SOLUTION: This system is provided with an inputting means for allowing a user to designate a custom-made merchandise, a processing means for receiving date inputted by a server, and for generating a custom design through a AI system, an information providing means for presenting the generated design plan to the user, and an interface means for allowing the user to correct and confirm a final design, and for allowing the server to transmit the final design to a 3D printer. This system is provided with a control means for instructing manufacture, a manufacturing means for manufacturing the custom-made merchandise designated by the user by a 3D printer, a quantity inspection means for inspecting the quantity of the completed manufactured merchandise, and a delivery means for delivering the manufactured merchandise passing the quantity inspection to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional systems for producing custom-made products have difficulty quickly and accurately reflecting the user's detailed requests, requiring significant costs and time. It is also difficult to maintain a consistently high level of quality for the manufactured products. Furthermore, when users design their own products, specialized knowledge and design skills are required, so there is no environment in place where general users can easily order custom-made products. The present invention aims to solve these problems and provide a system that efficiently provides high-quality custom-made products that meet the user's needs. [Means for solving the problem]

[0005] The present invention solves the aforementioned problems with a system that includes an input means for a user to specify a custom-made product, a processing means for receiving the input data from a server and generating a custom design through an AI system, an information provision means for presenting the generated design proposals to the user, an interface means for the user to modify and confirm the final design, a control means for transmitting the final design data to a 3D printer by the server and instructing production, a manufacturing means for manufacturing the custom-made product specified by the user using the 3D printer, a quality inspection means for inspecting the quality of the completed manufactured product, and a delivery means for delivering the manufactured product that passes the quality inspection to the user. Specifically, the AI ​​system optimizes the custom design based on past order data, trend information, and user preferences, and the server includes a management means for receiving the quality inspection results and initiating delivery procedures, thereby providing efficient and high-quality custom-made products.

[0006] "User" means any person or entity that uses the System to order custom-made products.

[0007] "Input means" refers to an interface, such as a form or application, through which a user enters details of the custom product desired.

[0008] "Server" refers to the computer system that receives request data from the user, passes the data to the AI ​​system, returns the generated design to the user's device, and sends the final design data to the 3D printer to instruct manufacturing.

[0009] "AI system" refers to software that uses artificial intelligence to analyze large amounts of 3D printer data and user preference data to generate optimal custom designs.

[0010] "Information provision means" refers to a mechanism for presenting the generated design proposals to the user, such as a preview screen or notification system.

[0011] "Interface means" refers to a mechanism that provides a UI (user interface) that allows users to revise and finalize design proposals.

[0012] "Control means" refers to the mechanism by which the server sends the final design data to the 3D printer and directs and manages the manufacturing process.

[0013] "3D printer" refers to a device that physically produces custom-made products based on design data sent from a server.

[0014] "Manufacturing means" refers to the entire process of using a 3D printer to manufacture a custom-made product specified by a user.

[0015] "Quality inspection means" refers to a system or process for inspecting completed manufactured goods to ensure that they are made as designed and meet the required quality standards.

[0016] "Delivery means" refers to the entire process of packaging manufactured products that have passed quality inspection and delivering them to users.

[0017] "Management means" refers to the software and procedures by which the server receives the quality inspection results and initiates the delivery process. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention provides a system that allows users to easily create custom-made products. This system includes many components, such as an input means for users to specify products according to their preferences, a processing means for receiving the input data from a server and generating custom designs through an AI system, and an information providing means for presenting the generated design proposals to the user.

[0040] The main steps of the system are as follows: First, the user uses a terminal to specify a custom-made product, inputting information such as the product category, design theme, desired color, and text. The terminal reads the input data and sends it to the server.

[0041] The server then receives the user's request data and extracts relevant information stored in a database (past order data, trend information, user preferences), which is then passed to the AI ​​system to generate a custom design.

[0042] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. During this process, it builds and evaluates design prototypes, creating multiple candidates. The resulting design proposals are then sent back to the server, where they are transferred to the user's device.

[0043] The device displays the generated design proposal to the user, providing a preview. The user can review the design proposal and customize it if necessary (for example, by adjusting colors or editing text). Once the user has finalized the design, the device sends that information to the server and confirms the manufacturing request.

[0044] The server then sends the final design data to the 3D printer's control system, which then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and any necessary adjustments are made automatically.

[0045] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc., and only products that pass this inspection are shipped.

[0046] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time. Finally, the delivery service delivers the product to the user.

[0047] As a concrete example, when a user orders a custom-made smartphone case, the following process takes place: First, the user inputs their preferred color and design theme using their device and sends it to the server. The server passes the data to the AI ​​system, which generates an optimized design proposal. The user reviews and adjusts the proposal and confirms the manufacturing request. The server then sends the final design to a 3D printer, which produces the product. Once the smartphone case passes quality inspection, it is delivered to the user via a shipping method.

[0048] The system of the present invention allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[0049] The processing flow will be explained below.

[0050] Step 1:

[0051] A user accesses the system's homepage using a terminal and enters the necessary information into an input form to request the manufacture of a custom-made product, such as specifying the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text to be inserted (e.g., name or message).

[0052] Step 2:

[0053] The terminal reads the information input by the user, generates formatted request data, and transmits it to the server.

[0054] Step 3:

[0055] The server receives the request data and extracts relevant information stored in the database (past order data, trend information, user preference data).

[0056] Step 4:

[0057] The server passes the extracted data to an AI system, which then instructs it to generate a custom design.

[0058] Step 5:

[0059] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates multiple candidates to generate optimal designs.

[0060] Step 6:

[0061] The server receives the design proposals generated by the AI ​​system and transfers them to the user's device.

[0062] Step 7:

[0063] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[0064] Step 8:

[0065] The user decides on the final design and presses the confirmation button to confirm the manufacturing request.

[0066] Step 9:

[0067] The terminal sends the final design data to the server and confirms the manufacturing request.

[0068] Step 10:

[0069] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[0070] Step 11:

[0071] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0072] Step 12:

[0073] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[0074] Step 13:

[0075] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[0076] Step 14:

[0077] The delivery service delivers the product that has passed the quality inspection to the user, who then receives the delivered product and confirms that the custom-made product is complete.

[0078] Example 1

[0079] 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."

[0080] Today's market demands systems that allow users to order custom-made products tailored to their preferences. However, existing systems often involve complicated processes, from design creation to manufacturing, quality inspection, and delivery. Furthermore, it is often impossible to check and adjust progress in real time during this process. This results in a poor user experience and ultimately makes it difficult to quickly deliver high-quality custom-made products.

[0081] 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.

[0082] In this invention, the server includes input means for a user to specify a custom-made product, processing means for receiving the data input by the server and generating a custom design through an AI system, information provision means for presenting the generated design proposals to the user, interface means for the user to modify and confirm the final design, control means for transmitting the final design data to a manufacturing device by the server and instructing manufacturing, manufacturing means for manufacturing the custom-made product specified by the user by the manufacturing device, quality inspection means for inspecting the quality of the completed manufactured product, delivery means for delivering manufactured products that pass the quality inspection to the user, monitoring means for performing real-time monitoring and adjustment during the manufacturing process, reporting means for notifying the server of the results of the quality inspection, and notification means for notifying the user of the delivery status in real time, thereby enabling users to receive custom-made products tailored to their preferences quickly and with high quality.

[0083] The "input means" is an interface device that allows the user to input information about the custom-made product (product category, design theme, color, text, etc.).

[0084] "Processing means" refers to a device that passes data received by the server from the input means to the AI ​​system and performs the data processing required to generate a custom design.

[0085] The "information providing means" is a display device that presents the generated custom design to the user so that the user can check the design.

[0086] "Interface means" refers to an interactive editing device that allows a user to modify and finalize the generated custom design.

[0087] The "control means" is a device that allows the server to send the final design data to the manufacturing equipment and instruct and manage the manufacturing process.

[0088] "Manufacturing means" refers to a manufacturing device that actually manufactures a custom-made product based on the final design data.

[0089] "Quality inspection means" refers to equipment for inspecting the quality of finished manufactured products, such as their appearance, dimensions, and durability.

[0090] The "delivery means" is a physical distribution device for delivering manufactured products that have passed the quality inspection to users.

[0091] "Monitoring means" means a device for monitoring progress and quality in real time during the manufacturing process and making adjustments as necessary.

[0092] The "reporting means" is a communication device for notifying the server of the results of the quality inspection.

[0093] The "notification means" is a communication device for notifying the user of the delivery status in real time.

[0094] The "AI system" is a system that uses artificial intelligence to analyze past order data, trend information, and user preference data to generate optimal custom designs.

[0095] "Manufacturing Equipment" refers to 3D printers and other machinery used to manufacture custom products.

[0096] The present invention relates to a system that allows users to easily manufacture customized products. The system comprises an input means for users to specify products based on their preferences, a processing means for receiving the input data from a server and generating a custom design through an AI system, and an information provision means for presenting the generated design proposals to the user. The system also includes an interface means for users to modify and finalize the final design, a control means for transmitting the final design data from the server to a manufacturing device and issuing manufacturing instructions, a manufacturing means for manufacturing the user-specified customized product using the manufacturing device, a quality inspection means for inspecting the quality of the completed manufactured product, a delivery means for delivering manufactured products that pass the quality inspection to the user, a monitoring means for monitoring and adjusting the manufacturing process in real time, a reporting means for notifying the server of the quality inspection results, and a notification means for notifying the user of the delivery status in real time.

[0097] Specifically, the process begins with the user specifying a custom product using a terminal. For example, the user uses a smartphone to access the custom order page through a specialized application or web browser. Here, the user enters details such as product category, design theme, desired color, and text. The terminal receives this data, validates it in real time, and then transmits it to the server using the secure HTTPS protocol.

[0098] The server temporarily stores the data received from the user in a database and extracts relevant information based on past order data, trend information, and user preferences. This data is passed to the AI ​​system, which instructs it to generate a custom design. The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate the optimal custom design. During this process, multiple design prototypes are created and each is evaluated. The generated design proposals are sent back to the server, which then transfers them to the user's device.

[0099] The device displays the generated design proposal to the user, allowing the user to preview it. The user can then check the displayed proposal, adjust colors and edit text as necessary, and confirm the final design. The device then sends this information back to the server to confirm the manufacturing request.

[0100] The server then sends the final design data to the 3D printer's control system, converting it into a format the 3D printer can understand (e.g., an STL file). The 3D printer then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and automatically adjusted to ensure quality is always maintained.

[0101] Once a product is completed, it undergoes a quality inspection. This inspection includes appearance, dimensions, durability, etc., and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. The shipping status is notified to the user in real time, and a final notification is sent to the user when delivery is complete.

[0102] Examples:

[0103] Below is a specific example where a user orders a custom smartphone case.

[0104] Prompt statement:

[0105] "In a scenario where a user is ordering a custom smartphone case, please generate design proposals for the following case: color blue, design theme marine, and custom text 'ocean'."

[0106] When this prompt is input into the generative AI model, the model generates design proposals for smartphone cases based on the specified requirements, which are then used in subsequent processes.

[0107] This system allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] The user specifies the custom-made product using the device. In this step, the user accesses the custom order page through a dedicated app or web browser. The information entered includes the product category (e.g., smartphone case), design theme (e.g., marine), desired color (e.g., blue), and text (e.g., "ocean"). The device temporarily stores the data entered by the user. Input: Information about the custom-made product from the user. Output: Stored user data.

[0111] Step 2:

[0112] The terminal validates the entered data in real time. Once validation is complete, it sends the data to the server using the HTTPS protocol, where the data integrity and format are checked. Input: Custom product data entered by the user. Output: User data sent to the server.

[0113] Step 3:

[0114] The server receives the input data and temporarily stores it in a database. It then extracts past order data, trend information, and user preference data from the database. The server integrates this data and prepares it to be passed to the AI ​​system. Input: User data sent from the terminal. Output: Integrated data to be passed to the AI ​​system.

[0115] Step 4:

[0116] The AI ​​system analyzes large amounts of 3D printer data, trend analysis, and user preference data based on data provided by the server. It builds multiple design prototypes, evaluates each candidate, and generates the optimal custom design proposal. Input: Data passed from the server. Output: Generated custom design proposal.

[0117] Step 5:

[0118] The server checks the design proposal received from the AI ​​system and transfers it to the user's device. The transferred data includes image files of the generated design proposal and related information. Input: Design proposal from the AI ​​system. Output: Design proposal data sent to the user's device.

[0119] Step 6:

[0120] The device displays the generated design proposals to the user. The user selects one of the multiple design proposals displayed and adjusts colors and edits text as necessary. Once the user has decided on the final design, the device sends that information to the server. Input: Design proposal sent from the server. Output: Final design data confirmed by the user is sent to the server.

[0121] Step 7:

[0122] The server sends the received final design data to the manufacturing equipment. The data is converted into a format that the 3D printer can understand (e.g., STL file). At this time, instructions for the manufacturing equipment are also sent. Input: Final design data from the terminal. Output: Design data and manufacturing instructions sent to the manufacturing equipment.

[0123] Step 8:

[0124] The manufacturing equipment produces products based on the design data received from the server. The manufacturing process is monitored in real time and automatically adjusted as needed. Once manufacturing is complete, the product is sent for quality inspection. Input: Design data from the server. Output: Manufactured product.

[0125] Step 9:

[0126] The quality inspection means inspects manufactured products. Inspection items include appearance, dimensions, durability, etc. If the product passes the quality inspection, the results are reported to the server. Input: Manufactured product. Output: Report of quality inspection results to the server.

[0127] Step 10:

[0128] The server receives the quality inspection results and starts the delivery procedure. Delivery status information is notified to the user in real time via a dedicated app or email. Input: Information on products that passed the quality inspection. Output: Start of delivery procedure, notification of delivery status to the user.

[0129] Step 11:

[0130] The delivery vehicle receives products ready for shipment and delivers them to the address specified by the user. Once delivery is complete, a final notification is sent to the user. Input: Products ready for shipment. Output: Products delivered to the user, notification of delivery completion sent.

[0131] (Application example 1)

[0132] 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."

[0133] Conventional custom-made product systems have had issues with making it difficult for users to easily design products according to their preferences, lacking real-time design previews and the ability to track the delivery status of manufactured products. Furthermore, users were limited to online ordering, unable to quickly order and receive custom-made products directly at the store.

[0134] 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.

[0135] In this invention, the server includes an input means for a user to specify a custom-made product, a processing means for receiving the data input by the server and generating a custom design through an AI system, a means for previewing the generated design proposal in real time through a smartphone application or tablet application, and a means for displaying the delivery status of the manufactured product in real time, thereby enabling users to easily design a custom-made product in a store and check the manufacturing and receiving status on the spot.

[0136] The "input means by which the user specifies a custom-made product" refers to a device or interface for inputting customization information such as the product category, design theme, color, and text desired by the user.

[0137] The "AI system" is a system that includes artificial intelligence algorithms that generate and optimize optimal custom designs based on past order data, trend information, and user preferences.

[0138] The "server" is a central control device that receives data from users, sends the data to the AI ​​system, manages the generated design proposals, sends the final design data to the 3D printer, manages quality inspection results, and handles delivery procedures.

[0139] "Information providing means" refers to a display or application that receives design proposals generated from the server and presents them to the user.

[0140] The "interface means" is an operation interface that allows the user to check the generated design proposal, make corrections, and make a final decision.

[0141] "Control means" refers to a system that sends the final design data to the 3D printer via a server and instructs the production of custom-made products.

[0142] "Manufacturing means" refers to the equipment used to actually manufacture custom-made products specified by the user using a 3D printer.

[0143] "Quality inspection means" refers to equipment or processes for inspecting the appearance, dimensions, durability, etc. of completed manufactured goods to determine whether they conform to quality standards.

[0144] "Delivery means" refers to the delivery system and procedures for delivering manufactured products that have passed quality inspection to users.

[0145] The "real-time preview means" is a display or application that allows the user to instantly view the generated design proposal and check and modify it.

[0146] "Means for displaying delivery status in real time" refers to a system or application that instantly updates the delivery progress of manufactured products and notifies the user.

[0147] This invention provides a system that allows users to easily manufacture customized products, and includes the following components. First, an input means is required for users to specify the customized products. This input means is implemented in a device such as a smartphone application or tablet application, and is used by users to input information such as product category, design theme, color, and text.

[0148] The server then receives input data from the user and has a processing means to generate a custom design through an AI system. The server optimizes the design based on past order data, trend information, and the user's preferences. Possible software to use is Python or Flask. For example, it generates a prompt message such as, "If the user specifies a smartphone case as the product category, selects modern as the design theme, and enters "Mr. A" in blue text, please generate the optimal design."

[0149] The generated design proposal is sent from the server to the terminal and is previewed in real time by the user via the information provision means. The user can check the generated design proposal using the terminal and make corrections as necessary. This is the interface means, and it is used by the user to finalize the design.

[0150] The server receives the final design data and has a control means for sending it to the 3D printer. The 3D printer has a manufacturing means for producing custom-made products specified by the user based on this design. Once manufactured, the products are inspected for appearance, dimensions, durability, etc. by a quality inspection means, and only products that pass the quality standards are shipped.

[0151] Furthermore, manufactured products that pass quality inspection are delivered to the user via a delivery method. The server also manages delivery procedures and has a function to display the delivery status on the terminal in real time, allowing the user to track the product from dispatch to arrival in real time.

[0152] This system allows users to intuitively create custom-made product designs in-store just as they would online, and check the status of their delivery on the spot, enabling faster and higher-quality custom-made products to be delivered.

[0153] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0154] Step 1:

[0155] The user uses the terminal to specify the custom-made product.

[0156] In this step, the user operates the smartphone application or tablet application to input the product category, design theme, color, text, etc. The input data is converted into a data format on the terminal and sent to the server.

[0157] Input: Product information (category, theme, color, text)

[0158] Output: Formatted data (data sent to the server)

[0159] Step 2:

[0160] The server receives the data entered by the user.

[0161] The server analyzes the data received from the device and stores it in a database, then converts the data into prompt format required for the generative AI model.

[0162] Input: Data from user (product information)

[0163] Output: Prompt sentence to the generative AI model

[0164] Step 3:

[0165] The server sends prompts to the generative AI model to generate a custom design.

[0166] The server sends the prompt text to the generative AI model, which then analyzes past order data, trend information, and user preference data to generate custom design proposals, which are then sent back to the server.

[0167] Input: Prompt sentence for generative AI model

[0168] Output: Custom design proposal

[0169] Step 4:

[0170] The server sends the generated design proposal to the terminal and provides a preview to the user.

[0171] The server sends the generated design proposal to the user's device, which displays it in real time, and the user can check the displayed design proposal.

[0172] Input: Custom design idea

[0173] Output: Preview your design on your device

[0174] Step 5:

[0175] The user modifies and finalizes the design proposal.

