System

Abstract

A system is provided.SOLUTION: A system comprising: means for generating an optimal training plan based on a user's goals and personal information; means for analyzing a training video uploaded by the user and providing form corrections and improvements; means for suggesting a nutritionally balanced diet plan based on the user's diet history and physical information; and means for providing rewards depending on goal achievement and training progress.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] Many women in their early to mid-twenties want to start exercising to maintain their health and shape, but find it difficult to get started due to reasons such as the inconvenience of going to the gym alone, a lack of interest in exercise, or financial constraints. They also face challenges such as difficulty maintaining motivation. Conventional systems and methods can take time to provide individual feedback to users, making it difficult to master correct form and effective training methods. The present invention aims to solve these problems and support users in continuing to train. [Means for solving the problem]

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

[0006] 1. A way to generate optimal training plans based on your goals and personal information.

[0007] 2. A means of analyzing training videos uploaded by users and providing form corrections and improvement suggestions.

[0008] 3. A means of proposing nutritionally balanced meal plans based on the user's dietary history and physical information.

[0009] 4. A means of providing rewards based on goal achievement and training continuity.

[0010] This allows users to carry out individually optimized training and nutritional management, enabling them to efficiently maintain their health and physique while maintaining their motivation.In addition, the training plan, video feedback, and meal plan methods send user data to a server and work in conjunction with a method for displaying the generated information on a device, providing users with the information they need in real time.

[0011] A "training plan" is a plan containing specific exercise and workout instructions generated by AI based on the user's physical information and goals.

[0012] "Video analysis" is the process in which AI analyzes training videos uploaded by users and identifies areas for correction and improvement in exercise form and movements.

[0013] "Form correction points" refers to specific points that should be improved by pointing out errors in the user's movements or posture during training.

[0014] A "meal plan" is a plan that proposes individual meal plans that take into consideration nutritional balance and goal achievement based on the user's dietary history and physical information.

[0015] "Reward means" is a mechanism that provides incentives (e.g., gacha tickets, avatar bonuses, coupon codes) that users can earn depending on their goal achievement and training continuity.

[0016] The "server" is a central computer system that receives data from users, generates training and meal plans using AI, and manages feedback and rewards.

[0017] "Device" means an electronic device (e.g., smartphone, tablet, or computer) through which a user enters information and receives training plans, feedback, and meal plans.

[0018] A "goal" is a specific health or fitness outcome that a user wants to achieve (e.g., a specific weight, increased strength, improved endurance, etc.).

[0019] "Personal information" refers to data necessary for individual training and nutritional management, such as the user's age, gender, exercise experience, and dietary history. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, and nutritional management and meal plans. Specific embodiments of the present invention that provide these functions to users are described below.

[0042] 1. Providing training plans

[0043] User: First, the user logs in to their account through the system login screen, then enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.).

[0044] Terminal: The terminal provides this information to the user as an input form and displays a button to send the form to the server after the user has entered the information.

[0045] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan tailored to the user's goals.

[0046] Device: Receives the generated training plan from the server and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[0047] 2. Video guide and feedback

[0048] User: The user records a training video and uploads it to the system via their device.

[0049] Device: Sends the uploaded video to the server and waits for feedback.

[0050] Server: The server passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[0051] Device: Receives feedback from the server and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[0052] 3. Nutritional management and meal plans

[0053] User: The user enters their dietary history, food preferences, allergy information, etc.

[0054] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[0055] Server: The server uses AI to analyze the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[0056] Device: Receives the meal plan sent from the server and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[0057] 4. Reward System

[0058] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[0059] Terminal: Sends this data to the server and waits for the reward to be calculated.

[0060] Server: The server evaluates the user's input data, calculates points and rewards, and generates rewards such as gacha tickets or coupon codes when the points exceed a certain threshold.

[0061] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[0062] Specific examples

[0063] 1. Examples of training plans provided:

[0064] User: User A enters a goal of "building muscle" and wants to do high-intensity training three times a week.

[0065] Server: AI generates a plan based on the data, including high-intensity interval training (HIIT).

[0066] Terminal: The generated plan is displayed on User A's terminal.

[0067] 2. Video guide and feedback example:

[0068] User: User B records a video of himself doing squats and uploads it to the system.

