system

Abstract

We provide the system. [Solution] A means of obtaining user design requirements, A method for generating 3D design data using an AI model based on acquired design requirements, A means for converting generated three-dimensional design data into data for a three-dimensional printing device, A means for transmitting data for a three-dimensional printing device to a printing device and generating physical device accessories, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Although auxiliary devices are usually excellent in function, there is a problem that their designs are uniform and it is difficult to reflect individuality. For this reason, there is a need for means that allow people who use the devices to customize the auxiliary devices individually according to their preferences and styles. Also, there is a lack of an efficient process for easily embodying a customized design in a physical form.

Means for Solving the Problems

[0005] The present invention provides a system that includes means for acquiring user design requests, means for generating three-dimensional design data using a generation AI model based on the acquired design requests, means for converting the generated three-dimensional design data into data for a three-dimensional printing device, and means for transmitting the data for the three-dimensional printing device to a printing device to generate physical device accessories. This system allows users to easily obtain custom accessories that specifically reflect their design requests, enabling them to reflect their individuality and style in auxiliary equipment.

[0006] "Means for obtaining user design requests" refers to interfaces and processes for collecting requests and instructions from users regarding customized designs.

[0007] "Methods for generating 3D design data using generative AI models" refers to algorithms and systems that utilize artificial intelligence technology to create digital 3D models based on the user's design requirements.

[0008] "Means of converting three-dimensional design data into data for three-dimensional printing equipment" refers to the process or technology of converting digital design data into a format that a three-dimensional printer can physically output.

[0009] "Means for transmitting data for a three-dimensional printing device to a printing device and generating physical device accessories" refers to the procedures and devices used to send commands to the printing press using the converted data and actually generate physical objects. [Brief explanation of the drawing]

[0010] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4]This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0011] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0012] First, let's explain the terminology used in the following explanation.

[0013] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0014] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0015] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0016] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. 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), or Bluetooth (registered trademark).

[0017] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0018] [First Embodiment]

[0019] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0020] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0021] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0022] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0023] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0024] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0025] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0026] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0027] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0028] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0029] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0030] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0031] This invention relates to a system for generating custom accessories that allow users to personalize assistive devices. The system aims to create three-dimensional design data using AI technology based on the user's design requests, and then convert that data into an actual physical shape. Specific embodiments for carrying out this invention are described below.

[0032] First, the user launches a dedicated application on their device and enters their requirements for the assistive device they wish to customize. These requirements are entered using a text-based interface or a simple sketching interface. During this process, the user can specify details such as colors, shapes, and design patterns.

[0033] Once the user completes their input, the terminal sends the data to the server. The server receives this data and generates 3D design data through a generative AI model. This AI model has the ability to calculate and output the optimal design based on the user's requests. The generated design data is highly customized according to the user's desired style and aesthetic sense.

[0034] Next, the server converts the generated 3D design data into a data format usable by a 3D printing device, namely G-code. This conversion ensures the data is in a format that can be accurately reproduced by a 3D printer. The converted data is then sent to the terminal for subsequent processing.

[0035] Users send G-code to a 3D printer via their terminal, and the printer then prints out custom accessories based on the data. This printing process faithfully reproduces pre-specified colors and designs. Users receive the finished product and attach it to their assistive devices, resulting in practical and aesthetically pleasing assistive device accessories tailored to their individual needs.

[0036] For example, if a user wants to customize a band to attach to a leg cast, they can specify the desired color, such as blue, and even the pattern or design they want on the surface. The AI ​​model then designs and prints the band based on these specifications, which not only complements the function of the cast but also becomes a unique item that expresses the user's individuality.

[0037] Thus, the present invention not only extends the functionality of the device, but also provides a means for individual users to customize the auxiliary device to their liking, thereby improving the user experience.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user launches the application on their device and enters their design requests. The device provides text boxes and sketching functions for entering design requests, allowing the user to input desired colors, shapes, patterns, etc.

[0041] Step 2:

[0042] The terminal organizes the user's design requests from the input format and sends them to the server as digital data. Data transmission takes place in real time over the network, enabling rapid processing.

[0043] Step 3:

[0044] The server analyzes the received design requests and generates 3D design data using a generation AI model. Based on the user's specific requests, the server utilizes AI technology to construct an appropriate design.

[0045] Step 4:

[0046] The server converts the generated 3D design data into G-code for 3D printing devices. The server then uses a slicing engine to format this data into a format suitable for the printer.

[0047] Step 5:

[0048] The server sends the generated G-code to the terminal. The terminal saves this G-code locally and prepares it for the subsequent printing process.

[0049] Step 6:

[0050] The user sends G-code to a 3D printer via a terminal to print out physical accessories. Based on instructions from the terminal, the printer generates objects according to the design.

[0051] Step 7:

[0052] Users receive printed accessories and attach them to their assistive devices. This allows the customized accessories to be used in a way that reflects the user's individuality and needs.

[0053] (Example 1)

[0054] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0055] There is a need for users to be able to easily and quickly generate customized assistive device accessories tailored to their individual needs. However, current technology lacks a way to efficiently translate users' specific design requirements into three-dimensional shapes and functions. As a result, it is difficult to accurately translate users' wishes into tangible forms, leading to a decrease in satisfaction.

[0056] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0057] In this invention, the server includes: a device means for acquiring user design requests; a device means for generating three-dimensional design information using a generation AI model based on the acquired design requests; and a device means for converting the generated three-dimensional design information into information for a visual reproduction device. This makes it possible to efficiently generate custom accessories that reflect the individual design requests of the user.

[0058] A "device for acquiring user design requests" is a device that provides an interface for users to input their design requests for customization and collects those requests as digital data.

[0059] A "generative AI model" is an artificial intelligence model that uses advanced algorithms to generate three-dimensional design data based on design requirements obtained from users.

[0060] "3D design information" refers to information about three-dimensional structures and shapes represented as digital data, and is fundamental data for reproducing physical objects.

[0061] A "device for converting information for visual reproduction devices" is a device that converts three-dimensional design information into a format that can be reproduced by a three-dimensional printing device, and prepares it as data for accurate printing.

[0062] A "device for generating physical accessories" is a device that uses information intended for visual reproduction devices to generate actual physical objects using equipment such as a three-dimensional printer.

[0063] This invention relates to a system that allows users to generate individualized auxiliary device accessories tailored to their specific needs. This system facilitates design customization and enables the rapid and accurate production of physical accessories.

[0064] First, the user launches a dedicated application on their device. This application provides a means for inputting design requests through a user interface. Users can input detailed design requests using text format or hand-drawn sketches available on the interface. An example of a prompt message could be, "Please create a flexible band with a red floral design."

[0065] Once the user has completed their input, the terminal sends the digital data of the design request to the server. The server uses a generative AI model to generate optimal 3D design information based on the user's request. This AI model, with its advanced algorithms, can quickly generate creative designs based on the provided prompt text.

[0066] Next, the server converts the 3D design information into information for visual reproduction devices, specifically G-code that can be understood by 3D printing devices. Dedicated data conversion software is used to prepare the design data for accurate printing. This conversion guarantees faithful reproduction of the design.

[0067] From this point onward, the user sends this G-code to a 3D printer via their terminal. The printer then accurately creates the physical accessory based on the specified visual features and shapes. The final product faithfully reproduces the user's desired colors and design patterns, and when attached to the assistive device, it becomes a practical and personalized accessory. For example, if a user customizes a band to attach to a leg cast, they can have it made blue with a star pattern as desired.

[0068] Thus, the present invention provides an effective means for accurately reflecting the user's design requirements and rapidly generating custom accessories. This greatly improves user satisfaction and convenience.

[0069] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0070] Step 1:

[0071] The user launches a dedicated application on their device and enters their design requests. At this time, the user can enter specific design prompts in text format or draw sketches using the app's hand-drawing function. The input may include specific design requests such as, "Please create a custom band with a blue floral design." This data is then output in digital format.

[0072] Step 2:

[0073] The terminal sends digital data of the design requests entered by the user to the server. The transmitted data includes text and sketch images. The server receives this data and prepares it for the subsequent design generation process. The input is the user's design request data, and the output is the data received by the server.

[0074] Step 3:

[0075] The server generates 3D design data using an AI model based on the received design data. The AI ​​model uses advanced algorithms to analyze the design based on the prompt text and generate data suitable for 3D design. The input is the user's prompt text and sketch data, and the output is 3D design data.

[0076] Step 4:

[0077] The server converts the generated 3D design data into G-code usable by a 3D printing device. Dedicated data conversion software is used to process the design data into a format that the printer can recognize. The input is 3D design data, and the output is G-code for the visual reproduction device.

[0078] Step 5:

[0079] The user sends a G-code to the 3D printer via a terminal to instruct it to print. The terminal checks the optimal printer settings and materials and prepares to start printing. The input is a G-code, and the output is a print instruction to the 3D printer.

[0080] Step 6:

[0081] The user operates the 3D printer to print the generated accessories. The printer accurately produces physical accessories based on the specified design. This allows the user to obtain original accessories that reflect their individual design requirements. The input is the print instructions, and the output is the physical product.

[0082] (Application Example 1)

[0083] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0084] Traditional customization of accessories for assistive devices presented challenges in instantly reflecting user requests, generating designs, and delivering products immediately, making on-the-spot service difficult. In particular, there was a lack of technology to reflect individual preferences in assistive device accessories while allowing customers to receive the finished product on the spot.

[0085] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0086] In this invention, the server includes means for acquiring the user's design requests, means for generating three-dimensional design data using a generation AI model based on the acquired design requests, and means for the user to generate the design data on the spot using a terminal at the store and receive the resulting product from a printing device. This makes it possible for the user to immediately receive a product that reflects their customized design at the store.

[0087] "Means of obtaining user design requests" refers to a method by which users input their wishes and requests regarding design through an interface, and the system receives that information.

[0088] "A method for generating three-dimensional design data using a generative AI model" refers to a method of generating a design as three-dimensional data using artificial intelligence based on user requests.

[0089] "Means for converting generated three-dimensional design data into data for a three-dimensional printing device" refers to a method for converting three-dimensional data created by AI into a specific data format that can be used by a printing device.

[0090] "Means for transmitting data for a 3D printing device to a printing device and generating physical equipment accessories" refers to a method of passing converted data to a printing device and thereby creating physical custom accessories.

[0091] "A means by which users generate design data on the spot using a terminal in a store and receive the printed product using a printing device" refers to a method in which users can create a design using a device installed in the store and immediately receive a product based on that design.

[0092] "A means by which users input handwritten requests using a user interface, and a means of realizing design generation that can be responded to immediately" refers to a method in which users can directly input handwritten design information and quickly create three-dimensional data based on it.

[0093] The system implementing this invention provides a platform for users to customize accessories for auxiliary devices in stores via an application installed on a terminal. The terminal has an interface for obtaining design requests from users and collects information through handwritten input and text input. These design requests are sent to a server and processed by a generative AI model. The generative AI model calculates the optimal design based on the requests and generates three-dimensional design data.

[0094] The server converts the generated 3D design data into data for 3D printing devices, i.e., G-code. In this process, it utilizes OpenAI's GPT-3 model and other tools to convert the design information into data. The converted data is then transmitted via a terminal to a 3D printer installed in the store. Users can then immediately receive their custom-designed accessories from this printer.

[0095] For example, if a user wants to design a smartwatch band, they would use a terminal to select the band's color and pattern, and then input "Design a band with blue stripes." The AI ​​would process this as a prompt, and a band with the desired stripe pattern would be printed in the store.

[0096] This system allows users to instantly acquire products that reflect their individuality in stores and enjoy their uniqueness through that experience.