[0176] The user can view the previewed design and make any necessary corrections. Once the corrections are complete, the user confirms the final design and sends the data to the server.

[0177] Input: Modified design information

[0178] Output: Finalized design data (data sent to server)

[0179] Step 6:

[0180] The server sends the final design data to the 3D printer to begin production.

[0181] The server receives the finalized design data and sends it to the 3D printer, which then produces the custom-made product based on the received design data.

[0182] Input: Finalized design data

[0183] Output: Manufacturing instructions for the 3D printer

[0184] Step 7:

[0185] 3D printers produce custom-made products and perform quality inspections.

[0186] The 3D printer uses the received design data to manufacture the product, and once manufactured, the product undergoes quality inspection to check its appearance, dimensions, durability, etc.

[0187] Input: Manufacturing instructions to the 3D printer

[0188] Output: Finished products and quality inspection results

[0189] Step 8:

[0190] The server receives the quality inspection results and starts the delivery procedure.

[0191] Products that pass the quality inspection are sent to the server's management system for delivery, which displays the delivery status on the terminal in real time.

[0192] Input: Quality Inspection Results

[0193] Output: Delivery status (notification to terminal)

[0194] 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.

[0195] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[0196] The main components of the system include an input means for users to specify custom-made products, a server, an AI system, an emotion engine, an information provision means, an interface means, a 3D printer, a quality inspection means, and a delivery means.

[0197] First, a user accesses the system's homepage using a terminal and requests the design of a custom-made product. At this time, the user inputs information such as the product category, design theme, desired color, and text. Sensors (e.g., a facial recognition camera and a voice analysis microphone) are also used to recognize the user's emotions. The terminal then transmits the input data and emotional data to the server.

[0198] The server then receives the request data and emotion data, extracts relevant information stored in a database (past order data, trend information, user preferences), and passes this data to the AI ​​system and emotion engine to generate a custom design.

[0199] The AI ​​system and emotion engine analyzes large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. This process involves building design prototypes and evaluating multiple candidates. The emotion engine selects and recommends designs based specifically on the user's emotion data.

[0200] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[0201] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[0202] After the 3D printer completes the product, a quality inspection is carried out. The inspection includes the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[0203] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[0204] The system of the present invention allows users to quickly and with high quality receive personalized custom-made products based on their preferences and emotions. The introduction of the emotion engine further improves the user experience and enables the provision of highly satisfying services.

[0205] The processing flow will be explained below.

[0206] Step 1:

[0207] The user accesses the system's homepage using a device and enters the necessary information into an input form to specify a custom-made product. Specifically, the user enters the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text insertion (e.g., name or message). In addition, emotion data is also obtained using a facial recognition camera and a voice analysis microphone.

[0208] Step 2:

[0209] The terminal reads the product information and emotion data input by the user, generates formatted request data, and transmits it to the server.

[0210] Step 3:

[0211] The server receives the request data and emotion data and extracts related information (past order data, trend information, user preference data) stored in a database.

[0212] Step 4:

[0213] The server passes the extracted data to an AI system and emotion engine, instructing it to generate a custom design.

[0214] Step 5:

[0215] The AI ​​system and emotion engine analyze large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates and generates multiple design candidates. The emotion engine selects and recommends designs based on the user's emotion data.

[0216] Step 6:

[0217] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device.

[0218] Step 7:

[0219] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[0220] Step 8:

[0221] The emotion engine analyzes the emotion data in real time and suggests optimal modifications based on the user's customizations. The user can then review the suggestions and make a final decision.

[0222] Step 9:

[0223] The user finalizes the design and presses the confirmation button for the manufacturing request.

[0224] Step 10:

[0225] The terminal sends the final design data to the server and confirms the manufacturing request.

[0226] Step 11:

[0227] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[0228] Step 12:

[0229] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0230] Step 13:

[0231] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[0232] Step 14:

[0233] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[0234] Step 15:

[0235] The delivery service delivers the product that has passed quality inspection to the user, who then accepts the delivery and confirms that the custom-made product was manufactured as expected.

[0236] Through these steps, users can easily order personalized custom-made products based on their preferences and emotions and receive them quickly and with high quality.

[0237] Example 2

[0238] 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."

[0239] Conventional custom-made product systems have difficulty generating personalized designs based on the user's emotions and preferences, and have been unable to provide products that satisfy the user. Furthermore, improving the efficiency of the manufacturing process and ensuring quality remain significant challenges. The present invention aims to solve these problems by providing a system that utilizes user emotion data to provide optimal custom designs and realize a high-quality manufacturing process.

[0240] 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.

[0241] In this invention, the server includes a means for the terminal to send input data and emotion data to the server, a means for the server to analyze the received data by extracting relevant information from a database and send it to the AI ​​system and emotion engine, and a means for the AI ​​system and emotion engine to generate a custom design, thereby enabling the generation of personalized custom designs based on the user's emotion data and a high-quality manufacturing process.

[0242] The "input means" is a means by which a user inputs information about the design of a custom-made product into the system.

[0243] A "terminal" is a device through which a user inputs information and transmits and receives data to and from a server.

[0244] A "server" is a computer system that processes data received from users and manages the design generation and manufacturing process.

[0245] A "database" is an information system for storing past order data, trend information, and user preference data.

[0246] An "AI system" is a system that uses artificial intelligence technology to analyze large amounts of data and generate optimal custom designs.

[0247] An "emotion engine" is a system that analyzes user emotional data and makes designs and recommendations based on the results.

[0248] "Information provision means" refers to the means for presenting design proposals generated by the AI ​​system and emotion engine to the user.

[0249] "Interface means" refers to the means by which a user can modify and finalize the generated design proposals.

[0250] "Control means" refers to the means by which the server sends the final design data to the 3D printer and instructs manufacturing.

[0251] A "3D printer" is a three-dimensional printing machine that manufactures products based on design data received from a server.

[0252] "Manufacturing means" refers to a means for manufacturing a custom-made product specified by a user using a 3D printer.

[0253] "Quality inspection means" refers to means for inspecting the quality of completed manufactured goods.

[0254] "Delivery means" refers to a means for delivering manufactured products that have passed the quality inspection to the user.

[0255] The "management means" is a means by which the server receives the quality inspection results and starts the delivery procedure.

[0256] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[0257] Hardware and software used

[0258] Terminal (device used by the user, e.g. smartphone, PC)

[0259] server

[0260] AI systems (e.g. TensorFlow, PyTorch)

[0261] Emotion engines (e.g., Affectiva)

[0262] Interface means (e.g., web browser, specific application)

[0263] 3D printer (e.g. Ultimaker S5)

[0264] Quality inspection methods (e.g., AI-enabled vision systems)

[0265] Shipping method (e.g. FedEx, UPS)

[0266] Explanation of the program's processing steps

[0267] User input and data submission

[0268] A user accesses the system's homepage using a terminal and requests a custom-made product design. The user inputs information such as product category, design theme, desired color, and text. Emotional data is also collected using a facial recognition camera and a voice analysis microphone. The terminal then transmits the input data and emotional data to the server.

[0269] Receiving and analyzing data

[0270] The server extracts the received request data and emotion data, as well as past order data, trend information, and user preference data stored in a database. The server passes this data to the AI ​​system and emotion engine, instructing it to generate a custom design.

[0271] Generate a custom design

[0272] The AI ​​system and emotion engine analyze large amounts of trend information, 3D printer data, user preference data, and emotion data to generate optimal custom designs. Multiple design candidates are constructed and evaluated. The emotion engine selects and recommends designs based on the user's emotion data.

[0273] Presentation of design proposals

[0274] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[0275] Final design confirmation and manufacturing

[0276] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[0277] Quality Inspection and Delivery

[0278] After the 3D printer completes the product, a quality inspection is carried out. The product's appearance, dimensions, durability, etc. are inspected, and only products that pass are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[0279] Specific examples

[0280] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[0281] Prompt sentence for generative AI model

[0282] "If a user wants to create a custom smartphone case, they first access their device. They enter information such as product category, design theme, desired color, and text, and then collect sentiment data."

[0283] "You send your input data and emotion data to our server, which then uses our AI system and emotion engine to generate custom design ideas."

[0284] "The generated design proposals are displayed to the user, who can then customize them as needed. The final design data is then sent to the server, and the manufacturing process begins."

[0285] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0286] Step 1:

[0287] The user initiates an order for a custom-made product on the device. Specifically, the user accesses the system's homepage and inputs information such as the product category, design theme, desired color, and text. The user also acquires emotional data using a facial recognition camera and a voice analysis microphone. The input data and emotional data are stored on the device.

[0288] Input: User input information (product category, design theme, desired color, text), emotional data

[0289] Output: A set of input data and emotion data

[0290] Step 2:

[0291] The device sends the input data and emotion data to the server. The device POSTs the dataset to the server as an HTTP request.

[0292] Input: A set of input data and emotion data

[0293] Output: Send data to the server

[0294] Step 3:

[0295] The server receives the request data and emotion data, analyzes the received data, and extracts past order data, trend information, and user preference data stored in a database.

[0296] Input: Request data and emotion data received by the server

[0297] Output: Analyzed related information (past order data, trend information, user preference data)

[0298] Step 4:

[0299] The server extracts the relevant information and passes the data to the AI ​​system and emotion engine using API calls and database queries.

[0300] Input: Parsed relevant information

[0301] Output: Sending data to AI systems and emotion engines

[0302] Step 5:

[0303] The AI ​​system and emotion engine generate custom designs, using neural networks to generate design ideas and emotion data as feedback to evaluate multiple design candidates.

[0304] Input: related information, emotion data

[0305] Output: Generated custom design proposal

[0306] Step 6:

[0307] The server transfers the generated design proposal to the user's device, and returns the generated design proposal to the device as an HTTP response.

[0308] Input: Generated custom design proposal

[0309] Output: Sending the design to the user's device

[0310] Step 7:

[0311] The device displays the design proposal to the user and accepts customization. Specifically, the design proposal is displayed on the screen, providing a preview function, and the user can customize it by adjusting colors, editing text, etc.

[0312] Input: Custom design idea

[0313] Output: User-customized design proposal

[0314] Step 8:

[0315] The user decides on the final design and the device sends it to the server. When the user clicks the confirm button, the device sends the final design data to the server via an HTTP request.

[0316] Input: User-customized design proposal

[0317] Output: Finalized design data

[0318] Step 9:

[0319] The server sends the final design to the 3D printer and starts production. The server sends the final design data to the 3D printer via a dedicated API or communication protocol.

[0320] Input: Finalized design data

[0321] Output: Send design data to a 3D printer

[0322] Step 10:

[0323] The 3D printer produces the product based on the design. The 3D printer produces the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0324] Input: Finalized design data

[0325] Output: Manufactured goods

[0326] Step 11:

[0327] The 3D printer completes the product and then a quality inspection is carried out, specifically, checking the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are reported.

[0328] Input: Manufactured goods

[0329] Output: Quality inspection result (pass / fail)

[0330] Step 12:

[0331] The server receives the quality inspection results and initiates the shipping process. For products that pass the inspection, the server initiates the shipping process and notifies the user of the shipping status information in real time.

[0332] Input: Quality inspection result (pass)

[0333] Output: Shipping process and status notification

[0334] Step 13:

[0335] The delivery service delivers the product to the user. The order is completed when the delivery service delivers the product to the user.

[0336] Input:Shipping procedure

[0337] Output: Product delivery completed to user

[0338] (Application example 2)

[0339] 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."

[0340] Conventional systems for providing custom-made products have the problem of being unable to provide sufficient advanced personalization based on the user's individual emotions and preferences. It is also difficult to reflect the user's emotional changes in real time during the product design generation and manufacturing process. This reduces the quality of the user experience. Furthermore, the lack of interactive communication with the user, such as presenting design proposals and proposing revisions through dialogue, can lead to low user satisfaction.

[0341] 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.

[0342] In this invention, the server includes an input device for a user to specify a custom-made product; a processing device for receiving the data input by the server and generating a custom design through an AI system; an information provision device for presenting the generated design proposals to the user; an interface device for the user to modify and confirm the final design; a control device for transmitting the final design data to a 3D printer and instructing production; a manufacturing device for producing the user-specified custom-made product using the 3D printer; a quality inspection device for inspecting the quality of the completed manufactured product; a delivery device for delivering the manufactured product that passes the quality inspection to the user; an emotion analysis device for acquiring user emotion data using smart glasses and analyzing the emotion data; and an emotion engine for generating an optimal custom design based on the analyzed emotion data. This enables advanced personalization based on the user's emotions and preferences, allowing product designs and manufacturing to be generated and reflected in real time to reflect the user's emotional changes. Furthermore, interactive communication improves the quality of the user experience and enables the provision of highly satisfying services.

[0343] "User" means an individual or legal entity ordering a custom-made product.

[0344] "Input means" refers to a device or interface that allows a user to input information and requests regarding a custom-made product.

[0345] "Server" means a computer system that receives input data from users and processes and manages the data.

[0346] "Processing means" refers to a device or program that has the functionality to allow the server to receive input data and generate a custom design through the AI ​​system.

[0347] The "AI system" is a system that utilizes artificial intelligence to generate optimal custom designs based on past order data, trend information, and user preferences.

[0348] The "information providing means" refers to a display or notification device that presents custom design proposals to the user.

[0349] "Interface means" refers to devices or software that allow the user to confirm and modify the generated design proposals and finalize the design.

[0350] "Control means" refers to a device or program that has the function of sending final design data from the server to the 3D printer and instructing manufacturing.

[0351] "Manufacturing means" refers to the equipment and process that uses a 3D printer to manufacture the custom-made product specified by the user.

[0352] "Quality inspection means" refers to devices and functions for inspecting the quality of manufactured products.

[0353] "Delivery means" refers to a logistics system for delivering manufactured products that have passed quality inspection to users.

[0354] "Smart glasses" are wearable devices that use built-in cameras and sensors to acquire and analyze the user's emotional data.

[0355] "Emotion analysis means" refers to a device or program that has the function of analyzing emotion data acquired from smart glasses or the like.

[0356] The "emotion engine" is a software module that generates optimal custom designs for users based on analyzed emotional data.

[0357] This invention provides a system that allows users to order custom-made products based on emotional data. The system analyzes the user's input data and emotional data, generates an optimal custom design, and then manufactures and delivers it. A specific embodiment of the system is described below.

[0358] Main components of the system

[0359] 1. Input Method

[0360] Users can specify custom-made products using smart glasses or a terminal, inputting information such as product category, design theme, desired color, and text.

[0361] 2. Server

[0362] The server receives the data and emotion data entered by the user, extracts past order data, trend information, and user preferences stored in a database, and passes this data to the AI ​​system and emotion engine to generate a custom design.

[0363] 3. AI Systems

[0364] The AI ​​system analyzes large amounts of data (e.g., 3D printer data, trend information, and user preference data) to generate optimal custom designs. The emotion engine selects and recommends designs based specifically on the user's emotional data.

[0365] 4. Smart Glasses and Emotion Analysis Methods

[0366] A user wears the smart glasses, and the camera captures the user's face and facial expressions. The emotion analysis means analyzes the captured image data and generates emotion data of the user. This data is then sent to the server.

[0367] 5. Means of providing information

[0368] The server transfers the design proposals generated by the AI ​​system and emotion engine to the user's device, which displays the generated design proposals to the user and provides a preview function.

[0369] 6. Interface Methods

[0370] Users can view the generated design proposals through their devices and customize them as needed. The emotion engine analyzes emotion data in real time and suggests optimal revisions to the user.

[0371] 7. Control Measures

[0372] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request, which then sends the final design data to the 3D printer to begin the manufacturing process.

[0373] 8. Manufacturing methods (3D printers) and quality inspection methods

[0374] The 3D printer manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically. After the product is completed, a quality inspection is carried out and only products that pass are shipped.

[0375] 9. Delivery method

[0376] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[0377] Specific examples

[0378] Examples of applications using smart glasses include the following processes:

[0379] 1. Store staff wearing smart glasses capture customer emotional data in real time.

[0380] 2. The server receives the emotion data and the user's input data and generates the optimal custom design proposal.

[0381] 3. The generated design proposal is displayed on the smart glasses display, providing the customer with a preview.

[0382] 4. The customer reviews and modifies the design and makes the final decision.

[0383] 5. The final design data is sent to the server and the product is manufactured using a 3D printer.

[0384] 6. After quality inspection, products that pass are delivered to the customer.

[0385] Prompt Sentence Examples

[0386] "Use smart glasses to capture customer sentiment data and generate design proposals for custom-made products in real time. Present the design proposals to the customer, and after final confirmation, confirm the order."

[0387] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0388] Step 1:

[0389] The user uses a terminal to specify a custom-made product and input information such as product category, design theme, desired color, text, etc. This input data is collected by the interface of the smart glasses or terminal used by the user, and then sent to the server.

[0390] Step 2:

[0391] The camera in the smart glasses captures the user's face, and the emotion analysis means processes the image data to generate emotion data of the user. The emotion data includes the user's facial expressions and emotional state (e.g., joy, surprise). The emotion data is sent to a server.

[0392] Step 3:

[0393] The server receives input data and emotional data from users and combines it with past order data, trend information, and user preferences stored in a database, creating the foundational data for the AI ​​system to generate optimal custom designs.

[0394] Step 4:

[0395] The server provides basic data to the AI ​​system and emotion engine and instructs them to generate custom designs. The AI ​​system generates design candidates based on past data and user preferences, and the emotion engine optimizes the design proposals based on the emotion data. The generated custom design proposals are returned to the server.

[0396] Step 5:

[0397] The server transfers the generated custom design proposal to the user's device, which displays the design proposal on its display, providing a preview function for the user, and providing an interface for the user to review the design proposal and customize it as needed.

[0398] Step 6:

[0399] The user uses the device to revise the design proposal and confirm the final design. The emotion engine analyzes the emotion data in real time and suggests the optimal revisions to the user. The finalised design data is sent to the server.

[0400] Step 7:

[0401] The server sends the finalized design data to the 3D printer, starting the manufacturing process. The 3D printer produces the custom-made product based on the design data. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0402] Step 8:

[0403] After the customized product is completed, the quality inspection means checks the product's appearance, dimensions, durability, etc. Only products that pass the quality inspection are shipped. The server manages the quality inspection results and initiates the shipping procedures for products that pass the inspection.

[0404] Step 9:

[0405] The server processes the delivery process and notifies the user of delivery status information in real time. Finally, the product is delivered to the user by the delivery service.

[0406] Through the above processing steps, users can quickly receive high-quality custom-made products based on their own emotions and preferences.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] [Second embodiment]

[0411] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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."