[0069] Server: AI analyzes the video and detects areas for improvement, such as "knees are too far forward."

[0070] Terminal: User B is shown specific form correction guidelines as a result of the analysis.

[0071] As a result, by using the system of the present invention, users can not only carry out an effective and personalized training plan, but also maintain proper form and consume a nutritionally balanced diet, thereby achieving sustained health and physique maintenance.

[0072] The processing flow will be explained below.

[0073] 1. Providing training plans

[0074] Step 1:

[0075] User: A user logs into the system and enters their account information.

[0076] Step 2:

[0077] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[0078] Step 3:

[0079] User: The user enters their information into the form and clicks the submit button.

[0080] Step 4:

[0081] Terminal: The terminal sends the entered information to the server.

[0082] Step 5:

[0083] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[0084] Step 6:

[0085] Server: The server sends the generated training plan to the device.

[0086] Step 7:

[0087] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[0088] 2. Video guide and feedback

[0089] Step 1:

[0090] User: The user records a video of themselves training.

[0091] Step 2:

[0092] User: The user uploads the video they have taken to the system via their device.

[0093] Step 3:

[0094] Device: Sends uploaded videos to the server.

[0095] Step 4:

[0096] Server: The server passes the received video to the AI ​​module.

[0097] Step 5:

[0098] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[0099] Step 6:

[0100] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[0101] Step 7:

[0102] Server: The server sends the generated feedback to the device.

[0103] Step 8:

[0104] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[0105] 3. Nutritional management and meal plans

[0106] Step 1:

[0107] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[0108] Step 2:

[0109] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[0110] Step 3:

[0111] User: The user clicks the submit button.

[0112] Step 4:

[0113] Terminal: The terminal sends the entered meal data to the server.

[0114] Step 5:

[0115] Server: The server uses AI to analyze the nutritional balance based on the data received.

[0116] Step 6:

[0117] Server: AI generates meal plans tailored to the user's goals.

[0118] Step 7:

[0119] Server: The server sends the generated meal plan to the device.

[0120] Step 8:

[0121] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[0122] 4. Reward System

[0123] Step 1:

[0124] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[0125] Step 2:

[0126] Terminal: The terminal sends this data to the server.

[0127] Step 3:

[0128] Server: The server evaluates the data received and calculates points.

[0129] Step 4:

[0130] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[0131] Step 5:

[0132] Server: The server sends the generated reward information to the terminal.

[0133] Step 6:

[0134] Terminal: The terminal displays the sent reward information to the user.

[0135] Example 1

[0136] 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."

[0137] In recent years, the importance of maintaining health and physique has increased, especially among young people. However, it is difficult to effectively provide individual training and meal plans and maintain high motivation. Furthermore, the lack of systems that provide accurate advice on proper training form and nutritional balance makes it difficult for users to sustainably manage their health. Therefore, there is a need to provide users with effective and efficient training and meal plans, as well as a reward system, to increase their motivation.

[0138] 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.

[0139] In this invention, the server includes: a means for a user to log in to the system and input personal information and goals; a means for generating an optimal training plan using an AI algorithm based on the input information; a means for uploading training videos filmed by the user to the system and analyzing form corrections and improvement suggestions using an AI module; a means for inputting the user's dietary history, food preferences, and allergy information and using an AI platform to suggest a nutritionally balanced meal plan based on the input; and a means for evaluating the user's training results and calculating and providing points and rewards. This makes it possible to provide individually optimized training and meal plans, and the accurate feedback and reward system further motivates users, enabling them to maintain their health and shape.

[0140] A "server" is a computing device that provides data and services to client terminals via the Internet or a local network.

[0141] "User" refers to an individual who uses the System to receive training plans, video feedback, meal plans, and rewards systems.

[0142] "Terminal" means a computing device or device that a user operates to input information or receive and display information from a server.

[0143] "Login" refers to the authentication procedure required for a user to access a system.

[0144] "Personal information" refers to information that can be used to identify a specific individual, such as a user's age, gender, and exercise experience.

[0145] "Goal" refers to the specific purpose that a user wants to achieve when using the system (e.g., maintaining health, losing weight, gaining muscle, etc.).

[0146] An "AI algorithm" is a calculation method that uses artificial intelligence to input user information and generate optimal training and meal plans.

