System

Abstract

A system is provided.SOLUTION: A system comprising: input means for a user to set an ideal body shape and clothes; means for generating an avatar based on data input by the input means; means for storing data of the generated avatar; means for scanning an actual body shape of the user using a dedicated suit; means for storing the scanned body shape data; means for comparing the stored body shape data of the avatar with the actual body shape data; means for generating a training plan and a nutrition plan based on the comparison result; and means for notifying the user of the generated plan.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In traditional fitness and health management systems, users need a strong will and consistent motivation to manage themselves in order to achieve their ideal body shape. However, this self-management is often difficult, especially in the process of achieving their goal, where maintaining motivation is challenging. Furthermore, users are rarely given a concrete visualization of their ideal body shape or training or nutrition plans based on that. Furthermore, opportunities for competition and interaction with other users are limited, and community-based support is lacking. This makes it difficult to maintain sustainable health management over the long term. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means: A system is provided that provides an input means for a user to set their ideal body type and clothing, and generates an avatar based on the input data. It also provides a means for saving the generated avatar data and scanning the user's actual body type using a dedicated suit. It also provides a means for saving the scanned body type data and comparing the avatar's body type data with the actual body type data, and generates a personalized training and nutrition plan based on the comparison results. It also includes a means for notifying the user of the generated plan. Furthermore, the system also provides a means for generating a progress report based on the user's training data and scanned body type data and distributing it to the user. It also provides a means for planning and setting up virtual fitness events that send motivational messages and reminders based on the progress report and encourage competition and interaction between users. By providing a means for compiling activity data during the event and displaying the results, a system is created that continuously motivates users toward their ideal body type.

[0006] "Input means" refers to the interface or device that allows the user to set their ideal body type and clothing.

[0007] An "avatar" is a digital representation of a person that visually recreates the ideal body type and clothing set by the user.

[0008] "Scanning means" refers to a device or system for obtaining a user's actual body shape data using a special suit or the like.

[0009] "Storage means" refers to a function that stores acquired data (such as avatar data and actual body shape data) in a storage device and makes it accessible as needed.

[0010] "Comparison method" refers to an algorithm or system that compares the ideal avatar's body data with the actual body data and analyzes the differences.

[0011] A "training plan" refers to a specific menu or schedule of exercise and fitness to help users get closer to their ideal body shape.

[0012] A "nutrition plan" refers to specific menus and guidelines for meals and nutritional intake that will help users achieve their ideal body shape.

[0013] "Notification means" refers to a system or device used to communicate generated training plans, nutrition plans, motivational messages, etc. to users.

[0014] "Progress Report" means a written or digital display that compiles and analyzes your training data and body shape change data and reports your progress.

[0015] "Motivational messages" refer to encouraging messages and notifications sent to users to encourage them to continue their efforts.

[0016] "Reminder" refers to messages or notifications that remind users to train and manage their nutrition.

[0017] "Virtual fitness event" refers to an online fitness or health management competition or social event in which users can participate.

[0018] "Activity data" refers to data such as the number of steps taken, calories burned, and exercise time obtained by the user during fitness events or daily training.

[0019] "Collection means" refers to a system or algorithm that collects user activity data during an event in bulk and performs statistical processing.

[0020] "Result display means" refers to the screen and report functions that visually provide users with aggregated activity data and event results. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0026] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0027] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. This system provides users with a means to continuously maintain their motivation and efficiently approach their ideal body type.

[0043] First, the user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it. This avatar visually reproduces the user's ideal appearance, and the generated avatar data is sent to a server for storage.

[0044] Next, the user puts on the special suit and activates the scanning function from a smartphone app. The device guides the user on the camera position and pose required for scanning. Once the user performs the scan, the device acquires the user's body shape data (e.g., height, weight, waist size, etc.) and sends it to the server. The server stores this body shape data and compares it with the avatar data.

[0045] The server then generates a training and nutrition plan tailored to the user based on the comparison results. This plan includes specific exercises and dietary guidelines to help the user achieve their ideal body shape. The plan is then sent to the user via their device.

[0046] Furthermore, when the user enters daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate a progress report and periodically delivers it to the user. This progress report includes the user's progress toward their goal, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress report. For example, if the user achieves a certain goal, a message such as "Great progress! Keep up the great work!" may be delivered.

[0047] A distinctive feature of this invention is the virtual fitness event. The server plans limited-time fitness events and notifies users to promote competition and interaction among users. When a user participates in an event, their device transmits their activity data to the server in real time, and the server compiles the activity data during the event and displays the results. In this way, users can compete with each other to achieve their ideal body shape, increasing their motivation.

[0048] This system helps users achieve their goals efficiently by visualizing their ideal body type and providing training and nutritional management based on that.

[0049] The processing flow will be explained below.

[0050] Step 1:

[0051] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[0052] Step 2:

[0053] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[0054] Step 3:

[0055] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[0056] Step 4:

[0057] Server: Stores the submitted avatar data, which is associated with the user's account.

[0058] Step 5:

[0059] User: Put on the special suit and activate the scanning function on the smartphone app.

[0060] Step 6:

[0061] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[0062] Step 7:

[0063] Device: Sends the acquired body shape data to the server.

[0064] Step 8:

[0065] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[0066] Step 9:

[0067] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[0068] Step 10:

[0069] Server: Delivers training and nutrition plans to users' accounts.

[0070] Step 11:

[0071] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[0072] Step 12:

[0073] User: Enters daily training and dietary data into the application.

[0074] Step 13:

[0075] Terminal: Sends input data to the server in real time.

[0076] Step 14:

[0077] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[0078] Step 15:

[0079] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[0080] Step 16:

[0081] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[0082] Step 17:

[0083] Server: Plans and configures virtual fitness events and notifies users.

[0084] Step 18:

[0085] User: Registers for an event and expresses their intention to attend.

[0086] Step 19:

[0087] Device: Provides users with more information about the event and how to participate.

[0088] Step 20:

[0089] Server: Collects and aggregates activity data sent by users during the event period.

[0090] Step 21:

[0091] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[0092] This series of steps allows users to stay motivated and effectively work towards their ideal body shape.

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] In today's society, it is difficult for individuals to find the right fitness and nutrition plan to achieve their ideal body shape. Existing systems lack the ability to provide customized plans based on individual body shape data and efficiently support users in achieving their goals while maintaining their motivation. Furthermore, they lack mechanisms to encourage competition and interaction between users and interactive features to support continuous training.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes a means for collecting a user's daily training data and dietary data and transmitting it to the server, a means for optimizing training and nutrition plans using a generative AI model, and a means for notifying the user of the generated plans. This allows for the provision of personalized fitness and nutrition plans based on individual body shape data, and for appropriate feedback and motivation according to the user's progress. Furthermore, by hosting virtual fitness events that encourage competition and interaction between users, an interactive experience can be provided to support continuous training.

[0098] "User" refers to an individual who utilizes the System to define their ideal body type and clothing and receive fitness and nutrition plans.

[0099] "Input means" refers to a device or software that provides an interface for users to input data such as their ideal body type and clothing into the system.

[0100] An "avatar" is a 3D model generated based on the user's desired body type and clothing.

[0101] The "specialized suit" refers to a wearable device used to accurately scan the user's actual body shape.

[0102] "Scanning means" refers to the equipment and technology used to acquire the user's body shape data using a special suit.

[0103] "Comparison means" refers to an algorithm or system for comparing stored avatar body data with actual body data.

[0104] "Generator" refers to the algorithms and / or generative AI models used to generate training and nutrition plans.

[0105] "Notification Method" refers to the mechanism used to notify users of generated plans and progress reports, such as smartphone notifications or in-app notifications.

[0106] "Progress Report" means a report generated based on a User's daily training and dietary data that indicates the User's progress toward goals and other progress.

[0107] "Motivational messages" refer to encouraging messages sent to users based on their progress and goal achievement.

[0108] "Reminders" refer to notifications that encourage users to continue training and managing their diet.

[0109] A "virtual fitness event" refers to a fitness event held on a digital platform to promote competition and interaction among users.

[0110] "Activity Data" refers to data collected during a user's fitness or training, such as calories burned and exercise time.

[0111] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. The system is configured and implemented as follows.

[0112] First, a user launches an application on their device and sets their ideal body type and clothing. The application on the device provides an input interface where the user selects their ideal body characteristics (e.g., muscular, slim, specific clothing, etc.). Software within the device is used to generate a 3D avatar based on the user's input data. Specifically, 3D modeling software such as Blender or Unity is used.

[0113] The generated 3D avatar data is sent from the device to the server in JSON format and stored in the server's database (e.g., MySQL or PostgreSQL).

[0114] Next, the user puts on the fitness suit and activates the scanning function within the application. The device provides the user with specific instructions on the camera position and pose required for scanning. The scanning is performed using the Structure Sensor and Kinect. When the user poses according to the instructions, the device uses these devices to obtain body shape data (e.g., height, weight, waist size, etc.) and sends it to the server.

[0115] The server compares the user's body shape data with the saved avatar data. This comparison is performed using the Python Scipy library. Based on the comparison results, the server uses a generative AI model (e.g., GPT or BERT) to generate a training and nutrition plan suitable for the user. This plan is then sent to the device and notified to the user.

[0116] When users enter their daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate progress reports and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress reports.

[0117] As a concrete example, assume that User A's ideal body type is muscular and slim waist. User A puts on a fitness suit at home, stands in the center of the room, and begins using the scanning function within the application. The device provides guidance such as, "Stand with your right feet shoulder-width apart and your arms hanging straight down," and uses the Structure Sensor to obtain data on height, weight, and waist size.

[0118] Based on the comparison result, the server inputs the following prompt sentence into the generative AI model:

[0119] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[0120] This allows the server to generate personalized training and nutrition plans based on individual body data and notify User A.

[0121] In addition, virtual fitness events are held regularly. The server sends event notifications to devices to promote competition and interaction among users. When users participate, their devices send activity data during the event in real time to the server, which then aggregates the data and displays the results.

[0122] In this way, the system of the present invention comprehensively provides a means for the user to efficiently approach their ideal body shape.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Step 1:

[0125] The user launches the application and sets their ideal body type and clothing.

[0126] Specific operation: The user taps the fitness app from the smartphone home screen to launch it, and then selects their ideal body type (e.g., muscular, slim) and clothing on the initial setup screen.

[0127] Input: User input data (ideal body type and clothing)

[0128] Output: Input ideal body type and clothing data

[0129] Step 2:

[0130] The device generates a 3D avatar based on the user's input data.

[0131] Specific operation: The device passes the user's input data to 3D modeling software (Blender or Unity) and obtains the generated 3D avatar.

[0132] Input: Ideal body type and clothing data

[0133] Data processing: Generate a 3D avatar using Blender or Unity

[0134] Output: Generated 3D avatar data (3D model)

[0135] Step 3:

[0136] The device sends the generated 3D avatar data to the server and stores it.

[0137] Specific operation: The device converts the 3D avatar data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database (MySQL or PostgreSQL).

[0138] Input: 3D avatar data (JSON format)

[0139] Output: Avatar data stored in the database

[0140] Step 4:

[0141] The user wears a special fitness suit and has their body data scanned.

[0142] Specific operation: The user puts on the fitness suit and activates the scan function in the app. The device provides specific instructions on camera position and pose, and uses the Structure Sensor and Kinect to capture body shape data.

[0143] Input: Camera image and user pose

[0144] Data calculation: Obtain data such as height, weight, and waist size using the Structure Sensor or Kinect

[0145] Output: Acquired body shape data (numerical data)

[0146] Step 5:

[0147] The body shape data acquired by the device is sent to a server and stored.

[0148] Specific operation: The device converts the acquired body shape data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database.

[0149] Input: Body shape data (JSON format)

[0150] Output: Body shape data stored in a database

[0151] Step 6:

[0152] The server compares the stored avatar body data with the actual body data.

[0153] Specific operation: The server uses Python's Scipy library to calculate the difference between the avatar data and the actual body shape data.

[0154] Input: Avatar data and body shape data

[0155] Data calculation: Calculate the difference of data using the Scipy library

[0156] Output: Comparison results (numerical data)

[0157] Step 7:

[0158] The server generates a training plan and a nutrition plan based on the comparison results.

[0159] Specific operation: The server inputs prompt sentences into a generative AI model (GPT or BERT) to generate training and nutrition plans suitable for the user.

[0160] Input: Comparison result data

[0161] Data calculation: Enter a prompt into the generative AI model to generate a plan

[0162] Output: Customized training and nutrition plans

[0163] Example prompt sentence:

[0164] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[0165] Step 8:

[0166] The server notifies the user of the generated plan.

[0167] Specific operation: The server sends the generated plan to the terminal, and the terminal displays a notification to the user.

[0168] Input: Customized training and nutrition plans

[0169] Output: A message to inform the user

[0170] Step 9:

[0171] The user enters daily training and dietary data into the app, which is then sent to the server by the device.

[0172] Specific operation: The user enters training and meal details into the app, and the device sends this information to the server in real time.

[0173] Input: User's daily training and diet data

[0174] Output: Data sent to the server

[0175] Step 10:

[0176] The server generates a progress report based on the user's input data and delivers it to the user periodically.

[0177] Specific behavior: The server generates and notifies the user of progress reports, including weight fluctuations and training results.

[0178] Input: User's daily training and diet data

[0179] Data calculation: Generate progress reports (processing statistical data)

[0180] Output: Progress reports and notification messages to the user

[0181] Step 11:

[0182] The server organizes virtual fitness events and notifies users.

[0183] Specific operation: The server generates event information and sends a notification to the user via the terminal to invite them to participate.

[0184] Input: Event information

[0185] Output: Event notification to the user

[0186] Step 12:

[0187] A user participates in an event, and the terminal transmits activity data during the event to the server.

[0188] Specific operation: A user participates in an event, and the device transmits activity data to the server in real time.

[0189] Input: User's activity data during the event

[0190] Output: Activity data sent to the server

[0191] Step 13:

[0192] The server will compile activity data during the event and display the results.

[0193] Specific operation: The server aggregates the event activity data and displays the results on a dashboard.

[0194] Input: Activity data during the event

[0195] Data Calculation: Aggregating data and generating results

[0196] Output: Results displayed in a dashboard

[0197] The above is the specific processing flow of this system.

[0198] (Application example 1)

[0199] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0200] Conventional fitness systems not only struggle to provide individually optimized plans to help users achieve their ideal body shape, but also lack mechanisms to maintain motivation. Competition and interaction between users is also limited, leaving the environment unsuitable for promoting sustained fitness activities. Furthermore, the tediousness of specific operations and the complexity of progress management are factors that prevent users from continuing to use the system.

[0201] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0202] In this invention, the server includes: an input means for a user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means for the user to implement and manage their fitness and nutrition plan in the virtual store; a means for users to participate in, compete with, and interact with each other in fitness events in the virtual store; a means for generating a progress report based on the scanned body type data and training data; a means for delivering the progress report to the user; a means for sending motivational messages and reminders based on the progress report; a means for automatically generating an individually optimized fitness plan using a generative AI model associated with the virtual store; a means for planning and setting up virtual fitness events to encourage competition and interaction between users and to encourage participation in the events; a means for compiling activity data during the event period and displaying the results; and a means for optimizing the user experience using prompt messages in the virtual store. This allows users to efficiently approach their ideal body shape through individually optimized fitness plans, while also maintaining motivation and encouraging competition and interaction among users to continue their fitness activities.

[0203] "User" refers to an individual who utilizes the System to set their ideal body type and clothing and receive fitness and nutrition plans.

[0204] "Input means" refers to the interface or device that allows the user to set their ideal body type and clothing.

[0205] An "avatar" is a three-dimensional virtual person that visually represents a user's ideal body type and clothing.

[0206] The "special suit" refers to a special wearable device used to accurately scan the user's actual body shape.

[0207] "Means of scanning" refers to the technology and equipment that uses a special suit to obtain the user's body data.

[0208] "Means for comparison" refers to the technology or algorithms used to analyze and compare the stored avatar body data with actual body data.

[0209] "Training Plan" refers to a plan that includes specific exercise menus and exercises to help users achieve their ideal body shape.

[0210] "Nutrition Plan" refers to personalized recommendations, including healthy eating guidelines and meal plans.

[0211] "Means for notification" refers to the interface or technology used to communicate the generated training and nutrition plans to the user.

[0212] "Virtual Store" means the online virtual environment provided for users to implement and manage their fitness and nutrition plans.

[0213] "Fitness Event" refers to an online event where users can engage in fitness activities through competition and interaction.

[0214] "Generative AI model" refers to the artificial intelligence techniques and algorithms used to automatically create personalized, optimized fitness plans.

[0215] A "prompt sentence" refers to a sentence used to input specific instructions or conditions into a generative AI model.

[0216] MODE FOR CARRYING OUT THE INVENTION

[0217] The system for implementing this invention mainly comprises a user, a server, and a terminal, and also includes technology for scanning the user's body shape data using a specialized suit and technology for generating individually optimized fitness and nutrition plans using a generative AI model.

[0218] Hardware and software used

[0219] Hardware: Smartphone, dedicated suit, camera

[0220] Software: Keras (used for loading and inferencing deep learning models), OpenCV (camera image acquisition and processing)

[0221] Description of system programs and processes

[0222] 1. User Input and Avatar Generation:

[0223] Users can input their ideal body type and clothing through a smartphone app. Based on this input data, the server uses Keras to generate a 3D avatar, which is then saved on the server.

[0224] 2. Body Scan:

[0225] The user wears a special suit and scans their body shape using their smartphone camera. The device uses OpenCV to get a real-time feed from the camera and collects body shape data, which is then sent to a server for storage.

[0226] 3. Plan Generation and Notification:

[0227] The server compares the stored avatar's body shape data with the user's actual body shape data and generates an exercise and nutrition plan. This plan is generated using a generative AI model using Keras. The generated plan is then sent to the user's smartphone.

[0228] 4. Progress Management and Reporting:

[0229] Users enter their daily training and dietary data into the app. The device sends this data to the server in real time. The server generates progress reports based on this data and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. The server also sends motivational messages and reminders based on the progress reports.

[0230] 5. Virtual Fitness Events:

[0231] The server plans limited-time virtual fitness events and notifies users to promote competition and interaction between users. When a user participates in an event, their device sends their activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[0232] Specific examples

[0233] An example of implementation:

[0234] After launching the app, the user sets their ideal body type as "height 180cm, weight 70kg, waist 80cm." A 3D avatar is generated based on these settings. The user then wears a special suit and scans their body, sending the collected body data to a server. The server uses this data to generate individually optimized training and nutrition plans and notifies the user. The user exercises based on the fitness plan and records their daily progress in the app. The server generates progress reports and distributes them to the user regularly. Users can also participate in limited-time virtual fitness events, where they can compete and interact with other users.

[0235] Example prompt sentence:

[0236] "Generate a 3D avatar for a user who sets their ideal body type as 'height 180cm, weight 70kg, waist 80cm'. Based on that avatar, propose a monthly fitness plan."

[0237] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0238] Step 1:

[0239] Ideal body type and clothing settings (input)

[0240] The user launches the smartphone app and sets their ideal body type and clothing.

[0241] Input: Ideal body data (e.g. height, weight, waist size) and clothing data entered by the user.

[0242] Specific action: Enter numbers or options into the app form and tap the settings button.

[0243] Output: The set ideal body type and clothing data is sent to the server.

[0244] Step 2:

[0245] Avatar generation

[0246] The server generates a 3D avatar using a generative AI model (Keras) based on the ideal body shape data sent by the user.

[0247] Input: User's ideal body type and clothing data.

[0248] Specific operation: The Keras model is executed on the server and a 3D avatar is generated.

[0249] Output: The generated 3D avatar data is saved on the server.

[0250] Step 3:

[0251] Body Scan

[0252] Users wear a special suit and scan their body shape using their smartphone camera, and the device uses OpenCV to get a real-time feed and collect the body shape data.

[0253] Input: Camera footage of a user wearing a specialized suit.

[0254] What it does: The app's scanning function is activated, and the user stands in front of the camera and strikes a suitable pose. The image is processed using OpenCV, and body shape data is extracted.

[0255] Output: The extracted body shape data is sent to the server.

[0256] Step 4:

[0257] Save and compare body shape data

[0258] The server stores the received body shape data and compares it with existing avatar data.

[0259] Input: Scanned body data and existing avatar data.

[0260] Specific operation: Body shape data is stored in a database on the server, and a comparison algorithm is run based on the stored data.

[0261] Output: The comparison results are generated.

[0262] Step 5:

[0263] Generate training and nutrition plans

[0264] Based on the comparison results, the server uses Keras to generate individually optimized training and nutrition plans.