[0423] The present invention provides a system that allows users to easily create custom-made products. This system includes many components, such as an input means for users to specify products according to their preferences, a processing means for receiving the input data from a server and generating custom designs through an AI system, and an information providing means for presenting the generated design proposals to the user.

[0424] The main steps of the system are as follows: First, the user uses a terminal to specify a custom-made product, inputting information such as the product category, design theme, desired color, and text. The terminal reads the input data and sends it to the server.

[0425] The server then receives the user's request data and extracts relevant information stored in a database (past order data, trend information, user preferences), which is then passed to the AI ​​system to generate a custom design.

[0426] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. During this process, it builds and evaluates design prototypes, creating multiple candidates. The resulting design proposals are then sent back to the server, where they are transferred to the user's device.

[0427] The device displays the generated design proposal to the user, providing a preview. The user can review the design proposal and customize it if necessary (for example, by adjusting colors or editing text). Once the user has finalized the design, the device sends that information to the server and confirms the manufacturing request.

[0428] The server then sends the final design data to the 3D printer's control system, which then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and any necessary adjustments are made automatically.

[0429] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc., and only products that pass this inspection are shipped.

[0430] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time. Finally, the delivery service delivers the product to the user.

[0431] As a concrete example, when a user orders a custom-made smartphone case, the following process takes place: First, the user inputs their preferred color and design theme using their device and sends it to the server. The server passes the data to the AI ​​system, which generates an optimized design proposal. The user reviews and adjusts the proposal and confirms the manufacturing request. The server then sends the final design to a 3D printer, which produces the product. Once the smartphone case passes quality inspection, it is delivered to the user via a shipping method.

[0432] The system of the present invention allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[0433] The processing flow will be explained below.

[0434] Step 1:

[0435] A user accesses the system's homepage using a terminal and enters the necessary information into an input form to request the manufacture of a custom-made product, such as specifying the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text to be inserted (e.g., name or message).

[0436] Step 2:

[0437] The terminal reads the information input by the user, generates formatted request data, and transmits it to the server.

[0438] Step 3:

[0439] The server receives the request data and extracts relevant information stored in the database (past order data, trend information, user preference data).

[0440] Step 4:

[0441] The server passes the extracted data to an AI system, which then instructs it to generate a custom design.

[0442] Step 5:

[0443] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates multiple candidates to generate optimal designs.

[0444] Step 6:

[0445] The server receives the design proposals generated by the AI ​​system and transfers them to the user's device.

[0446] Step 7:

[0447] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[0448] Step 8:

[0449] The user decides on the final design and presses the confirmation button to confirm the manufacturing request.

[0450] Step 9:

[0451] The terminal sends the final design data to the server and confirms the manufacturing request.

[0452] Step 10:

[0453] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[0454] Step 11:

[0455] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0456] Step 12:

[0457] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[0458] Step 13:

[0459] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[0460] Step 14:

[0461] The delivery service delivers the product that has passed the quality inspection to the user, who then receives the delivered product and confirms that the custom-made product is complete.

[0462] Example 1

[0463] 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."

[0464] Today's market demands systems that allow users to order custom-made products tailored to their preferences. However, existing systems often involve complicated processes, from design creation to manufacturing, quality inspection, and delivery. Furthermore, it is often impossible to check and adjust progress in real time during this process. This results in a poor user experience and ultimately makes it difficult to quickly deliver high-quality custom-made products.

[0465] 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.

[0466] In this invention, the server includes input means for a user to specify a custom-made product, processing means for receiving the data input by the server and generating a custom design through an AI system, information provision means for presenting the generated design proposals to the user, interface means for the user to modify and confirm the final design, control means for transmitting the final design data to a manufacturing device by the server and instructing manufacturing, manufacturing means for manufacturing the custom-made product specified by the user by the manufacturing device, quality inspection means for inspecting the quality of the completed manufactured product, delivery means for delivering manufactured products that pass the quality inspection to the user, monitoring means for performing real-time monitoring and adjustment during the manufacturing process, reporting means for notifying the server of the results of the quality inspection, and notification means for notifying the user of the delivery status in real time, thereby enabling users to receive custom-made products tailored to their preferences quickly and with high quality.

[0467] The "input means" is an interface device that allows the user to input information about the custom-made product (product category, design theme, color, text, etc.).

[0468] "Processing means" refers to a device that passes data received by the server from the input means to the AI ​​system and performs the data processing required to generate a custom design.

[0469] The "information providing means" is a display device that presents the generated custom design to the user so that the user can check the design.

[0470] "Interface means" refers to an interactive editing device that allows a user to modify and finalize the generated custom design.

[0471] The "control means" is a device that allows the server to send the final design data to the manufacturing equipment and instruct and manage the manufacturing process.

[0472] "Manufacturing means" refers to a manufacturing device that actually manufactures a custom-made product based on the final design data.

[0473] "Quality inspection means" refers to equipment for inspecting the quality of finished manufactured products, such as their appearance, dimensions, and durability.

[0474] The "delivery means" is a physical distribution device for delivering manufactured products that have passed the quality inspection to users.

[0475] "Monitoring means" means a device for monitoring progress and quality in real time during the manufacturing process and making adjustments as necessary.

[0476] The "reporting means" is a communication device for notifying the server of the results of the quality inspection.

[0477] The "notification means" is a communication device for notifying the user of the delivery status in real time.

[0478] The "AI system" is a system that uses artificial intelligence to analyze past order data, trend information, and user preference data to generate optimal custom designs.

[0479] "Manufacturing Equipment" refers to 3D printers and other machinery used to manufacture custom products.

[0480] The present invention relates to a system that allows users to easily manufacture customized products. The system comprises an input means for users to specify products based on their preferences, a processing means for receiving the input data from a server and generating a custom design through an AI system, and an information provision means for presenting the generated design proposals to the user. The system also includes an interface means for users to modify and finalize the final design, a control means for transmitting the final design data from the server to a manufacturing device and issuing manufacturing instructions, a manufacturing means for manufacturing the user-specified customized product using the manufacturing device, a quality inspection means for inspecting the quality of the completed manufactured product, a delivery means for delivering manufactured products that pass the quality inspection to the user, a monitoring means for monitoring and adjusting the manufacturing process in real time, a reporting means for notifying the server of the quality inspection results, and a notification means for notifying the user of the delivery status in real time.

[0481] Specifically, the process begins with the user specifying a custom product using a terminal. For example, the user uses a smartphone to access the custom order page through a specialized application or web browser. Here, the user enters details such as product category, design theme, desired color, and text. The terminal receives this data, validates it in real time, and then transmits it to the server using the secure HTTPS protocol.

[0482] The server temporarily stores the data received from the user in a database and extracts relevant information based on past order data, trend information, and user preferences. This data is passed to the AI ​​system, which instructs it to generate a custom design. The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate the optimal custom design. During this process, multiple design prototypes are created and each is evaluated. The generated design proposals are sent back to the server, which then transfers them to the user's device.

[0483] The device displays the generated design proposal to the user, allowing the user to preview it. The user can then check the displayed proposal, adjust colors and edit text as necessary, and confirm the final design. The device then sends this information back to the server to confirm the manufacturing request.

[0484] The server then sends the final design data to the 3D printer's control system, converting it into a format the 3D printer can understand (e.g., an STL file). The 3D printer then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and automatically adjusted to ensure quality is always maintained.

[0485] Once a product is completed, it undergoes a quality inspection. This inspection includes appearance, dimensions, durability, etc., and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. The shipping status is notified to the user in real time, and a final notification is sent to the user when delivery is complete.

[0486] Examples:

[0487] Below is a specific example where a user orders a custom smartphone case.

[0488] Prompt statement:

[0489] "In a scenario where a user is ordering a custom smartphone case, please generate design proposals for the following case: color blue, design theme marine, and custom text 'ocean'."

[0490] When this prompt is input into the generative AI model, the model generates design proposals for smartphone cases based on the specified requirements, which are then used in subsequent processes.

[0491] This system allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[0492] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0493] Step 1:

[0494] The user specifies the custom-made product using the device. In this step, the user accesses the custom order page through a dedicated app or web browser. The information entered includes the product category (e.g., smartphone case), design theme (e.g., marine), desired color (e.g., blue), and text (e.g., "ocean"). The device temporarily stores the data entered by the user. Input: Information about the custom-made product from the user. Output: Stored user data.

[0495] Step 2:

[0496] The terminal validates the entered data in real time. Once validation is complete, it sends the data to the server using the HTTPS protocol, where the data integrity and format are checked. Input: Custom product data entered by the user. Output: User data sent to the server.

[0497] Step 3:

[0498] The server receives the input data and temporarily stores it in a database. It then extracts past order data, trend information, and user preference data from the database. The server integrates this data and prepares it to be passed to the AI ​​system. Input: User data sent from the terminal. Output: Integrated data to be passed to the AI ​​system.

[0499] Step 4:

[0500] The AI ​​system analyzes large amounts of 3D printer data, trend analysis, and user preference data based on data provided by the server. It builds multiple design prototypes, evaluates each candidate, and generates the optimal custom design proposal. Input: Data passed from the server. Output: Generated custom design proposal.

[0501] Step 5:

[0502] The server checks the design proposal received from the AI ​​system and transfers it to the user's device. The transferred data includes image files of the generated design proposal and related information. Input: Design proposal from the AI ​​system. Output: Design proposal data sent to the user's device.

[0503] Step 6:

[0504] The device displays the generated design proposals to the user. The user selects one of the multiple design proposals displayed and adjusts colors and edits text as necessary. Once the user has decided on the final design, the device sends that information to the server. Input: Design proposal sent from the server. Output: Final design data confirmed by the user is sent to the server.

[0505] Step 7:

[0506] The server sends the received final design data to the manufacturing equipment. The data is converted into a format that the 3D printer can understand (e.g., STL file). At this time, instructions for the manufacturing equipment are also sent. Input: Final design data from the terminal. Output: Design data and manufacturing instructions sent to the manufacturing equipment.

[0507] Step 8:

[0508] The manufacturing equipment produces products based on the design data received from the server. The manufacturing process is monitored in real time and automatically adjusted as needed. Once manufacturing is complete, the product is sent for quality inspection. Input: Design data from the server. Output: Manufactured product.

[0509] Step 9:

[0510] The quality inspection means inspects manufactured products. Inspection items include appearance, dimensions, durability, etc. If the product passes the quality inspection, the results are reported to the server. Input: Manufactured product. Output: Report of quality inspection results to the server.

[0511] Step 10:

[0512] The server receives the quality inspection results and starts the delivery procedure. Delivery status information is notified to the user in real time via a dedicated app or email. Input: Information on products that passed the quality inspection. Output: Start of delivery procedure, notification of delivery status to the user.

[0513] Step 11:

[0514] The delivery vehicle receives products ready for shipment and delivers them to the address specified by the user. Once delivery is complete, a final notification is sent to the user. Input: Products ready for shipment. Output: Products delivered to the user, notification of delivery completion sent.

[0515] (Application example 1)

[0516] 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."

[0517] Conventional custom-made product systems have had issues with making it difficult for users to easily design products according to their preferences, lacking real-time design previews and the ability to track the delivery status of manufactured products. Furthermore, users were limited to online ordering, unable to quickly order and receive custom-made products directly at the store.

[0518] 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.

[0519] In this invention, the server includes an input means for a user to specify a custom-made product, a processing means for receiving the data input by the server and generating a custom design through an AI system, a means for previewing the generated design proposal in real time through a smartphone application or tablet application, and a means for displaying the delivery status of the manufactured product in real time, thereby enabling users to easily design a custom-made product in a store and check the manufacturing and receiving status on the spot.

[0520] The "input means by which the user specifies a custom-made product" refers to a device or interface for inputting customization information such as the product category, design theme, color, and text desired by the user.

[0521] The "AI system" is a system that includes artificial intelligence algorithms that generate and optimize optimal custom designs based on past order data, trend information, and user preferences.

[0522] The "server" is a central control device that receives data from users, sends the data to the AI ​​system, manages the generated design proposals, sends the final design data to the 3D printer, manages quality inspection results, and handles delivery procedures.

[0523] "Information providing means" refers to a display or application that receives design proposals generated from the server and presents them to the user.

[0524] The "interface means" is an operation interface that allows the user to check the generated design proposal, make corrections, and make a final decision.

[0525] "Control means" refers to a system that sends the final design data to the 3D printer via a server and instructs the production of custom-made products.

[0526] "Manufacturing means" refers to the equipment used to actually manufacture custom-made products specified by the user using a 3D printer.

[0527] "Quality inspection means" refers to equipment or processes for inspecting the appearance, dimensions, durability, etc. of completed manufactured goods to determine whether they conform to quality standards.

[0528] "Delivery means" refers to the delivery system and procedures for delivering manufactured products that have passed quality inspection to users.

[0529] The "real-time preview means" is a display or application that allows the user to instantly view the generated design proposal and check and modify it.

[0530] "Means for displaying delivery status in real time" refers to a system or application that instantly updates the delivery progress of manufactured products and notifies the user.

[0531] This invention provides a system that allows users to easily manufacture customized products, and includes the following components. First, an input means is required for users to specify the customized products. This input means is implemented in a device such as a smartphone application or tablet application, and is used by users to input information such as product category, design theme, color, and text.

[0532] The server then receives input data from the user and has a processing means to generate a custom design through an AI system. The server optimizes the design based on past order data, trend information, and the user's preferences. Possible software to use is Python or Flask. For example, it generates a prompt message such as, "If the user specifies a smartphone case as the product category, selects modern as the design theme, and enters "Mr. A" in blue text, please generate the optimal design."

[0533] The generated design proposal is sent from the server to the terminal and is previewed in real time by the user via the information provision means. The user can check the generated design proposal using the terminal and make corrections as necessary. This is the interface means, and it is used by the user to finalize the design.

[0534] The server receives the final design data and has a control means for sending it to the 3D printer. The 3D printer has a manufacturing means for producing custom-made products specified by the user based on this design. Once manufactured, the products are inspected for appearance, dimensions, durability, etc. by a quality inspection means, and only products that pass the quality standards are shipped.

[0535] Furthermore, manufactured products that pass quality inspection are delivered to the user via a delivery method. The server also manages delivery procedures and has a function to display the delivery status on the terminal in real time, allowing the user to track the product from dispatch to arrival in real time.

[0536] This system allows users to intuitively create custom-made product designs in-store just as they would online, and check the status of their delivery on the spot, enabling faster and higher-quality custom-made products to be delivered.

[0537] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0538] Step 1:

[0539] The user uses the terminal to specify the custom-made product.

[0540] In this step, the user operates the smartphone application or tablet application to input the product category, design theme, color, text, etc. The input data is converted into a data format on the terminal and sent to the server.

[0541] Input: Product information (category, theme, color, text)

[0542] Output: Formatted data (data sent to the server)

[0543] Step 2:

[0544] The server receives the data entered by the user.

[0545] The server analyzes the data received from the device and stores it in a database, then converts the data into prompt format required for the generative AI model.

[0546] Input: Data from user (product information)

[0547] Output: Prompt sentence to the generative AI model

[0548] Step 3:

[0549] The server sends prompts to the generative AI model to generate a custom design.

[0550] The server sends the prompt text to the generative AI model, which then analyzes past order data, trend information, and user preference data to generate custom design proposals, which are then sent back to the server.

[0551] Input: Prompt sentence for generative AI model

[0552] Output: Custom design proposal

[0553] Step 4:

[0554] The server sends the generated design proposal to the terminal and provides a preview to the user.

[0555] The server sends the generated design proposal to the user's device, which displays it in real time, and the user can check the displayed design proposal.

[0556] Input: Custom design idea

[0557] Output: Preview your design on your device

[0558] Step 5:

[0559] The user modifies and finalizes the design proposal.

[0560] The user can view the previewed design and make any necessary corrections. Once the corrections are complete, the user confirms the final design and sends the data to the server.

[0561] Input: Modified design information

[0562] Output: Finalized design data (data sent to server)

[0563] Step 6:

[0564] The server sends the final design data to the 3D printer to begin production.

[0565] The server receives the finalized design data and sends it to the 3D printer, which then produces the custom-made product based on the received design data.

[0566] Input: Finalized design data

[0567] Output: Manufacturing instructions for the 3D printer

[0568] Step 7:

[0569] 3D printers produce custom-made products and perform quality inspections.

[0570] The 3D printer uses the received design data to manufacture the product, and once manufactured, the product undergoes quality inspection to check its appearance, dimensions, durability, etc.

[0571] Input: Manufacturing instructions to the 3D printer

[0572] Output: Finished products and quality inspection results

[0573] Step 8:

[0574] The server receives the quality inspection results and starts the delivery procedure.

[0575] Products that pass the quality inspection are sent to the server's management system for delivery, which displays the delivery status on the terminal in real time.

[0576] Input: Quality Inspection Results

[0577] Output: Delivery status (notification to terminal)

[0578] 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.

[0579] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[0580] The main components of the system include an input means for users to specify custom-made products, a server, an AI system, an emotion engine, an information provision means, an interface means, a 3D printer, a quality inspection means, and a delivery means.

[0581] First, a user accesses the system's homepage using a terminal and requests the design of a custom-made product. At this time, the user inputs information such as the product category, design theme, desired color, and text. Sensors (e.g., a facial recognition camera and a voice analysis microphone) are also used to recognize the user's emotions. The terminal then transmits the input data and emotional data to the server.

[0582] The server then receives the request data and emotion data, extracts relevant information stored in a database (past order data, trend information, user preferences), and passes this data to the AI ​​system and emotion engine to generate a custom design.

[0583] The AI ​​system and emotion engine analyzes large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. This process involves building design prototypes and evaluating multiple candidates. The emotion engine selects and recommends designs based specifically on the user's emotion data.

[0584] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[0585] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[0586] After the 3D printer completes the product, a quality inspection is carried out. The inspection includes the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[0587] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[0588] The system of the present invention allows users to quickly and with high quality receive personalized custom-made products based on their preferences and emotions. The introduction of the emotion engine further improves the user experience and enables the provision of highly satisfying services.

[0589] The processing flow will be explained below.

[0590] Step 1:

[0591] The user accesses the system's homepage using a device and enters the necessary information into an input form to specify a custom-made product. Specifically, the user enters the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text insertion (e.g., name or message). In addition, emotion data is also obtained using a facial recognition camera and a voice analysis microphone.

[0592] Step 2:

[0593] The terminal reads the product information and emotion data input by the user, generates formatted request data, and transmits it to the server.

[0594] Step 3:

[0595] The server receives the request data and emotion data and extracts related information (past order data, trend information, user preference data) stored in a database.

[0596] Step 4:

[0597] The server passes the extracted data to an AI system and emotion engine, instructing it to generate a custom design.

[0598] Step 5:

[0599] The AI ​​system and emotion engine analyze large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates and generates multiple design candidates. The emotion engine selects and recommends designs based on the user's emotion data.