[0147] A "training plan" is a plan that includes specific exercise content, number of repetitions, number of sets, and rest times, generated based on the user's goals.

[0148] "Training video" refers to video data that a user has filmed of their own training.

[0149] The "AI module" is a computing unit that uses artificial intelligence to analyze training videos and provide form corrections and improvement suggestions.

[0150] "Dietary history" refers to a record of the meals a user has eaten up to now.

[0151] "Allergy information" refers to information indicating that a user has an allergic reaction to a particular food or substance.

[0152] A "meal plan" is a plan that includes specific nutritionally balanced menus and a list of ingredients that are suggested based on information entered by the user.

[0153] "Points" are evaluation units that are added up within the system based on a user's activities and achievements.

[0154] "Rewards" refer to incentives (e.g., gacha tickets, bonus coupons, etc.) provided based on the user's training results and continuation status.

[0155] The invention provides users looking to stay healthy and in shape with personalized training plans, video guides and feedback, nutritional management and meal plans, and a rewards system, all optimized using user input and AI algorithms.

[0156] Hardware and Software Configuration

[0157] Server: The server is a high-performance computing device that uses deep learning frameworks such as TensorFlow and PyTorch to generate training and meal plans, and video analysis libraries such as OpenCV and MediaPipe to analyze the training videos.

[0158] Terminal: A terminal is a smartphone or PC operated by a user, and information is input and displayed via a browser or mobile application.

[0159] User: The user accesses the system, logs in, and enters the necessary information to receive personalized training and meal plans.

[0160] Providing training plans

[0161] User: A user logs in to the system and enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, building muscle, etc.). For example, User A enters "building muscle" as their goal and wishes to do high-intensity training three times a week.

[0162] Terminal: The terminal provides this information as an input form, performs error checking, and then sends the information to the server.

[0163] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan. For example, the AI ​​might generate a plan that includes high-intensity interval training (HIIT).

[0164] On your device: The generated training plan will be displayed on your device, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[0165] Video Guides and Feedback

[0166] User: A user records a training video and uploads it to the system. For example, User B records a video of himself doing squats and uploads it to the system.

[0167] Device: The device sends the video to the server.

[0168] Server: The server passes the video to an AI module, which analyzes the form and movements. For example, the AI ​​can detect areas for improvement, such as "the knees are too far forward."

[0169] Device: The analysis results are displayed to the user, and the feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[0170] Nutritional management and meal plans provided

[0171] User: The user enters their dietary history, dietary preferences, and allergy information. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[0172] Terminal: The terminal sends this information to the server.

[0173] Server: The server uses an AI platform to analyze the nutritional balance based on the data and generate a meal plan tailored to the user's goals.

[0174] On your device: The generated meal plan will be displayed on your device, including the specific menu, list of ingredients, and cooking instructions.

[0175] Reward System

[0176] User: The user performs training and enters the results (exercise type, calories burned, number of days continued, etc.).

[0177] Terminal: The terminal sends the entered data to the server.

[0178] Server: The server evaluates the data and calculates points and rewards. For example, when points exceed a certain threshold, gacha tickets or bonus coupons are generated.

[0179] Device: Display generated reward information on your device. Rewards include perks to motivate you to stick to your training and meal plans.

[0180] Examples of prompt statements

[0181] "Create a strength training plan three times a week."

[0182] "Analyze the correct form of the squat and suggest areas for improvement."

[0183] "Create a weekly meal plan to help you stay healthy."

[0184] "Provide rewards based on the number of calories burned by the user in a week."

[0185] As described above, the system of the present invention allows users to implement effective and personalized training plans, while also enabling them to maintain their health and physique on an ongoing basis.

[0186] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0187] Providing training plans

[0188] Step 1:

[0189] User: The user opens the system's login screen and enters their username and password to log into their account. The information they enter is sent to the server via HTTPS.

[0190] Input: Username, Password

[0191] Output: Authentication token

[0192] Step 2:

[0193] Terminal: If authentication is successful, the terminal displays a form for entering age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.). The user enters the information and presses the "Submit" button.

[0194] Input: Age, Gender, Exercise Experience, Goal

[0195] Output: Validation result of user input data

[0196] Step 3:

[0197] Terminal: The entered information is checked for errors, and if there are no problems, it is sent to the server via HTTPS.