[0265] Input: The comparison result.

[0266] What it does: The Keras model runs on the server and generates appropriate training menus and nutritional guidelines.

[0267] Output: The generated training and nutrition plans are saved on the server.

[0268] Step 6:

[0269] User Notification

[0270] The server notifies the user of the generated training and nutrition plans on their smartphone.

[0271] Input: Generated training and nutrition plans.

[0272] Specific operation: Plan information is pushed to your smartphone via the notification system.

[0273] Output: User receives plan information.

[0274] Step 7:

[0275] Progress Management and Reporting

[0276] Users enter their daily training and dietary data into the app, which then transmits the data in real time to a server. The server then generates progress reports based on the data and periodically delivers them to the user.

[0277] Input: User-entered training and diet data.

[0278] What happens: You enter data into a form in the app and tap the save button, which sends the data to the server and generates a progress report.

[0279] Output: Progress reports and motivational messages are sent to the user.

[0280] Step 8:

[0281] Planning a Virtual Fitness Event

[0282] The server plans time-limited virtual fitness events and notifies users of them in order to promote competition and interaction between users.

[0283] Input: Event planning information.

[0284] Specific behavior: Event information is created on the server and notified to the user via push notification.

[0285] Output: An event notification is sent to the user.

[0286] Step 9:

[0287] Event data aggregation and display

[0288] When a user participates in an event, the device transmits the activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[0289] Input: User activity data during the event period.

[0290] What it does: The app collects data during the event and sends it to the server, which aggregates the data and generates results.

[0291] Output: The aggregated results are displayed on the event dashboard.

[0292] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0293] The present invention combines a system that allows users to set their ideal body type and clothing, and then provides a personalized fitness and nutrition plan based on that, with an "emotion engine" that recognizes the user's emotions. As the user approaches their ideal body type, the emotion engine grasps the user's emotional state in real time, enabling it to flexibly adjust the content of their activities. This provides a system that maximizes the user's motivation and the effectiveness of their fitness plan.

[0294] The user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it, sending this avatar data to a server for storage. The user then puts on the special suit and activates the body scan function from the smartphone app. The device guides the user through the camera position and poses required for the scan, acquires the user's body data, and sends it to the server. The server stores the received body data and compares it with the avatar data. Based on the results of this comparison, a training plan and nutrition plan tailored to the user is generated and notified to the user via the device.

[0295] This is where the emotion engine plays a key role. The emotion engine analyzes the user's emotional state in real time through facial recognition and voice analysis. For example, if the user is feeling stressed or fatigued, it will adjust the training plan and suggest relaxation exercises or short periods of rest. Also, if the user is highly motivated, it will suggest a more challenging training plan, helping them to engage in effective fitness activities.

[0296] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. This progress report includes the user's progress toward their goals, changes in weight and body fat percentage, as well as emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, motivating them to continue their fitness activities.

[0297] The emotion engine also suggests the best time to participate in virtual fitness events. For example, by sending notifications encouraging participation when a user is in a positive emotional state, users can optimize their performance when competing against other users. This way, users can be more motivated and stick to their fitness plans.

[0298] The entire system helps users effectively achieve their ideal body shape by visualizing it specifically and providing personalized training and nutrition plans using an emotion engine.

[0299] The processing flow will be explained below.

[0300] Step 1:

[0301] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[0302] Step 2:

[0303] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[0304] Step 3:

[0305] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[0306] Step 4:

[0307] Server: Stores the submitted avatar data, which is associated with the user's account.

[0308] Step 5:

[0309] User: Put on the special suit and activate the scanning function on the smartphone app.

[0310] Step 6:

[0311] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[0312] Step 7:

[0313] Device: Sends the acquired body shape data to the server.

[0314] Step 8:

[0315] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[0316] Step 9:

[0317] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[0318] Step 10:

[0319] Server: Delivers training and nutrition plans to users' accounts.

[0320] Step 11:

[0321] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[0322] Step 12:

[0323] User: Enters daily training and dietary data into the application.

[0324] Step 13:

[0325] Terminal: Sends input data to the server in real time.

[0326] Step 14:

[0327] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[0328] Step 15:

[0329] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[0330] Step 16:

[0331] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[0332] Step 17:

[0333] Server: Plans and configures virtual fitness events and notifies users.

[0334] Step 18:

[0335] User: Registers for an event and expresses their intention to attend.

[0336] Step 19:

[0337] Device: Provides users with more information about the event and how to participate.

[0338] Step 20:

[0339] Server: Collects and aggregates activity data sent by users during the event period.

[0340] Step 21:

[0341] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[0342] Step 22:

[0343] On the device: The emotion engine uses a camera and microphone to capture the user's face and voice so that it can analyze the user's emotional state in real time.

[0344] Step 23:

[0345] Terminal: Emotion data analyzed by the emotion engine is sent to the server.

[0346] Step 24:

[0347] Server: Analyzes emotional data and adjusts training and nutrition plans based on the user's emotional state.

[0348] Step 25:

[0349] Server: Adjusts and delivers motivational messages and reminders based on the user's emotional state.

[0350] Step 26:

[0351] Server: Based on the user's emotional state, the server notifies them when to participate in virtual fitness events. Through this process, users can effectively work towards their ideal body shape and stay motivated.

[0352] Example 2

[0353] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0354] Traditional fitness and nutrition plan providers provide plans based on the user's ideal body type and goal settings, but often provide a uniform plan without taking the user's emotional state into consideration. This can lead to problems such as a lack of motivation, difficulty continuing with the plan, and insufficient results. Furthermore, there is a lack of a comprehensive way to understand the user's progress and emotional state, making it easy for users to find themselves in a situation where they don't know how to adjust their training and nutrition plans.

[0355] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means: In this invention, the server includes an input means for the user to set an ideal body type and clothing, a means for generating an avatar based on the data input by the input means, a means for saving the data of the generated avatar, a means for scanning the actual body type of the user using dedicated clothing, a means for saving the scanned body type data, a means for comparing the saved avatar body type data with the actual body type data, a means for generating a training plan and a nutrition plan based on the comparison results, a means for notifying the user of the generated plans, a means including an emotion engine for analyzing the user's emotions, and a means for adjusting the training plan based on the analysis results of the emotion engine. The system also includes a means for generating a progress report based on the scanned body shape data and training data, a means for delivering the progress report to the user, a means for sending motivational messages and reminders based on the progress report, a means for recording the user's emotional state using an emotion engine, a means for generating a progress report including the emotional state, a means for planning and setting up virtual fitness events to promote competition and interaction between users and encouraging participation in the events, a means for aggregating activity data during the event period and displaying the results, and a means for analyzing the user's emotional state using the emotion engine and encouraging participation in the events when the user is in a positive emotional state. This allows the system to provide individually optimized training and nutrition plans taking the user's emotional state into consideration, thereby maintaining and improving the user's motivation. Furthermore, the system allows the user to effectively continue their fitness activities through comprehensive progress management and real-time feedback.

[0356] "User" means an individual who utilizes the System to set their ideal body shape and health goals and implement a fitness and nutrition plan.

[0357] "Input means" refers to the means by which a user inputs information about their ideal body type and clothing into the system, and includes, for example, a smartphone application or a web form.

[0358] "Avatar generation means" includes software and algorithms for generating a 3D avatar based on data entered by a user.

[0359] The "storage means" is a means for temporarily or long-term storing the generated avatar and scanned body data in a database.

[0360] "Specialized clothing" refers to specialized suits or wearable devices used to accurately scan the user's body shape.

[0361] The "scanning means" is a means of acquiring the actual body shape of a user wearing special clothing as digital data using a camera or sensor.

[0362] "Comparison means" includes algorithms and software for comparing stored avatar body data with actual scan data.

[0363] The "training plan generation means" is a means for generating an individually optimized fitness plan based on the results of the comparison of body type data.

[0364] The "nutritional plan generation means" is a means for generating an individually optimized meal and supplement plan based on the results of the comparison of body shape data.

[0365] "Notification means" refers to a means for notifying the user of the generated training plan or nutrition plan, and includes, for example, app notifications and emails.

[0366] An "emotion engine" includes software and hardware for analyzing a user's emotional state through facial recognition and voice analysis.

[0367] The "progress report generating means" is a means for generating a report summarizing the user's progress based on the scanned body type data and training data.

[0368] "Delivery means" refers to a means for delivering the generated progress report to the user, including, for example, an app notification, email, or online dashboard.

[0369] The "means for sending motivational messages" refers to a means for sending messages and reminders to maintain and improve the user's motivation based on the progress report.

[0370] A "virtual fitness event" is an online fitness event designed to promote competition and interaction between users.

[0371] "Event participation promotion means" refers to means of notifying or suggesting users to participate in a virtual fitness event.

[0372] The "activity data collection means" is a means for collecting the activity data of users during the event period and displaying the results.

[0373] The present invention is a system that allows users to set their ideal body type and clothing and then provides a personalized fitness and nutrition plan based on that. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions, allowing it to grasp the user's emotional state in real time and flexibly adjust the plan, thereby maximizing the user's motivation and the effectiveness of the fitness plan.

[0374] First, the user launches the application and inputs their ideal body type and clothing. Specifically, they enter values ​​such as height, weight, and waist size using a smartphone app or web form. The device receives this input data and uses 3D avatar generation software to generate a 3D avatar, which is then sent to the server. The server then stores the received avatar data in a database.

[0375] Next, the user puts on special clothing and undergoes a body scan. The body scan function is activated from the smartphone app, and the device guides the user on the camera position and pose. After the user poses as instructed, their body data is captured by the camera and sent from the device to a server. The server stores this body data in a database and compares it with stored 3D avatar data. Based on the comparison results, the server generates an individually optimized training and nutrition plan for the user, which is then communicated to the user via their device.

[0376] In addition, the emotion engine uses facial recognition and voice analysis to analyze the user's emotional state in real time. For example, if the user is feeling stressed, the emotion engine will suggest relaxation exercises or short breaks, and if the user is highly motivated, it will suggest a more challenging training plan.

[0377] When users enter their daily training and dietary data, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. The progress report includes the user's progress toward their goals, changes in weight and body fat percentage, and emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, encouraging them to continue their fitness activities.

[0378] The emotion engine also suggests participation in virtual fitness events based on the user's emotional state, and if the user is determined to be in a positive emotional state, it can further motivate them by notifying them and optimizing their performance when competing against other users.

[0379] Specific examples

[0380] For example, if a user enters the following data:

[0381] Ideal body type: Tall / Slim

[0382] Training data: 5km jog

[0383] Emotional state: Positive

[0384] Based on this data, the system would:

[0385] Avatar generation software creates 3D avatars

[0386] A specific training plan is generated based on a comparison of the scan data and the 3D avatar data.

[0387] The emotion engine analyzes the user's positive emotional state and suggests more challenging training.

[0388] Examples of prompts include:

[0389] text

[0390] Username: Yamada Taro

[0391] Ideal body type: Tall / Slim

[0392] Today's training data: 5km jog

[0393] Emotional state: Positive

[0394] Using this prompt, the system will provide the user with the optimal fitness and nutrition plan based on their condition.

[0395] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0396] Step 1: User Settings

[0397] The user launches the application and sets their ideal body type and clothing. A smartphone app or web form is used as the input method. When the user enters their ideal values ​​such as "height," "weight," and "waist size," the device receives this data. It also generates a 3D avatar based on the ideal body type. At this time, a generative AI model is used to generate prompts for the 3D avatar, and the 3D avatar is created based on these. The device then sends the generated 3D avatar data to the server, which stores it in a database.

[0398] Input: User's ideal body type data (height, weight, waist size, etc.)

[0399] Data processing: 3D avatar generation

[0400] Output: 3D avatar data (stored on the server)

[0401] Specific behavior:

[0402] The user launches the application and inputs their ideal body type data, such as height 180cm, weight 70kg, and waist size 80cm. The device then uses the generative AI model to generate a 3D avatar, which is then sent to a server for storage.

[0403] Step 2: Body scan and data submission

[0404] The user puts on the special clothing and activates the body scan function from a smartphone app. The device guides the user on the camera position and pose, and acquires body data of the user as they pose as instructed. The device then processes the acquired body data and sends it to the server. The server stores the received body data in a database and compares it with previously saved 3D avatar data.

[0405] Input: User's body shape data (scan results)

[0406] Data processing: Acquiring body shape data and comparing it with 3D avatar data

[0407] Output: Comparison results (saved on the server)

[0408] Specific behavior:

[0409] The user puts on the special clothing and activates the body scanning function from a smartphone app. They are guided to the correct camera position and pose. The device then takes a full-body photo of the user and acquires body data, which is then sent to a server and compared with the 3D avatar data.

[0410] Step 3: Create a training and nutrition plan

[0411] Based on the comparison results, the server generates an optimized training plan and nutrition plan for the user, using the system's training algorithm and nutrition plan generation engine, and notifies the user of the generated plan via their device.

[0412] Input: Comparison result

[0413] Data processing: generating training and nutrition plans

[0414] Output: Generated training and nutrition plans (notified to the user)

[0415] Specific behavior:

[0416] The server applies a training algorithm based on the comparison results to generate a training plan, and similarly uses a nutrition plan generation engine to create a personalized nutrition plan, which is then sent to the user via their device.

[0417] Step 4: Daily data entry and emotional state recording

[0418] Users input their daily training and dietary data into the application. The device receives this data and uses an emotion engine to analyze and record the user's emotional state. The device then transmits this data in real time to the server, which stores all the data in a database.

[0419] Input: Training data, Food data, Emotional state data

[0420] Data processing: Data reception and sentiment analysis

[0421] Output: Recorded data (stored on the server)

[0422] Specific behavior:

[0423] Users input details of their training and diet into the app, and the device uses an emotion engine to analyze their emotional state through facial recognition and voice analysis, and all data is sent and stored on a server.

[0424] Step 5: Generate a progress report

[0425] The server periodically generates a progress report for the user, which includes the progress of the goal, changes in weight and body fat percentage, and sentiment analysis results. The generated progress report is delivered to the user via their device.

[0426] Input: Scan data, training data, emotion data

[0427] Data Processing: Report Generation

[0428] Output: Progress report (delivered to user)

[0429] Specific behavior:

[0430] The server analyzes all data and generates a progress report that includes the user's progress toward their goal, changes in weight and body fat percentage, and sentiment analysis results. This report is then delivered to the user via their device.

[0431] Step 6: Propose a Virtual Fitness Event

[0432] The emotion engine monitors the user's emotional state in real time. If the user is determined to be in a positive emotional state, the device will suggest participating in a virtual fitness event. This suggestion will be sent to the user as a notification.

[0433] Input: Emotional state data

[0434] Data processing: sentiment analysis and event suggestion

[0435] Output: Event participation suggestion notification (notify user)

[0436] Specific behavior:

[0437] The emotion engine analyzes the user's emotional data in real time, and if a positive state is detected, the device will send a notification encouraging the user to participate in a virtual fitness event.

[0438] Through these processing steps, the system provides users with an effective fitness and nutrition plan to achieve their ideal body shape and helps motivate them to continue.

[0439] (Application example 2)

[0440] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0441] Conventional fitness and nutrition plan providing systems have difficulty taking into account the user's emotional state, making it difficult to maintain the user's motivation and drive to train. Furthermore, fitness activities at physical stores have the problem of not being able to properly adjust training based on the user's individual data in real time. This makes it difficult to provide a comprehensive fitness plan that effectively helps users achieve their ideal physique.

[0442] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0443] In this invention, the server includes: an input means for the user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means including an emotion engine that analyzes the user's emotional state in real time through facial recognition and voice analysis; a means for automatically adjusting the training plan based on the analysis results by the emotion engine; and a means for notifying the user of the adjusted plan using a smartphone or smart glasses.

[0444] This allows the system to grasp the user's emotional state in real time and flexibly adjust appropriate training and nutrition plans accordingly, effectively supporting fitness activities in physical stores while maintaining the user's motivation.

[0445] Definition of Terms

[0446] The "input means" is a means by which the user sets his or her ideal body type and clothing.

[0447] The "means for generating an avatar" is a means for generating a 3D model based on the data input by the input means.

[0448] The "means for saving avatar data" refers to a data accumulation means for storing data on the generated avatars.

[0449] "Means for scanning body shape" refers to a device and method for acquiring the user's actual body shape data using a special suit.

[0450] The "means for saving body type data" is a data accumulation means for storing scanned body type data.

[0451] The "comparison means" is a means for comparing the stored avatar's body shape data with the actual body shape data.

[0452] The "means for generating a training plan and a nutrition plan" is a means for creating an appropriate exercise and diet plan based on the comparison results.

[0453] The "means for notifying" is a means for notifying the user of the generated plan.

[0454] The "Emotion Engine" is an engine for analyzing the user's emotional state in real time through facial recognition and voice analysis.

[0455] "Means for automatic adjustment" refers to a means for changing the training plan based on the analysis results of the emotion engine.

[0456] "Smart devices" is a general term for portable information terminals such as smartphones and smart glasses.

[0457] A "scanning device" is a device that detects the user's body shape and obtains the necessary data.

[0458] The system of the present invention allows users to set their ideal body type and clothing, and provides fitness and nutrition plans based on those. The system incorporates an emotion engine, allowing it to flexibly adjust the plan according to the user's emotional state.

[0459] Hardware and Software Configuration

[0460] Hardware:

[0461] 1. Smartphone: The user sets their ideal body type and clothing and scans their body data.

[0462] 2. Smart glasses: These are used to understand the user's emotional state in real time and also display notifications.

[0463] 3. Server: Manages data, generates fitness plans, and creates progress reports.

[0464] 4. Scanning device: Accurately scans the user's body shape and captures data.

[0465] software:

[0466] 1. Applications: Applications installed by users on smartphones or smart glasses.

[0467] 2. Emotion Engine: An AI model that analyzes the user's emotional state through facial recognition and voice analysis.

[0468] 3. Database: Stores and manages user avatars, body data, and progress reports.

[0469] System processing overview

[0470] 1. User Input and Avatar Generation:

[0471] Users use a smartphone application to input their ideal body type and clothing.

[0472] The avatar generation program generates a 3D avatar based on the input data and stores it on the server.

[0473] 2. Actual body scan:

[0474] Users wear a special suit and use their smartphone camera or scanning device to obtain body data.

[0475] The acquired data is sent to a server in real time and stored.

[0476] 3. Plan Generation and Notification:

[0477] The server compares the stored avatar's body data with the actual body data and generates a fitness and nutrition plan based on the analysis results.

[0478] The generated plan will be notified to the user's smartphone.

[0479] 4. Emotional engine regulation:

[0480] Using the smart glasses or smartphone camera and microphone, the emotion engine analyzes the user's emotional state in real time.

[0481] The server automatically adjusts the training plan based on the emotional state data and notifies the user.

[0482] Specific examples

[0483] When a user arrives at the gym and puts on the smart glasses, the emotion engine analyzes the user's facial expressions and suggests relaxation exercises if it determines that the user is tired.

[0484] If the emotion engine determines that the user is in good spirits, they will be notified of a more challenging training plan.

[0485] Prompt Sentence Examples

[0486] Classify the user's current emotional state as "😊" (joy), "😞" (sadness), "😠" (anger), "😨" (surprise), etc. Suggest appropriate fitness plan adjustments based on the user's facial image and emotional state.

[0487] In this way, the system can understand the user's emotional state in real time and provide an appropriate training plan accordingly, thereby maintaining the user's motivation and supporting effective fitness activities.

[0488] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0489] Program processing steps

[0490] Step 1:

[0491] The user launches the smartphone app and selects their ideal body type and clothing. Based on the data entered (height, weight, ideal body fat percentage, clothing details, etc.), the device generates a 3D avatar. This 3D avatar data is then sent to the server and stored.

[0492] Input: User-supplied data about ideal body type and clothing

[0493] Output: Saved avatar data

[0494] Step 2:

[0495] The user puts on a special suit and scans their body shape data using a smartphone or scanning device. The device guides them on the camera position and pose required for the scan. The acquired body shape data is sent to a server and saved.

[0496] Input: Actual body shape data from scanning device

[0497] Output: Saved body shape data

[0498] Step 3:

[0499] The server compares the stored avatar's body data with the user's actual body data. Using a comparison algorithm, it calculates the difference between the user's current body shape and their ideal body shape. Based on this, it generates a personalized training and nutrition plan. The plan is then sent to the user's smartphone.

[0500] Input: Saved avatar data and actual body data

[0501] Output: Training and nutrition plans

[0502] Step 4:

[0503] The user wears smart glasses or a smartphone, and the emotion engine grasps the user's emotional state in real time through facial recognition and voice analysis, which is then sent to the server.