[0097] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0098] Step 1:

[0099] The user inputs design requests into the interface via a dedicated application on their device. The input includes specifications such as color, shape, and pattern. For example, a request might be "a band with blue stripes." Based on this, the device collects the request as text data.

[0100] Step 2:

[0101] The terminal sends the collected design requests to the server in data format. The server receives this text data and prepares to use the generating AI model. The server passes this data to the AI ​​model as a prompt message, requesting it to generate detailed 3D design information. Here, the input is the design request text from the user, and the output is the prompt message passed to the AI ​​model.

[0102] Step 3:

[0103] The generating AI model creates three-dimensional design data based on the prompt text. The AI ​​performs design calculations while considering the elements specified by the user. The server receives the three-dimensional design data obtained as output from the AI ​​model. The data obtained as output is detailed design information used in the next process.

[0104] Step 4:

[0105] The server converts the generated 3D design data into a data format (G-code) for 3D printing devices. Specifically, it performs a process to convert the design data into instructions that the printer can interpret. The input is 3D design data from the AI, and the output is a dataset in G-code format.

[0106] Step 5:

[0107] The server sends the converted G-code to the 3D printer in the store via a terminal. The terminal receives the G-code and passes it to the printer, instructing it to begin physical printing. Here, the input is the G-code, and the output is the actual print instruction.

[0108] Step 6:

[0109] The user receives a custom accessory printed using the store's 3D printer. The object is generated exactly according to the user's desired design, bringing their input to life as a physical product. The output resulting from this process is a unique product designed by the user.

[0110] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0111] This invention relates to a system that utilizes an emotion engine to recognize user emotions and generate custom accessories that reflect user requests. This system not only performs physical customization but also provides a more personalized experience by creating designs that take into account the user's emotional state.

[0112] First, users input their design requests using an application on their device. During the input stage, in addition to the text and sketches directly entered by the user, an emotion engine operates that recognizes emotions in real time using the camera and sensors. The emotion engine analyzes the user's facial expressions and voice tone to determine the user's current emotional state. This emotional information is then reflected in the design's colors, shapes, and patterns.

[0113] The device organizes both emotional information and design requests and sends them to the server. The server analyzes the received data and generates 3D design data using a generative AI model. In this process, the AI ​​model takes emotional information into account and incorporates appropriate design elements into the data. For example, if the user is relaxed, calm colors and curvilinear designs will be applied. On the other hand, if an active emotion is recognized, vibrant colors and dynamic shapes will be selected.

[0114] Once the design data is complete, the server converts it into data for use with a 3D printer and sends it back to the terminal. The terminal saves this data locally and prepares to send it to the 3D printer. At this stage, the user can actually print out the accessory.

[0115] The printed accessories are designed to be truly personalized, combining the user's emotions and desires. For example, if the system recognizes that the user is experiencing joy, bright, vibrant colors and colorful patterns will be reflected in the design. In this way, the present invention provides a new user experience that goes beyond a mere functional device by incorporating the user's emotions into the design.

[0116] The following describes the processing flow.

[0117] Step 1:

[0118] The user launches the application on their device and begins entering design requests. The device provides text fields and drawing tools for entering design requests, while the sentiment engine also runs in the background.

[0119] Step 2:

[0120] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and tone of voice. It then determines the user's emotional state and records this information as a log along with design requests.

[0121] Step 3:

[0122] The device sends data about the user's text input, sketches, and emotional state to the server. This transmission is performed using a secure protocol to protect the confidentiality of the data.

[0123] Step 4:

[0124] The server analyzes the received data and determines guidelines for customizing the design based on the acquired emotional information. The server then activates a generative AI model to generate three-dimensional design data, including design colors and forms that correspond to the user's emotions.

[0125] Step 5:

[0126] The server converts the generated 3D design data into G-code for 3D printing devices. The server then adjusts the data into a format that can be correctly executed by the printer and sends the data to the terminal.

[0127] Step 6:

[0128] The terminal receives the transmitted G-code and transfers it to the 3D printer. At this point, the user can verify that the specified design can be accurately printed.

[0129] Step 7:

[0130] Users receive printed accessories, and designs reflecting their emotions are applied to the assistive devices. Users then experience the customized designs, tailored to their own emotions and style, while utilizing the finished product.

[0131] (Example 2)

[0132] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0133] In today's world, there is a demand for the rapid and efficient delivery of customizable products that reflect the individuality and emotions of users. However, conventional systems fail to adequately reflect the emotional state of users, resulting in insufficient personalization accuracy.

[0134] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0135] In this invention, the server includes means for recognizing the user's emotional state using a camera and sensors and generating emotional information; means for generating three-dimensional design data using a generation AI model based on the acquired design requests and emotional information; and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. This makes it possible to create more personalized products by incorporating the user's emotional information into the design.

[0136] "User design requests" refer to the customization preferences and instructions that users input for the device.

[0137] "Emotional information" refers to data that represents the user's current emotional state, and is information generated by the emotion engine.

[0138] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates designs and plans based on the data provided.

[0139] "Three-dimensional design data" refers to digital data created by a generative AI model to represent the shape and design in three-dimensional space.

[0140] "Data for 3D printing equipment" refers to digital design data that has been converted into a format usable by 3D printing equipment.

[0141] A "printing device" refers to a device used to generate physical three-dimensional objects based on three-dimensional printing data.

[0142] A "user interface" refers to a method or device of interaction that allows a user to input data into a system or to view its output.

[0143] This invention is a system for generating custom accessories that reflect the user's emotional state. The user inputs their design requests through an application on their device. The input data is acquired via text, sketches, or camera, and an emotion engine is activated to analyze the user's emotions. This emotion engine uses the device's built-in camera and microphone to acquire emotional information from facial expressions and voice tone. It utilizes a facial recognition library and voice analysis tools in this process.

[0144] The acquired design requests and emotional information are organized by the terminal and sent to the server. The server generates 3D design data using a generative AI model. Based on the emotional and requested information, this model provides the optimal design using algorithms such as DALL-E or Stable Diffusion. A concrete example of a prompt might be an instruction such as, "Generate an accessory with a curved shape and calming colors that match a relaxed mood."

[0145] The server converts the generated 3D design data into a data format usable by 3D printers. CAD tools and 3D modeling software are used for this process. This converted data is then sent back to the terminal in real time.

[0146] Ultimately, the device sends the converted data to a 3D printer, which the user can then print out. The printed accessory becomes a unique item that reflects the user's individual emotions and desires. This allows users to have personalized accessories that resonate with their feelings on a daily basis.

[0147] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0148] Step 1:

[0149] The user launches the application on their device and enters their design requests. The input device used is either a keyboard or a touchscreen. The user uses text input or sketching functions to enter their design expectations and specific requests into the application. The input data obtained here serves as a basic design guideline and indicates preferred patterns.

[0150] Step 2:

[0151] The device activates an emotion engine to analyze the user's emotional state in real time. Using the camera and microphone, it captures data on the user's facial expressions and voice tone. This data is processed using a facial recognition library and voice analysis tools to determine the user's emotional state (e.g., relaxed, active, happy). The identified emotion is then used to reflect subsequent design elements.

[0152] Step 3:

[0153] The terminal integrates the acquired design requests and sentiment information and sends it to the server as a dataset. The transmitted data includes text instructions, sketch information, and sentiment information. This transmission is performed using a secure protocol (e.g., SSL). As output, this data is reliably delivered to the server.

[0154] Step 4:

[0155] The server generates 3D design data using a generative AI model based on the received data. The generative AI model takes text instructions and emotional information as prompts and creates appropriate design elements. For example, it might generate an accessory with a curved shape and calming colors to match a relaxed mood. The output is 3D design data with a custom design tailored to the user.

[0156] Step 5:

[0157] The server converts the generated 3D design data into a data format usable by a 3D printing device. CAD software or 3D modeling tools are used for this conversion. The converted data is sent to the terminal and saved locally. The output obtained through the conversion is a data file compatible with 3D printers.

[0158] Step 6:

[0159] The terminal starts the 3D printer preparation process based on the received data. The user can enter printout commands through the terminal's interface. Finally, the 3D printer creates a physical accessory. The output is a custom accessory based on the user's design and preferences.

[0160] (Application Example 2)

[0161] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0162] Modern consumers demand personalized, custom accessories, but traditional methods struggle to provide personalized designs that take into account the user's emotional state. Furthermore, it's difficult to create an immediate and intuitive shopping experience that responds to the user's mood. Therefore, there is a need to provide accessories that appropriately reflect the user's emotions.

[0163] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0164] In this invention, the server includes means for recognizing the user's emotional state, means for generating three-dimensional design data using an AI model based on the recognized emotional state and design requests, and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. This makes it possible to generate custom accessories that reflect the user's emotions in real time and to purchase them on the spot.

[0165] "Emotional state" refers to the user's current psychological and emotional state, analyzed from their facial expressions and tone of voice.

[0166] "Design requests" refer to design requirements for accessories, such as shape and color, specified by the user based on their own preferences and needs.

[0167] A "generative AI model" is a data generation algorithm that utilizes artificial intelligence technology to generate optimal three-dimensional design data based on emotional states and design requirements.

[0168] "Three-dimensional design data" refers to digital data generated by a generative AI model that describes the design of physical device accessories.

[0169] "Data for 3D printing equipment" refers to data that includes instructions necessary for a 3D printing equipment to generate a physical shape, based on 3D design data.

[0170] A "printing device" is a device that receives data for a three-dimensional printing device and actually outputs physical device accessories.

[0171] To implement this invention, a system is needed to analyze emotional states and generate custom accessories according to the user's design requests. The user's terminal is equipped with a camera and microphone for emotion recognition, thereby acquiring the user's emotional state in real time. The acquired emotional information and the design requests entered by the user are transmitted from the terminal to a server.

[0172] Based on this information, the server uses an advanced generative AI model to generate 3D design data. For example, if the user is relaxed, a design with calming colors will be applied. The server then uses the generated 3D design data to convert it into data for a 3D printer. The converted data is sent to the terminal, and ultimately, the 3D printer generates a physical custom accessory.

[0173] Specific hardware and software include devices such as smartphones and tablets, cloud-based emotion analysis software, generative AI models (e.g., DALL-E), and server systems for data conversion and transmission.

[0174] As a concrete example, suppose a user expresses feelings of excitement and joy while watching a sporting event. The design data generated using this information would be an accessory with vibrant colors and a dynamic shape.

[0175] An example of a prompt message would be: "The user is currently excited and in a state of joy. Generate a vibrant and lively design in response to this emotion."

[0176] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0177] Step 1:

[0178] The user uses a device to input design requests. During this process, the device uses its camera and microphone to capture the user's facial expressions and voice tone in real time, acquiring emotional data. The input consists of the user's specific requests (text and sketches) and emotional data, which are then used in the next step.

[0179] Step 2:

[0180] The terminal sends the acquired design requests and emotional data to the server. The emotional data reflects the user's current emotional state, and the server performs emotional analysis based on this data. As a result of the analysis, data indicating the emotional state is output.

[0181] Step 3:

[0182] The AI ​​model on the server generates three-dimensional design data based on the received emotional state and design request data. In this process, prompt sentences are given as input to the AI ​​model, and three-dimensional design data including colors and shapes corresponding to the emotions is output.

[0183] Step 4:

[0184] The server converts the generated 3D design data into data for use with a 3D printing device. Using 3D design data as input, the output is data in a format usable by the printing device.