[0198] Input: User-entered data

[0199] Output: Data to send to the server

[0200] Step 4:

[0201] Server: The server stores the received information in a database and inputs it into the AI ​​algorithm, which is built using TensorFlow and PyTorch to process the data and perform calculations to generate the optimal training plan.

[0202] Input: User-entered data

[0203] Output: Training plan

[0204] Step 5:

[0205] Device: The device receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[0206] Input: Training Plan

[0207] Output: what is displayed to the user

[0208] ---

[0209] Video Guides and Feedback

[0210] Step 1:

[0211] User: The user uses a smartphone or digital camera to record a training video, for example, recording their squat form.

[0212] Input: Recorded video file

[0213] Output: Video file saved on device

[0214] Step 2:

[0215] Terminal: The terminal provides an interface for selecting a video file and uploading it to the system. The user presses the "Upload" button.

[0216] Input: Select video file

[0217] Output: Data to send to server

[0218] Step 3:

[0219] Server: The server stores the received video file in temporary storage and passes it to the AI ​​module, which uses libraries such as OpenCV and MediaPipe to perform video analysis.

[0220] Input: Video data

[0221] Output: Analysis results (form corrections, improvement suggestions)

[0222] Step 4:

[0223] Terminal: Receives the analysis results sent from the server and displays them to the user. Feedback includes specific form corrections and suggestions for improvement.

[0224] Input: Analysis results

[0225] Output: what is displayed to the user

[0226] ---

[0227] Nutritional management and meal plans provided

[0228] Step 1:

[0229] User: The user enters their dietary history, food preferences, allergy information, etc. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[0230] Input: dietary history, food preferences, allergy information

[0231] Output: User data stored on the device

[0232] Step 2:

[0233] Terminal: The terminal displays this information in a form and provides a button to send it to the server once the user has completed the form.

[0234] Input: User data

[0235] Output: Data to send to server

[0236] Step 3:

[0237] Server: The server uses an AI platform, such as Amazon SageMaker or Google Cloud AI Platform, to analyze the nutritional balance based on the data and generate an optimal meal plan.

[0238] Input: User data

[0239] Output: Meal plan

[0240] Step 4:

[0241] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[0242] Enter: meal plan

[0243] Output: what is displayed to the user

[0244] ---

[0245] Reward System

[0246] Step 1:

[0247] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[0248] Input: Training results

[0249] Output: Data entered into the terminal

[0250] Step 2:

[0251] Terminal: The terminal sends the entered data to the server.

[0252] Input: Training data

[0253] Output: Data to send to server

[0254] Step 3:

[0255] Server: The server evaluates the received data, calculates points and rewards, and generates gacha tickets and bonus coupons when points exceed a certain threshold.

[0256] Input: Training data

[0257] Output: Points, rewards

[0258] Step 4:

[0259] Device: Receives generated reward information and displays it to the user. Rewards include perks to motivate them to continue their next workout or meal plan.

[0260] Input: Remuneration information

[0261] Output: what is displayed to the user

[0262] The above are the specific processing steps of this system, which allows users to implement effective and personalized training plans and maintain their health and physique on a continuous basis.

[0263] (Application example 1)

[0264] 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."

[0265] Conventional healthy lifestyle support systems lack the ability to provide individually customized training and meal plans, and lack adequate feedback on users' actual training form. As a result, it has been difficult to effectively maintain health and shape. Furthermore, food delivery services, in particular, do not offer menus tailored to users' health goals, limiting the means by which users can easily obtain meals that align with their health goals.

[0266] 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.

[0267] In this invention, the server includes: a means for generating an optimal training plan based on the user's goals and personal information; a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions; a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information; a means for providing rewards based on goal achievement and training continuity; a means for generating and providing a customized healthy food menu based on user data; and a means for analyzing exercise videos filmed by the user and providing feedback on form improvements. This allows users to easily obtain effective training and meal plans tailored to their health goals and receive feedback on training form corrections and improvements. Furthermore, particularly in the case of food delivery services, this allows for the provision of menus tailored to the user's health goals, providing a convenient way for users to obtain healthy meals.

[0268] "User goals" are specific goals that users want to achieve, such as maintaining their health or maintaining their figure.

[0269] "Personal information" refers to personal data such as a user's age, gender, and exercise experience.