[0504] Input: User's facial image and voice data

[0505] Output: User's emotional state

[0506] Step 5:

[0507] The server analyzes the emotional state data obtained by the emotion engine and automatically adjusts the training plan. For example, if the user is feeling stressed, it will recommend relaxation exercises, and if the user is highly motivated, it will create a training plan with a higher level of difficulty. This adjusted plan is then notified to the user again.

[0508] Input: User emotional state data

[0509] Output: Tailored training plan

[0510] Step 6:

[0511] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server, which then generates a progress report. The progress report includes the progress of goals, changes in weight and body fat percentage, and emotion analysis results. This report is then delivered to the user.

[0512] Input: Daily training data, diet data, emotional state data

[0513] Output: Progress report

[0514] Step 7:

[0515] Based on the progress reports, the server generates and sends motivational messages and reminders to the user, helping to keep the user motivated.

[0516] Input: Progress Report

[0517] Output: Motivational messages and reminders

[0518] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0519] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0520] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0521] [Second embodiment]

[0522] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0523] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0524] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0525] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0526] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0527] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0528] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0529] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0530] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0531] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0532] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0533] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0534] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. This system provides users with a means to continuously maintain their motivation and efficiently approach their ideal body type.

[0535] First, the user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it. This avatar visually reproduces the user's ideal appearance, and the generated avatar data is sent to a server for storage.

[0536] Next, the user puts on the special suit and activates the scanning function from a smartphone app. The device guides the user on the camera position and pose required for scanning. Once the user performs the scan, the device acquires the user's body shape data (e.g., height, weight, waist size, etc.) and sends it to the server. The server stores this body shape data and compares it with the avatar data.

[0537] The server then generates a training and nutrition plan tailored to the user based on the comparison results. This plan includes specific exercises and dietary guidelines to help the user achieve their ideal body shape. The plan is then sent to the user via their device.

[0538] Furthermore, when the user enters daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate a progress report and periodically delivers it to the user. This progress report includes the user's progress toward their goal, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress report. For example, if the user achieves a certain goal, a message such as "Great progress! Keep up the great work!" may be delivered.

[0539] A distinctive feature of this invention is the virtual fitness event. The server plans limited-time fitness events and notifies users to promote competition and interaction among users. When a user participates in an event, their device transmits their activity data to the server in real time, and the server compiles the activity data during the event and displays the results. In this way, users can compete with each other to achieve their ideal body shape, increasing their motivation.

[0540] This system helps users achieve their goals efficiently by visualizing their ideal body type and providing training and nutritional management based on that.

[0541] The processing flow will be explained below.

[0542] Step 1:

[0543] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[0544] Step 2:

[0545] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[0546] Step 3:

[0547] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[0548] Step 4:

[0549] Server: Stores the submitted avatar data, which is associated with the user's account.

[0550] Step 5:

[0551] User: Put on the special suit and activate the scanning function on the smartphone app.

[0552] Step 6:

[0553] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[0554] Step 7:

[0555] Device: Sends the acquired body shape data to the server.

[0556] Step 8:

[0557] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[0558] Step 9:

[0559] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[0560] Step 10:

[0561] Server: Delivers training and nutrition plans to users' accounts.

[0562] Step 11:

[0563] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[0564] Step 12:

[0565] User: Enters daily training and dietary data into the application.

[0566] Step 13:

[0567] Terminal: Sends input data to the server in real time.

[0568] Step 14:

[0569] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[0570] Step 15:

[0571] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[0572] Step 16:

[0573] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[0574] Step 17:

[0575] Server: Plans and configures virtual fitness events and notifies users.

[0576] Step 18:

[0577] User: Registers for an event and expresses their intention to attend.

[0578] Step 19:

[0579] Device: Provides users with more information about the event and how to participate.

[0580] Step 20:

[0581] Server: Collects and aggregates activity data sent by users during the event period.

[0582] Step 21:

[0583] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[0584] This series of steps allows users to stay motivated and effectively work towards their ideal body shape.

[0585] Example 1

[0586] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0587] In today's society, it is difficult for individuals to find the right fitness and nutrition plan to achieve their ideal body shape. Existing systems lack the ability to provide customized plans based on individual body shape data and efficiently support users in achieving their goals while maintaining their motivation. Furthermore, they lack mechanisms to encourage competition and interaction between users and interactive features to support continuous training.

[0588] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0589] In this invention, the server includes a means for collecting a user's daily training data and dietary data and transmitting it to the server, a means for optimizing training and nutrition plans using a generative AI model, and a means for notifying the user of the generated plans. This allows for the provision of personalized fitness and nutrition plans based on individual body shape data, and for appropriate feedback and motivation according to the user's progress. Furthermore, by hosting virtual fitness events that encourage competition and interaction between users, an interactive experience can be provided to support continuous training.

[0590] "User" refers to an individual who utilizes the System to define their ideal body type and clothing and receive fitness and nutrition plans.

[0591] "Input means" refers to a device or software that provides an interface for users to input data such as their ideal body type and clothing into the system.

[0592] An "avatar" is a 3D model generated based on the user's desired body type and clothing.

[0593] The "specialized suit" refers to a wearable device used to accurately scan the user's actual body shape.

[0594] "Scanning means" refers to the equipment and technology used to acquire the user's body shape data using a special suit.

[0595] "Comparison means" refers to an algorithm or system for comparing stored avatar body data with actual body data.

[0596] "Generator" refers to the algorithms and / or generative AI models used to generate training and nutrition plans.

[0597] "Notification Method" refers to the mechanism used to notify users of generated plans and progress reports, such as smartphone notifications or in-app notifications.

[0598] "Progress Report" means a report generated based on a User's daily training and dietary data that indicates the User's progress toward goals and other progress.

[0599] "Motivational messages" refer to encouraging messages sent to users based on their progress and goal achievement.

[0600] "Reminders" refer to notifications that encourage users to continue training and managing their diet.

[0601] A "virtual fitness event" refers to a fitness event held on a digital platform to promote competition and interaction among users.

[0602] "Activity Data" refers to data collected during a user's fitness or training, such as calories burned and exercise time.

[0603] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. The system is configured and implemented as follows.

[0604] First, a user launches an application on their device and sets their ideal body type and clothing. The application on the device provides an input interface where the user selects their ideal body characteristics (e.g., muscular, slim, specific clothing, etc.). Software within the device is used to generate a 3D avatar based on the user's input data. Specifically, 3D modeling software such as Blender or Unity is used.

[0605] The generated 3D avatar data is sent from the device to the server in JSON format and stored in the server's database (e.g., MySQL or PostgreSQL).

[0606] Next, the user puts on the fitness suit and activates the scanning function within the application. The device provides the user with specific instructions on the camera position and pose required for scanning. The scanning is performed using the Structure Sensor and Kinect. When the user poses according to the instructions, the device uses these devices to obtain body shape data (e.g., height, weight, waist size, etc.) and sends it to the server.

[0607] The server compares the user's body shape data with the saved avatar data. This comparison is performed using the Python Scipy library. Based on the comparison results, the server uses a generative AI model (e.g., GPT or BERT) to generate a training and nutrition plan suitable for the user. This plan is then sent to the device and notified to the user.

[0608] When users enter their daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate progress reports and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress reports.

[0609] As a concrete example, assume that User A's ideal body type is muscular and slim waist. User A puts on a fitness suit at home, stands in the center of the room, and begins using the scanning function within the application. The device provides guidance such as, "Stand with your right feet shoulder-width apart and your arms hanging straight down," and uses the Structure Sensor to obtain data on height, weight, and waist size.

[0610] Based on the comparison result, the server inputs the following prompt sentence into the generative AI model:

[0611] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[0612] This allows the server to generate personalized training and nutrition plans based on individual body data and notify User A.

[0613] In addition, virtual fitness events are held regularly. The server sends event notifications to devices to promote competition and interaction among users. When users participate, their devices send activity data during the event in real time to the server, which then aggregates the data and displays the results.

[0614] In this way, the system of the present invention comprehensively provides a means for the user to efficiently approach their ideal body shape.

[0615] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0616] Step 1:

[0617] The user launches the application and sets their ideal body type and clothing.

[0618] Specific operation: The user taps the fitness app from the smartphone home screen to launch it, and then selects their ideal body type (e.g., muscular, slim) and clothing on the initial setup screen.

[0619] Input: User input data (ideal body type and clothing)

[0620] Output: Input ideal body type and clothing data

[0621] Step 2:

[0622] The device generates a 3D avatar based on the user's input data.

[0623] Specific operation: The device passes the user's input data to 3D modeling software (Blender or Unity) and obtains the generated 3D avatar.

[0624] Input: Ideal body type and clothing data

[0625] Data processing: Generate a 3D avatar using Blender or Unity

[0626] Output: Generated 3D avatar data (3D model)

[0627] Step 3:

[0628] The device sends the generated 3D avatar data to the server and stores it.

[0629] Specific operation: The device converts the 3D avatar data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database (MySQL or PostgreSQL).

[0630] Input: 3D avatar data (JSON format)

[0631] Output: Avatar data stored in the database

[0632] Step 4:

[0633] The user wears a special fitness suit and has their body data scanned.

[0634] Specific operation: The user puts on the fitness suit and activates the scan function in the app. The device provides specific instructions on camera position and pose, and uses the Structure Sensor and Kinect to capture body shape data.

[0635] Input: Camera image and user pose

[0636] Data calculation: Obtain data such as height, weight, and waist size using the Structure Sensor or Kinect

[0637] Output: Acquired body shape data (numerical data)

[0638] Step 5:

[0639] The body shape data acquired by the device is sent to a server and stored.

[0640] Specific operation: The device converts the acquired body shape data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database.

[0641] Input: Body shape data (JSON format)

[0642] Output: Body shape data stored in a database

[0643] Step 6:

[0644] The server compares the stored avatar body data with the actual body data.

[0645] Specific operation: The server uses Python's Scipy library to calculate the difference between the avatar data and the actual body shape data.

[0646] Input: Avatar data and body shape data

[0647] Data calculation: Calculate the difference of data using the Scipy library

[0648] Output: Comparison results (numerical data)

[0649] Step 7:

[0650] The server generates a training plan and a nutrition plan based on the comparison results.

[0651] Specific operation: The server inputs prompt sentences into a generative AI model (GPT or BERT) to generate training and nutrition plans suitable for the user.

[0652] Input: Comparison result data

[0653] Data calculation: Enter a prompt into the generative AI model to generate a plan

[0654] Output: Customized training and nutrition plans

[0655] Example prompt sentence:

[0656] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[0657] Step 8:

[0658] The server notifies the user of the generated plan.

[0659] Specific operation: The server sends the generated plan to the terminal, and the terminal displays a notification to the user.

[0660] Input: Customized training and nutrition plans

[0661] Output: A message to inform the user

[0662] Step 9:

[0663] The user enters daily training and dietary data into the app, which is then sent to the server by the device.

[0664] Specific operation: The user enters training and meal details into the app, and the device sends this information to the server in real time.

[0665] Input: User's daily training and diet data

[0666] Output: Data sent to the server

[0667] Step 10:

[0668] The server generates a progress report based on the user's input data and delivers it to the user periodically.

[0669] Specific behavior: The server generates and notifies the user of progress reports, including weight fluctuations and training results.

[0670] Input: User's daily training and diet data

[0671] Data calculation: Generate progress reports (processing statistical data)

[0672] Output: Progress reports and notification messages to the user

[0673] Step 11:

[0674] The server organizes virtual fitness events and notifies users.

[0675] Specific operation: The server generates event information and sends a notification to the user via the terminal to invite them to participate.

[0676] Input: Event information

[0677] Output: Event notification to the user

[0678] Step 12:

[0679] A user participates in an event, and the terminal transmits activity data during the event to the server.

[0680] Specific operation: A user participates in an event, and the device transmits activity data to the server in real time.

[0681] Input: User's activity data during the event

[0682] Output: Activity data sent to the server

[0683] Step 13:

[0684] The server will compile activity data during the event and display the results.

[0685] Specific operation: The server aggregates the event activity data and displays the results on a dashboard.

[0686] Input: Activity data during the event

[0687] Data Calculation: Aggregating data and generating results

[0688] Output: Results displayed in a dashboard

[0689] The above is the specific processing flow of this system.

[0690] (Application example 1)

[0691] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0692] Conventional fitness systems not only struggle to provide individually optimized plans to help users achieve their ideal body shape, but also lack mechanisms to maintain motivation. Competition and interaction between users is also limited, leaving the environment unsuitable for promoting sustained fitness activities. Furthermore, the tediousness of specific operations and the complexity of progress management are factors that prevent users from continuing to use the system.

[0693] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0694] In this invention, the server includes: an input means for a user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means for the user to implement and manage their fitness and nutrition plan in the virtual store; a means for users to participate in, compete with, and interact with each other in fitness events in the virtual store; a means for generating a progress report based on the scanned body type data and training data; a means for delivering the progress report to the user; a means for sending motivational messages and reminders based on the progress report; a means for automatically generating an individually optimized fitness plan using a generative AI model associated with the virtual store; a means for planning and setting up virtual fitness events to encourage competition and interaction between users and to encourage participation in the events; a means for compiling activity data during the event period and displaying the results; and a means for optimizing the user experience using prompt messages in the virtual store. This allows users to efficiently approach their ideal body shape through individually optimized fitness plans, while also maintaining motivation and encouraging competition and interaction among users to continue their fitness activities.

[0695] "User" refers to an individual who utilizes the System to set their ideal body type and clothing and receive fitness and nutrition plans.

[0696] "Input means" refers to the interface or device that allows the user to set their ideal body type and clothing.

[0697] An "avatar" is a three-dimensional virtual person that visually represents a user's ideal body type and clothing.

[0698] The "special suit" refers to a special wearable device used to accurately scan the user's actual body shape.

[0699] "Means of scanning" refers to the technology and equipment that uses a special suit to obtain the user's body data.

[0700] "Means for comparison" refers to the technology or algorithms used to analyze and compare the stored avatar body data with actual body data.

[0701] "Training Plan" refers to a plan that includes specific exercise menus and exercises to help users achieve their ideal body shape.

[0702] "Nutrition Plan" refers to personalized recommendations, including healthy eating guidelines and meal plans.

[0703] "Means for notification" refers to the interface or technology used to communicate the generated training and nutrition plans to the user.

[0704] "Virtual Store" means the online virtual environment provided for users to implement and manage their fitness and nutrition plans.

[0705] "Fitness Event" refers to an online event where users can engage in fitness activities through competition and interaction.

[0706] "Generative AI model" refers to the artificial intelligence techniques and algorithms used to automatically create personalized, optimized fitness plans.

[0707] A "prompt sentence" refers to a sentence used to input specific instructions or conditions into a generative AI model.

[0708] MODE FOR CARRYING OUT THE INVENTION

[0709] The system for implementing this invention mainly comprises a user, a server, and a terminal, and also includes technology for scanning the user's body shape data using a specialized suit and technology for generating individually optimized fitness and nutrition plans using a generative AI model.

[0710] Hardware and software used

[0711] Hardware: Smartphone, dedicated suit, camera

[0712] Software: Keras (used for loading and inferencing deep learning models), OpenCV (camera image acquisition and processing)

[0713] Description of system programs and processes

[0714] 1. User Input and Avatar Generation:

[0715] Users can input their ideal body type and clothing through a smartphone app. Based on this input data, the server uses Keras to generate a 3D avatar, which is then saved on the server.

[0716] 2. Body Scan:

[0717] The user wears a special suit and scans their body shape using their smartphone camera. The device uses OpenCV to get a real-time feed from the camera and collects body shape data, which is then sent to a server for storage.

[0718] 3. Plan Generation and Notification:

[0719] The server compares the stored avatar's body shape data with the user's actual body shape data and generates an exercise and nutrition plan. This plan is generated using a generative AI model using Keras. The generated plan is then sent to the user's smartphone.

[0720] 4. Progress Management and Reporting:

[0721] Users enter their daily training and dietary data into the app. The device sends this data to the server in real time. The server generates progress reports based on this data and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. The server also sends motivational messages and reminders based on the progress reports.

[0722] 5. Virtual Fitness Events:

[0723] The server plans limited-time virtual fitness events and notifies users to promote competition and interaction between users. When a user participates in an event, their device sends their activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[0724] Specific examples

[0725] An example of implementation:

[0726] After launching the app, the user sets their ideal body type as "height 180cm, weight 70kg, waist 80cm." A 3D avatar is generated based on these settings. The user then wears a special suit and scans their body, sending the collected body data to a server. The server uses this data to generate individually optimized training and nutrition plans and notifies the user. The user exercises based on the fitness plan and records their daily progress in the app. The server generates progress reports and distributes them to the user regularly. Users can also participate in limited-time virtual fitness events, where they can compete and interact with other users.

[0727] Example prompt sentence:

[0728] "Generate a 3D avatar for a user who sets their ideal body type as 'height 180cm, weight 70kg, waist 80cm'. Based on that avatar, propose a monthly fitness plan."

[0729] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0730] Step 1:

[0731] Ideal body type and clothing settings (input)

[0732] The user launches the smartphone app and sets their ideal body type and clothing.

[0733] Input: Ideal body data (e.g. height, weight, waist size) and clothing data entered by the user.

[0734] Specific action: Enter numbers or options into the app form and tap the settings button.

[0735] Output: The set ideal body type and clothing data is sent to the server.

[0736] Step 2:

[0737] Avatar generation

[0738] The server generates a 3D avatar using a generative AI model (Keras) based on the ideal body shape data sent by the user.

[0739] Input: User's ideal body type and clothing data.

[0740] Specific operation: The Keras model is executed on the server and a 3D avatar is generated.

[0741] Output: The generated 3D avatar data is saved on the server.

[0742] Step 3:

[0743] Body Scan

[0744] Users wear a special suit and scan their body shape using their smartphone camera, and the device uses OpenCV to get a real-time feed and collect the body shape data.

[0745] Input: Camera footage of a user wearing a specialized suit.

[0746] What it does: The app's scanning function is activated, and the user stands in front of the camera and strikes a suitable pose. The image is processed using OpenCV, and body shape data is extracted.

[0747] Output: The extracted body shape data is sent to the server.

[0748] Step 4:

[0749] Save and compare body shape data

[0750] The server stores the received body shape data and compares it with existing avatar data.

[0751] Input: Scanned body data and existing avatar data.

[0752] Specific operation: Body shape data is stored in a database on the server, and a comparison algorithm is run based on the stored data.

[0753] Output: The comparison results are generated.

[0754] Step 5:

[0755] Generate training and nutrition plans

[0756] Based on the comparison results, the server uses Keras to generate individually optimized training and nutrition plans.

[0757] Input: The comparison result.

[0758] What it does: The Keras model runs on the server and generates appropriate training menus and nutritional guidelines.

[0759] Output: The generated training and nutrition plans are saved on the server.

[0760] Step 6:

[0761] User Notification

[0762] The server notifies the user of the generated training and nutrition plans on their smartphone.

[0763] Input: Generated training and nutrition plans.

[0764] Specific operation: Plan information is pushed to your smartphone via the notification system.

[0765] Output: User receives plan information.

[0766] Step 7:

[0767] Progress Management and Reporting

[0768] Users enter their daily training and dietary data into the app, which then transmits the data in real time to a server. The server then generates progress reports based on the data and periodically delivers them to the user.

[0769] Input: User-entered training and diet data.

[0770] What happens: You enter data into a form in the app and tap the save button, which sends the data to the server and generates a progress report.

[0771] Output: Progress reports and motivational messages are sent to the user.

[0772] Step 8:

[0773] Planning a Virtual Fitness Event

[0774] The server plans time-limited virtual fitness events and notifies users of them in order to promote competition and interaction between users.

[0775] Input: Event planning information.

[0776] Specific behavior: Event information is created on the server and notified to the user via push notification.

[0777] Output: An event notification is sent to the user.

[0778] Step 9:

[0779] Event data aggregation and display

[0780] When a user participates in an event, the device transmits the activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[0781] Input: User activity data during the event period.

[0782] What it does: The app collects data during the event and sends it to the server, which aggregates the data and generates results.

[0783] Output: The aggregated results are displayed on the event dashboard.

[0784] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0785] The present invention combines a system that allows users to set their ideal body type and clothing, and then provides a personalized fitness and nutrition plan based on that, with an "emotion engine" that recognizes the user's emotions. As the user approaches their ideal body type, the emotion engine grasps the user's emotional state in real time, enabling it to flexibly adjust the content of their activities. This provides a system that maximizes the user's motivation and the effectiveness of their fitness plan.