[0600] Step 6:

[0601] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device.

[0602] Step 7:

[0603] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[0604] Step 8:

[0605] The emotion engine analyzes the emotion data in real time and suggests optimal modifications based on the user's customizations. The user can then review the suggestions and make a final decision.

[0606] Step 9:

[0607] The user finalizes the design and presses the confirmation button for the manufacturing request.

[0608] Step 10:

[0609] The terminal sends the final design data to the server and confirms the manufacturing request.

[0610] Step 11:

[0611] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[0612] Step 12:

[0613] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0614] Step 13:

[0615] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[0616] Step 14:

[0617] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[0618] Step 15:

[0619] The delivery service delivers the product that has passed quality inspection to the user, who then accepts the delivery and confirms that the custom-made product was manufactured as expected.

[0620] Through these steps, users can easily order personalized custom-made products based on their preferences and emotions and receive them quickly and with high quality.

[0621] Example 2

[0622] 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."

[0623] Conventional custom-made product systems have difficulty generating personalized designs based on the user's emotions and preferences, and have been unable to provide products that satisfy the user. Furthermore, improving the efficiency of the manufacturing process and ensuring quality remain significant challenges. The present invention aims to solve these problems by providing a system that utilizes user emotion data to provide optimal custom designs and realize a high-quality manufacturing process.

[0624] 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.

[0625] In this invention, the server includes a means for the terminal to send input data and emotion data to the server, a means for the server to analyze the received data by extracting relevant information from a database and send it to the AI ​​system and emotion engine, and a means for the AI ​​system and emotion engine to generate a custom design, thereby enabling the generation of personalized custom designs based on the user's emotion data and a high-quality manufacturing process.

[0626] The "input means" is a means by which a user inputs information about the design of a custom-made product into the system.

[0627] A "terminal" is a device through which a user inputs information and transmits and receives data to and from a server.

[0628] A "server" is a computer system that processes data received from users and manages the design generation and manufacturing process.

[0629] A "database" is an information system for storing past order data, trend information, and user preference data.

[0630] An "AI system" is a system that uses artificial intelligence technology to analyze large amounts of data and generate optimal custom designs.

[0631] An "emotion engine" is a system that analyzes user emotional data and makes designs and recommendations based on the results.

[0632] "Information provision means" refers to the means for presenting design proposals generated by the AI ​​system and emotion engine to the user.

[0633] "Interface means" refers to the means by which a user can modify and finalize the generated design proposals.

[0634] "Control means" refers to the means by which the server sends the final design data to the 3D printer and instructs manufacturing.

[0635] A "3D printer" is a three-dimensional printing machine that manufactures products based on design data received from a server.

[0636] "Manufacturing means" refers to a means for manufacturing a custom-made product specified by a user using a 3D printer.

[0637] "Quality inspection means" refers to means for inspecting the quality of completed manufactured goods.

[0638] "Delivery means" refers to a means for delivering manufactured products that have passed the quality inspection to the user.

[0639] The "management means" is a means by which the server receives the quality inspection results and starts the delivery procedure.

[0640] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[0641] Hardware and software used

[0642] Terminal (device used by the user, e.g. smartphone, PC)

[0643] server

[0644] AI systems (e.g. TensorFlow, PyTorch)

[0645] Emotion engines (e.g., Affectiva)

[0646] Interface means (e.g., web browser, specific application)

[0647] 3D printer (e.g. Ultimaker S5)

[0648] Quality inspection methods (e.g., AI-enabled vision systems)

[0649] Shipping method (e.g. FedEx, UPS)

[0650] Explanation of the program's processing steps

[0651] User input and data submission

[0652] A user accesses the system's homepage using a terminal and requests a custom-made product design. The user inputs information such as product category, design theme, desired color, and text. Emotional data is also collected using a facial recognition camera and a voice analysis microphone. The terminal then transmits the input data and emotional data to the server.

[0653] Receiving and analyzing data

[0654] The server extracts the received request data and emotion data, as well as past order data, trend information, and user preference data stored in a database. The server passes this data to the AI ​​system and emotion engine, instructing it to generate a custom design.

[0655] Generate a custom design

[0656] The AI ​​system and emotion engine analyze large amounts of trend information, 3D printer data, user preference data, and emotion data to generate optimal custom designs. Multiple design candidates are constructed and evaluated. The emotion engine selects and recommends designs based on the user's emotion data.

[0657] Presentation of design proposals

[0658] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[0659] Final design confirmation and manufacturing

[0660] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[0661] Quality Inspection and Delivery

[0662] After the 3D printer completes the product, a quality inspection is carried out. The product's appearance, dimensions, durability, etc. are inspected, and only products that pass are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[0663] Specific examples

[0664] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[0665] Prompt sentence for generative AI model

[0666] "If a user wants to create a custom smartphone case, they first access their device. They enter information such as product category, design theme, desired color, and text, and then collect sentiment data."

[0667] "You send your input data and emotion data to our server, which then uses our AI system and emotion engine to generate custom design ideas."

[0668] "The generated design proposals are displayed to the user, who can then customize them as needed. The final design data is then sent to the server, and the manufacturing process begins."

[0669] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0670] Step 1:

[0671] The user initiates an order for a custom-made product on the device. Specifically, the user accesses the system's homepage and inputs information such as the product category, design theme, desired color, and text. The user also acquires emotional data using a facial recognition camera and a voice analysis microphone. The input data and emotional data are stored on the device.

[0672] Input: User input information (product category, design theme, desired color, text), emotional data

[0673] Output: A set of input data and emotion data

[0674] Step 2:

[0675] The device sends the input data and emotion data to the server. The device POSTs the dataset to the server as an HTTP request.

[0676] Input: A set of input data and emotion data

[0677] Output: Send data to the server

[0678] Step 3:

[0679] The server receives the request data and emotion data, analyzes the received data, and extracts past order data, trend information, and user preference data stored in a database.

[0680] Input: Request data and emotion data received by the server

[0681] Output: Analyzed related information (past order data, trend information, user preference data)

[0682] Step 4:

[0683] The server extracts the relevant information and passes the data to the AI ​​system and emotion engine using API calls and database queries.

[0684] Input: Parsed relevant information

[0685] Output: Sending data to AI systems and emotion engines

[0686] Step 5:

[0687] The AI ​​system and emotion engine generate custom designs, using neural networks to generate design ideas and emotion data as feedback to evaluate multiple design candidates.

[0688] Input: related information, emotion data

[0689] Output: Generated custom design proposal

[0690] Step 6:

[0691] The server transfers the generated design proposal to the user's device, and returns the generated design proposal to the device as an HTTP response.

[0692] Input: Generated custom design proposal

[0693] Output: Sending the design to the user's device

[0694] Step 7:

[0695] The device displays the design proposal to the user and accepts customization. Specifically, the design proposal is displayed on the screen, providing a preview function, and the user can customize it by adjusting colors, editing text, etc.

[0696] Input: Custom design idea

[0697] Output: User-customized design proposal

[0698] Step 8:

[0699] The user decides on the final design and the device sends it to the server. When the user clicks the confirm button, the device sends the final design data to the server via an HTTP request.

[0700] Input: User-customized design proposal

[0701] Output: Finalized design data

[0702] Step 9:

[0703] The server sends the final design to the 3D printer and starts production. The server sends the final design data to the 3D printer via a dedicated API or communication protocol.

[0704] Input: Finalized design data

[0705] Output: Send design data to a 3D printer

[0706] Step 10:

[0707] The 3D printer produces the product based on the design. The 3D printer produces the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0708] Input: Finalized design data

[0709] Output: Manufactured goods

[0710] Step 11:

[0711] The 3D printer completes the product and then a quality inspection is carried out, specifically, checking the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are reported.

[0712] Input: Manufactured goods

[0713] Output: Quality inspection result (pass / fail)

[0714] Step 12:

[0715] The server receives the quality inspection results and initiates the shipping process. For products that pass the inspection, the server initiates the shipping process and notifies the user of the shipping status information in real time.

[0716] Input: Quality inspection result (pass)

[0717] Output: Shipping process and status notification

[0718] Step 13:

[0719] The delivery service delivers the product to the user. The order is completed when the delivery service delivers the product to the user.

[0720] Input:Shipping procedure

[0721] Output: Product delivery completed to user

[0722] (Application example 2)

[0723] 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."

[0724] Conventional systems for providing custom-made products have the problem of being unable to provide sufficient advanced personalization based on the user's individual emotions and preferences. It is also difficult to reflect the user's emotional changes in real time during the product design generation and manufacturing process. This reduces the quality of the user experience. Furthermore, the lack of interactive communication with the user, such as presenting design proposals and proposing revisions through dialogue, can lead to low user satisfaction.

[0725] 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.

[0726] In this invention, the server includes an input device for a user to specify a custom-made product; a processing device for receiving the data input by the server and generating a custom design through an AI system; an information provision device for presenting the generated design proposals to the user; an interface device for the user to modify and confirm the final design; a control device for transmitting the final design data to a 3D printer and instructing production; a manufacturing device for producing the user-specified custom-made product using the 3D printer; a quality inspection device for inspecting the quality of the completed manufactured product; a delivery device for delivering the manufactured product that passes the quality inspection to the user; an emotion analysis device for acquiring user emotion data using smart glasses and analyzing the emotion data; and an emotion engine for generating an optimal custom design based on the analyzed emotion data. This enables advanced personalization based on the user's emotions and preferences, allowing product designs and manufacturing to be generated and reflected in real time to reflect the user's emotional changes. Furthermore, interactive communication improves the quality of the user experience and enables the provision of highly satisfying services.

[0727] "User" means an individual or legal entity ordering a custom-made product.

[0728] "Input means" refers to a device or interface that allows a user to input information and requests regarding a custom-made product.

[0729] "Server" means a computer system that receives input data from users and processes and manages the data.

[0730] "Processing means" refers to a device or program that has the functionality to allow the server to receive input data and generate a custom design through the AI ​​system.

[0731] The "AI system" is a system that utilizes artificial intelligence to generate optimal custom designs based on past order data, trend information, and user preferences.

[0732] The "information providing means" refers to a display or notification device that presents custom design proposals to the user.

[0733] "Interface means" refers to devices or software that allow the user to confirm and modify the generated design proposals and finalize the design.

[0734] "Control means" refers to a device or program that has the function of sending final design data from the server to the 3D printer and instructing manufacturing.

[0735] "Manufacturing means" refers to the equipment and process that uses a 3D printer to manufacture the custom-made product specified by the user.

[0736] "Quality inspection means" refers to devices and functions for inspecting the quality of manufactured products.

[0737] "Delivery means" refers to a logistics system for delivering manufactured products that have passed quality inspection to users.

[0738] "Smart glasses" are wearable devices that use built-in cameras and sensors to acquire and analyze the user's emotional data.

[0739] "Emotion analysis means" refers to a device or program that has the function of analyzing emotion data acquired from smart glasses or the like.

[0740] The "emotion engine" is a software module that generates optimal custom designs for users based on analyzed emotional data.

[0741] This invention provides a system that allows users to order custom-made products based on emotional data. The system analyzes the user's input data and emotional data, generates an optimal custom design, and then manufactures and delivers it. A specific embodiment of the system is described below.

[0742] Main components of the system

[0743] 1. Input Method

[0744] Users can specify custom-made products using smart glasses or a terminal, inputting information such as product category, design theme, desired color, and text.

[0745] 2. Server

[0746] The server receives the data and emotion data entered by the user, extracts past order data, trend information, and user preferences stored in a database, and passes this data to the AI ​​system and emotion engine to generate a custom design.

[0747] 3. AI Systems

[0748] The AI ​​system analyzes large amounts of data (e.g., 3D printer data, trend information, and user preference data) to generate optimal custom designs. The emotion engine selects and recommends designs based specifically on the user's emotional data.

[0749] 4. Smart Glasses and Emotion Analysis Methods

[0750] A user wears the smart glasses, and the camera captures the user's face and facial expressions. The emotion analysis means analyzes the captured image data and generates emotion data of the user. This data is then sent to the server.

[0751] 5. Means of providing information

[0752] The server transfers the design proposals generated by the AI ​​system and emotion engine to the user's device, which displays the generated design proposals to the user and provides a preview function.

[0753] 6. Interface Methods

[0754] Users can view the generated design proposals through their devices and customize them as needed. The emotion engine analyzes emotion data in real time and suggests optimal revisions to the user.

[0755] 7. Control Measures

[0756] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request, which then sends the final design data to the 3D printer to begin the manufacturing process.

[0757] 8. Manufacturing methods (3D printers) and quality inspection methods

[0758] The 3D printer manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically. After the product is completed, a quality inspection is carried out and only products that pass are shipped.

[0759] 9. Delivery method

[0760] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[0761] Specific examples

[0762] Examples of applications using smart glasses include the following processes:

[0763] 1. Store staff wearing smart glasses capture customer emotional data in real time.

[0764] 2. The server receives the emotion data and the user's input data and generates the optimal custom design proposal.

[0765] 3. The generated design proposal is displayed on the smart glasses display, providing the customer with a preview.

[0766] 4. The customer reviews and modifies the design and makes the final decision.

[0767] 5. The final design data is sent to the server and the product is manufactured using a 3D printer.

[0768] 6. After quality inspection, products that pass are delivered to the customer.

[0769] Prompt Sentence Examples

[0770] "Use smart glasses to capture customer sentiment data and generate design proposals for custom-made products in real time. Present the design proposals to the customer, and after final confirmation, confirm the order."

[0771] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0772] Step 1:

[0773] The user uses a terminal to specify a custom-made product and input information such as product category, design theme, desired color, text, etc. This input data is collected by the interface of the smart glasses or terminal used by the user, and then sent to the server.

[0774] Step 2:

[0775] The camera in the smart glasses captures the user's face, and the emotion analysis means processes the image data to generate emotion data of the user. The emotion data includes the user's facial expressions and emotional state (e.g., joy, surprise). The emotion data is sent to a server.

[0776] Step 3:

[0777] The server receives input data and emotional data from users and combines it with past order data, trend information, and user preferences stored in a database, creating the foundational data for the AI ​​system to generate optimal custom designs.

[0778] Step 4:

[0779] The server provides basic data to the AI ​​system and emotion engine and instructs them to generate custom designs. The AI ​​system generates design candidates based on past data and user preferences, and the emotion engine optimizes the design proposals based on the emotion data. The generated custom design proposals are returned to the server.

[0780] Step 5:

[0781] The server transfers the generated custom design proposal to the user's device, which displays the design proposal on its display, providing a preview function for the user, and providing an interface for the user to review the design proposal and customize it as needed.

[0782] Step 6:

[0783] The user uses the device to revise the design proposal and confirm the final design. The emotion engine analyzes the emotion data in real time and suggests the optimal revisions to the user. The finalised design data is sent to the server.

[0784] Step 7:

[0785] The server sends the finalized design data to the 3D printer, starting the manufacturing process. The 3D printer produces the custom-made product based on the design data. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0786] Step 8:

[0787] After the customized product is completed, the quality inspection means checks the product's appearance, dimensions, durability, etc. Only products that pass the quality inspection are shipped. The server manages the quality inspection results and initiates the shipping procedures for products that pass the inspection.

[0788] Step 9:

[0789] The server processes the delivery process and notifies the user of delivery status information in real time. Finally, the product is delivered to the user by the delivery service.

[0790] Through the above processing steps, users can quickly receive high-quality custom-made products based on their own emotions and preferences.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] [Third embodiment]

[0795] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0796] 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.

[0797] 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).

[0798] 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.

[0799] 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.

[0800] 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).

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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."

[0807] The present invention provides a system that allows users to easily create custom-made products. This system includes many components, such as an input means for users to specify products according to their preferences, a processing means for receiving the input data from a server and generating custom designs through an AI system, and an information providing means for presenting the generated design proposals to the user.

[0808] The main steps of the system are as follows: First, the user uses a terminal to specify a custom-made product, inputting information such as the product category, design theme, desired color, and text. The terminal reads the input data and sends it to the server.

[0809] The server then receives the user's request data and extracts relevant information stored in a database (past order data, trend information, user preferences), which is then passed to the AI ​​system to generate a custom design.

[0810] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. During this process, it builds and evaluates design prototypes, creating multiple candidates. The resulting design proposals are then sent back to the server, where they are transferred to the user's device.

[0811] The device displays the generated design proposal to the user, providing a preview. The user can review the design proposal and customize it if necessary (for example, by adjusting colors or editing text). Once the user has finalized the design, the device sends that information to the server and confirms the manufacturing request.

[0812] The server then sends the final design data to the 3D printer's control system, which then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and any necessary adjustments are made automatically.

[0813] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc., and only products that pass this inspection are shipped.

[0814] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time. Finally, the delivery service delivers the product to the user.

[0815] As a concrete example, when a user orders a custom-made smartphone case, the following process takes place: First, the user inputs their preferred color and design theme using their device and sends it to the server. The server passes the data to the AI ​​system, which generates an optimized design proposal. The user reviews and adjusts the proposal and confirms the manufacturing request. The server then sends the final design to a 3D printer, which produces the product. Once the smartphone case passes quality inspection, it is delivered to the user via a shipping method.

[0816] The system of the present invention allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[0817] The processing flow will be explained below.

[0818] Step 1:

[0819] A user accesses the system's homepage using a terminal and enters the necessary information into an input form to request the manufacture of a custom-made product, such as specifying the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text to be inserted (e.g., name or message).

[0820] Step 2:

[0821] The terminal reads the information input by the user, generates formatted request data, and transmits it to the server.

[0822] Step 3:

[0823] The server receives the request data and extracts relevant information stored in the database (past order data, trend information, user preference data).

[0824] Step 4:

[0825] The server passes the extracted data to an AI system, which then instructs it to generate a custom design.

[0826] Step 5:

[0827] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates multiple candidates to generate optimal designs.

[0828] Step 6:

[0829] The server receives the design proposals generated by the AI ​​system and transfers them to the user's device.

[0830] Step 7:

[0831] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[0832] Step 8:

[0833] The user decides on the final design and presses the confirmation button to confirm the manufacturing request.

[0834] Step 9:

[0835] The terminal sends the final design data to the server and confirms the manufacturing request.

[0836] Step 10:

[0837] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[0838] Step 11:

[0839] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0840] Step 12:

[0841] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[0842] Step 13:

[0843] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[0844] Step 14:

[0845] The delivery service delivers the product that has passed the quality inspection to the user, who then receives the delivered product and confirms that the custom-made product is complete.

[0846] Example 1

[0847] 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."

[0848] Today's market demands systems that allow users to order custom-made products tailored to their preferences. However, existing systems often involve complicated processes, from design creation to manufacturing, quality inspection, and delivery. Furthermore, it is often impossible to check and adjust progress in real time during this process. This results in a poor user experience and ultimately makes it difficult to quickly deliver high-quality custom-made products.