[0270] A "training plan" is a customized exercise schedule based on a user's goals.

[0271] A "training video" is a video file that records the exercise performed by a user.

[0272] "Form corrections" refer to problems with body movement or posture that need to be improved during training.

[0273] "Improvement suggestions" are specific correction methods and advice provided based on the corrections made to the form.

[0274] "Dietary history" refers to a record of the meals a user has eaten to date.

[0275] "Physical information" refers to data about a user's body, such as weight, height, and body fat percentage.

[0276] A "nutritional balanced meal plan" is a meal plan that includes a balanced amount of nutrients necessary to maintain health, based on the user's physical information and dietary history.

[0277] "Rewards" are incentives provided to users based on goal achievement and training continuity.

[0278] A "customized healthy food menu" is a specific meal plan generated by AI based on a user's health goals and dietary preferences.

[0279] "Analyzing exercise videos" refers to the process of using AI technology to analyze exercise videos taken by users and identify areas for improvement in their form.

[0280] "Feedback" refers to specific corrections and advice provided based on the analysis results.

[0281] A "server" is a central processing unit that analyzes data and manages generated information.

[0282] "Terminal" refers to the computer or smartphone used by the user to enter data or view generated information.

[0283] The present invention is a system that provides optimal training plans, video guides and feedback, nutritional management, and meal plans to support users who are trying to maintain their health and shape. This system is composed of a server, a terminal, and a user. Each component and its specific processing are described below.

[0284] 1. Providing training plans

[0285] User: First, log in to the system and enter their age, gender, exercise experience, and goals (maintaining health, losing weight, building muscle, etc.).

[0286] Terminal: This information is provided as an input form, and a button is displayed to send the form to the server after input.

[0287] Server: Runs AI algorithms based on the received information to generate an optimal training plan tailored to the user's goals.

[0288] Device: Receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[0289] 2. Video guide and feedback

[0290] User: Records training videos and uploads them to the system via a device.

[0291] Device: Sends the uploaded video to the server and waits for feedback.

[0292] Server: Passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[0293] The device receives feedback and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knees are at the wrong angle" or "Stand up straighter."

[0294] 3. Nutritional management and meal plans

[0295] User: Enter their dietary history, food preferences, allergy information, etc.

[0296] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[0297] Server: AI analyzes the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[0298] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[0299] 4. Reward System

[0300] User: Performs training and enters the results (exercise type, calories burned, number of days continued, etc.) into the device.

[0301] Terminal: Sends this data to the server and waits for the reward to be calculated.

[0302] Server: Evaluates user input data and calculates points and rewards. When points exceed a certain threshold, it generates rewards such as gacha tickets or coupon codes.

[0303] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[0304] 5. Healthy food delivery

[0305] User: Enter their health goals and dietary preferences.

[0306] Server: Generates customized healthy food menus and meal plans based on user data.

[0307] Device: Receives the provided meal plan and displays it to the user. The menu includes specific meal contents and ingredient information.

[0308] Hardware used: Cloud servers (e.g., AWS, Google Cloud), user devices (smartphones: iOS or Android)

[0309] Software used: Flask (web framework), TensorFlow and Keras (AI model framework), OpenCV (video analysis)

[0310] For example, a user can access the app and set a goal of "building muscle," and the AI ​​will generate a training plan that includes "high-intensity interval training (HIIT)." When a user films themselves doing squats and uploads them to the system, the AI ​​will provide feedback on areas for improvement, such as "your knees are too far forward." Furthermore, when a user types in "I want to know what healthy breakfast menu items are," the AI ​​will suggest specific customized menu items, such as "Smoothie Bowl."

[0311] In this way, users can easily obtain training and meal plans tailored to their health goals, and receive feedback on correcting and improving their training form.

[0312] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0313] Step 1:

[0314] The user logs into the system and enters personal information such as their age, gender, exercise experience, and goals.

[0315] Input: Age, Gender, Exercise Experience, Goal (e.g., Maintaining Health, Losing Weight, Gaining Muscle, etc.)

[0316] Action: Fill out the form on your device and press the "Submit" button.

[0317] Output: Input information is sent from the device to the server.

[0318] Step 2:

[0319] The server runs an AI algorithm based on the personal information it receives and generates an optimal training plan tailored to the user's goals.