[0786] The user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it, sending this avatar data to a server for storage. The user then puts on the special suit and activates the body scan function from the smartphone app. The device guides the user through the camera position and poses required for the scan, acquires the user's body data, and sends it to the server. The server stores the received body data and compares it with the avatar data. Based on the results of this comparison, a training plan and nutrition plan tailored to the user is generated and notified to the user via the device.

[0787] This is where the emotion engine plays a key role. The emotion engine analyzes the user's emotional state in real time through facial recognition and voice analysis. For example, if the user is feeling stressed or fatigued, it will adjust the training plan and suggest relaxation exercises or short periods of rest. Also, if the user is highly motivated, it will suggest a more challenging training plan, helping them to engage in effective fitness activities.

[0788] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. This progress report includes the user's progress toward their goals, changes in weight and body fat percentage, as well as emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, motivating them to continue their fitness activities.

[0789] The emotion engine also suggests the best time to participate in virtual fitness events. For example, by sending notifications encouraging participation when a user is in a positive emotional state, users can optimize their performance when competing against other users. This way, users can be more motivated and stick to their fitness plans.

[0790] The entire system helps users effectively achieve their ideal body shape by visualizing it specifically and providing personalized training and nutrition plans using an emotion engine.

[0791] The processing flow will be explained below.

[0792] Step 1:

[0793] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[0794] Step 2:

[0795] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[0796] Step 3:

[0797] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[0798] Step 4:

[0799] Server: Stores the submitted avatar data, which is associated with the user's account.

[0800] Step 5:

[0801] User: Put on the special suit and activate the scanning function on the smartphone app.

[0802] Step 6:

[0803] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[0804] Step 7:

[0805] Device: Sends the acquired body shape data to the server.

[0806] Step 8:

[0807] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[0808] Step 9:

[0809] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[0810] Step 10:

[0811] Server: Delivers training and nutrition plans to users' accounts.

[0812] Step 11:

[0813] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[0814] Step 12:

[0815] User: Enters daily training and dietary data into the application.

[0816] Step 13:

[0817] Terminal: Sends input data to the server in real time.

[0818] Step 14:

[0819] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[0820] Step 15:

[0821] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[0822] Step 16:

[0823] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[0824] Step 17:

[0825] Server: Plans and configures virtual fitness events and notifies users.

[0826] Step 18:

[0827] User: Registers for an event and expresses their intention to attend.

[0828] Step 19:

[0829] Device: Provides users with more information about the event and how to participate.

[0830] Step 20:

[0831] Server: Collects and aggregates activity data sent by users during the event period.

[0832] Step 21:

[0833] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[0834] Step 22:

[0835] On the device: The emotion engine uses a camera and microphone to capture the user's face and voice so that it can analyze the user's emotional state in real time.

[0836] Step 23:

[0837] Terminal: Emotion data analyzed by the emotion engine is sent to the server.

[0838] Step 24:

[0839] Server: Analyzes emotional data and adjusts training and nutrition plans based on the user's emotional state.

[0840] Step 25:

[0841] Server: Adjusts and delivers motivational messages and reminders based on the user's emotional state.

[0842] Step 26:

[0843] Server: Based on the user's emotional state, the server notifies them when to participate in virtual fitness events. Through this process, users can effectively work towards their ideal body shape and stay motivated.

[0844] Example 2

[0845] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0846] Traditional fitness and nutrition plan providers provide plans based on the user's ideal body type and goal settings, but often provide a uniform plan without taking the user's emotional state into consideration. This can lead to problems such as a lack of motivation, difficulty continuing with the plan, and insufficient results. Furthermore, there is a lack of a comprehensive way to understand the user's progress and emotional state, making it easy for users to find themselves in a situation where they don't know how to adjust their training and nutrition plans.

[0847] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means: In this invention, the server includes an input means for the user to set an ideal body type and clothing, a means for generating an avatar based on the data input by the input means, a means for saving the data of the generated avatar, a means for scanning the actual body type of the user using dedicated clothing, a means for saving the scanned body type data, a means for comparing the saved avatar body type data with the actual body type data, a means for generating a training plan and a nutrition plan based on the comparison results, a means for notifying the user of the generated plans, a means including an emotion engine for analyzing the user's emotions, and a means for adjusting the training plan based on the analysis results of the emotion engine. The system also includes a means for generating a progress report based on the scanned body shape data and training data, a means for delivering the progress report to the user, a means for sending motivational messages and reminders based on the progress report, a means for recording the user's emotional state using an emotion engine, a means for generating a progress report including the emotional state, a means for planning and setting up virtual fitness events to promote competition and interaction between users and encouraging participation in the events, a means for aggregating activity data during the event period and displaying the results, and a means for analyzing the user's emotional state using the emotion engine and encouraging participation in the events when the user is in a positive emotional state. This allows the system to provide individually optimized training and nutrition plans taking the user's emotional state into consideration, thereby maintaining and improving the user's motivation. Furthermore, the system allows the user to effectively continue their fitness activities through comprehensive progress management and real-time feedback.

[0848] "User" means an individual who utilizes the System to set their ideal body shape and health goals and implement a fitness and nutrition plan.

[0849] "Input means" refers to the means by which a user inputs information about their ideal body type and clothing into the system, and includes, for example, a smartphone application or a web form.

[0850] "Avatar generation means" includes software and algorithms for generating a 3D avatar based on data entered by a user.

[0851] The "storage means" is a means for temporarily or long-term storing the generated avatar and scanned body data in a database.

[0852] "Specialized clothing" refers to specialized suits or wearable devices used to accurately scan the user's body shape.

[0853] The "scanning means" is a means of acquiring the actual body shape of a user wearing special clothing as digital data using a camera or sensor.

[0854] "Comparison means" includes algorithms and software for comparing stored avatar body data with actual scan data.

[0855] The "training plan generation means" is a means for generating an individually optimized fitness plan based on the results of the comparison of body type data.

[0856] The "nutritional plan generation means" is a means for generating an individually optimized meal and supplement plan based on the results of the comparison of body shape data.

[0857] "Notification means" refers to a means for notifying the user of the generated training plan or nutrition plan, and includes, for example, app notifications and emails.

[0858] An "emotion engine" includes software and hardware for analyzing a user's emotional state through facial recognition and voice analysis.

[0859] The "progress report generating means" is a means for generating a report summarizing the user's progress based on the scanned body type data and training data.

[0860] "Delivery means" refers to a means for delivering the generated progress report to the user, including, for example, an app notification, email, or online dashboard.

[0861] The "means for sending motivational messages" refers to a means for sending messages and reminders to maintain and improve the user's motivation based on the progress report.

[0862] A "virtual fitness event" is an online fitness event designed to promote competition and interaction between users.

[0863] "Event participation promotion means" refers to means of notifying or suggesting users to participate in a virtual fitness event.

[0864] The "activity data collection means" is a means for collecting the activity data of users during the event period and displaying the results.

[0865] The present invention is a system that allows users to set their ideal body type and clothing and then provides a personalized fitness and nutrition plan based on that. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions, allowing it to grasp the user's emotional state in real time and flexibly adjust the plan, thereby maximizing the user's motivation and the effectiveness of the fitness plan.

[0866] First, the user launches the application and inputs their ideal body type and clothing. Specifically, they enter values ​​such as height, weight, and waist size using a smartphone app or web form. The device receives this input data and uses 3D avatar generation software to generate a 3D avatar, which is then sent to the server. The server then stores the received avatar data in a database.

[0867] Next, the user puts on special clothing and undergoes a body scan. The body scan function is activated from the smartphone app, and the device guides the user on the camera position and pose. After the user poses as instructed, their body data is captured by the camera and sent from the device to a server. The server stores this body data in a database and compares it with stored 3D avatar data. Based on the comparison results, the server generates an individually optimized training and nutrition plan for the user, which is then communicated to the user via their device.

[0868] In addition, the emotion engine uses facial recognition and voice analysis to analyze the user's emotional state in real time. For example, if the user is feeling stressed, the emotion engine will suggest relaxation exercises or short breaks, and if the user is highly motivated, it will suggest a more challenging training plan.

[0869] When users enter their daily training and dietary data, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. The progress report includes the user's progress toward their goals, changes in weight and body fat percentage, and emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, encouraging them to continue their fitness activities.

[0870] The emotion engine also suggests participation in virtual fitness events based on the user's emotional state, and if the user is determined to be in a positive emotional state, it can further motivate them by notifying them and optimizing their performance when competing against other users.

[0871] Specific examples

[0872] For example, if a user enters the following data:

[0873] Ideal body type: Tall / Slim

[0874] Training data: 5km jog

[0875] Emotional state: Positive

[0876] Based on this data, the system would:

[0877] Avatar generation software creates 3D avatars

[0878] A specific training plan is generated based on a comparison of the scan data and the 3D avatar data.

[0879] The emotion engine analyzes the user's positive emotional state and suggests more challenging training.

[0880] Examples of prompts include:

[0881] text

[0882] Username: Yamada Taro

[0883] Ideal body type: Tall / Slim

[0884] Today's training data: 5km jog

[0885] Emotional state: Positive

[0886] Using this prompt, the system will provide the user with the optimal fitness and nutrition plan based on their condition.

[0887] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0888] Step 1: User Settings

[0889] The user launches the application and sets their ideal body type and clothing. A smartphone app or web form is used as the input method. When the user enters their ideal values ​​such as "height," "weight," and "waist size," the device receives this data. It also generates a 3D avatar based on the ideal body type. At this time, a generative AI model is used to generate prompts for the 3D avatar, and the 3D avatar is created based on these. The device then sends the generated 3D avatar data to the server, which stores it in a database.

[0890] Input: User's ideal body type data (height, weight, waist size, etc.)

[0891] Data processing: 3D avatar generation

[0892] Output: 3D avatar data (stored on the server)

[0893] Specific behavior:

[0894] The user launches the application and inputs their ideal body type data, such as height 180cm, weight 70kg, and waist size 80cm. The device then uses the generative AI model to generate a 3D avatar, which is then sent to a server for storage.

[0895] Step 2: Body scan and data submission

[0896] The user puts on the special clothing and activates the body scan function from a smartphone app. The device guides the user on the camera position and pose, and acquires body data of the user as they pose as instructed. The device then processes the acquired body data and sends it to the server. The server stores the received body data in a database and compares it with previously saved 3D avatar data.

[0897] Input: User's body shape data (scan results)

[0898] Data processing: Acquiring body shape data and comparing it with 3D avatar data

[0899] Output: Comparison results (saved on the server)

[0900] Specific behavior:

[0901] The user puts on the special clothing and activates the body scanning function from a smartphone app. They are guided to the correct camera position and pose. The device then takes a full-body photo of the user and acquires body data, which is then sent to a server and compared with the 3D avatar data.

[0902] Step 3: Create a training and nutrition plan

[0903] Based on the comparison results, the server generates an optimized training plan and nutrition plan for the user, using the system's training algorithm and nutrition plan generation engine, and notifies the user of the generated plan via their device.

[0904] Input: Comparison result

[0905] Data processing: generating training and nutrition plans

[0906] Output: Generated training and nutrition plans (notified to the user)

[0907] Specific behavior:

[0908] The server applies a training algorithm based on the comparison results to generate a training plan, and similarly uses a nutrition plan generation engine to create a personalized nutrition plan, which is then sent to the user via their device.

[0909] Step 4: Daily data entry and emotional state recording

[0910] Users input their daily training and dietary data into the application. The device receives this data and uses an emotion engine to analyze and record the user's emotional state. The device then transmits this data in real time to the server, which stores all the data in a database.

[0911] Input: Training data, Food data, Emotional state data

[0912] Data processing: Data reception and sentiment analysis

[0913] Output: Recorded data (stored on the server)

[0914] Specific behavior:

[0915] Users input details of their training and diet into the app, and the device uses an emotion engine to analyze their emotional state through facial recognition and voice analysis, and all data is sent and stored on a server.

[0916] Step 5: Generate a progress report

[0917] The server periodically generates a progress report for the user, which includes the progress of the goal, changes in weight and body fat percentage, and sentiment analysis results. The generated progress report is delivered to the user via their device.

[0918] Input: Scan data, training data, emotion data

[0919] Data Processing: Report Generation

[0920] Output: Progress report (delivered to user)

[0921] Specific behavior:

[0922] The server analyzes all data and generates a progress report that includes the user's progress toward their goal, changes in weight and body fat percentage, and sentiment analysis results. This report is then delivered to the user via their device.

[0923] Step 6: Propose a Virtual Fitness Event

[0924] The emotion engine monitors the user's emotional state in real time. If the user is determined to be in a positive emotional state, the device will suggest participating in a virtual fitness event. This suggestion will be sent to the user as a notification.

[0925] Input: Emotional state data

[0926] Data processing: sentiment analysis and event suggestion

[0927] Output: Event participation suggestion notification (notify user)

[0928] Specific behavior:

[0929] The emotion engine analyzes the user's emotional data in real time, and if a positive state is detected, the device will send a notification encouraging the user to participate in a virtual fitness event.

[0930] Through these processing steps, the system provides users with an effective fitness and nutrition plan to achieve their ideal body shape and helps motivate them to continue.

[0931] (Application example 2)

[0932] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0933] Conventional fitness and nutrition plan providing systems have difficulty taking into account the user's emotional state, making it difficult to maintain the user's motivation and drive to train. Furthermore, fitness activities at physical stores have the problem of not being able to properly adjust training based on the user's individual data in real time. This makes it difficult to provide a comprehensive fitness plan that effectively helps users achieve their ideal physique.

[0934] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0935] In this invention, the server includes: an input means for the user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means including an emotion engine that analyzes the user's emotional state in real time through facial recognition and voice analysis; a means for automatically adjusting the training plan based on the analysis results by the emotion engine; and a means for notifying the user of the adjusted plan using a smartphone or smart glasses.

[0936] This allows the system to grasp the user's emotional state in real time and flexibly adjust appropriate training and nutrition plans accordingly, effectively supporting fitness activities in physical stores while maintaining the user's motivation.

[0937] Definition of Terms

[0938] The "input means" is a means by which the user sets his or her ideal body type and clothing.

[0939] The "means for generating an avatar" is a means for generating a 3D model based on the data input by the input means.

[0940] The "means for saving avatar data" refers to a data accumulation means for storing data on the generated avatars.

[0941] "Means for scanning body shape" refers to a device and method for acquiring the user's actual body shape data using a special suit.

[0942] The "means for saving body type data" is a data accumulation means for storing scanned body type data.

[0943] The "comparison means" is a means for comparing the stored avatar's body shape data with the actual body shape data.

[0944] The "means for generating a training plan and a nutrition plan" is a means for creating an appropriate exercise and diet plan based on the comparison results.

[0945] The "means for notifying" is a means for notifying the user of the generated plan.

[0946] The "Emotion Engine" is an engine for analyzing the user's emotional state in real time through facial recognition and voice analysis.

[0947] "Means for automatic adjustment" refers to a means for changing the training plan based on the analysis results of the emotion engine.

[0948] "Smart devices" is a general term for portable information terminals such as smartphones and smart glasses.

[0949] A "scanning device" is a device that detects the user's body shape and obtains the necessary data.

[0950] The system of the present invention allows users to set their ideal body type and clothing, and provides fitness and nutrition plans based on those. The system incorporates an emotion engine, allowing it to flexibly adjust the plan according to the user's emotional state.

[0951] Hardware and Software Configuration

[0952] Hardware:

[0953] 1. Smartphone: The user sets their ideal body type and clothing and scans their body data.

[0954] 2. Smart glasses: These are used to understand the user's emotional state in real time and also display notifications.

[0955] 3. Server: Manages data, generates fitness plans, and creates progress reports.

[0956] 4. Scanning device: Accurately scans the user's body shape and captures data.

[0957] software:

[0958] 1. Applications: Applications installed by users on smartphones or smart glasses.

[0959] 2. Emotion Engine: An AI model that analyzes the user's emotional state through facial recognition and voice analysis.

[0960] 3. Database: Stores and manages user avatars, body data, and progress reports.

[0961] System processing overview

[0962] 1. User Input and Avatar Generation:

[0963] Users use a smartphone application to input their ideal body type and clothing.

[0964] The avatar generation program generates a 3D avatar based on the input data and stores it on the server.

[0965] 2. Actual body scan:

[0966] Users wear a special suit and use their smartphone camera or scanning device to obtain body data.

[0967] The acquired data is sent to a server in real time and stored.

[0968] 3. Plan Generation and Notification:

[0969] The server compares the stored avatar's body data with the actual body data and generates a fitness and nutrition plan based on the analysis results.

[0970] The generated plan will be notified to the user's smartphone.

[0971] 4. Emotional engine regulation:

[0972] Using the smart glasses or smartphone camera and microphone, the emotion engine analyzes the user's emotional state in real time.

[0973] The server automatically adjusts the training plan based on the emotional state data and notifies the user.

[0974] Specific examples

[0975] When a user arrives at the gym and puts on the smart glasses, the emotion engine analyzes the user's facial expressions and suggests relaxation exercises if it determines that the user is tired.

[0976] If the emotion engine determines that the user is in good spirits, they will be notified of a more challenging training plan.

[0977] Prompt Sentence Examples

[0978] Classify the user's current emotional state as "😊" (joy), "😞" (sadness), "😠" (anger), "😨" (surprise), etc. Suggest appropriate fitness plan adjustments based on the user's facial image and emotional state.

[0979] In this way, the system can understand the user's emotional state in real time and provide an appropriate training plan accordingly, thereby maintaining the user's motivation and supporting effective fitness activities.

[0980] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0981] Program processing steps

[0982] Step 1:

[0983] The user launches the smartphone app and selects their ideal body type and clothing. Based on the data entered (height, weight, ideal body fat percentage, clothing details, etc.), the device generates a 3D avatar. This 3D avatar data is then sent to the server and stored.

[0984] Input: User-supplied data about ideal body type and clothing

[0985] Output: Saved avatar data

[0986] Step 2:

[0987] The user puts on a special suit and scans their body shape data using a smartphone or scanning device. The device guides them on the camera position and pose required for the scan. The acquired body shape data is sent to a server and saved.

[0988] Input: Actual body shape data from scanning device

[0989] Output: Saved body shape data

[0990] Step 3:

[0991] The server compares the stored avatar's body data with the user's actual body data. Using a comparison algorithm, it calculates the difference between the user's current body shape and their ideal body shape. Based on this, it generates a personalized training and nutrition plan. The plan is then sent to the user's smartphone.

[0992] Input: Saved avatar data and actual body data

[0993] Output: Training and nutrition plans

[0994] Step 4:

[0995] The user wears smart glasses or a smartphone, and the emotion engine grasps the user's emotional state in real time through facial recognition and voice analysis, which is then sent to the server.

[0996] Input: User's facial image and voice data

[0997] Output: User's emotional state

[0998] Step 5:

[0999] The server analyzes the emotional state data obtained by the emotion engine and automatically adjusts the training plan. For example, if the user is feeling stressed, it will recommend relaxation exercises, and if the user is highly motivated, it will create a training plan with a higher level of difficulty. This adjusted plan is then notified to the user again.

[1000] Input: User emotional state data

[1001] Output: Tailored training plan

[1002] Step 6:

[1003] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server, which then generates a progress report. The progress report includes the progress of goals, changes in weight and body fat percentage, and emotion analysis results. This report is then delivered to the user.

[1004] Input: Daily training data, diet data, emotional state data

[1005] Output: Progress report

[1006] Step 7:

[1007] Based on the progress reports, the server generates and sends motivational messages and reminders to the user, helping to keep the user motivated.

[1008] Input: Progress Report

[1009] Output: Motivational messages and reminders

[1010] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1011] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1012] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1013] [Third embodiment]

[1014] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1015] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1016] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1017] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1018] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1019] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1020] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1021] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1022] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1023] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1024] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1025] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1026] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. This system provides users with a means to continuously maintain their motivation and efficiently approach their ideal body type.

[1027] First, the user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it. This avatar visually reproduces the user's ideal appearance, and the generated avatar data is sent to a server for storage.

[1028] Next, the user puts on the special suit and activates the scanning function from a smartphone app. The device guides the user on the camera position and pose required for scanning. Once the user performs the scan, the device acquires the user's body shape data (e.g., height, weight, waist size, etc.) and sends it to the server. The server stores this body shape data and compares it with the avatar data.

[1029] The server then generates a training and nutrition plan tailored to the user based on the comparison results. This plan includes specific exercises and dietary guidelines to help the user achieve their ideal body shape. The plan is then sent to the user via their device.

[1030] Furthermore, when the user enters daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate a progress report and periodically delivers it to the user. This progress report includes the user's progress toward their goal, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress report. For example, if the user achieves a certain goal, a message such as "Great progress! Keep up the great work!" may be delivered.