[0849] 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.

[0850] In this invention, the server includes input means for a user to specify a custom-made product, processing means for receiving the data input by the server and generating a custom design through an AI system, information provision means for presenting the generated design proposals to the user, interface means for the user to modify and confirm the final design, control means for transmitting the final design data to a manufacturing device by the server and instructing manufacturing, manufacturing means for manufacturing the custom-made product specified by the user by the manufacturing device, quality inspection means for inspecting the quality of the completed manufactured product, delivery means for delivering manufactured products that pass the quality inspection to the user, monitoring means for performing real-time monitoring and adjustment during the manufacturing process, reporting means for notifying the server of the results of the quality inspection, and notification means for notifying the user of the delivery status in real time, thereby enabling users to receive custom-made products tailored to their preferences quickly and with high quality.

[0851] The "input means" is an interface device that allows the user to input information about the custom-made product (product category, design theme, color, text, etc.).

[0852] "Processing means" refers to a device that passes data received by the server from the input means to the AI ​​system and performs the data processing required to generate a custom design.

[0853] The "information providing means" is a display device that presents the generated custom design to the user so that the user can check the design.

[0854] "Interface means" refers to an interactive editing device that allows a user to modify and finalize the generated custom design.

[0855] The "control means" is a device that allows the server to send the final design data to the manufacturing equipment and instruct and manage the manufacturing process.

[0856] "Manufacturing means" refers to a manufacturing device that actually manufactures a custom-made product based on the final design data.

[0857] "Quality inspection means" refers to equipment for inspecting the quality of finished manufactured products, such as their appearance, dimensions, and durability.

[0858] The "delivery means" is a physical distribution device for delivering manufactured products that have passed the quality inspection to users.

[0859] "Monitoring means" means a device for monitoring progress and quality in real time during the manufacturing process and making adjustments as necessary.

[0860] The "reporting means" is a communication device for notifying the server of the results of the quality inspection.

[0861] The "notification means" is a communication device for notifying the user of the delivery status in real time.

[0862] The "AI system" is a system that uses artificial intelligence to analyze past order data, trend information, and user preference data to generate optimal custom designs.

[0863] "Manufacturing Equipment" refers to 3D printers and other machinery used to manufacture custom products.

[0864] The present invention relates to a system that allows users to easily manufacture customized products. The system comprises an input means for users to specify products based on their preferences, a processing means for receiving the input data from a server and generating a custom design through an AI system, and an information provision means for presenting the generated design proposals to the user. The system also includes an interface means for users to modify and finalize the final design, a control means for transmitting the final design data from the server to a manufacturing device and issuing manufacturing instructions, a manufacturing means for manufacturing the user-specified customized product using the manufacturing device, a quality inspection means for inspecting the quality of the completed manufactured product, a delivery means for delivering manufactured products that pass the quality inspection to the user, a monitoring means for monitoring and adjusting the manufacturing process in real time, a reporting means for notifying the server of the quality inspection results, and a notification means for notifying the user of the delivery status in real time.

[0865] Specifically, the process begins with the user specifying a custom product using a terminal. For example, the user uses a smartphone to access the custom order page through a specialized application or web browser. Here, the user enters details such as product category, design theme, desired color, and text. The terminal receives this data, validates it in real time, and then transmits it to the server using the secure HTTPS protocol.

[0866] The server temporarily stores the data received from the user in a database and extracts relevant information based on past order data, trend information, and user preferences. This data is passed to the AI ​​system, which instructs it to generate a custom design. The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate the optimal custom design. During this process, multiple design prototypes are created and each is evaluated. The generated design proposals are sent back to the server, which then transfers them to the user's device.

[0867] The device displays the generated design proposal to the user, allowing the user to preview it. The user can then check the displayed proposal, adjust colors and edit text as necessary, and confirm the final design. The device then sends this information back to the server to confirm the manufacturing request.

[0868] The server then sends the final design data to the 3D printer's control system, converting it into a format the 3D printer can understand (e.g., an STL file). The 3D printer then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and automatically adjusted to ensure quality is always maintained.

[0869] Once a product is completed, it undergoes a quality inspection. This inspection includes appearance, dimensions, durability, etc., and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. The shipping status is notified to the user in real time, and a final notification is sent to the user when delivery is complete.

[0870] Examples:

[0871] Below is a specific example where a user orders a custom smartphone case.

[0872] Prompt statement:

[0873] "In a scenario where a user is ordering a custom smartphone case, please generate design proposals for the following case: color blue, design theme marine, and custom text 'ocean'."

[0874] When this prompt is input into the generative AI model, the model generates design proposals for smartphone cases based on the specified requirements, which are then used in subsequent processes.

[0875] This system allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[0876] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0877] Step 1:

[0878] The user specifies the custom-made product using the device. In this step, the user accesses the custom order page through a dedicated app or web browser. The information entered includes the product category (e.g., smartphone case), design theme (e.g., marine), desired color (e.g., blue), and text (e.g., "ocean"). The device temporarily stores the data entered by the user. Input: Information about the custom-made product from the user. Output: Stored user data.

[0879] Step 2:

[0880] The terminal validates the entered data in real time. Once validation is complete, it sends the data to the server using the HTTPS protocol, where the data integrity and format are checked. Input: Custom product data entered by the user. Output: User data sent to the server.

[0881] Step 3:

[0882] The server receives the input data and temporarily stores it in a database. It then extracts past order data, trend information, and user preference data from the database. The server integrates this data and prepares it to be passed to the AI ​​system. Input: User data sent from the terminal. Output: Integrated data to be passed to the AI ​​system.

[0883] Step 4:

[0884] The AI ​​system analyzes large amounts of 3D printer data, trend analysis, and user preference data based on data provided by the server. It builds multiple design prototypes, evaluates each candidate, and generates the optimal custom design proposal. Input: Data passed from the server. Output: Generated custom design proposal.

[0885] Step 5:

[0886] The server checks the design proposal received from the AI ​​system and transfers it to the user's device. The transferred data includes image files of the generated design proposal and related information. Input: Design proposal from the AI ​​system. Output: Design proposal data sent to the user's device.

[0887] Step 6:

[0888] The device displays the generated design proposals to the user. The user selects one of the multiple design proposals displayed and adjusts colors and edits text as necessary. Once the user has decided on the final design, the device sends that information to the server. Input: Design proposal sent from the server. Output: Final design data confirmed by the user is sent to the server.

[0889] Step 7:

[0890] The server sends the received final design data to the manufacturing equipment. The data is converted into a format that the 3D printer can understand (e.g., STL file). At this time, instructions for the manufacturing equipment are also sent. Input: Final design data from the terminal. Output: Design data and manufacturing instructions sent to the manufacturing equipment.

[0891] Step 8:

[0892] The manufacturing equipment produces products based on the design data received from the server. The manufacturing process is monitored in real time and automatically adjusted as needed. Once manufacturing is complete, the product is sent for quality inspection. Input: Design data from the server. Output: Manufactured product.

[0893] Step 9:

[0894] The quality inspection means inspects manufactured products. Inspection items include appearance, dimensions, durability, etc. If the product passes the quality inspection, the results are reported to the server. Input: Manufactured product. Output: Report of quality inspection results to the server.

[0895] Step 10:

[0896] The server receives the quality inspection results and starts the delivery procedure. Delivery status information is notified to the user in real time via a dedicated app or email. Input: Information on products that passed the quality inspection. Output: Start of delivery procedure, notification of delivery status to the user.

[0897] Step 11:

[0898] The delivery vehicle receives products ready for shipment and delivers them to the address specified by the user. Once delivery is complete, a final notification is sent to the user. Input: Products ready for shipment. Output: Products delivered to the user, notification of delivery completion sent.

[0899] (Application example 1)

[0900] 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."

[0901] Conventional custom-made product systems have had issues with making it difficult for users to easily design products according to their preferences, lacking real-time design previews and the ability to track the delivery status of manufactured products. Furthermore, users were limited to online ordering, unable to quickly order and receive custom-made products directly at the store.

[0902] 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.

[0903] In this invention, the server includes an input means for a user to specify a custom-made product, a processing means for receiving the data input by the server and generating a custom design through an AI system, a means for previewing the generated design proposal in real time through a smartphone application or tablet application, and a means for displaying the delivery status of the manufactured product in real time, thereby enabling users to easily design a custom-made product in a store and check the manufacturing and receiving status on the spot.

[0904] The "input means by which the user specifies a custom-made product" refers to a device or interface for inputting customization information such as the product category, design theme, color, and text desired by the user.

[0905] The "AI system" is a system that includes artificial intelligence algorithms that generate and optimize optimal custom designs based on past order data, trend information, and user preferences.

[0906] The "server" is a central control device that receives data from users, sends the data to the AI ​​system, manages the generated design proposals, sends the final design data to the 3D printer, manages quality inspection results, and handles delivery procedures.

[0907] "Information providing means" refers to a display or application that receives design proposals generated from the server and presents them to the user.

[0908] The "interface means" is an operation interface that allows the user to check the generated design proposal, make corrections, and make a final decision.

[0909] "Control means" refers to a system that sends the final design data to the 3D printer via a server and instructs the production of custom-made products.

[0910] "Manufacturing means" refers to the equipment used to actually manufacture custom-made products specified by the user using a 3D printer.

[0911] "Quality inspection means" refers to equipment or processes for inspecting the appearance, dimensions, durability, etc. of completed manufactured goods to determine whether they conform to quality standards.

[0912] "Delivery means" refers to the delivery system and procedures for delivering manufactured products that have passed quality inspection to users.

[0913] The "real-time preview means" is a display or application that allows the user to instantly view the generated design proposal and check and modify it.

[0914] "Means for displaying delivery status in real time" refers to a system or application that instantly updates the delivery progress of manufactured products and notifies the user.

[0915] This invention provides a system that allows users to easily manufacture customized products, and includes the following components. First, an input means is required for users to specify the customized products. This input means is implemented in a device such as a smartphone application or tablet application, and is used by users to input information such as product category, design theme, color, and text.

[0916] The server then receives input data from the user and has a processing means to generate a custom design through an AI system. The server optimizes the design based on past order data, trend information, and the user's preferences. Possible software to use is Python or Flask. For example, it generates a prompt message such as, "If the user specifies a smartphone case as the product category, selects modern as the design theme, and enters "Mr. A" in blue text, please generate the optimal design."

[0917] The generated design proposal is sent from the server to the terminal and is previewed in real time by the user via the information provision means. The user can check the generated design proposal using the terminal and make corrections as necessary. This is the interface means, and it is used by the user to finalize the design.

[0918] The server receives the final design data and has a control means for sending it to the 3D printer. The 3D printer has a manufacturing means for producing custom-made products specified by the user based on this design. Once manufactured, the products are inspected for appearance, dimensions, durability, etc. by a quality inspection means, and only products that pass the quality standards are shipped.

[0919] Furthermore, manufactured products that pass quality inspection are delivered to the user via a delivery method. The server also manages delivery procedures and has a function to display the delivery status on the terminal in real time, allowing the user to track the product from dispatch to arrival in real time.

[0920] This system allows users to intuitively create custom-made product designs in-store just as they would online, and check the status of their delivery on the spot, enabling faster and higher-quality custom-made products to be delivered.

[0921] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0922] Step 1:

[0923] The user uses the terminal to specify the custom-made product.

[0924] In this step, the user operates the smartphone application or tablet application to input the product category, design theme, color, text, etc. The input data is converted into a data format on the terminal and sent to the server.

[0925] Input: Product information (category, theme, color, text)

[0926] Output: Formatted data (data sent to the server)

[0927] Step 2:

[0928] The server receives the data entered by the user.

[0929] The server analyzes the data received from the device and stores it in a database, then converts the data into prompt format required for the generative AI model.

[0930] Input: Data from user (product information)

[0931] Output: Prompt sentence to the generative AI model

[0932] Step 3:

[0933] The server sends prompts to the generative AI model to generate a custom design.

[0934] The server sends the prompt text to the generative AI model, which then analyzes past order data, trend information, and user preference data to generate custom design proposals, which are then sent back to the server.

[0935] Input: Prompt sentence for generative AI model

[0936] Output: Custom design proposal

[0937] Step 4:

[0938] The server sends the generated design proposal to the terminal and provides a preview to the user.

[0939] The server sends the generated design proposal to the user's device, which displays it in real time, and the user can check the displayed design proposal.

[0940] Input: Custom design idea

[0941] Output: Preview your design on your device

[0942] Step 5:

[0943] The user modifies and finalizes the design proposal.

[0944] The user can view the previewed design and make any necessary corrections. Once the corrections are complete, the user confirms the final design and sends the data to the server.

[0945] Input: Modified design information

[0946] Output: Finalized design data (data sent to server)

[0947] Step 6:

[0948] The server sends the final design data to the 3D printer to begin production.

[0949] The server receives the finalized design data and sends it to the 3D printer, which then produces the custom-made product based on the received design data.

[0950] Input: Finalized design data

[0951] Output: Manufacturing instructions for the 3D printer

[0952] Step 7:

[0953] 3D printers produce custom-made products and perform quality inspections.

[0954] The 3D printer uses the received design data to manufacture the product, and once manufactured, the product undergoes quality inspection to check its appearance, dimensions, durability, etc.

[0955] Input: Manufacturing instructions to the 3D printer

[0956] Output: Finished products and quality inspection results

[0957] Step 8:

[0958] The server receives the quality inspection results and starts the delivery procedure.

[0959] Products that pass the quality inspection are sent to the server's management system for delivery, which displays the delivery status on the terminal in real time.

[0960] Input: Quality Inspection Results

[0961] Output: Delivery status (notification to terminal)

[0962] 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.

[0963] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[0964] The main components of the system include an input means for users to specify custom-made products, a server, an AI system, an emotion engine, an information provision means, an interface means, a 3D printer, a quality inspection means, and a delivery means.

[0965] First, a user accesses the system's homepage using a terminal and requests the design of a custom-made product. At this time, the user inputs information such as the product category, design theme, desired color, and text. Sensors (e.g., a facial recognition camera and a voice analysis microphone) are also used to recognize the user's emotions. The terminal then transmits the input data and emotional data to the server.

[0966] The server then receives the request data and emotion data, extracts relevant information stored in a database (past order data, trend information, user preferences), and passes this data to the AI ​​system and emotion engine to generate a custom design.

[0967] The AI ​​system and emotion engine analyzes large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. This process involves building design prototypes and evaluating multiple candidates. The emotion engine selects and recommends designs based specifically on the user's emotion data.

[0968] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[0969] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[0970] After the 3D printer completes the product, a quality inspection is carried out. The inspection includes the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[0971] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[0972] The system of the present invention allows users to quickly and with high quality receive personalized custom-made products based on their preferences and emotions. The introduction of the emotion engine further improves the user experience and enables the provision of highly satisfying services.

[0973] The processing flow will be explained below.

[0974] Step 1:

[0975] The user accesses the system's homepage using a device and enters the necessary information into an input form to specify a custom-made product. Specifically, the user enters the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text insertion (e.g., name or message). In addition, emotion data is also obtained using a facial recognition camera and a voice analysis microphone.

[0976] Step 2:

[0977] The terminal reads the product information and emotion data input by the user, generates formatted request data, and transmits it to the server.

[0978] Step 3:

[0979] The server receives the request data and emotion data and extracts related information (past order data, trend information, user preference data) stored in a database.

[0980] Step 4:

[0981] The server passes the extracted data to an AI system and emotion engine, instructing it to generate a custom design.

[0982] Step 5:

[0983] The AI ​​system and emotion engine analyze large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates and generates multiple design candidates. The emotion engine selects and recommends designs based on the user's emotion data.

[0984] Step 6:

[0985] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device.

[0986] Step 7:

[0987] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[0988] Step 8:

[0989] The emotion engine analyzes the emotion data in real time and suggests optimal modifications based on the user's customizations. The user can then review the suggestions and make a final decision.

[0990] Step 9:

[0991] The user finalizes the design and presses the confirmation button for the manufacturing request.

[0992] Step 10:

[0993] The terminal sends the final design data to the server and confirms the manufacturing request.

[0994] Step 11:

[0995] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[0996] Step 12:

[0997] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[0998] Step 13:

[0999] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[1000] Step 14:

[1001] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[1002] Step 15:

[1003] The delivery service delivers the product that has passed quality inspection to the user, who then accepts the delivery and confirms that the custom-made product was manufactured as expected.

[1004] Through these steps, users can easily order personalized custom-made products based on their preferences and emotions and receive them quickly and with high quality.

[1005] Example 2

[1006] 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."

[1007] Conventional custom-made product systems have difficulty generating personalized designs based on the user's emotions and preferences, and have been unable to provide products that satisfy the user. Furthermore, improving the efficiency of the manufacturing process and ensuring quality remain significant challenges. The present invention aims to solve these problems by providing a system that utilizes user emotion data to provide optimal custom designs and realize a high-quality manufacturing process.

[1008] 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.

[1009] In this invention, the server includes a means for the terminal to send input data and emotion data to the server, a means for the server to analyze the received data by extracting relevant information from a database and send it to the AI ​​system and emotion engine, and a means for the AI ​​system and emotion engine to generate a custom design, thereby enabling the generation of personalized custom designs based on the user's emotion data and a high-quality manufacturing process.

[1010] The "input means" is a means by which a user inputs information about the design of a custom-made product into the system.

[1011] A "terminal" is a device through which a user inputs information and transmits and receives data to and from a server.

[1012] A "server" is a computer system that processes data received from users and manages the design generation and manufacturing process.

[1013] A "database" is an information system for storing past order data, trend information, and user preference data.

[1014] An "AI system" is a system that uses artificial intelligence technology to analyze large amounts of data and generate optimal custom designs.

[1015] An "emotion engine" is a system that analyzes user emotional data and makes designs and recommendations based on the results.

[1016] "Information provision means" refers to the means for presenting design proposals generated by the AI ​​system and emotion engine to the user.

[1017] "Interface means" refers to the means by which a user can modify and finalize the generated design proposals.

[1018] "Control means" refers to the means by which the server sends the final design data to the 3D printer and instructs manufacturing.

[1019] A "3D printer" is a three-dimensional printing machine that manufactures products based on design data received from a server.

[1020] "Manufacturing means" refers to a means for manufacturing a custom-made product specified by a user using a 3D printer.

[1021] "Quality inspection means" refers to means for inspecting the quality of completed manufactured goods.

[1022] "Delivery means" refers to a means for delivering manufactured products that have passed the quality inspection to the user.

[1023] The "management means" is a means by which the server receives the quality inspection results and starts the delivery procedure.