[0320] Input: Age, Gender, Exercise Experience, Goal

[0321] How it works: An AI model (using TensorFlow and Keras) processes the data and generates a personalized training plan.

[0322] Output: Generated training plan

[0323] Step 3:

[0324] The terminal receives the generated training plan from the server and displays it to the user.

[0325] Input: Generated training plan

[0326] Operation: The plan details (exercise content, number of repetitions and sets, rest time) will be displayed on the device screen.

[0327] Output: A training plan that users can view

[0328] Step 4:

[0329] Users film their training videos and upload them to the system via their devices.

[0330] Input: Filmed training video

[0331] How it works: Uses the device's camera to take a video and upload it to the system.

[0332] Output: Uploaded training videos

[0333] Step 5:

[0334] The server passes the received training video to the AI ​​module, which analyzes the video.

[0335] Input: Uploaded training video

[0336] Movement: Video analysis is performed using OpenCV to detect and evaluate form and movement.

[0337] Output: Form corrections and improvement suggestions as a result of the diagnosis

[0338] Step 6:

[0339] The terminal displays the feedback received from the server to the user.

[0340] Input: Feedback (form corrections, improvement suggestions)

[0341] How it works: Feedback is displayed on the device screen, including specific advice.

[0342] Output: Feedback that users can see

[0343] Step 7:

[0344] Users enter their dietary history, food preferences, allergy information, etc.

[0345] Input: dietary history, food preferences, allergy information

[0346] Action: Fill out the form on your device and press the "Submit" button.

[0347] Output: Input information is sent from the device to the server.

[0348] Step 8:

[0349] Based on the data received by the server, the AI ​​analyzes nutritional balance and generates a meal plan.

[0350] Input: dietary history, food preferences, allergy information

[0351] How it works: An AI model processes the data and generates a customized meal plan.

[0352] Output: Generated meal plan

[0353] Step 9:

[0354] The terminal receives the generated meal plan from the server and displays it to the user.

[0355] Input: Generated meal plan

[0356] How it works: The meal plan details (specific menu, ingredients, and cooking instructions) will be displayed on the device screen.

[0357] Output: Meal plan available for user review

[0358] Step 10:

[0359] The user inputs the results of their training and diet into the terminal.

[0360] Input: Training content, calories burned, number of days, meal content

[0361] Action: Enter the results into the input form on your device and press the "Submit" button.

[0362] Output: Input information is sent from the device to the server.

[0363] Step 11:

[0364] The server evaluates the received information and calculates the reward.

[0365] Input: Training content, calories burned, number of days, meal content

[0366] What it does: Evaluates data and generates rewards (points, gacha tickets, coupon codes, etc.) if it exceeds a certain threshold.

[0367] Output: Generated rewards

[0368] Step 12:

[0369] The terminal displays the reward information received from the server to the user.

[0370] Input: Remuneration information

[0371] Operation: The reward details (points, gacha tickets, coupon codes, etc.) will be displayed on the device screen.

[0372] Output: Reward details that users can check

[0373] Step 13:

[0374] The user views and orders a customized healthy food menu.

[0375] Input: User's health goals and dietary preferences

[0376] What it does: View the healthy food menu provided on the device and complete your order using your smartphone.

[0377] Output: Healthy food ordered

[0378] 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.

[0379] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, nutritional management and meal plans, and an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention that provide these functions to users are described below.

[0380] 1. Providing training plans

[0381] User: A user logs into the system and enters their account information and goals.

[0382] Terminal: The terminal displays a form for the user to enter information such as age, gender, exercise experience, and goals.

[0383] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[0384] Device: Displays the training plan received from the server to the user. The plan includes specific exercises, number of repetitions and sets, and rest periods.

[0385] 2. Video guide and feedback

[0386] User: The user records a video of themselves training and uploads it to the system.

[0387] Device: Sends uploaded videos to the server.

[0388] Server: The server receives the video and the AI ​​module analyzes the training form and movements.

[0389] Server: Generates specific form corrections and improvement proposals as analysis results.

[0390] On the device: Displays the feedback received from the server to the user and provides specific advice.

[0391] 3. Nutritional management and meal plans

[0392] User: The user enters their dietary history, preferences, and allergy information.

[0393] Terminal: The terminal displays the input form and sends the data to the server.