[1031] A distinctive feature of this invention is the virtual fitness event. The server plans limited-time fitness events and notifies users to promote competition and interaction among users. When a user participates in an event, their device transmits their activity data to the server in real time, and the server compiles the activity data during the event and displays the results. In this way, users can compete with each other to achieve their ideal body shape, increasing their motivation.

[1032] This system helps users achieve their goals efficiently by visualizing their ideal body type and providing training and nutritional management based on that.

[1033] The processing flow will be explained below.

[1034] Step 1:

[1035] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[1036] Step 2:

[1037] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[1038] Step 3:

[1039] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[1040] Step 4:

[1041] Server: Stores the submitted avatar data, which is associated with the user's account.

[1042] Step 5:

[1043] User: Put on the special suit and activate the scanning function on the smartphone app.

[1044] Step 6:

[1045] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[1046] Step 7:

[1047] Device: Sends the acquired body shape data to the server.

[1048] Step 8:

[1049] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[1050] Step 9:

[1051] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[1052] Step 10:

[1053] Server: Delivers training and nutrition plans to users' accounts.

[1054] Step 11:

[1055] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[1056] Step 12:

[1057] User: Enters daily training and dietary data into the application.

[1058] Step 13:

[1059] Terminal: Sends input data to the server in real time.

[1060] Step 14:

[1061] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[1062] Step 15:

[1063] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[1064] Step 16:

[1065] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[1066] Step 17:

[1067] Server: Plans and configures virtual fitness events and notifies users.

[1068] Step 18:

[1069] User: Registers for an event and expresses their intention to attend.

[1070] Step 19:

[1071] Device: Provides users with more information about the event and how to participate.

[1072] Step 20:

[1073] Server: Collects and aggregates activity data sent by users during the event period.

[1074] Step 21:

[1075] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[1076] This series of steps allows users to stay motivated and effectively work towards their ideal body shape.

[1077] Example 1

[1078] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1079] In today's society, it is difficult for individuals to find the right fitness and nutrition plan to achieve their ideal body shape. Existing systems lack the ability to provide customized plans based on individual body shape data and efficiently support users in achieving their goals while maintaining their motivation. Furthermore, they lack mechanisms to encourage competition and interaction between users and interactive features to support continuous training.

[1080] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1081] In this invention, the server includes a means for collecting a user's daily training data and dietary data and transmitting it to the server, a means for optimizing training and nutrition plans using a generative AI model, and a means for notifying the user of the generated plans. This allows for the provision of personalized fitness and nutrition plans based on individual body shape data, and for appropriate feedback and motivation according to the user's progress. Furthermore, by hosting virtual fitness events that encourage competition and interaction between users, an interactive experience can be provided to support continuous training.

[1082] "User" refers to an individual who utilizes the System to define their ideal body type and clothing and receive fitness and nutrition plans.

[1083] "Input means" refers to a device or software that provides an interface for users to input data such as their ideal body type and clothing into the system.

[1084] An "avatar" is a 3D model generated based on the user's desired body type and clothing.

[1085] The "specialized suit" refers to a wearable device used to accurately scan the user's actual body shape.

[1086] "Scanning means" refers to the equipment and technology used to acquire the user's body shape data using a special suit.

[1087] "Comparison means" refers to an algorithm or system for comparing stored avatar body data with actual body data.

[1088] "Generator" refers to the algorithms and / or generative AI models used to generate training and nutrition plans.

[1089] "Notification Method" refers to the mechanism used to notify users of generated plans and progress reports, such as smartphone notifications or in-app notifications.

[1090] "Progress Report" means a report generated based on a User's daily training and dietary data that indicates the User's progress toward goals and other progress.

[1091] "Motivational messages" refer to encouraging messages sent to users based on their progress and goal achievement.

[1092] "Reminders" refer to notifications that encourage users to continue training and managing their diet.

[1093] A "virtual fitness event" refers to a fitness event held on a digital platform to promote competition and interaction among users.

[1094] "Activity Data" refers to data collected during a user's fitness or training, such as calories burned and exercise time.

[1095] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. The system is configured and implemented as follows.

[1096] First, a user launches an application on their device and sets their ideal body type and clothing. The application on the device provides an input interface where the user selects their ideal body characteristics (e.g., muscular, slim, specific clothing, etc.). Software within the device is used to generate a 3D avatar based on the user's input data. Specifically, 3D modeling software such as Blender or Unity is used.

[1097] The generated 3D avatar data is sent from the device to the server in JSON format and stored in the server's database (e.g., MySQL or PostgreSQL).

[1098] Next, the user puts on the fitness suit and activates the scanning function within the application. The device provides the user with specific instructions on the camera position and pose required for scanning. The scanning is performed using the Structure Sensor and Kinect. When the user poses according to the instructions, the device uses these devices to obtain body shape data (e.g., height, weight, waist size, etc.) and sends it to the server.

[1099] The server compares the user's body shape data with the saved avatar data. This comparison is performed using the Python Scipy library. Based on the comparison results, the server uses a generative AI model (e.g., GPT or BERT) to generate a training and nutrition plan suitable for the user. This plan is then sent to the device and notified to the user.

[1100] When users enter their daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate progress reports and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress reports.

[1101] As a concrete example, assume that User A's ideal body type is muscular and slim waist. User A puts on a fitness suit at home, stands in the center of the room, and begins using the scanning function within the application. The device provides guidance such as, "Stand with your right feet shoulder-width apart and your arms hanging straight down," and uses the Structure Sensor to obtain data on height, weight, and waist size.

[1102] Based on the comparison result, the server inputs the following prompt sentence into the generative AI model:

[1103] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[1104] This allows the server to generate personalized training and nutrition plans based on individual body data and notify User A.

[1105] In addition, virtual fitness events are held regularly. The server sends event notifications to devices to promote competition and interaction among users. When users participate, their devices send activity data during the event in real time to the server, which then aggregates the data and displays the results.

[1106] In this way, the system of the present invention comprehensively provides a means for the user to efficiently approach their ideal body shape.

[1107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1108] Step 1:

[1109] The user launches the application and sets their ideal body type and clothing.

[1110] Specific operation: The user taps the fitness app from the smartphone home screen to launch it, and then selects their ideal body type (e.g., muscular, slim) and clothing on the initial setup screen.

[1111] Input: User input data (ideal body type and clothing)

[1112] Output: Input ideal body type and clothing data

[1113] Step 2:

[1114] The device generates a 3D avatar based on the user's input data.

[1115] Specific operation: The device passes the user's input data to 3D modeling software (Blender or Unity) and obtains the generated 3D avatar.

[1116] Input: Ideal body type and clothing data

[1117] Data processing: Generate a 3D avatar using Blender or Unity

[1118] Output: Generated 3D avatar data (3D model)

[1119] Step 3:

[1120] The device sends the generated 3D avatar data to the server and stores it.

[1121] Specific operation: The device converts the 3D avatar data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database (MySQL or PostgreSQL).

[1122] Input: 3D avatar data (JSON format)

[1123] Output: Avatar data stored in the database

[1124] Step 4:

[1125] The user wears a special fitness suit and has their body data scanned.

[1126] Specific operation: The user puts on the fitness suit and activates the scan function in the app. The device provides specific instructions on camera position and pose, and uses the Structure Sensor and Kinect to capture body shape data.

[1127] Input: Camera image and user pose

[1128] Data calculation: Obtain data such as height, weight, and waist size using the Structure Sensor or Kinect

[1129] Output: Acquired body shape data (numerical data)

[1130] Step 5:

[1131] The body shape data acquired by the device is sent to a server and stored.

[1132] Specific operation: The device converts the acquired body shape data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database.

[1133] Input: Body shape data (JSON format)

[1134] Output: Body shape data stored in a database

[1135] Step 6:

[1136] The server compares the stored avatar body data with the actual body data.

[1137] Specific operation: The server uses Python's Scipy library to calculate the difference between the avatar data and the actual body shape data.

[1138] Input: Avatar data and body shape data

[1139] Data calculation: Calculate the difference of data using the Scipy library

[1140] Output: Comparison results (numerical data)

[1141] Step 7:

[1142] The server generates a training plan and a nutrition plan based on the comparison results.

[1143] Specific operation: The server inputs prompt sentences into a generative AI model (GPT or BERT) to generate training and nutrition plans suitable for the user.

[1144] Input: Comparison result data

[1145] Data calculation: Enter a prompt into the generative AI model to generate a plan

[1146] Output: Customized training and nutrition plans

[1147] Example prompt sentence:

[1148] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[1149] Step 8:

[1150] The server notifies the user of the generated plan.

[1151] Specific operation: The server sends the generated plan to the terminal, and the terminal displays a notification to the user.

[1152] Input: Customized training and nutrition plans

[1153] Output: A message to inform the user

[1154] Step 9:

[1155] The user enters daily training and dietary data into the app, which is then sent to the server by the device.

[1156] Specific operation: The user enters training and meal details into the app, and the device sends this information to the server in real time.

[1157] Input: User's daily training and diet data

[1158] Output: Data sent to the server

[1159] Step 10:

[1160] The server generates a progress report based on the user's input data and delivers it to the user periodically.

[1161] Specific behavior: The server generates and notifies the user of progress reports, including weight fluctuations and training results.

[1162] Input: User's daily training and diet data

[1163] Data calculation: Generate progress reports (processing statistical data)

[1164] Output: Progress reports and notification messages to the user

[1165] Step 11:

[1166] The server organizes virtual fitness events and notifies users.

[1167] Specific operation: The server generates event information and sends a notification to the user via the terminal to invite them to participate.

[1168] Input: Event information

[1169] Output: Event notification to the user

[1170] Step 12:

[1171] A user participates in an event, and the terminal transmits activity data during the event to the server.

[1172] Specific operation: A user participates in an event, and the device transmits activity data to the server in real time.

[1173] Input: User's activity data during the event

[1174] Output: Activity data sent to the server

[1175] Step 13:

[1176] The server will compile activity data during the event and display the results.

[1177] Specific operation: The server aggregates the event activity data and displays the results on a dashboard.

[1178] Input: Activity data during the event

[1179] Data Calculation: Aggregating data and generating results

[1180] Output: Results displayed in a dashboard

[1181] The above is the specific processing flow of this system.

[1182] (Application example 1)

[1183] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1184] Conventional fitness systems not only struggle to provide individually optimized plans to help users achieve their ideal body shape, but also lack mechanisms to maintain motivation. Competition and interaction between users is also limited, leaving the environment unsuitable for promoting sustained fitness activities. Furthermore, the tediousness of specific operations and the complexity of progress management are factors that prevent users from continuing to use the system.

[1185] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1186] In this invention, the server includes: an input means for a user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means for the user to implement and manage their fitness and nutrition plan in the virtual store; a means for users to participate in, compete with, and interact with each other in fitness events in the virtual store; a means for generating a progress report based on the scanned body type data and training data; a means for delivering the progress report to the user; a means for sending motivational messages and reminders based on the progress report; a means for automatically generating an individually optimized fitness plan using a generative AI model associated with the virtual store; a means for planning and setting up virtual fitness events to encourage competition and interaction between users and to encourage participation in the events; a means for compiling activity data during the event period and displaying the results; and a means for optimizing the user experience using prompt messages in the virtual store. This allows users to efficiently approach their ideal body shape through individually optimized fitness plans, while also maintaining motivation and encouraging competition and interaction among users to continue their fitness activities.

[1187] "User" refers to an individual who utilizes the System to set their ideal body type and clothing and receive fitness and nutrition plans.

[1188] "Input means" refers to the interface or device that allows the user to set their ideal body type and clothing.

[1189] An "avatar" is a three-dimensional virtual person that visually represents a user's ideal body type and clothing.

[1190] The "special suit" refers to a special wearable device used to accurately scan the user's actual body shape.

[1191] "Means of scanning" refers to the technology and equipment that uses a special suit to obtain the user's body data.

[1192] "Means for comparison" refers to the technology or algorithms used to analyze and compare the stored avatar body data with actual body data.

[1193] "Training Plan" refers to a plan that includes specific exercise menus and exercises to help users achieve their ideal body shape.

[1194] "Nutrition Plan" refers to personalized recommendations, including healthy eating guidelines and meal plans.

[1195] "Means for notification" refers to the interface or technology used to communicate the generated training and nutrition plans to the user.

[1196] "Virtual Store" means the online virtual environment provided for users to implement and manage their fitness and nutrition plans.

[1197] "Fitness Event" refers to an online event where users can engage in fitness activities through competition and interaction.

[1198] "Generative AI model" refers to the artificial intelligence techniques and algorithms used to automatically create personalized, optimized fitness plans.

[1199] A "prompt sentence" refers to a sentence used to input specific instructions or conditions into a generative AI model.

[1200] MODE FOR CARRYING OUT THE INVENTION

[1201] The system for implementing this invention mainly comprises a user, a server, and a terminal, and also includes technology for scanning the user's body shape data using a specialized suit and technology for generating individually optimized fitness and nutrition plans using a generative AI model.

[1202] Hardware and software used

[1203] Hardware: Smartphone, dedicated suit, camera

[1204] Software: Keras (used for loading and inferencing deep learning models), OpenCV (camera image acquisition and processing)

[1205] Description of system programs and processes

[1206] 1. User Input and Avatar Generation:

[1207] Users can input their ideal body type and clothing through a smartphone app. Based on this input data, the server uses Keras to generate a 3D avatar, which is then saved on the server.

[1208] 2. Body Scan:

[1209] The user wears a special suit and scans their body shape using their smartphone camera. The device uses OpenCV to get a real-time feed from the camera and collects body shape data, which is then sent to a server for storage.

[1210] 3. Plan Generation and Notification:

[1211] The server compares the stored avatar's body shape data with the user's actual body shape data and generates an exercise and nutrition plan. This plan is generated using a generative AI model using Keras. The generated plan is then sent to the user's smartphone.

[1212] 4. Progress Management and Reporting:

[1213] Users enter their daily training and dietary data into the app. The device sends this data to the server in real time. The server generates progress reports based on this data and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. The server also sends motivational messages and reminders based on the progress reports.

[1214] 5. Virtual Fitness Events:

[1215] The server plans limited-time virtual fitness events and notifies users to promote competition and interaction between users. When a user participates in an event, their device sends their activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[1216] Specific examples

[1217] An example of implementation:

[1218] After launching the app, the user sets their ideal body type as "height 180cm, weight 70kg, waist 80cm." A 3D avatar is generated based on these settings. The user then wears a special suit and scans their body, sending the collected body data to a server. The server uses this data to generate individually optimized training and nutrition plans and notifies the user. The user exercises based on the fitness plan and records their daily progress in the app. The server generates progress reports and distributes them to the user regularly. Users can also participate in limited-time virtual fitness events, where they can compete and interact with other users.

[1219] Example prompt sentence:

[1220] "Generate a 3D avatar for a user who sets their ideal body type as 'height 180cm, weight 70kg, waist 80cm'. Based on that avatar, propose a monthly fitness plan."

[1221] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1222] Step 1:

[1223] Ideal body type and clothing settings (input)

[1224] The user launches the smartphone app and sets their ideal body type and clothing.

[1225] Input: Ideal body data (e.g. height, weight, waist size) and clothing data entered by the user.

[1226] Specific action: Enter numbers or options into the app form and tap the settings button.

[1227] Output: The set ideal body type and clothing data is sent to the server.

[1228] Step 2:

[1229] Avatar generation

[1230] The server generates a 3D avatar using a generative AI model (Keras) based on the ideal body shape data sent by the user.

[1231] Input: User's ideal body type and clothing data.

[1232] Specific operation: The Keras model is executed on the server and a 3D avatar is generated.

[1233] Output: The generated 3D avatar data is saved on the server.

[1234] Step 3:

[1235] Body Scan

[1236] Users wear a special suit and scan their body shape using their smartphone camera, and the device uses OpenCV to get a real-time feed and collect the body shape data.

[1237] Input: Camera footage of a user wearing a specialized suit.

[1238] What it does: The app's scanning function is activated, and the user stands in front of the camera and strikes a suitable pose. The image is processed using OpenCV, and body shape data is extracted.

[1239] Output: The extracted body shape data is sent to the server.

[1240] Step 4:

[1241] Save and compare body shape data

[1242] The server stores the received body shape data and compares it with existing avatar data.

[1243] Input: Scanned body data and existing avatar data.

[1244] Specific operation: Body shape data is stored in a database on the server, and a comparison algorithm is run based on the stored data.

[1245] Output: The comparison results are generated.

[1246] Step 5:

[1247] Generate training and nutrition plans

[1248] Based on the comparison results, the server uses Keras to generate individually optimized training and nutrition plans.

[1249] Input: The comparison result.

[1250] What it does: The Keras model runs on the server and generates appropriate training menus and nutritional guidelines.

[1251] Output: The generated training and nutrition plans are saved on the server.

[1252] Step 6:

[1253] User Notification

[1254] The server notifies the user of the generated training and nutrition plans on their smartphone.

[1255] Input: Generated training and nutrition plans.

[1256] Specific operation: Plan information is pushed to your smartphone via the notification system.

[1257] Output: User receives plan information.

[1258] Step 7:

[1259] Progress Management and Reporting

[1260] Users enter their daily training and dietary data into the app, which then transmits the data in real time to a server. The server then generates progress reports based on the data and periodically delivers them to the user.

[1261] Input: User-entered training and diet data.

[1262] What happens: You enter data into a form in the app and tap the save button, which sends the data to the server and generates a progress report.

[1263] Output: Progress reports and motivational messages are sent to the user.

[1264] Step 8:

[1265] Planning a Virtual Fitness Event

[1266] The server plans time-limited virtual fitness events and notifies users of them in order to promote competition and interaction between users.

[1267] Input: Event planning information.

[1268] Specific behavior: Event information is created on the server and notified to the user via push notification.

[1269] Output: An event notification is sent to the user.

[1270] Step 9:

[1271] Event data aggregation and display

[1272] When a user participates in an event, the device transmits the activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[1273] Input: User activity data during the event period.

[1274] What it does: The app collects data during the event and sends it to the server, which aggregates the data and generates results.

[1275] Output: The aggregated results are displayed on the event dashboard.

[1276] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1277] The present invention combines a system that allows users to set their ideal body type and clothing, and then provides a personalized fitness and nutrition plan based on that, with an "emotion engine" that recognizes the user's emotions. As the user approaches their ideal body type, the emotion engine grasps the user's emotional state in real time, enabling it to flexibly adjust the content of their activities. This provides a system that maximizes the user's motivation and the effectiveness of their fitness plan.

[1278] The user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it, sending this avatar data to a server for storage. The user then puts on the special suit and activates the body scan function from the smartphone app. The device guides the user through the camera position and poses required for the scan, acquires the user's body data, and sends it to the server. The server stores the received body data and compares it with the avatar data. Based on the results of this comparison, a training plan and nutrition plan tailored to the user is generated and notified to the user via the device.

[1279] This is where the emotion engine plays a key role. The emotion engine analyzes the user's emotional state in real time through facial recognition and voice analysis. For example, if the user is feeling stressed or fatigued, it will adjust the training plan and suggest relaxation exercises or short periods of rest. Also, if the user is highly motivated, it will suggest a more challenging training plan, helping them to engage in effective fitness activities.

[1280] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. This progress report includes the user's progress toward their goals, changes in weight and body fat percentage, as well as emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, motivating them to continue their fitness activities.

[1281] The emotion engine also suggests the best time to participate in virtual fitness events. For example, by sending notifications encouraging participation when a user is in a positive emotional state, users can optimize their performance when competing against other users. This way, users can be more motivated and stick to their fitness plans.

[1282] The entire system helps users effectively achieve their ideal body shape by visualizing it specifically and providing personalized training and nutrition plans using an emotion engine.

[1283] The processing flow will be explained below.

[1284] Step 1:

[1285] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[1286] Step 2:

[1287] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[1288] Step 3:

[1289] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[1290] Step 4:

[1291] Server: Stores the submitted avatar data, which is associated with the user's account.

[1292] Step 5:

[1293] User: Put on the special suit and activate the scanning function on the smartphone app.

[1294] Step 6:

[1295] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[1296] Step 7:

[1297] Device: Sends the acquired body shape data to the server.

[1298] Step 8:

[1299] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[1300] Step 9:

[1301] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[1302] Step 10:

[1303] Server: Delivers training and nutrition plans to users' accounts.

[1304] Step 11:

[1305] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[1306] Step 12:

[1307] User: Enters daily training and dietary data into the application.

[1308] Step 13:

[1309] Terminal: Sends input data to the server in real time.