[1024] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[1025] Hardware and software used

[1026] Terminal (device used by the user, e.g. smartphone, PC)

[1027] server

[1028] AI systems (e.g. TensorFlow, PyTorch)

[1029] Emotion engines (e.g., Affectiva)

[1030] Interface means (e.g., web browser, specific application)

[1031] 3D printer (e.g. Ultimaker S5)

[1032] Quality inspection methods (e.g., AI-enabled vision systems)

[1033] Shipping method (e.g. FedEx, UPS)

[1034] Explanation of the program's processing steps

[1035] User input and data submission

[1036] A user accesses the system's homepage using a terminal and requests a custom-made product design. The user inputs information such as product category, design theme, desired color, and text. Emotional data is also collected using a facial recognition camera and a voice analysis microphone. The terminal then transmits the input data and emotional data to the server.

[1037] Receiving and analyzing data

[1038] The server extracts the received request data and emotion data, as well as past order data, trend information, and user preference data stored in a database. The server passes this data to the AI ​​system and emotion engine, instructing it to generate a custom design.

[1039] Generate a custom design

[1040] The AI ​​system and emotion engine analyze large amounts of trend information, 3D printer data, user preference data, and emotion data to generate optimal custom designs. Multiple design candidates are constructed and evaluated. The emotion engine selects and recommends designs based on the user's emotion data.

[1041] Presentation of design proposals

[1042] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[1043] Final design confirmation and manufacturing

[1044] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[1045] Quality Inspection and Delivery

[1046] After the 3D printer completes the product, a quality inspection is carried out. The product's appearance, dimensions, durability, etc. are inspected, and only products that pass are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[1047] Specific examples

[1048] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[1049] Prompt sentence for generative AI model

[1050] "If a user wants to create a custom smartphone case, they first access their device. They enter information such as product category, design theme, desired color, and text, and then collect sentiment data."

[1051] "You send your input data and emotion data to our server, which then uses our AI system and emotion engine to generate custom design ideas."

[1052] "The generated design proposals are displayed to the user, who can then customize them as needed. The final design data is then sent to the server, and the manufacturing process begins."

[1053] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1054] Step 1:

[1055] The user initiates an order for a custom-made product on the device. Specifically, the user accesses the system's homepage and inputs information such as the product category, design theme, desired color, and text. The user also acquires emotional data using a facial recognition camera and a voice analysis microphone. The input data and emotional data are stored on the device.

[1056] Input: User input information (product category, design theme, desired color, text), emotional data

[1057] Output: A set of input data and emotion data

[1058] Step 2:

[1059] The device sends the input data and emotion data to the server. The device POSTs the dataset to the server as an HTTP request.

[1060] Input: A set of input data and emotion data

[1061] Output: Send data to the server

[1062] Step 3:

[1063] The server receives the request data and emotion data, analyzes the received data, and extracts past order data, trend information, and user preference data stored in a database.

[1064] Input: Request data and emotion data received by the server

[1065] Output: Analyzed related information (past order data, trend information, user preference data)

[1066] Step 4:

[1067] The server extracts the relevant information and passes the data to the AI ​​system and emotion engine using API calls and database queries.

[1068] Input: Parsed relevant information

[1069] Output: Sending data to AI systems and emotion engines

[1070] Step 5:

[1071] The AI ​​system and emotion engine generate custom designs, using neural networks to generate design ideas and emotion data as feedback to evaluate multiple design candidates.

[1072] Input: related information, emotion data

[1073] Output: Generated custom design proposal

[1074] Step 6:

[1075] The server transfers the generated design proposal to the user's device, and returns the generated design proposal to the device as an HTTP response.

[1076] Input: Generated custom design proposal

[1077] Output: Sending the design to the user's device

[1078] Step 7:

[1079] The device displays the design proposal to the user and accepts customization. Specifically, the design proposal is displayed on the screen, providing a preview function, and the user can customize it by adjusting colors, editing text, etc.

[1080] Input: Custom design idea

[1081] Output: User-customized design proposal

[1082] Step 8:

[1083] The user decides on the final design and the device sends it to the server. When the user clicks the confirm button, the device sends the final design data to the server via an HTTP request.

[1084] Input: User-customized design proposal

[1085] Output: Finalized design data

[1086] Step 9:

[1087] The server sends the final design to the 3D printer and starts production. The server sends the final design data to the 3D printer via a dedicated API or communication protocol.

[1088] Input: Finalized design data

[1089] Output: Send design data to a 3D printer

[1090] Step 10:

[1091] The 3D printer produces the product based on the design. The 3D printer produces the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[1092] Input: Finalized design data

[1093] Output: Manufactured goods

[1094] Step 11:

[1095] The 3D printer completes the product and then a quality inspection is carried out, specifically, checking the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are reported.

[1096] Input: Manufactured goods

[1097] Output: Quality inspection result (pass / fail)

[1098] Step 12:

[1099] The server receives the quality inspection results and initiates the shipping process. For products that pass the inspection, the server initiates the shipping process and notifies the user of the shipping status information in real time.

[1100] Input: Quality inspection result (pass)

[1101] Output: Shipping process and status notification

[1102] Step 13:

[1103] The delivery service delivers the product to the user. The order is completed when the delivery service delivers the product to the user.

[1104] Input:Shipping procedure

[1105] Output: Product delivery completed to user

[1106] (Application example 2)

[1107] 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."

[1108] Conventional systems for providing custom-made products have the problem of being unable to provide sufficient advanced personalization based on the user's individual emotions and preferences. It is also difficult to reflect the user's emotional changes in real time during the product design generation and manufacturing process. This reduces the quality of the user experience. Furthermore, the lack of interactive communication with the user, such as presenting design proposals and proposing revisions through dialogue, can lead to low user satisfaction.

[1109] 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.

[1110] In this invention, the server includes an input means for a user to specify a custom-made product; a processing means for receiving the data input by the server and generating a custom design through an AI system; an information provision means for presenting the generated design proposals to the user; an interface means for the user to modify and confirm the final design; a control means for transmitting the final design data to the 3D printer and instructing production; a manufacturing means for producing the user-specified custom-made product using the 3D printer; a quality inspection means for inspecting the quality of the completed manufactured product; a delivery means for delivering manufactured products that pass the quality inspection to the user; an emotion analysis means for acquiring user emotion data using smart glasses and analyzing the emotion data; and an emotion engine for generating optimal custom designs based on the analyzed emotion data. This enables advanced personalization based on the user's emotions and preferences, allowing product designs and manufacturing to be generated and reflected in real time to reflect the user's emotional changes. Furthermore, interactive communication improves the quality of the user experience and enables the provision of highly satisfying services.

[1111] "User" means an individual or legal entity ordering a custom-made product.

[1112] "Input means" refers to a device or interface that allows a user to input information and requests regarding a custom-made product.

[1113] "Server" means a computer system that receives input data from users and processes and manages the data.

[1114] "Processing means" refers to a device or program that has the functionality to allow the server to receive input data and generate a custom design through the AI ​​system.

[1115] The "AI system" is a system that utilizes artificial intelligence to generate optimal custom designs based on past order data, trend information, and user preferences.

[1116] The "information providing means" refers to a display or notification device that presents custom design proposals to the user.

[1117] "Interface means" refers to devices or software that allow the user to confirm and modify the generated design proposals and finalize the design.

[1118] "Control means" refers to a device or program that has the function of sending final design data from the server to the 3D printer and instructing manufacturing.

[1119] "Manufacturing means" refers to the equipment and process that uses a 3D printer to manufacture the custom-made product specified by the user.

[1120] "Quality inspection means" refers to devices and functions for inspecting the quality of manufactured products.

[1121] "Delivery means" refers to a logistics system for delivering manufactured products that have passed quality inspection to users.

[1122] "Smart glasses" are wearable devices that use built-in cameras and sensors to acquire and analyze the user's emotional data.

[1123] "Emotion analysis means" refers to a device or program that has the function of analyzing emotion data acquired from smart glasses or the like.

[1124] The "emotion engine" is a software module that generates optimal custom designs for users based on analyzed emotional data.

[1125] This invention provides a system that allows users to order custom-made products based on emotional data. The system analyzes the user's input data and emotional data, generates an optimal custom design, and then manufactures and delivers it. A specific embodiment of the system is described below.

[1126] Main components of the system

[1127] 1. Input Method

[1128] Users can specify custom-made products using smart glasses or a terminal, inputting information such as product category, design theme, desired color, and text.

[1129] 2. Server

[1130] The server receives the data and emotion data entered by the user, extracts past order data, trend information, and user preferences stored in a database, and passes this data to the AI ​​system and emotion engine to generate a custom design.

[1131] 3. AI Systems

[1132] The AI ​​system analyzes large amounts of data (e.g., 3D printer data, trend information, and user preference data) to generate optimal custom designs. The emotion engine selects and recommends designs based specifically on the user's emotional data.

[1133] 4. Smart Glasses and Emotion Analysis Methods

[1134] A user wears the smart glasses, and the camera captures the user's face and facial expressions. The emotion analysis means analyzes the captured image data and generates emotion data of the user. This data is then sent to the server.

[1135] 5. Means of providing information

[1136] The server transfers the design proposals generated by the AI ​​system and emotion engine to the user's device, which displays the generated design proposals to the user and provides a preview function.

[1137] 6. Interface Methods

[1138] Users can view the generated design proposals through their devices and customize them as needed. The emotion engine analyzes emotion data in real time and suggests optimal revisions to the user.

[1139] 7. Control Measures

[1140] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request, which then sends the final design data to the 3D printer to begin the manufacturing process.

[1141] 8. Manufacturing methods (3D printers) and quality inspection methods

[1142] The 3D printer manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically. After the product is completed, a quality inspection is carried out and only products that pass are shipped.

[1143] 9. Delivery method

[1144] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[1145] Specific examples

[1146] Examples of applications using smart glasses include the following processes:

[1147] 1. Store staff wearing smart glasses capture customer emotional data in real time.

[1148] 2. The server receives the emotion data and the user's input data and generates the optimal custom design proposal.

[1149] 3. The generated design proposal is displayed on the smart glasses display, providing the customer with a preview.

[1150] 4. The customer reviews and modifies the design and makes the final decision.

[1151] 5. The final design data is sent to the server and the product is manufactured using a 3D printer.

[1152] 6. After quality inspection, products that pass are delivered to the customer.

[1153] Prompt Sentence Examples

[1154] "Use smart glasses to capture customer sentiment data and generate design proposals for custom-made products in real time. Present the design proposals to the customer, and after final confirmation, confirm the order."

[1155] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1156] Step 1:

[1157] The user uses a terminal to specify a custom-made product and input information such as product category, design theme, desired color, text, etc. This input data is collected by the interface of the smart glasses or terminal used by the user, and then sent to the server.

[1158] Step 2:

[1159] The camera in the smart glasses captures the user's face, and the emotion analysis means processes the image data to generate emotion data of the user. The emotion data includes the user's facial expressions and emotional state (e.g., joy, surprise). The emotion data is sent to a server.

[1160] Step 3:

[1161] The server receives input data and emotional data from users and combines it with past order data, trend information, and user preferences stored in a database, creating the foundational data for the AI ​​system to generate optimal custom designs.

[1162] Step 4:

[1163] The server provides basic data to the AI ​​system and emotion engine and instructs them to generate custom designs. The AI ​​system generates design candidates based on past data and user preferences, and the emotion engine optimizes the design proposals based on the emotion data. The generated custom design proposals are returned to the server.

[1164] Step 5:

[1165] The server transfers the generated custom design proposal to the user's device, which displays the design proposal on its display, providing a preview function for the user, and providing an interface for the user to review the design proposal and customize it as needed.

[1166] Step 6:

[1167] The user uses the device to revise the design proposal and confirm the final design. The emotion engine analyzes the emotion data in real time and suggests the optimal revisions to the user. The finalised design data is sent to the server.

[1168] Step 7:

[1169] The server sends the finalized design data to the 3D printer, starting the manufacturing process. The 3D printer produces the custom-made product based on the design data. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[1170] Step 8:

[1171] After the customized product is completed, the quality inspection means checks the product's appearance, dimensions, durability, etc. Only products that pass the quality inspection are shipped. The server manages the quality inspection results and initiates the shipping procedures for products that pass the inspection.

[1172] Step 9:

[1173] The server processes the delivery process and notifies the user of delivery status information in real time. Finally, the product is delivered to the user by the delivery service.

[1174] Through the above processing steps, users can quickly receive high-quality custom-made products based on their own emotions and preferences.

[1175] 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.

[1176] 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.

[1177] 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.

[1178] [Fourth embodiment]

[1179] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1180] 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.

[1181] 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).

[1182] 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.

[1183] 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.

[1184] 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).

[1185] 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.

[1186] 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.

[1187] 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.

[1188] 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.

[1189] 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.

[1190] 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.

[1191] 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."

[1192] The present invention provides a system that allows users to easily create custom-made products. This system includes many components, such as an input means for users to specify products according to their preferences, a processing means for receiving the input data from a server and generating custom designs through an AI system, and an information providing means for presenting the generated design proposals to the user.

[1193] The main steps of the system are as follows: First, the user uses a terminal to specify a custom-made product, inputting information such as the product category, design theme, desired color, and text. The terminal reads the input data and sends it to the server.

[1194] The server then receives the user's request data and extracts relevant information stored in a database (past order data, trend information, user preferences), which is then passed to the AI ​​system to generate a custom design.

[1195] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. During this process, it builds and evaluates design prototypes, creating multiple candidates. The resulting design proposals are then sent back to the server, where they are transferred to the user's device.

[1196] The device displays the generated design proposal to the user, providing a preview. The user can review the design proposal and customize it if necessary (for example, by adjusting colors or editing text). Once the user has finalized the design, the device sends that information to the server and confirms the manufacturing request.

[1197] The server then sends the final design data to the 3D printer's control system, which then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and any necessary adjustments are made automatically.

[1198] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc., and only products that pass this inspection are shipped.

[1199] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time. Finally, the delivery service delivers the product to the user.

[1200] As a concrete example, when a user orders a custom-made smartphone case, the following process takes place: First, the user inputs their preferred color and design theme using their device and sends it to the server. The server passes the data to the AI ​​system, which generates an optimized design proposal. The user reviews and adjusts the proposal and confirms the manufacturing request. The server then sends the final design to a 3D printer, which produces the product. Once the smartphone case passes quality inspection, it is delivered to the user via a shipping method.

[1201] The system of the present invention allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[1202] The processing flow will be explained below.

[1203] Step 1:

[1204] A user accesses the system's homepage using a terminal and enters the necessary information into an input form to request the manufacture of a custom-made product, such as specifying the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text to be inserted (e.g., name or message).

[1205] Step 2:

[1206] The terminal reads the information input by the user, generates formatted request data, and transmits it to the server.

[1207] Step 3:

[1208] The server receives the request data and extracts relevant information stored in the database (past order data, trend information, user preference data).

[1209] Step 4:

[1210] The server passes the extracted data to an AI system, which then instructs it to generate a custom design.

[1211] Step 5:

[1212] The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates multiple candidates to generate optimal designs.

[1213] Step 6:

[1214] The server receives the design proposals generated by the AI ​​system and transfers them to the user's device.

[1215] Step 7:

[1216] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[1217] Step 8:

[1218] The user decides on the final design and presses the confirmation button to confirm the manufacturing request.

[1219] Step 9:

[1220] The terminal sends the final design data to the server and confirms the manufacturing request.

[1221] Step 10:

[1222] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[1223] Step 11:

[1224] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[1225] Step 12:

[1226] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[1227] Step 13:

[1228] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[1229] Step 14:

[1230] The delivery service delivers the product that has passed the quality inspection to the user, who then receives the delivered product and confirms that the custom-made product is complete.

[1231] Example 1

[1232] 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."

[1233] Today's market demands systems that allow users to order custom-made products tailored to their preferences. However, existing systems often involve complicated processes, from design creation to manufacturing, quality inspection, and delivery. Furthermore, it is often impossible to check and adjust progress in real time during this process. This results in a poor user experience and ultimately makes it difficult to quickly deliver high-quality custom-made products.

[1234] 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.

[1235] In this invention, the server includes input means for a user to specify a custom-made product, processing means for receiving the data input by the server and generating a custom design through an AI system, information provision means for presenting the generated design proposals to the user, interface means for the user to modify and confirm the final design, control means for transmitting the final design data to a manufacturing device by the server and instructing manufacturing, manufacturing means for manufacturing the custom-made product specified by the user by the manufacturing device, quality inspection means for inspecting the quality of the completed manufactured product, delivery means for delivering manufactured products that pass the quality inspection to the user, monitoring means for performing real-time monitoring and adjustment during the manufacturing process, reporting means for notifying the server of the results of the quality inspection, and notification means for notifying the user of the delivery status in real time, thereby enabling users to receive custom-made products tailored to their preferences quickly and with high quality.

[1236] The "input means" is an interface device that allows the user to input information about the custom-made product (product category, design theme, color, text, etc.).

[1237] "Processing means" refers to a device that passes data received by the server from the input means to the AI ​​system and performs the data processing required to generate a custom design.

[1238] The "information providing means" is a display device that presents the generated custom design to the user so that the user can check the design.

[1239] "Interface means" refers to an interactive editing device that allows a user to modify and finalize the generated custom design.

[1240] The "control means" is a device that allows the server to send the final design data to the manufacturing equipment and instruct and manage the manufacturing process.

[1241] "Manufacturing means" refers to a manufacturing device that actually manufactures a custom-made product based on the final design data.

[1242] "Quality inspection means" refers to equipment for inspecting the quality of finished manufactured products, such as their appearance, dimensions, and durability.

[1243] The "delivery means" is a physical distribution device for delivering manufactured products that have passed the quality inspection to users.

[1244] "Monitoring means" means a device for monitoring progress and quality in real time during the manufacturing process and making adjustments as necessary.

[1245] The "reporting means" is a communication device for notifying the server of the results of the quality inspection.

[1246] The "notification means" is a communication device for notifying the user of the delivery status in real time.

[1247] The "AI system" is a system that uses artificial intelligence to analyze past order data, trend information, and user preference data to generate optimal custom designs.

[1248] "Manufacturing Equipment" refers to 3D printers and other machinery used to manufacture custom products.

[1249] The present invention relates to a system that allows users to easily manufacture customized products. The system comprises an input means for users to specify products based on their preferences, a processing means for receiving the input data from a server and generating a custom design through an AI system, and an information provision means for presenting the generated design proposals to the user. The system also includes an interface means for users to modify and finalize the final design, a control means for transmitting the final design data from the server to a manufacturing device and issuing manufacturing instructions, a manufacturing means for manufacturing the user-specified customized product using the manufacturing device, a quality inspection means for inspecting the quality of the completed manufactured product, a delivery means for delivering manufactured products that pass the quality inspection to the user, a monitoring means for monitoring and adjusting the manufacturing process in real time, a reporting means for notifying the server of the quality inspection results, and a notification means for notifying the user of the delivery status in real time.