[0394] Server: The server receives the data and the AI ​​analyzes the nutritional balance. It then generates a meal plan based on the analysis.

[0395] Device: The meal plan sent from the server is displayed to the user, including the specific menu and ingredients used.

[0396] 4. Reward System

[0397] User: The user enters the training results.

[0398] Terminal: The terminal sends data to the server.

[0399] Server: The server evaluates the data and calculates points. When a certain number of points is reached, it generates a reward.

[0400] Terminal: Displays reward information sent from the server to the user, including gacha tickets and coupons.

[0401] 5. Combining Emotion Engines

[0402] User: The system collects the user's voice and facial expressions.

[0403] On the device: The emotion engine analyzes the data and recognizes the user's emotions.

[0404] Server: The server receives the results of the emotion engine and adjusts the training plan and feedback content in real time.

[0405] Terminal: Displays adjusted plans and feedback from the server to the user.

[0406] Specific examples

[0407] 1. Training plan and emotion recognition example:

[0408] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[0409] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[0410] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[0411] Device: User A sees the adjusted plan.

[0412] 2. Video guide and emotion recognition example:

[0413] User: User B films and uploads a squat video.

[0414] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[0415] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[0416] Device: Feedback is displayed to User B.

[0417] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[0418] The processing flow will be explained below.

[0419] 1. Providing training plans

[0420] Step 1:

[0421] User: A user logs into the system and enters their account information.

[0422] Step 2:

[0423] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[0424] Step 3:

[0425] User: The user enters their information into the form and clicks the submit button.

[0426] Step 4:

[0427] Terminal: The terminal sends the entered information to the server.

[0428] Step 5:

[0429] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[0430] Step 6:

[0431] Server: The server sends the generated training plan to the device.

[0432] Step 7:

[0433] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[0434] 2. Video guide and feedback

[0435] Step 1:

[0436] User: The user records a video of themselves training.

[0437] Step 2:

[0438] User: The user uploads the video they have taken to the system via their device.

[0439] Step 3:

[0440] Device: Sends uploaded videos to the server.

[0441] Step 4:

[0442] Server: The server passes the received video to the AI ​​module.

[0443] Step 5:

[0444] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[0445] Step 6:

[0446] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[0447] Step 7:

[0448] Server: The server sends the generated feedback to the device.

[0449] Step 8:

[0450] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[0451] 3. Nutritional management and meal plans

[0452] Step 1:

[0453] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[0454] Step 2:

[0455] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[0456] Step 3:

[0457] User: The user clicks the submit button.

[0458] Step 4:

[0459] Terminal: The terminal sends the entered meal data to the server.

[0460] Step 5:

[0461] Server: The server uses AI to analyze the nutritional balance based on the data received.

[0462] Step 6:

[0463] Server: AI generates meal plans tailored to the user's goals.

[0464] Step 7:

[0465] Server: The server sends the generated meal plan to the device.

[0466] Step 8:

[0467] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[0468] 4. Reward System

[0469] Step 1:

[0470] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[0471] Step 2:

[0472] Terminal: The terminal sends this data to the server.

[0473] Step 3:

[0474] Server: The server evaluates the data received and calculates points.

[0475] Step 4:

[0476] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[0477] Step 5:

[0478] Server: The server sends the generated reward information to the terminal.

[0479] Step 6:

[0480] Terminal: The terminal displays the sent reward information to the user.

[0481] 5. Combining Emotion Engines

[0482] Step 1:

[0483] User: The device collects the user's voice and facial expressions.

[0484] Step 2:

[0485] On the device: The emotion engine analyzes the collected data and identifies the user's emotions.

[0486] Step 3:

[0487] Server: The server receives the results from the emotion engine and adjusts the training plan and feedback in real time.

[0488] Step 4:

[0489] Server: Sends adjusted training plans and feedback to the device.

[0490] Step 5:

[0491] Device: The device displays the adjusted plan and feedback to the user, including personalized messages and training advice based on the user's emotions.

[0492] Specific examples

[0493] 1. Training plan and emotion recognition example:

[0494] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[0495] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[0496] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[0497] Device: User A sees the adjusted plan.

[0498] 2. Video guide and emotion recognition example:

[0499] User: User B films and uploads a squat video.

[0500] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[0501] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[0502] Device: Feedback is displayed to User B.