[1310] Step 14:

[1311] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[1312] Step 15:

[1313] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[1314] Step 16:

[1315] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[1316] Step 17:

[1317] Server: Plans and configures virtual fitness events and notifies users.

[1318] Step 18:

[1319] User: Registers for an event and expresses their intention to attend.

[1320] Step 19:

[1321] Device: Provides users with more information about the event and how to participate.

[1322] Step 20:

[1323] Server: Collects and aggregates activity data sent by users during the event period.

[1324] Step 21:

[1325] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[1326] Step 22:

[1327] On the device: The emotion engine uses a camera and microphone to capture the user's face and voice so that it can analyze the user's emotional state in real time.

[1328] Step 23:

[1329] Terminal: Emotion data analyzed by the emotion engine is sent to the server.

[1330] Step 24:

[1331] Server: Analyzes emotional data and adjusts training and nutrition plans based on the user's emotional state.

[1332] Step 25:

[1333] Server: Adjusts and delivers motivational messages and reminders based on the user's emotional state.

[1334] Step 26:

[1335] Server: Based on the user's emotional state, the server notifies them when to participate in virtual fitness events. Through this process, users can effectively work towards their ideal body shape and stay motivated.

[1336] Example 2

[1337] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1338] Traditional fitness and nutrition plan providers provide plans based on the user's ideal body type and goal settings, but often provide a uniform plan without taking the user's emotional state into consideration. This can lead to problems such as a lack of motivation, difficulty continuing with the plan, and insufficient results. Furthermore, there is a lack of a comprehensive way to understand the user's progress and emotional state, making it easy for users to find themselves in a situation where they don't know how to adjust their training and nutrition plans.

[1339] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means: In this invention, the server includes an input means for the user to set an ideal body type and clothing, a means for generating an avatar based on the data input by the input means, a means for saving the data of the generated avatar, a means for scanning the actual body type of the user using dedicated clothing, a means for saving the scanned body type data, a means for comparing the saved avatar body type data with the actual body type data, a means for generating a training plan and a nutrition plan based on the comparison results, a means for notifying the user of the generated plans, a means including an emotion engine for analyzing the user's emotions, and a means for adjusting the training plan based on the analysis results of the emotion engine. The system also includes a means for generating a progress report based on the scanned body shape data and training data, a means for delivering the progress report to the user, a means for sending motivational messages and reminders based on the progress report, a means for recording the user's emotional state using an emotion engine, a means for generating a progress report including the emotional state, a means for planning and setting up virtual fitness events to promote competition and interaction between users and encouraging participation in the events, a means for aggregating activity data during the event period and displaying the results, and a means for analyzing the user's emotional state using the emotion engine and encouraging participation in the events when the user is in a positive emotional state. This allows the system to provide individually optimized training and nutrition plans taking the user's emotional state into consideration, thereby maintaining and improving the user's motivation. Furthermore, the system allows the user to effectively continue their fitness activities through comprehensive progress management and real-time feedback.

[1340] "User" means an individual who utilizes the System to set their ideal body shape and health goals and implement a fitness and nutrition plan.

[1341] "Input means" refers to the means by which a user inputs information about their ideal body type and clothing into the system, and includes, for example, a smartphone application or a web form.

[1342] "Avatar generation means" includes software and algorithms for generating a 3D avatar based on data entered by a user.

[1343] The "storage means" is a means for temporarily or long-term storing the generated avatar and scanned body data in a database.

[1344] "Specialized clothing" refers to specialized suits or wearable devices used to accurately scan the user's body shape.

[1345] The "scanning means" is a means of acquiring the actual body shape of a user wearing special clothing as digital data using a camera or sensor.

[1346] "Comparison means" includes algorithms and software for comparing stored avatar body data with actual scan data.

[1347] The "training plan generation means" is a means for generating an individually optimized fitness plan based on the results of the comparison of body type data.

[1348] The "nutritional plan generation means" is a means for generating an individually optimized meal and supplement plan based on the results of the comparison of body shape data.

[1349] "Notification means" refers to a means for notifying the user of the generated training plan or nutrition plan, and includes, for example, app notifications and emails.

[1350] An "emotion engine" includes software and hardware for analyzing a user's emotional state through facial recognition and voice analysis.

[1351] The "progress report generating means" is a means for generating a report summarizing the user's progress based on the scanned body type data and training data.

[1352] "Delivery means" refers to a means for delivering the generated progress report to the user, including, for example, an app notification, email, or online dashboard.

[1353] The "means for sending motivational messages" refers to a means for sending messages and reminders to maintain and improve the user's motivation based on the progress report.

[1354] A "virtual fitness event" is an online fitness event designed to promote competition and interaction between users.

[1355] "Event participation promotion means" refers to means of notifying or suggesting users to participate in a virtual fitness event.

[1356] The "activity data collection means" is a means for collecting the activity data of users during the event period and displaying the results.

[1357] The present invention is a system that allows users to set their ideal body type and clothing and then provides a personalized fitness and nutrition plan based on that. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions, allowing it to grasp the user's emotional state in real time and flexibly adjust the plan, thereby maximizing the user's motivation and the effectiveness of the fitness plan.

[1358] First, the user launches the application and inputs their ideal body type and clothing. Specifically, they enter values ​​such as height, weight, and waist size using a smartphone app or web form. The device receives this input data and uses 3D avatar generation software to generate a 3D avatar, which is then sent to the server. The server then stores the received avatar data in a database.

[1359] Next, the user puts on special clothing and undergoes a body scan. The body scan function is activated from the smartphone app, and the device guides the user on the camera position and pose. After the user poses as instructed, their body data is captured by the camera and sent from the device to a server. The server stores this body data in a database and compares it with stored 3D avatar data. Based on the comparison results, the server generates an individually optimized training and nutrition plan for the user, which is then communicated to the user via their device.

[1360] In addition, the emotion engine uses facial recognition and voice analysis to analyze the user's emotional state in real time. For example, if the user is feeling stressed, the emotion engine will suggest relaxation exercises or short breaks, and if the user is highly motivated, it will suggest a more challenging training plan.

[1361] When users enter their daily training and dietary data, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. The progress report includes the user's progress toward their goals, changes in weight and body fat percentage, and emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, encouraging them to continue their fitness activities.

[1362] The emotion engine also suggests participation in virtual fitness events based on the user's emotional state, and if the user is determined to be in a positive emotional state, it can further motivate them by notifying them and optimizing their performance when competing against other users.

[1363] Specific examples

[1364] For example, if a user enters the following data:

[1365] Ideal body type: Tall / Slim

[1366] Training data: 5km jog

[1367] Emotional state: Positive

[1368] Based on this data, the system would:

[1369] Avatar generation software creates 3D avatars

[1370] A specific training plan is generated based on a comparison of the scan data and the 3D avatar data.

[1371] The emotion engine analyzes the user's positive emotional state and suggests more challenging training.

[1372] Examples of prompts include:

[1373] text

[1374] Username: Yamada Taro

[1375] Ideal body type: Tall / Slim

[1376] Today's training data: 5km jog

[1377] Emotional state: Positive

[1378] Using this prompt, the system will provide the user with the optimal fitness and nutrition plan based on their condition.

[1379] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1380] Step 1: User Settings

[1381] The user launches the application and sets their ideal body type and clothing. A smartphone app or web form is used as the input method. When the user enters their ideal values ​​such as "height," "weight," and "waist size," the device receives this data. It also generates a 3D avatar based on the ideal body type. At this time, a generative AI model is used to generate prompts for the 3D avatar, and the 3D avatar is created based on these. The device then sends the generated 3D avatar data to the server, which stores it in a database.

[1382] Input: User's ideal body type data (height, weight, waist size, etc.)

[1383] Data processing: 3D avatar generation

[1384] Output: 3D avatar data (stored on the server)

[1385] Specific behavior:

[1386] The user launches the application and inputs their ideal body type data, such as height 180cm, weight 70kg, and waist size 80cm. The device then uses the generative AI model to generate a 3D avatar, which is then sent to a server for storage.

[1387] Step 2: Body scan and data submission

[1388] The user puts on the special clothing and activates the body scan function from a smartphone app. The device guides the user on the camera position and pose, and acquires body data of the user as they pose as instructed. The device then processes the acquired body data and sends it to the server. The server stores the received body data in a database and compares it with previously saved 3D avatar data.

[1389] Input: User's body shape data (scan results)

[1390] Data processing: Acquiring body shape data and comparing it with 3D avatar data

[1391] Output: Comparison results (saved on the server)

[1392] Specific behavior:

[1393] The user puts on the special clothing and activates the body scanning function from a smartphone app. They are guided to the correct camera position and pose. The device then takes a full-body photo of the user and acquires body data, which is then sent to a server and compared with the 3D avatar data.

[1394] Step 3: Create a training and nutrition plan

[1395] Based on the comparison results, the server generates an optimized training plan and nutrition plan for the user, using the system's training algorithm and nutrition plan generation engine, and notifies the user of the generated plan via their device.

[1396] Input: Comparison result

[1397] Data processing: generating training and nutrition plans

[1398] Output: Generated training and nutrition plans (notified to the user)

[1399] Specific behavior:

[1400] The server applies a training algorithm based on the comparison results to generate a training plan, and similarly uses a nutrition plan generation engine to create a personalized nutrition plan, which is then sent to the user via their device.

[1401] Step 4: Daily data entry and emotional state recording

[1402] Users input their daily training and dietary data into the application. The device receives this data and uses an emotion engine to analyze and record the user's emotional state. The device then transmits this data in real time to the server, which stores all the data in a database.

[1403] Input: Training data, Food data, Emotional state data

[1404] Data processing: Data reception and sentiment analysis

[1405] Output: Recorded data (stored on the server)

[1406] Specific behavior:

[1407] Users input details of their training and diet into the app, and the device uses an emotion engine to analyze their emotional state through facial recognition and voice analysis, and all data is sent and stored on a server.

[1408] Step 5: Generate a progress report

[1409] The server periodically generates a progress report for the user, which includes the progress of the goal, changes in weight and body fat percentage, and sentiment analysis results. The generated progress report is delivered to the user via their device.

[1410] Input: Scan data, training data, emotion data

[1411] Data Processing: Report Generation

[1412] Output: Progress report (delivered to user)

[1413] Specific behavior:

[1414] The server analyzes all data and generates a progress report that includes the user's progress toward their goal, changes in weight and body fat percentage, and sentiment analysis results. This report is then delivered to the user via their device.

[1415] Step 6: Propose a Virtual Fitness Event

[1416] The emotion engine monitors the user's emotional state in real time. If the user is determined to be in a positive emotional state, the device will suggest participating in a virtual fitness event. This suggestion will be sent to the user as a notification.

[1417] Input: Emotional state data

[1418] Data processing: sentiment analysis and event suggestion

[1419] Output: Event participation suggestion notification (notify user)

[1420] Specific behavior:

[1421] The emotion engine analyzes the user's emotional data in real time, and if a positive state is detected, the device will send a notification encouraging the user to participate in a virtual fitness event.

[1422] Through these processing steps, the system provides users with an effective fitness and nutrition plan to achieve their ideal body shape and helps motivate them to continue.

[1423] (Application example 2)

[1424] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1425] Conventional fitness and nutrition plan providing systems have difficulty taking into account the user's emotional state, making it difficult to maintain the user's motivation and drive to train. Furthermore, fitness activities at physical stores have the problem of not being able to properly adjust training based on the user's individual data in real time. This makes it difficult to provide a comprehensive fitness plan that effectively helps users achieve their ideal physique.

[1426] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1427] In this invention, the server includes: an input means for the user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means including an emotion engine that analyzes the user's emotional state in real time through facial recognition and voice analysis; a means for automatically adjusting the training plan based on the analysis results by the emotion engine; and a means for notifying the user of the adjusted plan using a smartphone or smart glasses.

[1428] This allows the system to grasp the user's emotional state in real time and flexibly adjust appropriate training and nutrition plans accordingly, effectively supporting fitness activities in physical stores while maintaining the user's motivation.

[1429] Definition of Terms

[1430] The "input means" is a means by which the user sets his or her ideal body type and clothing.

[1431] The "means for generating an avatar" is a means for generating a 3D model based on the data input by the input means.

[1432] The "means for saving avatar data" refers to a data accumulation means for storing data on the generated avatars.

[1433] "Means for scanning body shape" refers to a device and method for acquiring the user's actual body shape data using a special suit.

[1434] The "means for saving body type data" is a data accumulation means for storing scanned body type data.

[1435] The "comparison means" is a means for comparing the stored avatar's body shape data with the actual body shape data.

[1436] The "means for generating a training plan and a nutrition plan" is a means for creating an appropriate exercise and diet plan based on the comparison results.

[1437] The "means for notifying" is a means for notifying the user of the generated plan.

[1438] The "Emotion Engine" is an engine for analyzing the user's emotional state in real time through facial recognition and voice analysis.

[1439] "Means for automatic adjustment" refers to a means for changing the training plan based on the analysis results of the emotion engine.

[1440] "Smart devices" is a general term for portable information terminals such as smartphones and smart glasses.

[1441] A "scanning device" is a device that detects the user's body shape and obtains the necessary data.

[1442] The system of the present invention allows users to set their ideal body type and clothing, and provides fitness and nutrition plans based on those. The system incorporates an emotion engine, allowing it to flexibly adjust the plan according to the user's emotional state.

[1443] Hardware and Software Configuration

[1444] Hardware:

[1445] 1. Smartphone: The user sets their ideal body type and clothing and scans their body data.

[1446] 2. Smart glasses: These are used to understand the user's emotional state in real time and also display notifications.

[1447] 3. Server: Manages data, generates fitness plans, and creates progress reports.

[1448] 4. Scanning device: Accurately scans the user's body shape and captures data.

[1449] software:

[1450] 1. Applications: Applications installed by users on smartphones or smart glasses.

[1451] 2. Emotion Engine: An AI model that analyzes the user's emotional state through facial recognition and voice analysis.

[1452] 3. Database: Stores and manages user avatars, body data, and progress reports.

[1453] System processing overview

[1454] 1. User Input and Avatar Generation:

[1455] Users use a smartphone application to input their ideal body type and clothing.

[1456] The avatar generation program generates a 3D avatar based on the input data and stores it on the server.

[1457] 2. Actual body scan:

[1458] Users wear a special suit and use their smartphone camera or scanning device to obtain body data.

[1459] The acquired data is sent to a server in real time and stored.

[1460] 3. Plan Generation and Notification:

[1461] The server compares the stored avatar's body data with the actual body data and generates a fitness and nutrition plan based on the analysis results.

[1462] The generated plan will be notified to the user's smartphone.

[1463] 4. Emotional engine regulation:

[1464] Using the smart glasses or smartphone camera and microphone, the emotion engine analyzes the user's emotional state in real time.

[1465] The server automatically adjusts the training plan based on the emotional state data and notifies the user.

[1466] Specific examples

[1467] When a user arrives at the gym and puts on the smart glasses, the emotion engine analyzes the user's facial expressions and suggests relaxation exercises if it determines that the user is tired.

[1468] If the emotion engine determines that the user is in good spirits, they will be notified of a more challenging training plan.

[1469] Prompt Sentence Examples

[1470] Classify the user's current emotional state as "😊" (joy), "😞" (sadness), "😠" (anger), "😨" (surprise), etc. Suggest appropriate fitness plan adjustments based on the user's facial image and emotional state.

[1471] In this way, the system can understand the user's emotional state in real time and provide an appropriate training plan accordingly, thereby maintaining the user's motivation and supporting effective fitness activities.

[1472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1473] Program processing steps

[1474] Step 1:

[1475] The user launches the smartphone app and selects their ideal body type and clothing. Based on the data entered (height, weight, ideal body fat percentage, clothing details, etc.), the device generates a 3D avatar. This 3D avatar data is then sent to the server and stored.

[1476] Input: User-supplied data about ideal body type and clothing

[1477] Output: Saved avatar data

[1478] Step 2:

[1479] The user puts on a special suit and scans their body shape data using a smartphone or scanning device. The device guides them on the camera position and pose required for the scan. The acquired body shape data is sent to a server and saved.

[1480] Input: Actual body shape data from scanning device

[1481] Output: Saved body shape data

[1482] Step 3:

[1483] The server compares the stored avatar's body data with the user's actual body data. Using a comparison algorithm, it calculates the difference between the user's current body shape and their ideal body shape. Based on this, it generates a personalized training and nutrition plan. The plan is then sent to the user's smartphone.

[1484] Input: Saved avatar data and actual body data

[1485] Output: Training and nutrition plans

[1486] Step 4:

[1487] The user wears smart glasses or a smartphone, and the emotion engine grasps the user's emotional state in real time through facial recognition and voice analysis, which is then sent to the server.

[1488] Input: User's facial image and voice data

[1489] Output: User's emotional state

[1490] Step 5:

[1491] The server analyzes the emotional state data obtained by the emotion engine and automatically adjusts the training plan. For example, if the user is feeling stressed, it will recommend relaxation exercises, and if the user is highly motivated, it will create a training plan with a higher level of difficulty. This adjusted plan is then notified to the user again.

[1492] Input: User emotional state data

[1493] Output: Tailored training plan

[1494] Step 6:

[1495] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server, which then generates a progress report. The progress report includes the progress of goals, changes in weight and body fat percentage, and emotion analysis results. This report is then delivered to the user.

[1496] Input: Daily training data, diet data, emotional state data

[1497] Output: Progress report

[1498] Step 7:

[1499] Based on the progress reports, the server generates and sends motivational messages and reminders to the user, helping to keep the user motivated.

[1500] Input: Progress Report

[1501] Output: Motivational messages and reminders

[1502] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1503] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1504] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1505] [Fourth embodiment]

[1506] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1507] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1508] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1509] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1510] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1511] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1512] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1513] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1514] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1515] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1516] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1517] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1518] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1519] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. This system provides users with a means to continuously maintain their motivation and efficiently approach their ideal body type.

[1520] First, the user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it. This avatar visually reproduces the user's ideal appearance, and the generated avatar data is sent to a server for storage.

[1521] Next, the user puts on the special suit and activates the scanning function from a smartphone app. The device guides the user on the camera position and pose required for scanning. Once the user performs the scan, the device acquires the user's body shape data (e.g., height, weight, waist size, etc.) and sends it to the server. The server stores this body shape data and compares it with the avatar data.

[1522] The server then generates a training and nutrition plan tailored to the user based on the comparison results. This plan includes specific exercises and dietary guidelines to help the user achieve their ideal body shape. The plan is then sent to the user via their device.

[1523] Furthermore, when the user enters daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate a progress report and periodically delivers it to the user. This progress report includes the user's progress toward their goal, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress report. For example, if the user achieves a certain goal, a message such as "Great progress! Keep up the great work!" may be delivered.

[1524] A distinctive feature of this invention is the virtual fitness event. The server plans limited-time fitness events and notifies users to promote competition and interaction among users. When a user participates in an event, their device transmits their activity data to the server in real time, and the server compiles the activity data during the event and displays the results. In this way, users can compete with each other to achieve their ideal body shape, increasing their motivation.

[1525] This system helps users achieve their goals efficiently by visualizing their ideal body type and providing training and nutritional management based on that.

[1526] The processing flow will be explained below.

[1527] Step 1:

[1528] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[1529] Step 2:

[1530] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[1531] Step 3:

[1532] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[1533] Step 4:

[1534] Server: Stores the submitted avatar data, which is associated with the user's account.

[1535] Step 5:

[1536] User: Put on the special suit and activate the scanning function on the smartphone app.

[1537] Step 6:

[1538] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[1539] Step 7:

[1540] Device: Sends the acquired body shape data to the server.

[1541] Step 8:

[1542] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[1543] Step 9:

[1544] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[1545] Step 10:

[1546] Server: Delivers training and nutrition plans to users' accounts.

[1547] Step 11:

[1548] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[1549] Step 12:

[1550] User: Enters daily training and dietary data into the application.

[1551] Step 13:

[1552] Terminal: Sends input data to the server in real time.

[1553] Step 14:

[1554] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[1555] Step 15:

[1556] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[1557] Step 16:

[1558] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[1559] Step 17:

[1560] Server: Plans and configures virtual fitness events and notifies users.

[1561] Step 18:

[1562] User: Registers for an event and expresses their intention to attend.

[1563] Step 19:

[1564] Device: Provides users with more information about the event and how to participate.

[1565] Step 20:

[1566] Server: Collects and aggregates activity data sent by users during the event period.

[1567] Step 21:

[1568] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[1569] This series of steps allows users to stay motivated and effectively work towards their ideal body shape.