[0185] Step 5:

[0186] The terminal locally stores the data for the 3D printer received from the server and sends it to the printer based on user instructions. At this stage, the data is converted into a physical shape, and a custom accessory is generated. The input is the stored data, and the output is a physical accessory customized by the user.

[0187] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0188] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0189] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0190] [Second Embodiment]

[0191] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0192] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0193] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0194] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0195] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0196] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0197] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0198] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0199] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0200] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0201] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0202] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0203] This invention relates to a system for generating custom accessories that allow users to personalize assistive devices. The system aims to create three-dimensional design data using AI technology based on the user's design requests, and then convert that data into an actual physical shape. Specific embodiments for carrying out this invention are described below.

[0204] First, the user launches a dedicated application on their device and enters their requirements for the assistive device they wish to customize. These requirements are entered using a text-based interface or a simple sketching interface. During this process, the user can specify details such as colors, shapes, and design patterns.

[0205] Once the user completes their input, the terminal sends the data to the server. The server receives this data and generates 3D design data through a generative AI model. This AI model has the ability to calculate and output the optimal design based on the user's requests. The generated design data is highly customized according to the user's desired style and aesthetic sense.

[0206] Next, the server converts the generated 3D design data into a data format usable by a 3D printing device, namely G-code. This conversion ensures the data is in a format that can be accurately reproduced by a 3D printer. The converted data is then sent to the terminal for subsequent processing.

[0207] Users send G-code to a 3D printer via their terminal, and the printer then prints out custom accessories based on the data. This printing process faithfully reproduces pre-specified colors and designs. Users receive the finished product and attach it to their assistive devices, resulting in practical and aesthetically pleasing assistive device accessories tailored to their individual needs.

[0208] For example, if a user wants to customize a band to attach to a leg cast, they can specify the desired color, such as blue, and even the pattern or design they want on the surface. The AI ​​model then designs and prints the band based on these specifications, which not only complements the function of the cast but also becomes a unique item that expresses the user's individuality.

[0209] Thus, the present invention not only extends the functionality of the device, but also provides a means for individual users to customize the auxiliary device to their liking, thereby improving the user experience.

[0210] The following describes the processing flow.

[0211] Step 1:

[0212] The user launches the application on their device and enters their design requests. The device provides text boxes and sketching functions for entering design requests, allowing the user to input desired colors, shapes, patterns, etc.

[0213] Step 2:

[0214] The terminal organizes the user's design requests from the input format and sends them to the server as digital data. Data transmission takes place in real time over the network, enabling rapid processing.

[0215] Step 3:

[0216] The server analyzes the received design requests and generates 3D design data using a generation AI model. Based on the user's specific requests, the server utilizes AI technology to construct an appropriate design.

[0217] Step 4:

[0218] The server converts the generated 3D design data into G-code for 3D printing devices. The server then uses a slicing engine to format this data into a format suitable for the printer.

[0219] Step 5:

[0220] The server sends the generated G-code to the terminal. The terminal saves this G-code locally and prepares it for the subsequent printing process.

[0221] Step 6:

[0222] The user sends G-code to a 3D printer via a terminal to print out physical accessories. Based on instructions from the terminal, the printer generates objects according to the design.

[0223] Step 7:

[0224] Users receive printed accessories and attach them to their assistive devices. This allows the customized accessories to be used in a way that reflects the user's individuality and needs.

[0225] (Example 1)

[0226] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0227] There is a need for users to be able to easily and quickly generate customized assistive device accessories tailored to their individual needs. However, current technology lacks a way to efficiently translate users' specific design requirements into three-dimensional shapes and functions. As a result, it is difficult to accurately translate users' wishes into tangible forms, leading to a decrease in satisfaction.

[0228] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0229] In this invention, the server includes: a device means for acquiring user design requests; a device means for generating three-dimensional design information using a generation AI model based on the acquired design requests; and a device means for converting the generated three-dimensional design information into information for a visual reproduction device. This makes it possible to efficiently generate custom accessories that reflect the individual design requests of the user.

[0230] A "device for acquiring user design requests" is a device that provides an interface for users to input their design requests for customization and collects those requests as digital data.

[0231] A "generative AI model" is an artificial intelligence model that uses advanced algorithms to generate three-dimensional design data based on design requirements obtained from users.

[0232] "3D design information" refers to information about three-dimensional structures and shapes represented as digital data, and is fundamental data for reproducing physical objects.

[0233] A "device for converting information for visual reproduction devices" is a device that converts three-dimensional design information into a format that can be reproduced by a three-dimensional printing device, and prepares it as data for accurate printing.

[0234] A "device for generating physical accessories" is a device that uses information intended for visual reproduction devices to generate actual physical objects using equipment such as a three-dimensional printer.

[0235] This invention relates to a system that allows users to generate individualized auxiliary device accessories tailored to their specific needs. This system facilitates design customization and enables the rapid and accurate production of physical accessories.

[0236] First, the user launches a dedicated application on their device. This application provides a means for inputting design requests through a user interface. Users can input detailed design requests using text format or hand-drawn sketches available on the interface. An example of a prompt message could be, "Please create a flexible band with a red floral design."

[0237] Once the user has completed their input, the terminal sends the digital data of the design request to the server. The server uses a generative AI model to generate optimal 3D design information based on the user's request. This AI model, with its advanced algorithms, can quickly generate creative designs based on the provided prompt text.

[0238] Next, the server converts the 3D design information into information for visual reproduction devices, specifically G-code that can be understood by 3D printing devices. Dedicated data conversion software is used to prepare the design data for accurate printing. This conversion guarantees faithful reproduction of the design.

[0239] From this point onward, the user sends this G-code to a 3D printer via their terminal. The printer then accurately creates the physical accessory based on the specified visual features and shapes. The final product faithfully reproduces the user's desired colors and design patterns, and when attached to the assistive device, it becomes a practical and personalized accessory. For example, if a user customizes a band to attach to a leg cast, they can have it made blue with a star pattern as desired.

[0240] Thus, the present invention provides an effective means for accurately reflecting the user's design requirements and rapidly generating custom accessories. This greatly improves user satisfaction and convenience.

[0241] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0242] Step 1:

[0243] The user launches a dedicated application on their device and enters their design requests. At this time, the user can enter specific design prompts in text format or draw sketches using the app's hand-drawing function. The input may include specific design requests such as, "Please create a custom band with a blue floral design." This data is then output in digital format.

[0244] Step 2:

[0245] The terminal sends digital data of the design requests entered by the user to the server. The transmitted data includes text and sketch images. The server receives this data and prepares it for the subsequent design generation process. The input is the user's design request data, and the output is the data received by the server.

[0246] Step 3:

[0247] The server generates 3D design data using an AI model based on the received design data. The AI ​​model uses advanced algorithms to analyze the design based on the prompt text and generate data suitable for 3D design. The input is the user's prompt text and sketch data, and the output is 3D design data.

[0248] Step 4:

[0249] The server converts the generated 3D design data into G-code usable by a 3D printing device. Dedicated data conversion software is used to process the design data into a format that the printer can recognize. The input is 3D design data, and the output is G-code for the visual reproduction device.

[0250] Step 5:

[0251] The user sends a G-code to the 3D printer via a terminal to instruct it to print. The terminal checks the optimal printer settings and materials and prepares to start printing. The input is a G-code, and the output is a print instruction to the 3D printer.

[0252] Step 6:

[0253] The user operates the 3D printer to print the generated accessories. The printer accurately produces physical accessories based on the specified design. This allows the user to obtain original accessories that reflect their individual design requirements. The input is the print instructions, and the output is the physical product.

[0254] (Application Example 1)

[0255] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0256] Traditional customization of accessories for assistive devices presented challenges in instantly reflecting user requests, generating designs, and delivering products immediately, making on-the-spot service difficult. In particular, there was a lack of technology to reflect individual preferences in assistive device accessories while allowing customers to receive the finished product on the spot.

[0257] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0258] In this invention, the server includes means for acquiring the user's design requests, means for generating three-dimensional design data using a generation AI model based on the acquired design requests, and means for the user to generate the design data on the spot using a terminal at the store and receive the resulting product from a printing device. This makes it possible for the user to immediately receive a product that reflects their customized design at the store.

[0259] "Means of obtaining user design requests" refers to a method by which users input their wishes and requests regarding design through an interface, and the system receives that information.

[0260] "A method for generating three-dimensional design data using a generative AI model" refers to a method of generating a design as three-dimensional data using artificial intelligence based on user requests.

[0261] "Means for converting generated three-dimensional design data into data for a three-dimensional printing device" refers to a method for converting three-dimensional data created by AI into a specific data format that can be used by a printing device.

[0262] "Means for transmitting data for a 3D printing device to a printing device and generating physical equipment accessories" refers to a method of passing converted data to a printing device and thereby creating physical custom accessories.

[0263] "A means by which users generate design data on the spot using a terminal in a store and receive the printed product using a printing device" refers to a method in which users can create a design using a device installed in the store and immediately receive a product based on that design.

[0264] "A means by which users input handwritten requests using a user interface, and a means of realizing design generation that can be responded to immediately" refers to a method in which users can directly input handwritten design information and quickly create three-dimensional data based on it.

[0265] The system implementing this invention provides a platform for users to customize accessories for auxiliary devices in stores via an application installed on a terminal. The terminal has an interface for obtaining design requests from users and collects information through handwritten input and text input. These design requests are sent to a server and processed by a generative AI model. The generative AI model calculates the optimal design based on the requests and generates three-dimensional design data.

[0266] The server converts the generated 3D design data into data for 3D printing devices, i.e., G-code. This conversion utilizes OpenAI's GPT-3 model and other tools to transform the design information into data. The converted data is then transmitted via a terminal to a 3D printer installed within the store. Users can then instantly receive their custom-designed accessories from this printer.

[0267] For example, if a user wants to design a smartwatch band, they would use a terminal to select the band's color and pattern, and then input "Design a band with blue stripes." The AI ​​would process this as a prompt, and a band with the desired stripe pattern would be printed in the store.

[0268] This system allows users to instantly acquire products that reflect their individuality in stores and enjoy their uniqueness through that experience.

[0269] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0270] Step 1:

[0271] The user inputs design requests into the interface via a dedicated application on their device. The input includes specifications such as color, shape, and pattern. For example, a request might be "a band with blue stripes." Based on this, the device collects the request as text data.

[0272] Step 2:

[0273] The terminal sends the collected design requests to the server in data format. The server receives this text data and prepares to use the generating AI model. The server passes this data to the AI ​​model as a prompt message, requesting it to generate detailed 3D design information. Here, the input is the design request text from the user, and the output is the prompt message passed to the AI ​​model.

[0274] Step 3:

[0275] The generating AI model creates three-dimensional design data based on the prompt text. The AI ​​performs design calculations while considering the elements specified by the user. The server receives the three-dimensional design data obtained as output from the AI ​​model. The data obtained as output is detailed design information used in the next process.

[0276] Step 4:

[0277] The server converts the generated 3D design data into a data format (G-code) for 3D printing devices. Specifically, it performs a process to convert the design data into instructions that the printer can interpret. The input is 3D design data from the AI, and the output is a dataset in G-code format.

[0278] Step 5:

[0279] The server sends the converted G-code to the 3D printer in the store via a terminal. The terminal receives the G-code and passes it to the printer, instructing it to begin physical printing. Here, the input is the G-code, and the output is the actual print instruction.

[0280] Step 6:

[0281] The user receives a custom accessory printed using the store's 3D printer. The object is generated exactly according to the user's desired design, bringing their input to life as a physical product. The output resulting from this process is a unique product designed by the user.