[1250] Specifically, the process begins with the user specifying a custom product using a terminal. For example, the user uses a smartphone to access the custom order page through a specialized application or web browser. Here, the user enters details such as product category, design theme, desired color, and text. The terminal receives this data, validates it in real time, and then transmits it to the server using the secure HTTPS protocol.

[1251] The server temporarily stores the data received from the user in a database and extracts relevant information based on past order data, trend information, and user preferences. This data is passed to the AI ​​system, which instructs it to generate a custom design. The AI ​​system analyzes large amounts of 3D printer data, trend information, and user preference data to generate the optimal custom design. During this process, multiple design prototypes are created and each is evaluated. The generated design proposals are sent back to the server, which then transfers them to the user's device.

[1252] The device displays the generated design proposal to the user, allowing the user to preview it. The user can then check the displayed proposal, adjust colors and edit text as necessary, and confirm the final design. The device then sends this information back to the server to confirm the manufacturing request.

[1253] The server then sends the final design data to the 3D printer's control system, converting it into a format the 3D printer can understand (e.g., an STL file). The 3D printer then produces the custom-made product specified by the user based on the design. The production process is monitored in real time and automatically adjusted to ensure quality is always maintained.

[1254] Once a product is completed, it undergoes a quality inspection. This inspection includes appearance, dimensions, durability, etc., and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. The shipping status is notified to the user in real time, and a final notification is sent to the user when delivery is complete.

[1255] Examples:

[1256] Below is a specific example where a user orders a custom smartphone case.

[1257] Prompt statement:

[1258] "In a scenario where a user is ordering a custom smartphone case, please generate design proposals for the following case: color blue, design theme marine, and custom text 'ocean'."

[1259] When this prompt is input into the generative AI model, the model generates design proposals for smartphone cases based on the specified requirements, which are then used in subsequent processes.

[1260] This system allows users to receive custom-made products tailored to their preferences quickly and with high quality.

[1261] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1262] Step 1:

[1263] The user specifies the custom-made product using the device. In this step, the user accesses the custom order page through a dedicated app or web browser. The information entered includes the product category (e.g., smartphone case), design theme (e.g., marine), desired color (e.g., blue), and text (e.g., "ocean"). The device temporarily stores the data entered by the user. Input: Information about the custom-made product from the user. Output: Stored user data.

[1264] Step 2:

[1265] The terminal validates the entered data in real time. Once validation is complete, it sends the data to the server using the HTTPS protocol, where the data integrity and format are checked. Input: Custom product data entered by the user. Output: User data sent to the server.

[1266] Step 3:

[1267] The server receives the input data and temporarily stores it in a database. It then extracts past order data, trend information, and user preference data from the database. The server integrates this data and prepares it to be passed to the AI ​​system. Input: User data sent from the terminal. Output: Integrated data to be passed to the AI ​​system.

[1268] Step 4:

[1269] The AI ​​system analyzes large amounts of 3D printer data, trend analysis, and user preference data based on data provided by the server. It builds multiple design prototypes, evaluates each candidate, and generates the optimal custom design proposal. Input: Data passed from the server. Output: Generated custom design proposal.

[1270] Step 5:

[1271] The server checks the design proposal received from the AI ​​system and transfers it to the user's device. The transferred data includes image files of the generated design proposal and related information. Input: Design proposal from the AI ​​system. Output: Design proposal data sent to the user's device.

[1272] Step 6:

[1273] The device displays the generated design proposals to the user. The user selects one of the multiple design proposals displayed and adjusts colors and edits text as necessary. Once the user has decided on the final design, the device sends that information to the server. Input: Design proposal sent from the server. Output: Final design data confirmed by the user is sent to the server.

[1274] Step 7:

[1275] The server sends the received final design data to the manufacturing equipment. The data is converted into a format that the 3D printer can understand (e.g., STL file). At this time, instructions for the manufacturing equipment are also sent. Input: Final design data from the terminal. Output: Design data and manufacturing instructions sent to the manufacturing equipment.

[1276] Step 8:

[1277] The manufacturing equipment produces products based on the design data received from the server. The manufacturing process is monitored in real time and automatically adjusted as needed. Once manufacturing is complete, the product is sent for quality inspection. Input: Design data from the server. Output: Manufactured product.

[1278] Step 9:

[1279] The quality inspection means inspects manufactured products. Inspection items include appearance, dimensions, durability, etc. If the product passes the quality inspection, the results are reported to the server. Input: Manufactured product. Output: Report of quality inspection results to the server.

[1280] Step 10:

[1281] The server receives the quality inspection results and starts the delivery procedure. Delivery status information is notified to the user in real time via a dedicated app or email. Input: Information on products that passed the quality inspection. Output: Start of delivery procedure, notification of delivery status to the user.

[1282] Step 11:

[1283] The delivery vehicle receives products ready for shipment and delivers them to the address specified by the user. Once delivery is complete, a final notification is sent to the user. Input: Products ready for shipment. Output: Products delivered to the user, notification of delivery completion sent.

[1284] (Application example 1)

[1285] 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."

[1286] Conventional custom-made product systems have had issues with making it difficult for users to easily design products according to their preferences, lacking real-time design previews and the ability to track the delivery status of manufactured products. Furthermore, users were limited to online ordering, unable to quickly order and receive custom-made products directly at the store.

[1287] 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.

[1288] In this invention, the server includes an input means for a user to specify a custom-made product, a processing means for receiving the data input by the server and generating a custom design through an AI system, a means for previewing the generated design proposal in real time through a smartphone application or tablet application, and a means for displaying the delivery status of the manufactured product in real time, thereby enabling users to easily design a custom-made product in a store and check the manufacturing and receiving status on the spot.

[1289] The "input means by which the user specifies a custom-made product" refers to a device or interface for inputting customization information such as the product category, design theme, color, and text desired by the user.

[1290] The "AI system" is a system that includes artificial intelligence algorithms that generate and optimize optimal custom designs based on past order data, trend information, and user preferences.

[1291] The "server" is a central control device that receives data from users, sends the data to the AI ​​system, manages the generated design proposals, sends the final design data to the 3D printer, manages quality inspection results, and handles delivery procedures.

[1292] "Information providing means" refers to a display or application that receives design proposals generated from the server and presents them to the user.

[1293] The "interface means" is an operation interface that allows the user to check the generated design proposal, make corrections, and make a final decision.

[1294] "Control means" refers to a system that sends the final design data to the 3D printer via a server and instructs the production of custom-made products.

[1295] "Manufacturing means" refers to the equipment used to actually manufacture custom-made products specified by the user using a 3D printer.

[1296] "Quality inspection means" refers to equipment or processes for inspecting the appearance, dimensions, durability, etc. of completed manufactured goods to determine whether they conform to quality standards.

[1297] "Delivery means" refers to the delivery system and procedures for delivering manufactured products that have passed quality inspection to users.

[1298] The "real-time preview means" is a display or application that allows the user to instantly view the generated design proposal and check and modify it.

[1299] "Means for displaying delivery status in real time" refers to a system or application that instantly updates the delivery progress of manufactured products and notifies the user.

[1300] This invention provides a system that allows users to easily manufacture customized products, and includes the following components. First, an input means is required for users to specify the customized products. This input means is implemented in a device such as a smartphone application or tablet application, and is used by users to input information such as product category, design theme, color, and text.

[1301] The server then receives input data from the user and has a processing means to generate a custom design through an AI system. The server optimizes the design based on past order data, trend information, and the user's preferences. Possible software to use is Python or Flask. For example, it generates a prompt message such as, "If the user specifies a smartphone case as the product category, selects modern as the design theme, and enters "Mr. A" in blue text, please generate the optimal design."

[1302] The generated design proposal is sent from the server to the terminal and is previewed in real time by the user via the information provision means. The user can check the generated design proposal using the terminal and make corrections as necessary. This is the interface means, and it is used by the user to finalize the design.

[1303] The server receives the final design data and has a control means for sending it to the 3D printer. The 3D printer has a manufacturing means for producing custom-made products specified by the user based on this design. Once manufactured, the products are inspected for appearance, dimensions, durability, etc. by a quality inspection means, and only products that pass the quality standards are shipped.

[1304] Furthermore, manufactured products that pass quality inspection are delivered to the user via a delivery method. The server also manages delivery procedures and has a function to display the delivery status on the terminal in real time, allowing the user to track the product from dispatch to arrival in real time.

[1305] This system allows users to intuitively create custom-made product designs in-store just as they would online, and check the status of their delivery on the spot, enabling faster and higher-quality custom-made products to be delivered.

[1306] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1307] Step 1:

[1308] The user uses the terminal to specify the custom-made product.

[1309] In this step, the user operates the smartphone application or tablet application to input the product category, design theme, color, text, etc. The input data is converted into a data format on the terminal and sent to the server.

[1310] Input: Product information (category, theme, color, text)

[1311] Output: Formatted data (data sent to the server)

[1312] Step 2:

[1313] The server receives the data entered by the user.

[1314] The server analyzes the data received from the device and stores it in a database, then converts the data into prompt format required for the generative AI model.

[1315] Input: Data from user (product information)

[1316] Output: Prompt sentence to the generative AI model

[1317] Step 3:

[1318] The server sends prompts to the generative AI model to generate a custom design.

[1319] The server sends the prompt text to the generative AI model, which then analyzes past order data, trend information, and user preference data to generate custom design proposals, which are then sent back to the server.

[1320] Input: Prompt sentence for generative AI model

[1321] Output: Custom design proposal

[1322] Step 4:

[1323] The server sends the generated design proposal to the terminal and provides a preview to the user.

[1324] The server sends the generated design proposal to the user's device, which displays it in real time, and the user can check the displayed design proposal.

[1325] Input: Custom design idea

[1326] Output: Preview your design on your device

[1327] Step 5:

[1328] The user modifies and finalizes the design proposal.

[1329] The user can view the previewed design and make any necessary corrections. Once the corrections are complete, the user confirms the final design and sends the data to the server.

[1330] Input: Modified design information

[1331] Output: Finalized design data (data sent to server)

[1332] Step 6:

[1333] The server sends the final design data to the 3D printer to begin production.

[1334] The server receives the finalized design data and sends it to the 3D printer, which then produces the custom-made product based on the received design data.

[1335] Input: Finalized design data

[1336] Output: Manufacturing instructions for the 3D printer

[1337] Step 7:

[1338] 3D printers produce custom-made products and perform quality inspections.

[1339] The 3D printer uses the received design data to manufacture the product, and once manufactured, the product undergoes quality inspection to check its appearance, dimensions, durability, etc.

[1340] Input: Manufacturing instructions to the 3D printer

[1341] Output: Finished products and quality inspection results

[1342] Step 8:

[1343] The server receives the quality inspection results and starts the delivery procedure.

[1344] Products that pass the quality inspection are sent to the server's management system for delivery, which displays the delivery status on the terminal in real time.

[1345] Input: Quality Inspection Results

[1346] Output: Delivery status (notification to terminal)

[1347] 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.

[1348] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[1349] The main components of the system include an input means for users to specify custom-made products, a server, an AI system, an emotion engine, an information provision means, an interface means, a 3D printer, a quality inspection means, and a delivery means.

[1350] First, a user accesses the system's homepage using a terminal and requests the design of a custom-made product. At this time, the user inputs information such as the product category, design theme, desired color, and text. Sensors (e.g., a facial recognition camera and a voice analysis microphone) are also used to recognize the user's emotions. The terminal then transmits the input data and emotional data to the server.

[1351] The server then receives the request data and emotion data, extracts relevant information stored in a database (past order data, trend information, user preferences), and passes this data to the AI ​​system and emotion engine to generate a custom design.

[1352] The AI ​​system and emotion engine analyzes large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. This process involves building design prototypes and evaluating multiple candidates. The emotion engine selects and recommends designs based specifically on the user's emotion data.

[1353] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[1354] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[1355] After the 3D printer completes the product, a quality inspection is carried out. The inspection includes the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[1356] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[1357] The system of the present invention allows users to quickly and with high quality receive personalized custom-made products based on their preferences and emotions. The introduction of the emotion engine further improves the user experience and enables the provision of highly satisfying services.

[1358] The processing flow will be explained below.

[1359] Step 1:

[1360] The user accesses the system's homepage using a device and enters the necessary information into an input form to specify a custom-made product. Specifically, the user enters the product category (e.g., smartphone case), design theme (e.g., natural scenery), desired color, and text insertion (e.g., name or message). In addition, emotion data is also obtained using a facial recognition camera and a voice analysis microphone.

[1361] Step 2:

[1362] The terminal reads the product information and emotion data input by the user, generates formatted request data, and transmits it to the server.

[1363] Step 3:

[1364] The server receives the request data and emotion data and extracts related information (past order data, trend information, user preference data) stored in a database.

[1365] Step 4:

[1366] The server passes the extracted data to an AI system and emotion engine, instructing it to generate a custom design.

[1367] Step 5:

[1368] The AI ​​system and emotion engine analyze large amounts of 3D printer data, trend information, user preference data, and emotion data to generate optimal custom designs. Specifically, it builds design prototypes and evaluates and generates multiple design candidates. The emotion engine selects and recommends designs based on the user's emotion data.

[1369] Step 6:

[1370] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device.

[1371] Step 7:

[1372] The device displays the generated design proposal to the user and provides a preview function, allowing the user to review the design proposal and customize it as needed (e.g., adjust colors or edit text).

[1373] Step 8:

[1374] The emotion engine analyzes the emotion data in real time and suggests optimal modifications based on the user's customizations. The user can then review the suggestions and make a final decision.

[1375] Step 9:

[1376] The user finalizes the design and presses the confirmation button for the manufacturing request.

[1377] Step 10:

[1378] The terminal sends the final design data to the server and confirms the manufacturing request.

[1379] Step 11:

[1380] The server then sends the final design data to the 3D printer control system, starting the manufacturing process.

[1381] Step 12:

[1382] The 3D printer manufactures the product based on the design data received from the server, and the manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[1383] Step 13:

[1384] After the 3D printer completes the product, it undergoes a quality inspection, which includes the product's appearance, dimensions, durability, etc.

[1385] Step 14:

[1386] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[1387] Step 15:

[1388] The delivery service delivers the product that has passed quality inspection to the user, who then accepts the delivery and confirms that the custom-made product was manufactured as expected.

[1389] Through these steps, users can easily order personalized custom-made products based on their preferences and emotions and receive them quickly and with high quality.

[1390] Example 2

[1391] 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."

[1392] Conventional custom-made product systems have difficulty generating personalized designs based on the user's emotions and preferences, and have been unable to provide products that satisfy the user. Furthermore, improving the efficiency of the manufacturing process and ensuring quality remain significant challenges. The present invention aims to solve these problems by providing a system that utilizes user emotion data to provide optimal custom designs and realize a high-quality manufacturing process.

[1393] 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.

[1394] In this invention, the server includes a means for the terminal to send input data and emotion data to the server, a means for the server to analyze the received data by extracting relevant information from a database and send it to the AI ​​system and emotion engine, and a means for the AI ​​system and emotion engine to generate a custom design, thereby enabling the generation of personalized custom designs based on the user's emotion data and a high-quality manufacturing process.

[1395] The "input means" is a means by which a user inputs information about the design of a custom-made product into the system.

[1396] A "terminal" is a device through which a user inputs information and transmits and receives data to and from a server.

[1397] A "server" is a computer system that processes data received from users and manages the design generation and manufacturing process.

[1398] A "database" is an information system for storing past order data, trend information, and user preference data.

[1399] An "AI system" is a system that uses artificial intelligence technology to analyze large amounts of data and generate optimal custom designs.

[1400] An "emotion engine" is a system that analyzes user emotional data and makes designs and recommendations based on the results.

[1401] "Information provision means" refers to the means for presenting design proposals generated by the AI ​​system and emotion engine to the user.

[1402] "Interface means" refers to the means by which a user can modify and finalize the generated design proposals.

[1403] "Control means" refers to the means by which the server sends the final design data to the 3D printer and instructs manufacturing.

[1404] A "3D printer" is a three-dimensional printing machine that manufactures products based on design data received from a server.

[1405] "Manufacturing means" refers to a means for manufacturing a custom-made product specified by a user using a 3D printer.

[1406] "Quality inspection means" refers to means for inspecting the quality of completed manufactured goods.

[1407] "Delivery means" refers to a means for delivering manufactured products that have passed the quality inspection to the user.

[1408] The "management means" is a means by which the server receives the quality inspection results and starts the delivery procedure.

[1409] The present invention provides a system that allows users to easily order custom-made products. In particular, by combining it with an emotion engine that analyzes the user's emotion data and optimizes the design based on this, it is possible to provide more personalized products.

[1410] Hardware and software used

[1411] Terminal (device used by the user, e.g. smartphone, PC)

[1412] server

[1413] AI systems (e.g. TensorFlow, PyTorch)

[1414] Emotion engines (e.g., Affectiva)

[1415] Interface means (e.g., web browser, specific application)

[1416] 3D printer (e.g. Ultimaker S5)

[1417] Quality inspection methods (e.g., AI-enabled vision systems)

[1418] Shipping method (e.g. FedEx, UPS)

[1419] Explanation of the program's processing steps

[1420] User input and data submission

[1421] A user accesses the system's homepage using a terminal and requests a custom-made product design. The user inputs information such as product category, design theme, desired color, and text. Emotional data is also collected using a facial recognition camera and a voice analysis microphone. The terminal then transmits the input data and emotional data to the server.

[1422] Receiving and analyzing data

[1423] The server extracts the received request data and emotion data, as well as past order data, trend information, and user preference data stored in a database. The server passes this data to the AI ​​system and emotion engine, instructing it to generate a custom design.

[1424] Generate a custom design

[1425] The AI ​​system and emotion engine analyze large amounts of trend information, 3D printer data, user preference data, and emotion data to generate optimal custom designs. Multiple design candidates are constructed and evaluated. The emotion engine selects and recommends designs based on the user's emotion data.

[1426] Presentation of design proposals

[1427] The server receives the design proposals generated by the AI ​​system and emotion engine and transfers them to the user's device. The device displays the generated design proposals to the user and provides a preview function. The user reviews the design proposals and customizes them as needed (e.g., adjusting colors or editing text). The emotion engine analyzes the emotion data in real time and suggests optimal revisions to the user.

[1428] Final design confirmation and manufacturing

[1429] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request. The server then sends the final design data to the 3D printer's control system, starting the manufacturing process. The 3D printer then manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time, and any necessary adjustments are made automatically.