[1570] Example 1

[1571] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1572] In today's society, it is difficult for individuals to find the right fitness and nutrition plan to achieve their ideal body shape. Existing systems lack the ability to provide customized plans based on individual body shape data and efficiently support users in achieving their goals while maintaining their motivation. Furthermore, they lack mechanisms to encourage competition and interaction between users and interactive features to support continuous training.

[1573] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1574] In this invention, the server includes a means for collecting a user's daily training data and dietary data and transmitting it to the server, a means for optimizing training and nutrition plans using a generative AI model, and a means for notifying the user of the generated plans. This allows for the provision of personalized fitness and nutrition plans based on individual body shape data, and for appropriate feedback and motivation according to the user's progress. Furthermore, by hosting virtual fitness events that encourage competition and interaction between users, an interactive experience can be provided to support continuous training.

[1575] "User" refers to an individual who utilizes the System to define their ideal body type and clothing and receive fitness and nutrition plans.

[1576] "Input means" refers to a device or software that provides an interface for users to input data such as their ideal body type and clothing into the system.

[1577] An "avatar" is a 3D model generated based on the user's desired body type and clothing.

[1578] The "specialized suit" refers to a wearable device used to accurately scan the user's actual body shape.

[1579] "Scanning means" refers to the equipment and technology used to acquire the user's body shape data using a special suit.

[1580] "Comparison means" refers to an algorithm or system for comparing stored avatar body data with actual body data.

[1581] "Generator" refers to the algorithms and / or generative AI models used to generate training and nutrition plans.

[1582] "Notification Method" refers to the mechanism used to notify users of generated plans and progress reports, such as smartphone notifications or in-app notifications.

[1583] "Progress Report" means a report generated based on a User's daily training and dietary data that indicates the User's progress toward goals and other progress.

[1584] "Motivational messages" refer to encouraging messages sent to users based on their progress and goal achievement.

[1585] "Reminders" refer to notifications that encourage users to continue training and managing their diet.

[1586] A "virtual fitness event" refers to a fitness event held on a digital platform to promote competition and interaction among users.

[1587] "Activity Data" refers to data collected during a user's fitness or training, such as calories burned and exercise time.

[1588] The present invention is a system that allows users to set their ideal body type and clothing as an avatar, and then proposes personalized fitness and nutrition plans based on that avatar data. The system is configured and implemented as follows.

[1589] First, a user launches an application on their device and sets their ideal body type and clothing. The application on the device provides an input interface where the user selects their ideal body characteristics (e.g., muscular, slim, specific clothing, etc.). Software within the device is used to generate a 3D avatar based on the user's input data. Specifically, 3D modeling software such as Blender or Unity is used.

[1590] The generated 3D avatar data is sent from the device to the server in JSON format and stored in the server's database (e.g., MySQL or PostgreSQL).

[1591] Next, the user puts on the fitness suit and activates the scanning function within the application. The device provides the user with specific instructions on the camera position and pose required for scanning. The scanning is performed using the Structure Sensor and Kinect. When the user poses according to the instructions, the device uses these devices to obtain body shape data (e.g., height, weight, waist size, etc.) and sends it to the server.

[1592] The server compares the user's body shape data with the saved avatar data. This comparison is performed using the Python Scipy library. Based on the comparison results, the server uses a generative AI model (e.g., GPT or BERT) to generate a training and nutrition plan suitable for the user. This plan is then sent to the device and notified to the user.

[1593] When users enter their daily training and dietary data into the application, the device sends this data to the server in real time. The server uses this data to generate progress reports and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. Motivational messages and reminders are also sent based on the progress reports.

[1594] As a concrete example, assume that User A's ideal body type is muscular and slim waist. User A puts on a fitness suit at home, stands in the center of the room, and begins using the scanning function within the application. The device provides guidance such as, "Stand with your right feet shoulder-width apart and your arms hanging straight down," and uses the Structure Sensor to obtain data on height, weight, and waist size.

[1595] Based on the comparison result, the server inputs the following prompt sentence into the generative AI model:

[1596] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[1597] This allows the server to generate personalized training and nutrition plans based on individual body data and notify User A.

[1598] In addition, virtual fitness events are held regularly. The server sends event notifications to devices to promote competition and interaction among users. When users participate, their devices send activity data during the event in real time to the server, which then aggregates the data and displays the results.

[1599] In this way, the system of the present invention comprehensively provides a means for the user to efficiently approach their ideal body shape.

[1600] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1601] Step 1:

[1602] The user launches the application and sets their ideal body type and clothing.

[1603] Specific operation: The user taps the fitness app from the smartphone home screen to launch it, and then selects their ideal body type (e.g., muscular, slim) and clothing on the initial setup screen.

[1604] Input: User input data (ideal body type and clothing)

[1605] Output: Input ideal body type and clothing data

[1606] Step 2:

[1607] The device generates a 3D avatar based on the user's input data.

[1608] Specific operation: The device passes the user's input data to 3D modeling software (Blender or Unity) and obtains the generated 3D avatar.

[1609] Input: Ideal body type and clothing data

[1610] Data processing: Generate a 3D avatar using Blender or Unity

[1611] Output: Generated 3D avatar data (3D model)

[1612] Step 3:

[1613] The device sends the generated 3D avatar data to the server and stores it.

[1614] Specific operation: The device converts the 3D avatar data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database (MySQL or PostgreSQL).

[1615] Input: 3D avatar data (JSON format)

[1616] Output: Avatar data stored in the database

[1617] Step 4:

[1618] The user wears a special fitness suit and has their body data scanned.

[1619] Specific operation: The user puts on the fitness suit and activates the scan function in the app. The device provides specific instructions on camera position and pose, and uses the Structure Sensor and Kinect to capture body shape data.

[1620] Input: Camera image and user pose

[1621] Data calculation: Obtain data such as height, weight, and waist size using the Structure Sensor or Kinect

[1622] Output: Acquired body shape data (numerical data)

[1623] Step 5:

[1624] The body shape data acquired by the device is sent to a server and stored.

[1625] Specific operation: The device converts the acquired body shape data into JSON format and sends a POST request to the server API endpoint. The server stores the received data in a database.

[1626] Input: Body shape data (JSON format)

[1627] Output: Body shape data stored in a database

[1628] Step 6:

[1629] The server compares the stored avatar body data with the actual body data.

[1630] Specific operation: The server uses Python's Scipy library to calculate the difference between the avatar data and the actual body shape data.

[1631] Input: Avatar data and body shape data

[1632] Data calculation: Calculate the difference of data using the Scipy library

[1633] Output: Comparison results (numerical data)

[1634] Step 7:

[1635] The server generates a training plan and a nutrition plan based on the comparison results.

[1636] Specific operation: The server inputs prompt sentences into a generative AI model (GPT or BERT) to generate training and nutrition plans suitable for the user.

[1637] Input: Comparison result data

[1638] Data calculation: Enter a prompt into the generative AI model to generate a plan

[1639] Output: Customized training and nutrition plans

[1640] Example prompt sentence:

[1641] "Generate a training plan to increase muscle mass for a user who weighs 70 kg and is 175 cm tall."

[1642] Step 8:

[1643] The server notifies the user of the generated plan.

[1644] Specific operation: The server sends the generated plan to the terminal, and the terminal displays a notification to the user.

[1645] Input: Customized training and nutrition plans

[1646] Output: A message to inform the user

[1647] Step 9:

[1648] The user enters daily training and dietary data into the app, which is then sent to the server by the device.

[1649] Specific operation: The user enters training and meal details into the app, and the device sends this information to the server in real time.

[1650] Input: User's daily training and diet data

[1651] Output: Data sent to the server

[1652] Step 10:

[1653] The server generates a progress report based on the user's input data and delivers it to the user periodically.

[1654] Specific behavior: The server generates and notifies the user of progress reports, including weight fluctuations and training results.

[1655] Input: User's daily training and diet data

[1656] Data calculation: Generate progress reports (processing statistical data)

[1657] Output: Progress reports and notification messages to the user

[1658] Step 11:

[1659] The server organizes virtual fitness events and notifies users.

[1660] Specific operation: The server generates event information and sends a notification to the user via the terminal to invite them to participate.

[1661] Input: Event information

[1662] Output: Event notification to the user

[1663] Step 12:

[1664] A user participates in an event, and the terminal transmits activity data during the event to the server.

[1665] Specific operation: A user participates in an event, and the device transmits activity data to the server in real time.

[1666] Input: User's activity data during the event

[1667] Output: Activity data sent to the server

[1668] Step 13:

[1669] The server will compile activity data during the event and display the results.

[1670] Specific operation: The server aggregates the event activity data and displays the results on a dashboard.

[1671] Input: Activity data during the event

[1672] Data Calculation: Aggregating data and generating results

[1673] Output: Results displayed in a dashboard

[1674] The above is the specific processing flow of this system.

[1675] (Application example 1)

[1676] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1677] Conventional fitness systems not only struggle to provide individually optimized plans to help users achieve their ideal body shape, but also lack mechanisms to maintain motivation. Competition and interaction between users is also limited, leaving the environment unsuitable for promoting sustained fitness activities. Furthermore, the tediousness of specific operations and the complexity of progress management are factors that prevent users from continuing to use the system.

[1678] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1679] In this invention, the server includes: an input means for a user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means for the user to implement and manage their fitness and nutrition plan in the virtual store; a means for users to participate in, compete with, and interact with each other in fitness events in the virtual store; a means for generating a progress report based on the scanned body type data and training data; a means for delivering the progress report to the user; a means for sending motivational messages and reminders based on the progress report; a means for automatically generating an individually optimized fitness plan using a generative AI model associated with the virtual store; a means for planning and setting up virtual fitness events to encourage competition and interaction between users and to encourage participation in the events; a means for compiling activity data during the event period and displaying the results; and a means for optimizing the user experience using prompt messages in the virtual store. This allows users to efficiently approach their ideal body shape through individually optimized fitness plans, while also maintaining motivation and encouraging competition and interaction among users to continue their fitness activities.

[1680] "User" refers to an individual who utilizes the System to set their ideal body type and clothing and receive fitness and nutrition plans.

[1681] "Input means" refers to the interface or device that allows the user to set their ideal body type and clothing.

[1682] An "avatar" is a three-dimensional virtual person that visually represents a user's ideal body type and clothing.

[1683] The "special suit" refers to a special wearable device used to accurately scan the user's actual body shape.

[1684] "Means of scanning" refers to the technology and equipment that uses a special suit to obtain the user's body data.

[1685] "Means for comparison" refers to the technology or algorithms used to analyze and compare the stored avatar body data with actual body data.

[1686] "Training Plan" refers to a plan that includes specific exercise menus and exercises to help users achieve their ideal body shape.

[1687] "Nutrition Plan" refers to personalized recommendations, including healthy eating guidelines and meal plans.

[1688] "Means for notification" refers to the interface or technology used to communicate the generated training and nutrition plans to the user.

[1689] "Virtual Store" means the online virtual environment provided for users to implement and manage their fitness and nutrition plans.

[1690] "Fitness Event" refers to an online event where users can engage in fitness activities through competition and interaction.

[1691] "Generative AI model" refers to the artificial intelligence techniques and algorithms used to automatically create personalized, optimized fitness plans.

[1692] A "prompt sentence" refers to a sentence used to input specific instructions or conditions into a generative AI model.

[1693] MODE FOR CARRYING OUT THE INVENTION

[1694] The system for implementing this invention mainly comprises a user, a server, and a terminal, and also includes technology for scanning the user's body shape data using a specialized suit and technology for generating individually optimized fitness and nutrition plans using a generative AI model.

[1695] Hardware and software used

[1696] Hardware: Smartphone, dedicated suit, camera

[1697] Software: Keras (used for loading and inferencing deep learning models), OpenCV (camera image acquisition and processing)

[1698] Description of system programs and processes

[1699] 1. User Input and Avatar Generation:

[1700] Users can input their ideal body type and clothing through a smartphone app. Based on this input data, the server uses Keras to generate a 3D avatar, which is then saved on the server.

[1701] 2. Body Scan:

[1702] The user wears a special suit and scans their body shape using their smartphone camera. The device uses OpenCV to get a real-time feed from the camera and collects body shape data, which is then sent to a server for storage.

[1703] 3. Plan Generation and Notification:

[1704] The server compares the stored avatar's body shape data with the user's actual body shape data and generates an exercise and nutrition plan. This plan is generated using a generative AI model using Keras. The generated plan is then sent to the user's smartphone.

[1705] 4. Progress Management and Reporting:

[1706] Users enter their daily training and dietary data into the app. The device sends this data to the server in real time. The server generates progress reports based on this data and periodically delivers them to the user. These progress reports include the user's progress toward their goals, weight changes, and changes in body fat percentage. The server also sends motivational messages and reminders based on the progress reports.

[1707] 5. Virtual Fitness Events:

[1708] The server plans limited-time virtual fitness events and notifies users to promote competition and interaction between users. When a user participates in an event, their device sends their activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[1709] Specific examples

[1710] An example of implementation:

[1711] After launching the app, the user sets their ideal body type as "height 180cm, weight 70kg, waist 80cm." A 3D avatar is generated based on these settings. The user then wears a special suit and scans their body, sending the collected body data to a server. The server uses this data to generate individually optimized training and nutrition plans and notifies the user. The user exercises based on the fitness plan and records their daily progress in the app. The server generates progress reports and distributes them to the user regularly. Users can also participate in limited-time virtual fitness events, where they can compete and interact with other users.

[1712] Example prompt sentence:

[1713] "Generate a 3D avatar for a user who sets their ideal body type as 'height 180cm, weight 70kg, waist 80cm'. Based on that avatar, propose a monthly fitness plan."

[1714] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1715] Step 1:

[1716] Ideal body type and clothing settings (input)

[1717] The user launches the smartphone app and sets their ideal body type and clothing.

[1718] Input: Ideal body data (e.g. height, weight, waist size) and clothing data entered by the user.

[1719] Specific action: Enter numbers or options into the app form and tap the settings button.

[1720] Output: The set ideal body type and clothing data is sent to the server.

[1721] Step 2:

[1722] Avatar generation

[1723] The server generates a 3D avatar using a generative AI model (Keras) based on the ideal body shape data sent by the user.

[1724] Input: User's ideal body type and clothing data.

[1725] Specific operation: The Keras model is executed on the server and a 3D avatar is generated.

[1726] Output: The generated 3D avatar data is saved on the server.

[1727] Step 3:

[1728] Body Scan

[1729] Users wear a special suit and scan their body shape using their smartphone camera, and the device uses OpenCV to get a real-time feed and collect the body shape data.

[1730] Input: Camera footage of a user wearing a specialized suit.

[1731] What it does: The app's scanning function is activated, and the user stands in front of the camera and strikes a suitable pose. The image is processed using OpenCV, and body shape data is extracted.

[1732] Output: The extracted body shape data is sent to the server.

[1733] Step 4:

[1734] Save and compare body shape data

[1735] The server stores the received body shape data and compares it with existing avatar data.

[1736] Input: Scanned body data and existing avatar data.

[1737] Specific operation: Body shape data is stored in a database on the server, and a comparison algorithm is run based on the stored data.

[1738] Output: The comparison results are generated.

[1739] Step 5:

[1740] Generate training and nutrition plans

[1741] Based on the comparison results, the server uses Keras to generate individually optimized training and nutrition plans.

[1742] Input: The comparison result.

[1743] What it does: The Keras model runs on the server and generates appropriate training menus and nutritional guidelines.

[1744] Output: The generated training and nutrition plans are saved on the server.

[1745] Step 6:

[1746] User Notification

[1747] The server notifies the user of the generated training and nutrition plans on their smartphone.

[1748] Input: Generated training and nutrition plans.

[1749] Specific operation: Plan information is pushed to your smartphone via the notification system.

[1750] Output: User receives plan information.

[1751] Step 7:

[1752] Progress Management and Reporting

[1753] Users enter their daily training and dietary data into the app, which then transmits the data in real time to a server. The server then generates progress reports based on the data and periodically delivers them to the user.

[1754] Input: User-entered training and diet data.

[1755] What happens: You enter data into a form in the app and tap the save button, which sends the data to the server and generates a progress report.

[1756] Output: Progress reports and motivational messages are sent to the user.

[1757] Step 8:

[1758] Planning a Virtual Fitness Event

[1759] The server plans time-limited virtual fitness events and notifies users of them in order to promote competition and interaction between users.

[1760] Input: Event planning information.

[1761] Specific behavior: Event information is created on the server and notified to the user via push notification.

[1762] Output: An event notification is sent to the user.

[1763] Step 9:

[1764] Event data aggregation and display

[1765] When a user participates in an event, the device transmits the activity data to the server in real time, and the server compiles the activity data during the event and displays the results.

[1766] Input: User activity data during the event period.

[1767] What it does: The app collects data during the event and sends it to the server, which aggregates the data and generates results.

[1768] Output: The aggregated results are displayed on the event dashboard.

[1769] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1770] The present invention combines a system that allows users to set their ideal body type and clothing, and then provides a personalized fitness and nutrition plan based on that, with an "emotion engine" that recognizes the user's emotions. As the user approaches their ideal body type, the emotion engine grasps the user's emotional state in real time, enabling it to flexibly adjust the content of their activities. This provides a system that maximizes the user's motivation and the effectiveness of their fitness plan.

[1771] The user launches the application and selects their ideal body type and clothing. The device receives the user's input data and generates a 3D avatar based on it, sending this avatar data to a server for storage. The user then puts on the special suit and activates the body scan function from the smartphone app. The device guides the user through the camera position and poses required for the scan, acquires the user's body data, and sends it to the server. The server stores the received body data and compares it with the avatar data. Based on the results of this comparison, a training plan and nutrition plan tailored to the user is generated and notified to the user via the device.

[1772] This is where the emotion engine plays a key role. The emotion engine analyzes the user's emotional state in real time through facial recognition and voice analysis. For example, if the user is feeling stressed or fatigued, it will adjust the training plan and suggest relaxation exercises or short periods of rest. Also, if the user is highly motivated, it will suggest a more challenging training plan, helping them to engage in effective fitness activities.

[1773] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. This progress report includes the user's progress toward their goals, changes in weight and body fat percentage, as well as emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, motivating them to continue their fitness activities.

[1774] The emotion engine also suggests the best time to participate in virtual fitness events. For example, by sending notifications encouraging participation when a user is in a positive emotional state, users can optimize their performance when competing against other users. This way, users can be more motivated and stick to their fitness plans.

[1775] The entire system helps users effectively achieve their ideal body shape by visualizing it specifically and providing personalized training and nutrition plans using an emotion engine.

[1776] The processing flow will be explained below.

[1777] Step 1:

[1778] User: Launches the application and accesses the avatar creation feature. The user inputs their ideal body type and clothing (e.g., height, weight, waist size, clothing preference, etc.).

[1779] Step 2:

[1780] Terminal: Receives user input data and generates a 3D avatar based on it. The generated avatar data is displayed visually to the user.

[1781] Step 3:

[1782] Terminal: Sends the generated avatar's body shape data and clothing information to the server.

[1783] Step 4:

[1784] Server: Stores the submitted avatar data, which is associated with the user's account.

[1785] Step 5:

[1786] User: Put on the special suit and activate the scanning function on the smartphone app.

[1787] Step 6:

[1788] Device: Displays instructions to start scanning and guides the user on the camera position and pose. Once the user performs the scan, the device acquires the user's body data (e.g., height, weight, waist size, etc.).

[1789] Step 7:

[1790] Device: Sends the acquired body shape data to the server.

[1791] Step 8:

[1792] Server: Stores the received user body data. The data is encrypted and associated with the user's account.

[1793] Step 9:

[1794] Server: Compares the saved avatar body data with the actual body data, analyzes the differences, and generates a training and nutrition plan tailored to the user.

[1795] Step 10:

[1796] Server: Delivers training and nutrition plans to users' accounts.

[1797] Step 11:

[1798] Terminal: Notifies the user of the training plan and nutrition plan received from the server and displays them on the application screen.

[1799] Step 12:

[1800] User: Enters daily training and dietary data into the application.

[1801] Step 13:

[1802] Terminal: Sends input data to the server in real time.

[1803] Step 14:

[1804] Server: Generates progress reports based on the received data, including the user's progress toward their goals, weight gain, and body fat percentage.

[1805] Step 15:

[1806] Server: Delivers progress reports to the user's account, as well as sending motivational messages and reminders.

[1807] Step 16:

[1808] Terminal: Progress reports and motivational messages are notified to the user and displayed within the application.

[1809] Step 17:

[1810] Server: Plans and configures virtual fitness events and notifies users.

[1811] Step 18:

[1812] User: Registers for an event and expresses their intention to attend.

[1813] Step 19:

[1814] Device: Provides users with more information about the event and how to participate.