[0282] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0283] The present invention relates to a system that utilizes an emotion engine for recognizing the user's emotion and generates a custom accessory that reflects the user's desires. This system not only performs physical customization but also creates a design considering the user's emotional state, thereby providing a more personalized experience.

[0284] First, the user inputs design desires using an application on the terminal. At the input stage, in addition to the text and sketches directly input by the user, an emotion engine that recognizes emotions in real time using a camera and sensors is operating. The emotion engine analyzes the user's facial expressions and voice tones and determines the current emotional state of the user. This emotional information is reflected in the color, shape, and pattern of the design.

[0285] The terminal organizes both the emotional information and the design desires and transmits them to the server. The server analyzes the received data and generates three-dimensional design data using a generation AI model. In this process, the AI model takes the emotional information into consideration and incorporates appropriate design elements into the data. For example, when the user is relaxed, a gentle color tone and a curvilinear design are applied. On the other hand, when an active emotion is recognized, bright colors and dynamic shapes are selected.

[0286] When the design data is completed, the server converts it into data for a three-dimensional printing device and sends it back to the terminal. The terminal locally stores this data and prepares to send it to the three-dimensional printer. At this stage, the user can actually print out the accessory.

[0287] The printed accessories are designed to be truly personalized, combining the user's emotions and desires. For example, if the system recognizes that the user is experiencing joy, bright, vibrant colors and colorful patterns will be reflected in the design. In this way, the present invention provides a new user experience that goes beyond a mere functional device by incorporating the user's emotions into the design.

[0288] The following describes the processing flow.

[0289] Step 1:

[0290] The user launches the application on their device and begins entering design requests. The device provides text fields and drawing tools for entering design requests, while the sentiment engine also runs in the background.

[0291] Step 2:

[0292] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and tone of voice. It then determines the user's emotional state and records this information as a log along with design requests.

[0293] Step 3:

[0294] The device sends data about the user's text input, sketches, and emotional state to the server. This transmission is performed using a secure protocol to protect the confidentiality of the data.

[0295] Step 4:

[0296] The server analyzes the received data and determines guidelines for customizing the design based on the acquired emotional information. The server then activates a generative AI model to generate three-dimensional design data, including design colors and forms that correspond to the user's emotions.

[0297] Step 5:

[0298] The server converts the generated 3D design data into G-code for 3D printing devices. The server then adjusts the data into a format that can be correctly executed by the printer and sends the data to the terminal.

[0299] Step 6:

[0300] The terminal receives the transmitted G-code and transfers it to the 3D printer. At this point, the user can verify that the specified design can be accurately printed.

[0301] Step 7:

[0302] Users receive printed accessories, and designs reflecting their emotions are applied to the assistive devices. Users then experience the customized designs, tailored to their own emotions and style, while utilizing the finished product.

[0303] (Example 2)

[0304] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0305] In today's world, there is a demand for the rapid and efficient delivery of customizable products that reflect the individuality and emotions of users. However, conventional systems fail to adequately reflect the emotional state of users, resulting in insufficient personalization accuracy.

[0306] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0307] In this invention, the server includes: means for recognizing the emotional state of the user using a camera and sensors and generating emotional information; means for generating three-dimensional design data using an AI model generated based on the obtained design requirements and emotional information; and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. By incorporating the emotional information of the user into the design, it becomes possible to generate more personalized products.

[0308] The "design requirements of the user" refers to the wishes and instructions regarding customization input by the user to the device.

[0309] The "emotional information" is data representing the current emotional state of the user and refers to the information generated by the emotion engine.

[0310] The "generative AI model" refers to an artificial intelligence algorithm that automatically generates designs or designs based on the provided data.

[0311] The "three-dimensional design data" refers to digital data created by the generative AI model to represent the shape and design in three-dimensional space.

[0312] The "data for a three-dimensional printing device" refers to digital design data converted into a format that can be used by a three-dimensional printing device.

[0313] The "printing device" refers to a device for generating a physical three-dimensional object based on three-dimensional printing data.

[0314] The "user interface" refers to a method or device for interaction for the user to input data to the system or check the output.

[0315] This invention is a system for generating custom accessories that reflect the user's emotional state. The user inputs their design requests through an application on their device. The input data is acquired via text, sketches, or camera, and an emotion engine is activated to analyze the user's emotions. This emotion engine uses the device's built-in camera and microphone to acquire emotional information from facial expressions and voice tone. It utilizes a facial recognition library and voice analysis tools in this process.

[0316] The acquired design requests and emotional information are organized by the terminal and sent to the server. The server generates 3D design data using a generative AI model. Based on the emotional and requested information, this model provides the optimal design using algorithms such as DALL-E or Stable Diffusion. A concrete example of a prompt might be an instruction such as, "Generate an accessory with a curved shape and calming colors that match a relaxed mood."

[0317] The server converts the generated 3D design data into a data format usable by 3D printers. CAD tools and 3D modeling software are used for this process. This converted data is then sent back to the terminal in real time.

[0318] Ultimately, the device sends the converted data to a 3D printer, which the user can then print out. The printed accessory becomes a unique item that reflects the user's individual emotions and desires. This allows users to have personalized accessories that resonate with their feelings on a daily basis.

[0319] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0320] Step 1:

[0321] The user launches the application on their device and enters their design requests. The input device used is either a keyboard or a touchscreen. The user uses text input or sketching functions to enter their design expectations and specific requests into the application. The input data obtained here serves as a basic design guideline and indicates preferred patterns.

[0322] Step 2:

[0323] The device activates an emotion engine to analyze the user's emotional state in real time. Using the camera and microphone, it captures data on the user's facial expressions and voice tone. This data is processed using a facial recognition library and voice analysis tools to determine the user's emotional state (e.g., relaxed, active, happy). The identified emotion is then used to reflect subsequent design elements.

[0324] Step 3:

[0325] The terminal integrates the acquired design requests and sentiment information and sends it to the server as a dataset. The transmitted data includes text instructions, sketch information, and sentiment information. This transmission is performed using a secure protocol (e.g., SSL). As output, this data is reliably delivered to the server.

[0326] Step 4:

[0327] The server generates 3D design data using a generative AI model based on the received data. The generative AI model takes text instructions and emotional information as prompts and creates appropriate design elements. For example, it might generate an accessory with a curved shape and calming colors to match a relaxed mood. The output is 3D design data with a custom design tailored to the user.

[0328] Step 5:

[0329] The server converts the generated 3D design data into a data format usable by a 3D printing device. CAD software or 3D modeling tools are used for this conversion. The converted data is sent to the terminal and saved locally. The output obtained through the conversion is a data file compatible with 3D printers.

[0330] Step 6:

[0331] The terminal starts the 3D printer preparation process based on the received data. The user can enter printout commands through the terminal's interface. Finally, the 3D printer creates a physical accessory. The output is a custom accessory based on the user's design and preferences.

[0332] (Application Example 2)

[0333] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0334] Modern consumers demand personalized, custom accessories, but traditional methods struggle to provide personalized designs that take into account the user's emotional state. Furthermore, it's difficult to create an immediate and intuitive shopping experience that responds to the user's mood. Therefore, there is a need to provide accessories that appropriately reflect the user's emotions.

[0335] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0336] In this invention, the server includes means for recognizing the user's emotional state, means for generating three-dimensional design data using an AI model based on the recognized emotional state and design requests, and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. This makes it possible to generate custom accessories that reflect the user's emotions in real time and to purchase them on the spot.

[0337] "Emotional state" refers to the user's current psychological and emotional state, analyzed from their facial expressions and tone of voice.

[0338] "Design requests" refer to design requirements for accessories, such as shape and color, specified by the user based on their own preferences and needs.

[0339] A "generative AI model" is a data generation algorithm that utilizes artificial intelligence technology to generate optimal three-dimensional design data based on emotional states and design requirements.

[0340] "Three-dimensional design data" refers to digital data generated by a generative AI model that describes the design of physical device accessories.

[0341] "Data for 3D printing equipment" refers to data that includes instructions necessary for a 3D printing equipment to generate a physical shape, based on 3D design data.

[0342] A "printing device" is a device that receives data for a three-dimensional printing device and actually outputs physical device accessories.

[0343] To implement this invention, a system is needed to analyze emotional states and generate custom accessories according to the user's design requests. The user's terminal is equipped with a camera and microphone for emotion recognition, thereby acquiring the user's emotional state in real time. The acquired emotional information and the design requests entered by the user are transmitted from the terminal to a server.

[0344] Based on this information, the server uses an advanced generative AI model to generate 3D design data. For example, if the user is relaxed, a design with calming colors will be applied. The server then uses the generated 3D design data to convert it into data for a 3D printer. The converted data is sent to the terminal, and ultimately, the 3D printer generates a physical custom accessory.

[0345] Specific hardware and software include devices such as smartphones and tablets, cloud-based emotion analysis software, generative AI models (e.g., DALL-E), and server systems for data conversion and transmission.

[0346] As a concrete example, suppose a user expresses feelings of excitement and joy while watching a sporting event. The design data generated using this information would be an accessory with vibrant colors and a dynamic shape.

[0347] An example of a prompt message would be: "The user is currently excited and in a state of joy. Generate a vibrant and lively design in response to this emotion."

[0348] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0349] Step 1:

[0350] The user uses a device to input design requests. During this process, the device uses its camera and microphone to capture the user's facial expressions and voice tone in real time, acquiring emotional data. The input consists of the user's specific requests (text and sketches) and emotional data, which are then used in the next step.

[0351] Step 2:

[0352] The terminal sends the acquired design requests and emotional data to the server. The emotional data reflects the user's current emotional state, and the server performs emotional analysis based on this data. As a result of the analysis, data indicating the emotional state is output.

[0353] Step 3:

[0354] The AI ​​model on the server generates three-dimensional design data based on the received emotional state and design request data. In this process, prompt sentences are given as input to the AI ​​model, and three-dimensional design data including colors and shapes corresponding to the emotions is output.

[0355] Step 4:

[0356] The server converts the generated 3D design data into data for use with a 3D printing device. Using 3D design data as input, the output is data in a format usable by the printing device.

[0357] Step 5:

[0358] The terminal locally stores the data for the 3D printer received from the server and sends it to the printer based on user instructions. At this stage, the data is converted into a physical shape, and a custom accessory is generated. The input is the stored data, and the output is a physical accessory customized by the user.

[0359] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0360] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0361] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0362] [Third Embodiment]

[0363] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0364] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0365] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0366] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0367] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0368] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0369] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0370] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0371] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0372] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0373] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0374] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0375] This invention relates to a system for generating custom accessories that allow users to personalize assistive devices. The system aims to create three-dimensional design data using AI technology based on the user's design requests, and then convert that data into an actual physical shape. Specific embodiments for carrying out this invention are described below.

[0376] First, the user launches a dedicated application on their device and enters their requirements for the assistive device they wish to customize. These requirements are entered using a text-based interface or a simple sketching interface. During this process, the user can specify details such as colors, shapes, and design patterns.

[0377] Once the user completes their input, the terminal sends the data to the server. The server receives this data and generates 3D design data through a generative AI model. This AI model has the ability to calculate and output the optimal design based on the user's requests. The generated design data is highly customized according to the user's desired style and aesthetic sense.

[0378] Next, the server converts the generated 3D design data into a data format usable by a 3D printing device, namely G-code. This conversion ensures the data is in a format that can be accurately reproduced by a 3D printer. The converted data is then sent to the terminal for subsequent processing.

[0379] Users send G-code to a 3D printer via their terminal, and the printer then prints out custom accessories based on the data. This printing process faithfully reproduces pre-specified colors and designs. Users receive the finished product and attach it to their assistive devices, resulting in practical and aesthetically pleasing assistive device accessories tailored to their individual needs.