[1430] Quality Inspection and Delivery

[1431] After the 3D printer completes the product, a quality inspection is carried out. The product's appearance, dimensions, durability, etc. are inspected, and only products that pass are shipped. The server receives the quality inspection results and initiates the shipping process for products that pass. Delivery status information is notified to the user in real time. Finally, the delivery service delivers the product to the user.

[1432] Specific examples

[1433] For example, when a user orders a custom smartphone case, the process is as follows: First, the user inputs their preferred color and design theme using their device, while also capturing emotion data using a facial recognition camera. The server passes the data to the AI ​​system and emotion engine to generate an optimized design proposal. The user then reviews and adjusts the proposal and confirms the manufacturing order. The server then sends the final design to a 3D printer, and the smartphone case that passes quality inspection is delivered to the user.

[1434] Prompt sentence for generative AI model

[1435] "If a user wants to create a custom smartphone case, they first access their device. They enter information such as product category, design theme, desired color, and text, and then collect sentiment data."

[1436] "You send your input data and emotion data to our server, which then uses our AI system and emotion engine to generate custom design ideas."

[1437] "The generated design proposals are displayed to the user, who can then customize them as needed. The final design data is then sent to the server, and the manufacturing process begins."

[1438] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1439] Step 1:

[1440] The user initiates an order for a custom-made product on the device. Specifically, the user accesses the system's homepage and inputs information such as the product category, design theme, desired color, and text. The user also acquires emotional data using a facial recognition camera and a voice analysis microphone. The input data and emotional data are stored on the device.

[1441] Input: User input information (product category, design theme, desired color, text), emotional data

[1442] Output: A set of input data and emotion data

[1443] Step 2:

[1444] The device sends the input data and emotion data to the server. The device POSTs the dataset to the server as an HTTP request.

[1445] Input: A set of input data and emotion data

[1446] Output: Send data to the server

[1447] Step 3:

[1448] The server receives the request data and emotion data, analyzes the received data, and extracts past order data, trend information, and user preference data stored in a database.

[1449] Input: Request data and emotion data received by the server

[1450] Output: Analyzed related information (past order data, trend information, user preference data)

[1451] Step 4:

[1452] The server extracts the relevant information and passes the data to the AI ​​system and emotion engine using API calls and database queries.

[1453] Input: Parsed relevant information

[1454] Output: Sending data to AI systems and emotion engines

[1455] Step 5:

[1456] The AI ​​system and emotion engine generate custom designs, using neural networks to generate design ideas and emotion data as feedback to evaluate multiple design candidates.

[1457] Input: related information, emotion data

[1458] Output: Generated custom design proposal

[1459] Step 6:

[1460] The server transfers the generated design proposal to the user's device, and returns the generated design proposal to the device as an HTTP response.

[1461] Input: Generated custom design proposal

[1462] Output: Sending the design to the user's device

[1463] Step 7:

[1464] The device displays the design proposal to the user and accepts customization. Specifically, the design proposal is displayed on the screen, providing a preview function, and the user can customize it by adjusting colors, editing text, etc.

[1465] Input: Custom design idea

[1466] Output: User-customized design proposal

[1467] Step 8:

[1468] The user decides on the final design and the device sends it to the server. When the user clicks the confirm button, the device sends the final design data to the server via an HTTP request.

[1469] Input: User-customized design proposal

[1470] Output: Finalized design data

[1471] Step 9:

[1472] The server sends the final design to the 3D printer and starts production. The server sends the final design data to the 3D printer via a dedicated API or communication protocol.

[1473] Input: Finalized design data

[1474] Output: Send design data to a 3D printer

[1475] Step 10:

[1476] The 3D printer produces the product based on the design. The 3D printer produces the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[1477] Input: Finalized design data

[1478] Output: Manufactured goods

[1479] Step 11:

[1480] The 3D printer completes the product and then a quality inspection is carried out, specifically, checking the appearance, dimensions, durability, etc. of the product, and only products that pass the inspection are reported.

[1481] Input: Manufactured goods

[1482] Output: Quality inspection result (pass / fail)

[1483] Step 12:

[1484] The server receives the quality inspection results and initiates the shipping process. For products that pass the inspection, the server initiates the shipping process and notifies the user of the shipping status information in real time.

[1485] Input: Quality inspection result (pass)

[1486] Output: Shipping process and status notification

[1487] Step 13:

[1488] The delivery service delivers the product to the user. The order is completed when the delivery service delivers the product to the user.

[1489] Input:Shipping procedure

[1490] Output: Product delivery completed to user

[1491] (Application example 2)

[1492] 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."

[1493] Conventional systems for providing custom-made products have the problem of being unable to provide sufficient advanced personalization based on the user's individual emotions and preferences. It is also difficult to reflect the user's emotional changes in real time during the product design generation and manufacturing process. This reduces the quality of the user experience. Furthermore, the lack of interactive communication with the user, such as presenting design proposals and proposing revisions through dialogue, can lead to low user satisfaction.

[1494] 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.

[1495] In this invention, the server includes an input means for a user to specify a custom-made product; a processing means for receiving the data input by the server and generating a custom design through an AI system; an information provision means for presenting the generated design proposals to the user; an interface means for the user to modify and confirm the final design; a control means for transmitting the final design data to the 3D printer and instructing production; a manufacturing means for producing the user-specified custom-made product using the 3D printer; a quality inspection means for inspecting the quality of the completed manufactured product; a delivery means for delivering manufactured products that pass the quality inspection to the user; an emotion analysis means for acquiring user emotion data using smart glasses and analyzing the emotion data; and an emotion engine for generating optimal custom designs based on the analyzed emotion data. This enables advanced personalization based on the user's emotions and preferences, allowing product designs and manufacturing to be generated and reflected in real time to reflect the user's emotional changes. Furthermore, interactive communication improves the quality of the user experience and enables the provision of highly satisfying services.

[1496] "User" means an individual or legal entity ordering a custom-made product.

[1497] "Input means" refers to a device or interface that allows a user to input information and requests regarding a custom-made product.

[1498] "Server" means a computer system that receives input data from users and processes and manages the data.

[1499] "Processing means" refers to a device or program that has the functionality to allow the server to receive input data and generate a custom design through the AI ​​system.

[1500] The "AI system" is a system that utilizes artificial intelligence to generate optimal custom designs based on past order data, trend information, and user preferences.

[1501] The "information providing means" refers to a display or notification device that presents custom design proposals to the user.

[1502] "Interface means" refers to devices or software that allow the user to confirm and modify the generated design proposals and finalize the design.

[1503] "Control means" refers to a device or program that has the function of sending final design data from the server to the 3D printer and instructing manufacturing.

[1504] "Manufacturing means" refers to the equipment and process that uses a 3D printer to manufacture the custom-made product specified by the user.

[1505] "Quality inspection means" refers to devices and functions for inspecting the quality of manufactured products.

[1506] "Delivery means" refers to a logistics system for delivering manufactured products that have passed quality inspection to users.

[1507] "Smart glasses" are wearable devices that use built-in cameras and sensors to acquire and analyze the user's emotional data.

[1508] "Emotion analysis means" refers to a device or program that has the function of analyzing emotion data acquired from smart glasses or the like.

[1509] The "emotion engine" is a software module that generates optimal custom designs for users based on analyzed emotional data.

[1510] This invention provides a system that allows users to order custom-made products based on emotional data. The system analyzes the user's input data and emotional data, generates an optimal custom design, and then manufactures and delivers it. A specific embodiment of the system is described below.

[1511] Main components of the system

[1512] 1. Input Method

[1513] Users can specify custom-made products using smart glasses or a terminal, inputting information such as product category, design theme, desired color, and text.

[1514] 2. Server

[1515] The server receives the data and emotion data entered by the user, extracts past order data, trend information, and user preferences stored in a database, and passes this data to the AI ​​system and emotion engine to generate a custom design.

[1516] 3. AI Systems

[1517] The AI ​​system analyzes large amounts of data (e.g., 3D printer data, trend information, and user preference data) to generate optimal custom designs. The emotion engine selects and recommends designs based specifically on the user's emotional data.

[1518] 4. Smart Glasses and Emotion Analysis Methods

[1519] A user wears the smart glasses, and the camera captures the user's face and facial expressions. The emotion analysis means analyzes the captured image data and generates emotion data of the user. This data is then sent to the server.

[1520] 5. Means of providing information

[1521] The server transfers the design proposals generated by the AI ​​system and emotion engine to the user's device, which displays the generated design proposals to the user and provides a preview function.

[1522] 6. Interface Methods

[1523] Users can view the generated design proposals through their devices and customize them as needed. The emotion engine analyzes emotion data in real time and suggests optimal revisions to the user.

[1524] 7. Control Measures

[1525] Once the user has finalized the design, the device sends the information to the server and confirms the manufacturing request, which then sends the final design data to the 3D printer to begin the manufacturing process.

[1526] 8. Manufacturing methods (3D printers) and quality inspection methods

[1527] The 3D printer manufactures the product based on the design data received from the server. The manufacturing process is monitored in real time and any necessary adjustments are made automatically. After the product is completed, a quality inspection is carried out and only products that pass are shipped.

[1528] 9. Delivery method

[1529] The server receives the quality inspection results and initiates the shipping process for products that pass the inspection. The user is notified of the shipping status in real time.

[1530] Specific examples

[1531] Examples of applications using smart glasses include the following processes:

[1532] 1. Store staff wearing smart glasses capture customer emotional data in real time.

[1533] 2. The server receives the emotion data and the user's input data and generates the optimal custom design proposal.

[1534] 3. The generated design proposal is displayed on the smart glasses display, providing the customer with a preview.

[1535] 4. The customer reviews and modifies the design and makes the final decision.

[1536] 5. The final design data is sent to the server and the product is manufactured using a 3D printer.

[1537] 6. After quality inspection, products that pass are delivered to the customer.

[1538] Prompt Sentence Examples

[1539] "Use smart glasses to capture customer sentiment data and generate design proposals for custom-made products in real time. Present the design proposals to the customer, and after final confirmation, confirm the order."

[1540] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1541] Step 1:

[1542] The user specifies the custom-made product using the terminal and inputs information such as product category, design theme, desired color, text, etc. This input data is collected by the interface of the smart glasses or terminal used by the user, and then transmitted to the server.

[1543] Step 2:

[1544] The camera in the smart glasses captures the user's face, and the emotion analysis means processes the image data to generate emotion data of the user. The emotion data includes the user's facial expressions and emotional state (e.g., joy, surprise). The emotion data is sent to a server.

[1545] Step 3:

[1546] The server receives input and emotional data from users and combines it with past order data, trend information, and user preferences stored in a database, creating the foundational data for the AI ​​system to generate optimal custom designs.

[1547] Step 4:

[1548] The server provides basic data to the AI ​​system and emotion engine and instructs them to generate custom designs. The AI ​​system generates design candidates based on past data and user preferences, and the emotion engine optimizes the design proposals based on the emotion data. The generated custom design proposals are returned to the server.

[1549] Step 5:

[1550] The server transfers the generated custom design proposal to the user's device, which displays the design proposal on its display, providing a preview function for the user, and providing an interface for the user to review the design proposal and customize it as needed.

[1551] Step 6:

[1552] The user uses the device to revise the design proposal and confirm the final design. The emotion engine analyzes the emotion data in real time and suggests the optimal revisions to the user. The finalised design data is sent to the server.

[1553] Step 7:

[1554] The server sends the finalized design data to the 3D printer, starting the manufacturing process. The 3D printer produces the custom-made product based on the design data. The manufacturing process is monitored in real time and any necessary adjustments are made automatically.

[1555] Step 8:

[1556] After the customized product is completed, the quality inspection means checks the product's appearance, dimensions, durability, etc. Only products that pass the quality inspection are shipped. The server manages the quality inspection results and initiates the shipping procedures for products that pass the inspection.

[1557] Step 9:

[1558] The server processes the delivery process and notifies the user of delivery status information in real time. Finally, the product is delivered to the user by the delivery service.

[1559] Through the above processing steps, users can quickly receive high-quality custom-made products based on their own emotions and preferences.

[1560] 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.

[1561] 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.

[1562] 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.

[1563] 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.

[1564] 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.

[1565] 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.

[1566] 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).

[1567] 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.

[1568] 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."

[1569] 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.

[1570] 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).

[1571] 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.

[1572] 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.

[1573] 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.

[1574] 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.

[1575] 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.

[1576] 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.

[1577] 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.

[1578] 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.

[1579] 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.

[1580] 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.

[1581] The following is further disclosed regarding the above embodiment.

[1582] (Claim 1)

[1583] an input means for a user to specify a custom-made product;

[1584] a processing means for receiving the data input by the server and generating a custom design through an AI system;

[1585] an information providing means for presenting the generated design proposal to a user;

[1586] an interface means for a user to modify and finalize the final design;

[1587] A control means for transmitting the final design data to the 3D printer by the server and instructing manufacturing;

[1588] A manufacturing means for manufacturing custom-made products specified by a user using a 3D printer;

[1589] a quality inspection means for inspecting the quality of the completed manufactured goods;

[1590] A system including a delivery means for delivering manufactured products that have passed quality inspection to users.

[1591] (Claim 2)

[1592] 10. The system of claim 1, wherein the AI ​​system optimizes custom designs based on past order data, trend information, and user preferences.

[1593] (Claim 3)

[1594] 2. The system according to claim 1, further comprising a management means for receiving the quality inspection results and initiating the delivery procedure.

[1595] "Example 1"

[1596] (Claim 1)

[1597] an input means for a user to specify a custom-made product;

[1598] a processing means for receiving the data input by the server and generating a custom design through an AI system;

[1599] an information providing means for presenting the generated design proposal to a user;

[1600] an interface means for a user to modify and finalize the final design;

[1601] a control means for transmitting the final design data to a manufacturing device by a server and instructing the manufacturing;

[1602] a manufacturing means for manufacturing a custom-made product designated by a user using a manufacturing device;

[1603] a quality inspection means for inspecting the quality of the completed manufactured goods;

[1604] a delivery means for delivering manufactured products that have passed the quality inspection to users;

[1605] a monitoring means for real-time monitoring and adjustment during the manufacturing process;

[1606] reporting means for notifying the server of the results of the quality inspection;

[1607] The system includes a notification means for notifying users of delivery status in real time.

[1608] (Claim 2)

[1609] 10. The system of claim 1, wherein the AI ​​system optimizes custom designs based on past order data, trend information, and user preferences.

[1610] (Claim 3)

[1611] 2. The system according to claim 1, further comprising a management means for receiving the quality inspection results and initiating the delivery procedure.

[1612] "Application Example 1"

[1613] (Claim 1)

[1614] an input means for a user to specify a custom-made product;

[1615] a processing means for receiving the data input by the server and generating a custom design through an AI system;

[1616] an information providing means for presenting the generated design proposal to a user;

[1617] an interface means for a user to modify and finalize the final design;

[1618] A control means for transmitting the final design data to the 3D printer by the server and instructing manufacturing;

[1619] A manufacturing means for manufacturing custom-made products specified by a user using a 3D printer;

[1620] a quality inspection means for inspecting the quality of the completed manufactured goods;

[1621] a delivery means for delivering manufactured products that have passed the quality inspection to users;

[1622] A means for previewing the generated design proposal in real time through a smartphone or tablet application;

[1623] a means for displaying the delivery status of manufactured goods in real time;

[1624] A system including:

[1625] (Claim 2)

[1626] 10. The system of claim 1, wherein the AI ​​system optimizes custom designs based on past order data, trend information, and user preferences.

[1627] (Claim 3)

[1628] 2. The system according to claim 1, further comprising a management means for receiving the quality inspection results and initiating the delivery procedure.

[1629] "Example 2: Combining Emotion Engines"

[1630] (Claim 1)

[1631] an input means for a user to specify a custom-made product;

[1632] A means for the terminal to transmit input data and emotion data to a server;

[1633] means for analyzing the received data by extracting relevant information from a database and transmitting the information to the AI ​​system and the emotion engine;

[1634] A means for AI systems and emotion engines to generate custom designs;

[1635] an information providing means for presenting the generated design proposal to a user;

[1636] an interface means for a user to modify and finalize the final design;

[1637] A means for the terminal to transmit the confirmed design data to a server;

[1638] A control means for the server to send the final design data to the 3D printer and instruct manufacturing;

[1639] A manufacturing means for manufacturing custom-made products specified by a user using a 3D printer;

[1640] a quality inspection means for inspecting the quality of the completed manufactured goods;

[1641] A system including a delivery means for delivering manufactured products that have passed quality inspection to users.

[1642] (Claim 2)

[1643] 10. The system of claim 1, wherein the AI ​​system optimizes custom designs based on past order data, trend information, and user preference and emotion data.

[1644] (Claim 3)

[1645] 2. The system according to claim 1, further comprising a management means for receiving the quality inspection results and initiating the delivery procedure.

[1646] "Application example 2 when combining emotion engines"

[1647] (Claim 1)

[1648] an input means for a user to specify a custom-made product;

[1649] a processing means for receiving the data input by the server and generating a custom design through an AI system;

[1650] an information providing means for presenting the generated design proposal to a user;

[1651] an interface means for a user to modify and finalize the final design;

[1652] A control means for transmitting the final design data to the 3D printer by the server and instructing manufacturing;

[1653] A manufacturing means for manufacturing custom-made products specified by a user using a 3D printer;

[1654] a quality inspection means for inspecting the quality of the completed manufactured goods;

[1655] a delivery means for delivering manufactured products that have passed the quality inspection to users;

[1656] emotion analysis means for acquiring emotion data of a user through the smart glasses and analyzing the emotion data;

[1657] A system including an emotion engine for generating optimal custom designs based on analyzed emotion data.

[1658] (Claim 2)

[1659] 10. The system of claim 1, wherein the AI ​​system optimizes the custom design based on past order data, trend information, and user preferences, and further adjusts the design based on user emotional data.

[1660] (Claim 3)

[1661] 2. The system of claim 1, wherein the server receives the quality inspection results, initiates the delivery process, and includes a management means for notifying the user of status information in real time. [Explanation of symbols]

[1662] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an input means for a user to specify a custom-made product; a processing means for receiving the data input by the server and generating a custom design through an AI system; an information providing means for presenting the generated design proposal to a user; an interface means for a user to modify and finalize the final design; A control means for transmitting the final design data to the 3D printer by the server and instructing manufacturing; A manufacturing means for manufacturing custom-made products specified by a user using a 3D printer; a quality inspection means for inspecting the quality of the completed manufactured goods; A system including a delivery means for delivering manufactured products that have passed quality inspection to users.

2. 10. The system of claim 1, wherein the AI ​​system optimizes custom designs based on past order data, trend information, and user preferences.

3. 2. The system according to claim 1, further comprising a management means for receiving the quality inspection results and initiating the delivery procedure.

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