[1815] Step 20:

[1816] Server: Collects and aggregates activity data sent by users during the event period.

[1817] Step 21:

[1818] Server: Updates the event leaderboard based on the aggregated data and displays the results to users. Prizes are awarded to the top winners.

[1819] Step 22:

[1820] On the device: The emotion engine uses a camera and microphone to capture the user's face and voice so that it can analyze the user's emotional state in real time.

[1821] Step 23:

[1822] Terminal: Emotion data analyzed by the emotion engine is sent to the server.

[1823] Step 24:

[1824] Server: Analyzes emotional data and adjusts training and nutrition plans based on the user's emotional state.

[1825] Step 25:

[1826] Server: Adjusts and delivers motivational messages and reminders based on the user's emotional state.

[1827] Step 26:

[1828] Server: Based on the user's emotional state, the server notifies them when to participate in virtual fitness events. Through this process, users can effectively work towards their ideal body shape and stay motivated.

[1829] Example 2

[1830] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1831] Traditional fitness and nutrition plan providers provide plans based on the user's ideal body type and goal settings, but often provide a uniform plan without taking the user's emotional state into consideration. This can lead to problems such as a lack of motivation, difficulty continuing with the plan, and insufficient results. Furthermore, there is a lack of a comprehensive way to understand the user's progress and emotional state, making it easy for users to find themselves in a situation where they don't know how to adjust their training and nutrition plans.

[1832] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means: In this invention, the server includes an input means for the user to set an ideal body type and clothing, a means for generating an avatar based on the data input by the input means, a means for saving the data of the generated avatar, a means for scanning the actual body type of the user using dedicated clothing, a means for saving the scanned body type data, a means for comparing the saved avatar body type data with the actual body type data, a means for generating a training plan and a nutrition plan based on the comparison results, a means for notifying the user of the generated plans, a means including an emotion engine for analyzing the user's emotions, and a means for adjusting the training plan based on the analysis results of the emotion engine. The system also includes a means for generating a progress report based on the scanned body shape data and training data, a means for delivering the progress report to the user, a means for sending motivational messages and reminders based on the progress report, a means for recording the user's emotional state using an emotion engine, a means for generating a progress report including the emotional state, a means for planning and setting up virtual fitness events to promote competition and interaction between users and encouraging participation in the events, a means for aggregating activity data during the event period and displaying the results, and a means for analyzing the user's emotional state using the emotion engine and encouraging participation in the events when the user is in a positive emotional state. This allows the system to provide individually optimized training and nutrition plans taking the user's emotional state into consideration, thereby maintaining and improving the user's motivation. Furthermore, the system allows the user to effectively continue their fitness activities through comprehensive progress management and real-time feedback.

[1833] "User" means an individual who utilizes the System to set their ideal body shape and health goals and implement a fitness and nutrition plan.

[1834] "Input means" refers to the means by which a user inputs information about their ideal body type and clothing into the system, and includes, for example, a smartphone application or a web form.

[1835] "Avatar generation means" includes software and algorithms for generating a 3D avatar based on data entered by a user.

[1836] The "storage means" is a means for temporarily or long-term storing the generated avatar and scanned body data in a database.

[1837] "Specialized clothing" refers to specialized suits or wearable devices used to accurately scan the user's body shape.

[1838] The "scanning means" is a means of acquiring the actual body shape of a user wearing special clothing as digital data using a camera or sensor.

[1839] "Comparison means" includes algorithms and software for comparing stored avatar body data with actual scan data.

[1840] The "training plan generation means" is a means for generating an individually optimized fitness plan based on the results of the comparison of body type data.

[1841] The "nutritional plan generation means" is a means for generating an individually optimized meal and supplement plan based on the results of the comparison of body shape data.

[1842] "Notification means" refers to a means for notifying the user of the generated training plan or nutrition plan, and includes, for example, app notifications and emails.

[1843] An "emotion engine" includes software and hardware for analyzing a user's emotional state through facial recognition and voice analysis.

[1844] The "progress report generating means" is a means for generating a report summarizing the user's progress based on the scanned body type data and training data.

[1845] "Delivery means" refers to a means for delivering the generated progress report to the user, including, for example, an app notification, email, or online dashboard.

[1846] The "means for sending motivational messages" refers to a means for sending messages and reminders to maintain and improve the user's motivation based on the progress report.

[1847] A "virtual fitness event" is an online fitness event designed to promote competition and interaction between users.

[1848] "Event participation promotion means" refers to means of notifying or suggesting users to participate in a virtual fitness event.

[1849] The "activity data collection means" is a means for collecting the activity data of users during the event period and displaying the results.

[1850] The present invention is a system that allows users to set their ideal body type and clothing and then provides a personalized fitness and nutrition plan based on that. Furthermore, the system is equipped with an emotion engine that recognizes the user's emotions, allowing it to grasp the user's emotional state in real time and flexibly adjust the plan, thereby maximizing the user's motivation and the effectiveness of the fitness plan.

[1851] First, the user launches the application and inputs their ideal body type and clothing. Specifically, they enter values ​​such as height, weight, and waist size using a smartphone app or web form. The device receives this input data and uses 3D avatar generation software to generate a 3D avatar, which is then sent to the server. The server then stores the received avatar data in a database.

[1852] Next, the user puts on special clothing and undergoes a body scan. The body scan function is activated from the smartphone app, and the device guides the user on the camera position and pose. After the user poses as instructed, their body data is captured by the camera and sent from the device to a server. The server stores this body data in a database and compares it with stored 3D avatar data. Based on the comparison results, the server generates an individually optimized training and nutrition plan for the user, which is then communicated to the user via their device.

[1853] In addition, the emotion engine uses facial recognition and voice analysis to analyze the user's emotional state in real time. For example, if the user is feeling stressed, the emotion engine will suggest relaxation exercises or short breaks, and if the user is highly motivated, it will suggest a more challenging training plan.

[1854] When users enter their daily training and dietary data, the emotion engine also records their emotional state at that time. The device sends this data to the server in real time, and the server generates a progress report. The progress report includes the user's progress toward their goals, changes in weight and body fat percentage, and emotional analysis results, and is delivered to the user. This allows users to gain a comprehensive understanding of their physical and emotional state, encouraging them to continue their fitness activities.

[1855] The emotion engine also suggests participation in virtual fitness events based on the user's emotional state, and if the user is determined to be in a positive emotional state, it can further motivate them by notifying them and optimizing their performance when competing against other users.

[1856] Specific examples

[1857] For example, if a user enters the following data:

[1858] Ideal body type: Tall / Slim

[1859] Training data: 5km jog

[1860] Emotional state: Positive

[1861] Based on this data, the system would:

[1862] Avatar generation software creates 3D avatars

[1863] A specific training plan is generated based on a comparison of the scan data and the 3D avatar data.

[1864] The emotion engine analyzes the user's positive emotional state and suggests more challenging training.

[1865] Examples of prompts include:

[1866] text

[1867] Username: Yamada Taro

[1868] Ideal body type: Tall / Slim

[1869] Today's training data: 5km jog

[1870] Emotional state: Positive

[1871] Using this prompt, the system will provide the user with the optimal fitness and nutrition plan based on their condition.

[1872] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1873] Step 1: User Settings

[1874] The user launches the application and sets their ideal body type and clothing. A smartphone app or web form is used as the input method. When the user enters their ideal values ​​such as "height," "weight," and "waist size," the device receives this data. It also generates a 3D avatar based on the ideal body type. At this time, a generative AI model is used to generate prompts for the 3D avatar, and the 3D avatar is created based on these. The device then sends the generated 3D avatar data to the server, which stores it in a database.

[1875] Input: User's ideal body type data (height, weight, waist size, etc.)

[1876] Data processing: 3D avatar generation

[1877] Output: 3D avatar data (stored on the server)

[1878] Specific behavior:

[1879] The user launches the application and inputs their ideal body type data, such as height 180cm, weight 70kg, and waist size 80cm. The device then uses the generative AI model to generate a 3D avatar, which is then sent to a server for storage.

[1880] Step 2: Body scan and data submission

[1881] The user puts on the special clothing and activates the body scan function from a smartphone app. The device guides the user on the camera position and pose, and acquires body data of the user as they pose as instructed. The device then processes the acquired body data and sends it to the server. The server stores the received body data in a database and compares it with previously saved 3D avatar data.

[1882] Input: User's body shape data (scan results)

[1883] Data processing: Acquiring body shape data and comparing it with 3D avatar data

[1884] Output: Comparison results (saved on the server)

[1885] Specific behavior:

[1886] The user puts on the special clothing and activates the body scanning function from a smartphone app. They are guided to the correct camera position and pose. The device then takes a full-body photo of the user and acquires body data, which is then sent to a server and compared with the 3D avatar data.

[1887] Step 3: Create a training and nutrition plan

[1888] Based on the comparison results, the server generates an optimized training plan and nutrition plan for the user, using the system's training algorithm and nutrition plan generation engine, and notifies the user of the generated plan via their device.

[1889] Input: Comparison result

[1890] Data processing: generating training and nutrition plans

[1891] Output: Generated training and nutrition plans (notified to the user)

[1892] Specific behavior:

[1893] The server applies a training algorithm based on the comparison results to generate a training plan, and similarly uses a nutrition plan generation engine to create a personalized nutrition plan, which is then sent to the user via their device.

[1894] Step 4: Daily data entry and emotional state recording

[1895] Users input their daily training and dietary data into the application. The device receives this data and uses an emotion engine to analyze and record the user's emotional state. The device then transmits this data in real time to the server, which stores all the data in a database.

[1896] Input: Training data, Food data, Emotional state data

[1897] Data processing: Data reception and sentiment analysis

[1898] Output: Recorded data (stored on the server)

[1899] Specific behavior:

[1900] Users input details of their training and diet into the app, and the device uses an emotion engine to analyze their emotional state through facial recognition and voice analysis, and all data is sent and stored on a server.

[1901] Step 5: Generate a progress report

[1902] The server periodically generates a progress report for the user, which includes the progress of the goal, changes in weight and body fat percentage, and sentiment analysis results. The generated progress report is delivered to the user via their device.

[1903] Input: Scan data, training data, emotion data

[1904] Data Processing: Report Generation

[1905] Output: Progress report (delivered to user)

[1906] Specific behavior:

[1907] The server analyzes all data and generates a progress report that includes the user's progress toward their goal, changes in weight and body fat percentage, and sentiment analysis results. This report is then delivered to the user via their device.

[1908] Step 6: Propose a Virtual Fitness Event

[1909] The emotion engine monitors the user's emotional state in real time. If the user is determined to be in a positive emotional state, the device will suggest participating in a virtual fitness event. This suggestion will be sent to the user as a notification.

[1910] Input: Emotional state data

[1911] Data processing: sentiment analysis and event suggestion

[1912] Output: Event participation suggestion notification (notify user)

[1913] Specific behavior:

[1914] The emotion engine analyzes the user's emotional data in real time, and if a positive state is detected, the device will send a notification encouraging the user to participate in a virtual fitness event.

[1915] Through these processing steps, the system provides users with an effective fitness and nutrition plan to achieve their ideal body shape and helps motivate them to continue.

[1916] (Application example 2)

[1917] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1918] Conventional fitness and nutrition plan providing systems have difficulty taking into account the user's emotional state, making it difficult to maintain the user's motivation and drive to train. Furthermore, fitness activities at physical stores have the problem of not being able to properly adjust training based on the user's individual data in real time. This makes it difficult to provide a comprehensive fitness plan that effectively helps users achieve their ideal physique.

[1919] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1920] In this invention, the server includes: an input means for the user to set their ideal body type and clothing; a means for generating an avatar based on the data input by the input means; a means for saving the generated avatar data; a means for scanning the user's actual body type using a dedicated suit; a means for saving the scanned body type data; a means for comparing the saved avatar body type data with the actual body type data; a means for generating a training plan and a nutrition plan based on the comparison results; a means for notifying the user of the generated plan; a means including an emotion engine that analyzes the user's emotional state in real time through facial recognition and voice analysis; a means for automatically adjusting the training plan based on the analysis results by the emotion engine; and a means for notifying the user of the adjusted plan using a smartphone or smart glasses.

[1921] This allows the system to grasp the user's emotional state in real time and flexibly adjust appropriate training and nutrition plans accordingly, effectively supporting fitness activities in physical stores while maintaining the user's motivation.

[1922] Definition of Terms

[1923] The "input means" is a means by which the user sets his or her ideal body type and clothing.

[1924] The "means for generating an avatar" is a means for generating a 3D model based on the data input by the input means.

[1925] The "means for saving avatar data" refers to a data accumulation means for storing data on the generated avatars.

[1926] "Means for scanning body shape" refers to a device and method for acquiring the user's actual body shape data using a special suit.

[1927] The "means for saving body type data" is a data accumulation means for storing scanned body type data.

[1928] The "comparison means" is a means for comparing the stored avatar's body shape data with the actual body shape data.

[1929] The "means for generating a training plan and a nutrition plan" is a means for creating an appropriate exercise and diet plan based on the comparison results.

[1930] The "means for notifying" is a means for notifying the user of the generated plan.

[1931] The "Emotion Engine" is an engine for analyzing the user's emotional state in real time through facial recognition and voice analysis.

[1932] "Means for automatic adjustment" refers to a means for changing the training plan based on the analysis results of the emotion engine.

[1933] "Smart devices" is a general term for portable information terminals such as smartphones and smart glasses.

[1934] A "scanning device" is a device that detects the user's body shape and obtains the necessary data.

[1935] The system of the present invention allows users to set their ideal body type and clothing, and provides fitness and nutrition plans based on those. The system incorporates an emotion engine, allowing it to flexibly adjust the plan according to the user's emotional state.

[1936] Hardware and Software Configuration

[1937] Hardware:

[1938] 1. Smartphone: The user sets their ideal body type and clothing and scans their body data.

[1939] 2. Smart glasses: These are used to understand the user's emotional state in real time and also display notifications.

[1940] 3. Server: Manages data, generates fitness plans, and creates progress reports.

[1941] 4. Scanning device: Accurately scans the user's body shape and captures data.

[1942] software:

[1943] 1. Applications: Applications installed by users on smartphones or smart glasses.

[1944] 2. Emotion Engine: An AI model that analyzes the user's emotional state through facial recognition and voice analysis.

[1945] 3. Database: Stores and manages user avatars, body data, and progress reports.

[1946] System processing overview

[1947] 1. User Input and Avatar Generation:

[1948] Users use a smartphone application to input their ideal body type and clothing.

[1949] The avatar generation program generates a 3D avatar based on the input data and stores it on the server.

[1950] 2. Actual body scan:

[1951] Users wear a special suit and use their smartphone camera or scanning device to obtain body data.

[1952] The acquired data is sent to a server in real time and stored.

[1953] 3. Plan Generation and Notification:

[1954] The server compares the stored avatar's body data with the actual body data and generates a fitness and nutrition plan based on the analysis results.

[1955] The generated plan will be notified to the user's smartphone.

[1956] 4. Emotional engine regulation:

[1957] Using the smart glasses or smartphone camera and microphone, the emotion engine analyzes the user's emotional state in real time.

[1958] The server automatically adjusts the training plan based on the emotional state data and notifies the user.

[1959] Specific examples

[1960] When a user arrives at the gym and puts on the smart glasses, the emotion engine analyzes the user's facial expressions and suggests relaxation exercises if it determines that the user is tired.

[1961] If the emotion engine determines that the user is in good spirits, they will be notified of a more challenging training plan.

[1962] Prompt Sentence Examples

[1963] Classify the user's current emotional state as "😊" (joy), "😞" (sadness), "😠" (anger), "😨" (surprise), etc. Suggest appropriate fitness plan adjustments based on the user's facial image and emotional state.

[1964] In this way, the system can understand the user's emotional state in real time and provide an appropriate training plan accordingly, thereby maintaining the user's motivation and supporting effective fitness activities.

[1965] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1966] Program processing steps

[1967] Step 1:

[1968] The user launches the smartphone app and selects their ideal body type and clothing. Based on the data entered (height, weight, ideal body fat percentage, clothing details, etc.), the device generates a 3D avatar. This 3D avatar data is then sent to the server and stored.

[1969] Input: User-supplied data about ideal body type and clothing

[1970] Output: Saved avatar data

[1971] Step 2:

[1972] The user puts on a special suit and scans their body shape data using a smartphone or scanning device. The device guides them on the camera position and pose required for the scan. The acquired body shape data is sent to a server and saved.

[1973] Input: Actual body shape data from scanning device

[1974] Output: Saved body shape data

[1975] Step 3:

[1976] The server compares the stored avatar's body data with the user's actual body data. Using a comparison algorithm, it calculates the difference between the user's current body shape and their ideal body shape. Based on this, it generates a personalized training and nutrition plan. The plan is then sent to the user's smartphone.

[1977] Input: Saved avatar data and actual body data

[1978] Output: Training and nutrition plans

[1979] Step 4:

[1980] The user wears smart glasses or a smartphone, and the emotion engine grasps the user's emotional state in real time through facial recognition and voice analysis, which is then sent to the server.

[1981] Input: User's facial image and voice data

[1982] Output: User's emotional state

[1983] Step 5:

[1984] The server analyzes the emotional state data obtained by the emotion engine and automatically adjusts the training plan. For example, if the user is feeling stressed, it will recommend relaxation exercises, and if the user is highly motivated, it will create a training plan with a higher level of difficulty. This adjusted plan is then notified to the user again.

[1985] Input: User emotional state data

[1986] Output: Tailored training plan

[1987] Step 6:

[1988] When users enter their daily training and dietary data into the application, the emotion engine also records their emotional state at that time. The device sends this data to the server, which then generates a progress report. The progress report includes the progress of goals, changes in weight and body fat percentage, and emotion analysis results. This report is then delivered to the user.

[1989] Input: Daily training data, diet data, emotional state data

[1990] Output: Progress report

[1991] Step 7:

[1992] Based on the progress reports, the server generates and sends motivational messages and reminders to the user, helping to keep the user motivated.

[1993] Input: Progress Report

[1994] Output: Motivational messages and reminders

[1995] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1996] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1997] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1998] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1999] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2000] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2001] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2002] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2003] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2004] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2005] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2006] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2007] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2008] 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.

[2009] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2010] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2011] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2012] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2013] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2014] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2015] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2016] The following is further disclosed regarding the above embodiment.

[2017] (Claim 1)

[2018] an input means for the user to set their ideal body type and clothing;

[2019] means for generating an avatar based on the data input by the input means;

[2020] A means for storing the generated avatar data;

[2021] A method to scan the user's actual body shape using a special suit,

[2022] a means for storing the scanned body shape data;

[2023] means for comparing the stored avatar body shape data with actual body shape data;

[2024] means for generating a training plan and a nutrition plan based on the results of said comparison;

[2025] means for notifying a user of the generated plan;

[2026] A system including:

[2027] (Claim 2)

[2028] means for generating a progress report based on the scanned body shape data and training data;

[2029] means for delivering said progress report to a user;

[2030] means for sending motivational messages and reminders based on said progress reports;

[2031] The system of claim 1 further comprising:

[2032] (Claim 3)

[2033] Plan and host virtual fitness events to promote competition and interaction among users.

[2034] a means for promoting participation in said event;

[2035] A means for aggregating activity data during the event period and displaying the results

[2036] The system of claim 1 further comprising:

[2037] "Example 1"

[2038] (Claim 1)

[2039] an input means for the user to set their ideal body type and clothing;

[2040] means for generating an avatar based on the data input by the input means;

[2041] A means for storing the generated avatar data;

[2042] A method to scan the user's actual body shape using a special suit,

[2043] a means for storing the scanned body shape data;

[2044] means for comparing the stored avatar body shape data with actual body shape data;

[2045] means for generating a training plan and a nutrition plan based on the results of said comparison;

[2046] A means to optimize training and nutrition plans through generative AI models; and

[2047] means for notifying a user of the generated plan;

[2048] A mea...

Claims

1. an input means for the user to set their ideal body type and clothing; means for generating an avatar based on the data input by the input means; A means for storing the generated avatar data; A method to scan the user's actual body shape using a special suit, a means for storing the scanned body shape data; means for comparing the stored avatar body shape data with actual body shape data; means for generating a training plan and a nutrition plan based on the results of said comparison; means for notifying a user of the generated plan; A system including:

2. means for generating a progress report based on the scanned body shape data and training data; means for delivering said progress report to a user; means for sending motivational messages and reminders based on said progress reports; The system of claim 1 further comprising:

3. Plan and host virtual fitness events to promote competition and interaction among users. a means for promoting participation in said event; A means for aggregating activity data during the event period and displaying the results The system of claim 1 further comprising:

Images