[0380] For example, if a user wants to customize a band to attach to a leg cast, they can specify the desired color, such as blue, and even the pattern or design they want on the surface. The AI ​​model then designs and prints the band based on these specifications, which not only complements the function of the cast but also becomes a unique item that expresses the user's individuality.

[0381] Thus, the present invention not only extends the functionality of the device, but also provides a means for individual users to customize the auxiliary device to their liking, thereby improving the user experience.

[0382] The following describes the processing flow.

[0383] Step 1:

[0384] The user launches the application on their device and enters their design requests. The device provides text boxes and sketching functions for entering design requests, allowing the user to input desired colors, shapes, patterns, etc.

[0385] Step 2:

[0386] The terminal organizes the user's design requests from the input format and sends them to the server as digital data. Data transmission takes place in real time over the network, enabling rapid processing.

[0387] Step 3:

[0388] The server analyzes the received design requests and generates 3D design data using a generation AI model. Based on the user's specific requests, the server utilizes AI technology to construct an appropriate design.

[0389] Step 4:

[0390] The server converts the generated 3D design data into G-code for 3D printing devices. The server then uses a slicing engine to format this data into a format suitable for the printer.

[0391] Step 5:

[0392] The server sends the generated G-code to the terminal. The terminal saves this G-code locally and prepares it for the subsequent printing process.

[0393] Step 6:

[0394] The user sends G-code to a 3D printer via a terminal to print out physical accessories. Based on instructions from the terminal, the printer generates objects according to the design.

[0395] Step 7:

[0396] Users receive printed accessories and attach them to their assistive devices. This allows the customized accessories to be used in a way that reflects the user's individuality and needs.

[0397] (Example 1)

[0398] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0399] There is a need for users to be able to easily and quickly generate customized assistive device accessories tailored to their individual needs. However, current technology lacks a way to efficiently translate users' specific design requirements into three-dimensional shapes and functions. As a result, it is difficult to accurately translate users' wishes into tangible forms, leading to a decrease in satisfaction.

[0400] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0401] In this invention, the server includes: a device means for acquiring user design requests; a device means for generating three-dimensional design information using a generation AI model based on the acquired design requests; and a device means for converting the generated three-dimensional design information into information for a visual reproduction device. This makes it possible to efficiently generate custom accessories that reflect the individual design requests of the user.

[0402] A "device for acquiring user design requests" is a device that provides an interface for users to input their design requests for customization and collects those requests as digital data.

[0403] A "generative AI model" is an artificial intelligence model that uses advanced algorithms to generate three-dimensional design data based on design requirements obtained from users.

[0404] "3D design information" refers to information about three-dimensional structures and shapes represented as digital data, and is fundamental data for reproducing physical objects.

[0405] A "device for converting information for visual reproduction devices" is a device that converts three-dimensional design information into a format that can be reproduced by a three-dimensional printing device, and prepares it as data for accurate printing.

[0406] A "device for generating physical accessories" is a device that uses information intended for visual reproduction devices to generate actual physical objects using equipment such as a three-dimensional printer.

[0407] This invention relates to a system that allows users to generate individualized auxiliary device accessories tailored to their specific needs. This system facilitates design customization and enables the rapid and accurate production of physical accessories.

[0408] First, the user launches a dedicated application on their device. This application provides a means for inputting design requests through a user interface. Users can input detailed design requests using text format or hand-drawn sketches available on the interface. An example of a prompt message could be, "Please create a flexible band with a red floral design."

[0409] Once the user has completed their input, the terminal sends the digital data of the design request to the server. The server uses a generative AI model to generate optimal 3D design information based on the user's request. This AI model, with its advanced algorithms, can quickly generate creative designs based on the provided prompt text.

[0410] Next, the server converts the 3D design information into information for visual reproduction devices, specifically G-code that can be understood by 3D printing devices. Dedicated data conversion software is used to prepare the design data for accurate printing. This conversion guarantees faithful reproduction of the design.

[0411] From this point onward, the user sends this G-code to a 3D printer via their terminal. The printer then accurately creates the physical accessory based on the specified visual features and shapes. The final product faithfully reproduces the user's desired colors and design patterns, and when attached to the assistive device, it becomes a practical and personalized accessory. For example, if a user customizes a band to attach to a leg cast, they can have it made blue with a star pattern as desired.

[0412] Thus, the present invention provides an effective means for accurately reflecting the user's design requirements and rapidly generating custom accessories. This greatly improves user satisfaction and convenience.

[0413] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0414] Step 1:

[0415] The user launches a dedicated application on their device and enters their design requests. At this time, the user can enter specific design prompts in text format or draw sketches using the app's hand-drawing function. The input may include specific design requests such as, "Please create a custom band with a blue floral design." This data is then output in digital format.

[0416] Step 2:

[0417] The terminal sends digital data of the design requests entered by the user to the server. The transmitted data includes text and sketch images. The server receives this data and prepares it for the subsequent design generation process. The input is the user's design request data, and the output is the data received by the server.

[0418] Step 3:

[0419] The server generates 3D design data using an AI model based on the received design data. The AI ​​model uses advanced algorithms to analyze the design based on the prompt text and generate data suitable for 3D design. The input is the user's prompt text and sketch data, and the output is 3D design data.

[0420] Step 4:

[0421] The server converts the generated 3D design data into G-code usable by a 3D printing device. Dedicated data conversion software is used to process the design data into a format that the printer can recognize. The input is 3D design data, and the output is G-code for the visual reproduction device.

[0422] Step 5:

[0423] The user sends a G-code to the 3D printer via a terminal to instruct it to print. The terminal checks the optimal printer settings and materials and prepares to start printing. The input is a G-code, and the output is a print instruction to the 3D printer.

[0424] Step 6:

[0425] The user operates the 3D printer to print the generated accessories. The printer accurately produces physical accessories based on the specified design. This allows the user to obtain original accessories that reflect their individual design requirements. The input is the print instructions, and the output is the physical product.

[0426] (Application Example 1)

[0427] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0428] Traditional customization of accessories for assistive devices presented challenges in instantly reflecting user requests, generating designs, and delivering products immediately, making on-the-spot service difficult. In particular, there was a lack of technology to reflect individual preferences in assistive device accessories while allowing customers to receive the finished product on the spot.

[0429] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0430] In this invention, the server includes means for acquiring the user's design requests, means for generating three-dimensional design data using a generation AI model based on the acquired design requests, and means for the user to generate the design data on the spot using a terminal at the store and receive the resulting product from a printing device. This makes it possible for the user to immediately receive a product that reflects their customized design at the store.

[0431] "Means of obtaining user design requests" refers to a method by which users input their wishes and requests regarding design through an interface, and the system receives that information.

[0432] "A method for generating three-dimensional design data using a generative AI model" refers to a method of generating a design as three-dimensional data using artificial intelligence based on user requests.

[0433] "Means for converting generated three-dimensional design data into data for a three-dimensional printing device" refers to a method for converting three-dimensional data created by AI into a specific data format that can be used by a printing device.

[0434] "Means for transmitting data for a 3D printing device to a printing device and generating physical equipment accessories" refers to a method of passing converted data to a printing device and thereby creating physical custom accessories.

[0435] "A means by which users generate design data on the spot using a terminal in a store and receive the printed product using a printing device" refers to a method in which users can create a design using a device installed in the store and immediately receive a product based on that design.

[0436] "A means by which users input handwritten requests using a user interface, and a means of realizing design generation that can be responded to immediately" refers to a method in which users can directly input handwritten design information and quickly create three-dimensional data based on it.

[0437] The system implementing this invention provides a platform for users to customize accessories for auxiliary devices in stores via an application installed on a terminal. The terminal has an interface for obtaining design requests from users and collects information through handwritten input and text input. These design requests are sent to a server and processed by a generative AI model. The generative AI model calculates the optimal design based on the requests and generates three-dimensional design data.

[0438] The server converts the generated 3D design data into data for 3D printing devices, i.e., G-code. This conversion utilizes OpenAI's GPT-3 model and other tools to transform the design information into data. The converted data is then transmitted via a terminal to a 3D printer installed within the store. Users can then instantly receive their custom-designed accessories from this printer.

[0439] For example, if a user wants to design a smartwatch band, they would use a terminal to select the band's color and pattern, and then input "Design a band with blue stripes." The AI ​​would process this as a prompt, and a band with the desired stripe pattern would be printed in the store.

[0440] This system allows users to instantly acquire products that reflect their individuality in stores and enjoy their uniqueness through that experience.

[0441] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0442] Step 1:

[0443] The user inputs design requests into the interface via a dedicated application on their device. The input includes specifications such as color, shape, and pattern. For example, a request might be "a band with blue stripes." Based on this, the device collects the request as text data.

[0444] Step 2:

[0445] The terminal sends the collected design requests to the server in data format. The server receives this text data and prepares to use the generating AI model. The server passes this data to the AI ​​model as a prompt message, requesting it to generate detailed 3D design information. Here, the input is the design request text from the user, and the output is the prompt message passed to the AI ​​model.

[0446] Step 3:

[0447] The generating AI model creates three-dimensional design data based on the prompt text. The AI ​​performs design calculations while considering the elements specified by the user. The server receives the three-dimensional design data obtained as output from the AI ​​model. The data obtained as output is detailed design information used in the next process.

[0448] Step 4:

[0449] The server converts the generated 3D design data into a data format (G-code) for 3D printing devices. Specifically, it performs a process to convert the design data into instructions that the printer can interpret. The input is 3D design data from the AI, and the output is a dataset in G-code format.

[0450] Step 5:

[0451] The server sends the converted G-code to the 3D printer in the store via a terminal. The terminal receives the G-code and passes it to the printer, instructing it to begin physical printing. Here, the input is the G-code, and the output is the actual print instruction.

[0452] Step 6:

[0453] The user receives a custom accessory printed using the store's 3D printer. The object is generated exactly according to the user's desired design, bringing their input to life as a physical product. The output resulting from this process is a unique product designed by the user.

[0454] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0455] This invention relates to a system that utilizes an emotion engine to recognize user emotions and generate custom accessories that reflect user requests. This system not only performs physical customization but also provides a more personalized experience by creating designs that take into account the user's emotional state.

[0456] First, users input their design requests using an application on their device. During the input stage, in addition to the text and sketches directly entered by the user, an emotion engine operates that recognizes emotions in real time using the camera and sensors. The emotion engine analyzes the user's facial expressions and voice tone to determine the user's current emotional state. This emotional information is then reflected in the design's colors, shapes, and patterns.

[0457] The device organizes both emotional information and design requests and sends them to the server. The server analyzes the received data and generates 3D design data using a generative AI model. In this process, the AI ​​model takes emotional information into account and incorporates appropriate design elements into the data. For example, if the user is relaxed, calm colors and curvilinear designs will be applied. On the other hand, if an active emotion is recognized, vibrant colors and dynamic shapes will be selected.

[0458] Once the design data is complete, the server converts it into data for use with a 3D printer and sends it back to the terminal. The terminal saves this data locally and prepares to send it to the 3D printer. At this stage, the user can actually print out the accessory.

[0459] The printed accessories are designed to be truly personalized, combining the user's emotions and desires. For example, if the system recognizes that the user is experiencing joy, bright, vibrant colors and colorful patterns will be reflected in the design. In this way, the present invention provides a new user experience that goes beyond a mere functional device by incorporating the user's emotions into the design.

[0460] The following describes the processing flow.

[0461] Step 1:

[0462] The user launches the application on their device and begins entering design requests. The device provides text fields and drawing tools for entering design requests, while the sentiment engine also runs in the background.

[0463] Step 2:

[0464] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and tone of voice. It then determines the user's emotional state and records this information as a log along with design requests.

[0465] Step 3:

[0466] The device sends data about the user's text input, sketches, and emotional state to the server. This transmission is performed using a secure protocol to protect the confidentiality of the data.

[0467] Step 4:

[0468] The server analyzes the received data and determines guidelines for customizing the design based on the acquired emotional information. The server then activates a generative AI model to generate three-dimensional design data, including design colors and forms that correspond to the user's emotions.

[0469] Step 5:

[0470] The server converts the generated 3D design data into G-code for 3D printing devices. The server then adjusts the data into a format that can be correctly executed by the printer and sends the data to the terminal.

[0471] Step 6:

[0472] The terminal receives the transmitted G-code and transfers it to the 3D printer. At this point, the user can verify that the specified design can be accurately printed.

[0473] Step 7:

[0474] Users receive printed accessories, and designs reflecting their emotions are applied to the assistive devices. Users then experience the customized designs, tailored to their own emotions and style, while utilizing the finished product.

[0475] (Example 2)

[0476] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0477] In today's world, there is a demand for the rapid and efficient delivery of customizable products that reflect the individuality and emotions of users. However, conventional systems fail to adequately reflect the emotional state of users, resulting in insufficient personalization accuracy.

[0478] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0479] In this invention, the server includes means for recognizing the user's emotional state using a camera and sensors and generating emotional information; means for generating three-dimensional design data using a generation AI model based on the acquired design requests and emotional information; and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. This makes it possible to create more personalized products by incorporating the user's emotional information into the design.

[0480] "User design requests" refer to the customization preferences and instructions that users input for the device.

[0481] "Emotional information" refers to data that represents the user's current emotional state, and is information generated by the emotion engine.

[0482] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates designs and plans based on the data provided.

[0483] "Three-dimensional design data" refers to digital data created by a generative AI model to represent the shape and design in three-dimensional space.

[0484] "Data for 3D printing equipment" refers to digital design data that has been converted into a format usable by 3D printing equipment.

[0485] A "printing device" refers to a device used to generate physical three-dimensional objects based on three-dimensional printing data.

[0486] A "user interface" refers to a method or device of interaction that allows a user to input data into a system or to view its output.

[0487] This invention is a system for generating custom accessories that reflect the user's emotional state. The user inputs their design requests through an application on their device. The input data is acquired via text, sketches, or camera, and an emotion engine is activated to analyze the user's emotions. This emotion engine uses the device's built-in camera and microphone to acquire emotional information from facial expressions and voice tone. It utilizes a facial recognition library and voice analysis tools in this process.

[0488] The acquired design requests and emotional information are organized by the terminal and sent to the server. The server generates 3D design data using a generative AI model. Based on the emotional and requested information, this model provides the optimal design using algorithms such as DALL-E or Stable Diffusion. A concrete example of a prompt might be an instruction such as, "Generate an accessory with a curved shape and calming colors that match a relaxed mood."

[0489] The server converts the generated 3D design data into a data format usable by 3D printers. CAD tools and 3D modeling software are used for this process. This converted data is then sent back to the terminal in real time.

[0490] Ultimately, the device sends the converted data to a 3D printer, which the user can then print out. The printed accessory becomes a unique item that reflects the user's individual emotions and desires. This allows users to have personalized accessories that resonate with their feelings on a daily basis.

[0491] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0492] Step 1:

[0493] The user launches the application on their device and enters their design requests. The input device used is either a keyboard or a touchscreen. The user uses text input or sketching functions to enter their design expectations and specific requests into the application. The input data obtained here serves as a basic design guideline and indicates preferred patterns.

[0494] Step 2:

[0495] The device activates an emotion engine to analyze the user's emotional state in real time. Using the camera and microphone, it captures data on the user's facial expressions and voice tone. This data is processed using a facial recognition library and voice analysis tools to determine the user's emotional state (e.g., relaxed, active, happy). The identified emotion is then used to reflect subsequent design elements.

[0496] Step 3:

[0497] The terminal integrates the acquired design requests and sentiment information and sends it to the server as a dataset. The transmitted data includes text instructions, sketch information, and sentiment information. This transmission is performed using a secure protocol (e.g., SSL). As output, this data is reliably delivered to the server.

[0498] Step 4:

[0499] The server generates 3D design data using a generative AI model based on the received data. The generative AI model takes text instructions and emotional information as prompts and creates appropriate design elements. For example, it might generate an accessory with a curved shape and calming colors to match a relaxed mood. The output is 3D design data with a custom design tailored to the user.

[0500] Step 5:

[0501] The server converts the generated 3D design data into a data format usable by a 3D printing device. CAD software or 3D modeling tools are used for this conversion. The converted data is sent to the terminal and saved locally. The output obtained through the conversion is a data file compatible with 3D printers.

[0502] Step 6:

[0503] The terminal starts the 3D printer preparation process based on the received data. The user can enter printout commands through the terminal's interface. Finally, the 3D printer creates a physical accessory. The output is a custom accessory based on the user's design and preferences.

[0504] (Application Example 2)

[0505] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0506] Modern consumers demand personalized, custom accessories, but traditional methods struggle to provide personalized designs that take into account the user's emotional state. Furthermore, it's difficult to create an immediate and intuitive shopping experience that responds to the user's mood. Therefore, there is a need to provide accessories that appropriately reflect the user's emotions.

[0507] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0508] In this invention, the server includes means for recognizing the user's emotional state, means for generating three-dimensional design data using an AI model based on the recognized emotional state and design requests, and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. This makes it possible to generate custom accessories that reflect the user's emotions in real time and to purchase them on the spot.

[0509] "Emotional state" refers to the user's current psychological and emotional state, analyzed from their facial expressions and tone of voice.

[0510] "Design requests" refer to design requirements for accessories, such as shape and color, specified by the user based on their own preferences and needs.

[0511] A "generative AI model" is a data generation algorithm that utilizes artificial intelligence technology to generate optimal three-dimensional design data based on emotional states and design requirements.

[0512] "Three-dimensional design data" refers to digital data generated by a generative AI model that describes the design of physical device accessories.

[0513] "Data for 3D printing equipment" refers to data that includes instructions necessary for a 3D printing equipment to generate a physical shape, based on 3D design data.

[0514] A "printing device" is a device that receives data for a three-dimensional printing device and actually outputs physical device accessories.

[0515] To implement this invention, a system is needed to analyze emotional states and generate custom accessories according to the user's design requests. The user's terminal is equipped with a camera and microphone for emotion recognition, thereby acquiring the user's emotional state in real time. The acquired emotional information and the design requests entered by the user are transmitted from the terminal to a server.

[0516] Based on this information, the server uses an advanced generative AI model to generate 3D design data. For example, if the user is relaxed, a design with calming colors will be applied. The server then uses the generated 3D design data to convert it into data for a 3D printer. The converted data is sent to the terminal, and ultimately, the 3D printer generates a physical custom accessory.

[0517] Specific hardware and software include devices such as smartphones and tablets, cloud-based emotion analysis software, generative AI models (e.g., DALL-E), and server systems for data conversion and transmission.

[0518] As a concrete example, suppose a user expresses feelings of excitement and joy while watching a sporting event. The design data generated using this information would be an accessory with vibrant colors and a dynamic shape.

[0519] An example of a prompt message would be: "The user is currently excited and in a state of joy. Generate a vibrant and lively design in response to this emotion."

[0520] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0521] Step 1:

[0522] The user uses a device to input design requests. During this process, the device uses its camera and microphone to capture the user's facial expressions and voice tone in real time, acquiring emotional data. The input consists of the user's specific requests (text and sketches) and emotional data, which are then used in the next step.

[0523] Step 2:

[0524] The terminal sends the acquired design requests and emotional data to the server. The emotional data reflects the user's current emotional state, and the server performs emotional analysis based on this data. As a result of the analysis, data indicating the emotional state is output.

[0525] Step 3:

[0526] The AI ​​model on the server generates three-dimensional design data based on the received emotional state and design request data. In this process, prompt sentences are given as input to the AI ​​model, and three-dimensional design data including colors and shapes corresponding to the emotions is output.

[0527] Step 4:

[0528] The server converts the generated 3D design data into data for use with a 3D printing device. Using 3D design data as input, the output is data in a format usable by the printing device.

[0529] Step 5:

[0530] The terminal locally stores the data for the 3D printer received from the server and sends it to the printer based on user instructions. At this stage, the data is converted into a physical shape, and a custom accessory is generated. The input is the stored data, and the output is a physical accessory customized by the user.

[0531] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0532] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0533] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0534] [Fourth Embodiment]

[0535] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0536] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0537] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0538] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0539] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0540] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0541] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0542] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0543] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0544] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0545] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0546] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0547] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0548] This invention relates to a system for generating custom accessories that allow users to personalize assistive devices. The system aims to create three-dimensional design data using AI technology based on the user's design requests, and then convert that data into an actual physical shape. Specific embodiments for carrying out this invention are described below.

[0549] First, the user launches a dedicated application on their device and enters their requirements for the assistive device they wish to customize. These requirements are entered using a text-based interface or a simple sketching interface. During this process, the user can specify details such as colors, shapes, and design patterns.

[0550] Once the user completes their input, the terminal sends the data to the server. The server receives this data and generates 3D design data through a generative AI model. This AI model has the ability to calculate and output the optimal design based on the user's requests. The generated design data is highly customized according to the user's desired style and aesthetic sense.

[0551] Next, the server converts the generated 3D design data into a data format usable by a 3D printing device, namely G-code. This conversion ensures the data is in a format that can be accurately reproduced by a 3D printer. The converted data is then sent to the terminal for subsequent processing.

[0552] Users send G-code to a 3D printer via their terminal, and the printer then prints out custom accessories based on the data. This printing process faithfully reproduces pre-specified colors and designs. Users receive the finished product and attach it to their assistive devices, resulting in practical and aesthetically pleasing assistive device accessories tailored to their individual needs.

[0553] For example, if a user wants to customize a band to attach to a leg cast, they can specify the desired color, such as blue, and even the pattern or design they want on the surface. The AI ​​model then designs and prints the band based on these specifications, which not only complements the function of the cast but also becomes a unique item that expresses the user's individuality.

[0554] Thus, the present invention not only extends the functionality of the device, but also provides a means for individual users to customize the auxiliary device to their liking, thereby improving the user experience.

[0555] The following describes the processing flow.

[0556] Step 1:

[0557] The user launches the application on their device and enters their design requests. The device provides text boxes and sketching functions for entering design requests, allowing the user to input desired colors, shapes, patterns, etc.

[0558] Step 2:

[0559] The terminal organizes the user's design requests from the input format and sends them to the server as digital data. Data transmission takes place in real time over the network, enabling rapid processing.

[0560] Step 3:

[0561] The server analyzes the received design requests and generates 3D design data using a generation AI model. Based on the user's specific requests, the server utilizes AI technology to construct an appropriate design.

[0562] Step 4:

[0563] The server converts the generated 3D design data into G-code for 3D printing devices. The server then uses a slicing engine to format this data into a format suitable for the printer.

[0564] Step 5:

[0565] The server sends the generated G-code to the terminal. The terminal saves this G-code locally and prepares it for the subsequent printing process.

[0566] Step 6:

[0567] The user sends G-code to a 3D printer via a terminal to print out physical accessories. Based on instructions from the terminal, the printer generates objects according to the design.

[0568] Step 7:

[0569] Users receive printed accessories and attach them to their assistive devices. This allows the customized accessories to be used in a way that reflects the user's individuality and needs.

[0570] (Example 1)

[0571] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0572] There is a need for users to be able to easily and quickly generate customized assistive device accessories tailored to their individual needs. However, current technology lacks a way to efficiently translate users' specific design requirements into three-dimensional shapes and functions. As a result, it is difficult to accurately translate users' wishes into tangible forms, leading to a decrease in satisfaction.

[0573] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0574] In this invention, the server includes: a device means for acquiring user design requests; a device means for generating three-dimensional design information using a generation AI model based on the acquired design requests; and a device means for converting the generated three-dimensional design information into information for a visual reproduction device. This makes it possible to efficiently generate custom accessories that reflect the individual design requests of the user.

[0575] A "device for acquiring user design requests" is a device that provides an interface for users to input their design requests for customization and collects those requests as digital data.

[0576] A "generative AI model" is an artificial intelligence model that uses advanced algorithms to generate three-dimensional design data based on design requirements obtained from users.

[0577] "3D design information" refers to information about three-dimensional structures and shapes represented as digital data, and is fundamental data for reproducing physical objects.

[0578] A "device for converting information for visual reproduction devices" is a device that converts three-dimensional design information into a format that can be reproduced by a three-dimensional printing device, and prepares it as data for accurate printing.

[0579] A "device for generating physical accessories" is a device that uses information intended for visual reproduction devices to generate actual physical objects using equipment such as a three-dimensional printer.

[0580] This invention relates to a system that allows users to generate individualized auxiliary device accessories tailored to their specific needs. This system facilitates design customization and enables the rapid and accurate production of physical accessories.

[0581] First, the user launches a dedicated application on their device. This application provides a means for inputting design requests through a user interface. Users can input detailed design requests using text format or hand-drawn sketches available on the interface. An example of a prompt message could be, "Please create a flexible band with a red floral design."

[0582] Once the user has completed their input, the terminal sends the digital data of the design request to the server. The server uses a generative AI model to generate optimal 3D design information based on the user's request. This AI model, with its advanced algorithms, can quickly generate creative designs based on the provided prompt text.

[0583] Next, the server converts the 3D design information into information for visual reproduction devices, specifically G-code that can be understood by 3D printing devices. Dedicated data conversion software is used to prepare the design data for accurate printing. This conversion guarantees faithful reproduction of the design.

[0584] From this point onward, the user sends this G-code to a 3D printer via their terminal. The printer then accurately creates the physical accessory based on the specified visual features and shapes. The final product faithfully reproduces the user's desired colors and design patterns, and when attached to the assistive device, it becomes a practical and personalized accessory. For example, if a user customizes a band to attach to a leg cast, they can have it made blue with a star pattern as desired.

[0585] Thus, the present invention provides an effective means for accurately reflecting the user's design requirements and rapidly generating custom accessories. This greatly improves user satisfaction and convenience.

[0586] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0587] Step 1:

[0588] The user launches a dedicated application on their device and enters their design requests. At this time, the user can enter specific design prompts in text format or draw sketches using the app's hand-drawing function. The input may include specific design requests such as, "Please create a custom band with a blue floral design." This data is then output in digital format.

[0589] Step 2:

[0590] The terminal sends digital data of the design requests entered by the user to the server. The transmitted data includes text and sketch images. The server receives this data and prepares it for the subsequent design generation process. The input is the user's design request data, and the output is the data received by the server.

[0591] Step 3:

[0592] The server generates 3D design data using an AI model based on the received design data. The AI ​​model uses advanced algorithms to analyze the design based on the prompt text and generate data suitable for 3D design. The input is the user's prompt text and sketch data, and the output is 3D design data.

[0593] Step 4:

[0594] The server converts the generated 3D design data into G-code usable by a 3D printing device. Dedicated data conversion software is used to process the design data into a format that the printer can recognize. The input is 3D design data, and the output is G-code for the visual reproduction device.

[0595] Step 5:

[0596] The user sends a G-code to the 3D printer via a terminal to instruct it to print. The terminal checks the optimal printer settings and materials and prepares to start printing. The input is a G-code, and the output is a print instruction to the 3D printer.

[0597] Step 6:

[0598] The user operates the 3D printer to print the generated accessories. The printer accurately produces physical accessories based on the specified design. This allows the user to obtain original accessories that reflect their individual design requirements. The input is the print instructions, and the output is the physical product.

[0599] (Application Example 1)

[0600] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0601] Traditional customization of accessories for assistive devices presented challenges in instantly reflecting user requests, generating designs, and delivering products immediately, making on-the-spot service difficult. In particular, there was a lack of technology to reflect individual preferences in assistive device accessories while allowing customers to receive the finished product on the spot.

[0602] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0603] In this invention, the server includes means for acquiring the user's design requests, means for generating three-dimensional design data using a generation AI model based on the acquired design requests, and means for the user to generate the design data on the spot using a terminal at the store and receive the resulting product from a printing device. This makes it possible for the user to immediately receive a product that reflects their customized design at the store.

[0604] "Means of obtaining user design requests" refers to a method by which users input their wishes and requests regarding design through an interface, and the system receives that information.

[0605] "A method for generating three-dimensional design data using a generative AI model" refers to a method of generating a design as three-dimensional data using artificial intelligence based on user requests.

[0606] "Means for converting generated three-dimensional design data into data for a three-dimensional printing device" refers to a method for converting three-dimensional data created by AI into a specific data format that can be used by a printing device.

[0607] "Means for transmitting data for a 3D printing device to a printing device and generating physical equipment accessories" refers to a method of passing converted data to a printing device and thereby creating physical custom accessories.

[0608] "A means by which users generate design data on the spot using a terminal in a store and receive the printed product using a printing device" refers to a method in which users can create a design using a device installed in the store and immediately receive a product based on that design.

[0609] "A means by which users input handwritten requests using a user interface, and a means of realizing design generation that can be responded to immediately" refers to a method in which users can directly input handwritten design information and quickly create three-dimensional data based on it.

[0610] The system implementing this invention provides a platform for users to customize accessories for auxiliary devices in stores via an application installed on a terminal. The terminal has an interface for obtaining design requests from users and collects information through handwritten input and text input. These design requests are sent to a server and processed by a generative AI model. The generative AI model calculates the optimal design based on the requests and generates three-dimensional design data.

[0611] The server converts the generated 3D design data into data for 3D printing devices, i.e., G-code. This conversion utilizes OpenAI's GPT-3 model and other tools to transform the design information into data. The converted data is then transmitted via a terminal to a 3D printer installed within the store. Users can then instantly receive their custom-designed accessories from this printer.

[0612] For example, if a user wants to design a smartwatch band, they would use a terminal to select the band's color and pattern, and then input "Design a band with blue stripes." The AI ​​would process this as a prompt, and a band with the desired stripe pattern would be printed in the store.

[0613] This system allows users to instantly acquire products that reflect their individuality in stores and enjoy their uniqueness through that experience.

[0614] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0615] Step 1:

[0616] The user inputs design requests into the interface via a dedicated application on their device. The input includes specifications such as color, shape, and pattern. For example, a request might be "a band with blue stripes." Based on this, the device collects the request as text data.

[0617] Step 2:

[0618] The terminal sends the collected design requests to the server in data format. The server receives this text data and prepares to use the generating AI model. The server passes this data to the AI ​​model as a prompt message, requesting it to generate detailed 3D design information. Here, the input is the design request text from the user, and the output is the prompt message passed to the AI ​​model.

[0619] Step 3:

[0620] The generating AI model creates three-dimensional design data based on the prompt text. The AI ​​performs design calculations while considering the elements specified by the user. The server receives the three-dimensional design data obtained as output from the AI ​​model. The data obtained as output is detailed design information used in the next process.

[0621] Step 4:

[0622] The server converts the generated 3D design data into a data format (G-code) for 3D printing devices. Specifically, it performs a process to convert the design data into instructions that the printer can interpret. The input is 3D design data from the AI, and the output is a dataset in G-code format.

[0623] Step 5:

[0624] The server sends the converted G-code to the 3D printer in the store via a terminal. The terminal receives the G-code and passes it to the printer, instructing it to begin physical printing. Here, the input is the G-code, and the output is the actual print instruction.

[0625] Step 6:

[0626] The user receives a custom accessory printed using the store's 3D printer. The object is generated exactly according to the user's desired design, bringing their input to life as a physical product. The output resulting from this process is a unique product designed by the user.

[0627] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0628] This invention relates to a system that utilizes an emotion engine to recognize user emotions and generate custom accessories that reflect user requests. This system not only performs physical customization but also provides a more personalized experience by creating designs that take into account the user's emotional state.

[0629] First, users input their design requests using an application on their device. During the input stage, in addition to the text and sketches directly entered by the user, an emotion engine operates that recognizes emotions in real time using the camera and sensors. The emotion engine analyzes the user's facial expressions and voice tone to determine the user's current emotional state. This emotional information is then reflected in the design's colors, shapes, and patterns.

[0630] The device organizes both emotional information and design requests and sends them to the server. The server analyzes the received data and generates 3D design data using a generative AI model. In this process, the AI ​​model takes emotional information into account and incorporates appropriate design elements into the data. For example, if the user is relaxed, calm colors and curvilinear designs will be applied. On the other hand, if an active emotion is recognized, vibrant colors and dynamic shapes will be selected.

[0631] Once the design data is complete, the server converts it into data for use with a 3D printer and sends it back to the terminal. The terminal saves this data locally and prepares to send it to the 3D printer. At this stage, the user can actually print out the accessory.

[0632] The printed accessories are designed to be truly personalized, combining the user's emotions and desires. For example, if the system recognizes that the user is experiencing joy, bright, vibrant colors and colorful patterns will be reflected in the design. In this way, the present invention provides a new user experience that goes beyond a mere functional device by incorporating the user's emotions into the design.

[0633] The following describes the processing flow.

[0634] Step 1:

[0635] The user launches the application on their device and begins entering design requests. The device provides text fields and drawing tools for entering design requests, while the sentiment engine also runs in the background.

[0636] Step 2:

[0637] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and tone of voice. It then determines the user's emotional state and records this information as a log along with design requests.

[0638] Step 3:

[0639] The device sends data about the user's text input, sketches, and emotional state to the server. This transmission is performed using a secure protocol to protect the confidentiality of the data.

[0640] Step 4:

[0641] The server analyzes the received data and determines guidelines for customizing the design based on the acquired emotional information. The server then activates a generative AI model to generate three-dimensional design data, including design colors and forms that correspond to the user's emotions.

[0642] Step 5:

[0643] The server converts the generated 3D design data into G-code for 3D printing devices. The server then adjusts the data into a format that can be correctly executed by the printer and sends the data to the terminal.

[0644] Step 6:

[0645] The terminal receives the transmitted G-code and transfers it to the 3D printer. At this point, the user can verify that the specified design can be accurately printed.

[0646] Step 7:

[0647] Users receive printed accessories, and designs reflecting their emotions are applied to the assistive devices. Users then experience the customized designs, tailored to their own emotions and style, while utilizing the finished product.

[0648] (Example 2)

[0649] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0650] In today's world, there is a demand for the rapid and efficient delivery of customizable products that reflect the individuality and emotions of users. However, conventional systems fail to adequately reflect the emotional state of users, resulting in insufficient personalization accuracy.

[0651] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0652] In this invention, the server includes means for recognizing the user's emotional state using a camera and sensors and generating emotional information; means for generating three-dimensional design data using a generation AI model based on the acquired design requests and emotional information; and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. This makes it possible to create more personalized products by incorporating the user's emotional information into the design.

[0653] "User design requests" refer to the customization preferences and instructions that users input for the device.

[0654] "Emotional information" refers to data that represents the user's current emotional state, and is information generated by the emotion engine.

[0655] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates designs and plans based on the data provided.

[0656] "Three-dimensional design data" refers to digital data created by a generative AI model to represent the shape and design in three-dimensional space.

[0657] "Data for 3D printing equipment" refers to digital design data that has been converted into a format usable by 3D printing equipment.

[0658] A "printing device" refers to a device used to generate physical three-dimensional objects based on three-dimensional printing data.

[0659] A "user interface" refers to a method or device of interaction that allows a user to input data into a system or to view its output.

[0660] This invention is a system for generating custom accessories that reflect the user's emotional state. The user inputs their design requests through an application on their device. The input data is acquired via text, sketches, or camera, and an emotion engine is activated to analyze the user's emotions. This emotion engine uses the device's built-in camera and microphone to acquire emotional information from facial expressions and voice tone. It utilizes a facial recognition library and voice analysis tools in this process.

[0661] The acquired design requests and emotional information are organized by the terminal and sent to the server. The server generates 3D design data using a generative AI model. Based on the emotional and requested information, this model provides the optimal design using algorithms such as DALL-E or Stable Diffusion. A concrete example of a prompt might be an instruction such as, "Generate an accessory with a curved shape and calming colors that match a relaxed mood."

[0662] The server converts the generated 3D design data into a data format usable by 3D printers. CAD tools and 3D modeling software are used for this process. This converted data is then sent back to the terminal in real time.

[0663] Ultimately, the device sends the converted data to a 3D printer, which the user can then print out. The printed accessory becomes a unique item that reflects the user's individual emotions and desires. This allows users to have personalized accessories that resonate with their feelings on a daily basis.

[0664] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0665] Step 1:

[0666] The user launches the application on their device and enters their design requests. The input device used is either a keyboard or a touchscreen. The user uses text input or sketching functions to enter their design expectations and specific requests into the application. The input data obtained here serves as a basic design guideline and indicates preferred patterns.

[0667] Step 2:

[0668] The device activates an emotion engine to analyze the user's emotional state in real time. Using the camera and microphone, it captures data on the user's facial expressions and voice tone. This data is processed using a facial recognition library and voice analysis tools to determine the user's emotional state (e.g., relaxed, active, happy). The identified emotion is then used to reflect subsequent design elements.

[0669] Step 3:

[0670] The terminal integrates the acquired design requests and sentiment information and sends it to the server as a dataset. The transmitted data includes text instructions, sketch information, and sentiment information. This transmission is performed using a secure protocol (e.g., SSL). As output, this data is reliably delivered to the server.

[0671] Step 4:

[0672] The server generates 3D design data using a generative AI model based on the received data. The generative AI model takes text instructions and emotional information as prompts and creates appropriate design elements. For example, it might generate an accessory with a curved shape and calming colors to match a relaxed mood. The output is 3D design data with a custom design tailored to the user.

[0673] Step 5:

[0674] The server converts the generated 3D design data into a data format usable by a 3D printing device. CAD software or 3D modeling tools are used for this conversion. The converted data is sent to the terminal and saved locally. The output obtained through the conversion is a data file compatible with 3D printers.

[0675] Step 6:

[0676] The terminal starts the 3D printer preparation process based on the received data. The user can enter printout commands through the terminal's interface. Finally, the 3D printer creates a physical accessory. The output is a custom accessory based on the user's design and preferences.

[0677] (Application Example 2)

[0678] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0679] Modern consumers demand personalized, custom accessories, but traditional methods struggle to provide personalized designs that take into account the user's emotional state. Furthermore, it's difficult to create an immediate and intuitive shopping experience that responds to the user's mood. Therefore, there is a need to provide accessories that appropriately reflect the user's emotions.

[0680] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0681] In this invention, the server includes means for recognizing the user's emotional state, means for generating three-dimensional design data using an AI model based on the recognized emotional state and design requests, and means for converting the generated three-dimensional design data into data for a three-dimensional printing device. This makes it possible to generate custom accessories that reflect the user's emotions in real time and to purchase them on the spot.

[0682] "Emotional state" refers to the user's current psychological and emotional state, analyzed from their facial expressions and tone of voice.

[0683] "Design requests" refer to design requirements for accessories, such as shape and color, specified by the user based on their own preferences and needs.

[0684] A "generative AI model" is a data generation algorithm that utilizes artificial intelligence technology to generate optimal three-dimensional design data based on emotional states and design requirements.

[0685] "Three-dimensional design data" refers to digital data generated by a generative AI model that describes the design of physical device accessories.

[0686] "Data for 3D printing equipment" refers to data that includes instructions necessary for a 3D printing equipment to generate a physical shape, based on 3D design data.

[0687] A "printing device" is a device that receives data for a three-dimensional printing device and actually outputs physical device accessories.

[0688] To implement this invention, a system is needed to analyze emotional states and generate custom accessories according to the user's design requests. The user's terminal is equipped with a camera and microphone for emotion recognition, thereby acquiring the user's emotional state in real time. The acquired emotional information and the design requests entered by the user are transmitted from the terminal to a server.

[0689] Based on this information, the server uses an advanced generative AI model to generate 3D design data. For example, if the user is relaxed, a design with calming colors will be applied. The server then uses the generated 3D design data to convert it into data for a 3D printer. The converted data is sent to the terminal, and ultimately, the 3D printer generates a physical custom accessory.

[0690] Specific hardware and software include devices such as smartphones and tablets, cloud-based emotion analysis software, generative AI models (e.g., DALL-E), and server systems for data conversion and transmission.

[0691] As a concrete example, suppose a user expresses feelings of excitement and joy while watching a sporting event. The design data generated using this information would be an accessory with vibrant colors and a dynamic shape.

[0692] An example of a prompt message would be: "The user is currently excited and in a state of joy. Generate a vibrant and lively design in response to this emotion."

[0693] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0694] Step 1:

[0695] The user uses a device to input design requests. During this process, the device uses its camera and microphone to capture the user's facial expressions and voice tone in real time, acquiring emotional data. The input consists of the user's specific requests (text and sketches) and emotional data, which are then used in the next step.

[0696] Step 2:

[0697] The terminal sends the acquired design requests and emotional data to the server. The emotional data reflects the user's current emotional state, and the server performs emotional analysis based on this data. As a result of the analysis, data indicating the emotional state is output.

[0698] Step 3:

[0699] The AI ​​model on the server generates three-dimensional design data based on the received emotional state and design request data. In this process, prompt sentences are given as input to the AI ​​model, and three-dimensional design data including colors and shapes corresponding to the emotions is output.

[0700] Step 4:

[0701] The server converts the generated 3D design data into data for use with a 3D printing device. Using 3D design data as input, the output is data in a format usable by the printing device.

[0702] Step 5:

[0703] The terminal locally stores the data for the 3D printer received from the server and sends it to the printer based on user instructions. At this stage, the data is converted into a physical shape, and a custom accessory is generated. The input is the stored data, and the output is a physical accessory customized by the user.

[0704] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0705] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0706] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0707] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0708] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0709] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0710] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0711] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0712] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0713] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0714] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0715] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0716] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0717] 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.

[0718] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0719] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0720] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0721] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0722] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0723] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0724] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0725] The following is further disclosed regarding the embodiments described above.

[0726] (Claim 1)

[0727] [Means for obtaining user design requests,

[0728] [Means for generating three-dimensional design data using an AI model based on acquired design requirements,

[0729] [Means for converting generated three-dimensional design data into data for a three-dimensional printing device,

[0730] [Means for transmitting data for a three-dimensional printing device to a printing device and generating physical device accessories,

[0731] A system that includes this.

[0732] (Claim 2)

[0733] [Means for specifying the colors and shapes based on the design data from which data for a three-dimensional printing device has been generated, according to claim 1.

[0734] (Claim 3)

[0735] [A system according to claim 1, which allows a user to input a handwritten request using a user interface.

[0736] "Example 1"

[0737] (Claim 1)

[0738] [Device means for obtaining user design requirements,

[0739] [An apparatus and means for generating three-dimensional design information using an AI model based on acquired design requirements,

[0740] [A device and means for converting the generated three-dimensional design information into information for a visual reproduction device,

[0741] [A device and means for transferring information for a visual reproduction device to a reproduction device and generating physical accessories,

[0742] [A device means that sends information from a terminal to a visual reproduction device and performs reproduction according to the settings,

[0743] A system that includes this.

[0744] (Claim 2)

[0745] A system according to claim 1, which sets visual features and shapes based on design information from which information for a visual reproduction device has been generated.

[0746] (Claim 3)

[0747] [A device in which a user inputs a handwritten request using a user interface. The system according to claim 1.

[0748] "Application Example 1"

[0749] (Claim 1)

[0750] [Means for obtaining user design requests,

[0751] [Means for generating three-dimensional design data using an AI model based on acquired design requirements,

[0752] [Means for converting generated three-dimensional design data into data for a three-dimensional printing device,

[0753] [Means for transmitting data for a three-dimensional printing device to a printing device and generating physical equipment accessories,

[0754] [Means for a store where a user generates design data on the spot using a terminal and receives the output from a printing device,

[0755] A system that includes this.

[0756] (Claim 2)

[0757] [Means for specifying the colors and shapes based on the design data from which data for a three-dimensional printing device has been generated, according to claim 1.

[0758] (Claim 3)

[0759] [A means by which a user inputs a handwritten request using a user interface, and a means of generating a design that can be responded to immediately, according to claim 1.

[0760] "Example 2 of combining an emotion engine"

[0761] (Claim 1)

[0762] [Means for acquiring user design requests and emotional information,

[0763] [Means for recognizing the user's emotional state using a camera and sensors and generating emotional information,

[0764] [Means for generating three-dimensional design data using an AI model based on acquired design requests and emotional information,

[0765] [Means for converting generated three-dimensional design data into data for a three-dimensional printing device,

[0766] [Means for transmitting data for a three-dimensional printing device to a printing device and generating physical device accessories,

[0767] A system that includes this.

[0768] (Claim 2)

[0769] [A system according to claim 1, which specifies the colors and shapes based on design data generated for a three-dimensional printing device, based on the user's emotional information.

[0770] (Claim 3)

[0771] [The system according to claim 1, which provides a means for a user to input handwritten information regarding requests and emotions using a user interface.

[0772] "Application example 2 when combining with an emotional engine"

[0773] (Claim 1)

[0774] [Means for recognizing the emotional state of the user,

[0775] [Means for obtaining user design requests,

[0776] [Means for generating three-dimensional design data using an AI model based on recognized emotional states and design requirements,

[0777] [Means for converting generated three-dimensional design data into data for a three-dimensional printing device,

[0778] [Means for transmitting data for a three-dimensional printing device to a printing device and generating physical device accessories,

[0779] A system that includes this.

[0780] (Claim 2)

[0781] [Means for specifying the colors and shapes based on the design data from which data for a three-dimensional printing device has been generated, according to claim 1.

[0782] (Claim 3)

[0783] [A system according to claim 1, which allows a user to input a handwritten request using a user interface. [Explanation of Symbols]

[0784] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining user design requirements, A method for generating 3D design data using an AI model based on acquired design requirements, A means for converting generated three-dimensional design data into data for a three-dimensional printing device, A means for transmitting data for a three-dimensional printing device to a printing device and generating physical device accessories, A system that includes this.

2. The system according to claim 1, further comprising means for specifying colors and shapes based on design data from which data for a three-dimensional printing device has been generated.

3. The system according to claim 1, further comprising means for a user to input a handwritten request using a user interface.

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