[0503] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[0504] Example 2

[0505] 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."

[0506] In today's busy lifestyles, personalized training plans and nutritional management are important for effectively maintaining health and physique. However, few systems offer optimal plans tailored to individual needs, and coaching users on proper form and maintaining motivation during training can be challenging. Furthermore, there are few systems that provide feedback based on the user's emotions. This makes it difficult for many users to effectively and sustainably manage their health.

[0507] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0508] In this invention, the server includes a means for generating an optimal training plan based on the user's goals and personal information, a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions, a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information, and a means for recognizing the user's emotions and adjusting the training plan and feedback content based on the results. This allows users to receive training and nutritional management tailored to their individual needs, while providing accurate form guidance and maintaining motivation during the process. Furthermore, providing feedback based on emotions enables more effective and sustainable health management.

[0509] "User" refers to an individual who uses the system to maintain their health and fitness.

[0510] "Goals" refer to the specific objectives that users aim to achieve in order to maintain their health and physique.

[0511] "Personal information" refers to data relating to an individual user, such as age, gender, exercise experience, and physical characteristics.

[0512] "Training Plan" refers to a plan that includes customized exercise content, number of repetitions, number of sets, rest times, etc. to help a user achieve their goals.

[0513] "Video" refers to video data that users film while training and upload to the system.

[0514] "Form" refers to the user's body movements and posture during training.

[0515] "Areas to be corrected" refers to areas in the user's training form that need improvement.

[0516] "Improvement suggestions" refer to specific methods and advice to make the user's training form more effective.

[0517] "Dietary history" refers to a record of the foods and dietary content that a user has consumed in the past.

[0518] "Physical information" refers to health-related data such as a user's height, weight, and allergy information.

[0519] "Nutritional balance" refers to the proper distribution of nutrients necessary to maintain physical health.

[0520] "Meal plan" refers to the specific meal contents proposed taking into consideration the user's nutritional balance.

[0521] "Rewards" refers to incentives that users can receive based on achieving their goals and continuing their training.

[0522] "Emotion" refers to the psychological state recognized from the user's voice and facial expression.

[0523] "Feedback" refers to providing appropriate advice and information regarding the user's training and diet.

[0524] "Server" refers to the computer system that processes user data and generates various plans and feedback.

[0525] "Terminal" refers to a device (e.g., a smartphone or PC) that a user uses to access the system, input data, and display results.

[0526] The present invention is a system that provides users who are aiming to maintain their health and physique with personalized training plans, video guides and feedback, nutritional management and meal plans, and feedback using an emotion engine.

[0527] Providing training plans

[0528] User: A user logs into the system and enters their account information and goals.

[0529] Device: The device (e.g., a smartphone or PC) uses HTML and JavaScript to display a form for the user to enter information such as age, gender, exercise experience, and goals.

[0530] Server: The server receives the input information and generates an optimal training plan using a TensorFlow model developed in Python.

[0531] Device: The training plan received from the server is displayed to the user using HTML and CSS. The training plan includes specific exercises, number of repetitions and sets, and rest periods.

[0532] Video Guides and Feedback

[0533] User: Records videos of themselves training and uploads them to the system.

[0534] Device: Uploaded videos are sent to the server using the REST API.

[0535] Server: The server receives the video and analyzes it using Python and OpenCV. As a result of the analysis, it generates corrections and improvement suggestions for the player's form.

[0536] Terminal: Feedback received from the server is displayed to the user using HTML and CSS.

[0537] Nutritional management and meal plans provided

[0538] User: Enters dietary history, preferences, and allergy information.

[0539] Terminal: Displays input forms created with HTML and JavaScript and sends data to the server.

[0540] Server: Receives the data, analyzes nutritional balance using a TensorFlow model developed in Python, and generates a meal plan.

[0541] Device: The meal plan sent from the server is displayed to the user using HTML and CSS, including the specific menu and ingredients used.

[0542] Reward System

[0543] User: Enter training results.

[0544] Terminal: The input results are sent to the server using JavaScript's Ajax function.

[0545] Server: The server evaluates the data, calculates points using a Python script, and generates rewards when a certain number of points are reached. Rewards include perks and coupons for gacha and avatar acquisition.

[0546] Terminal: Reward information sent from the server is displayed to the user using HTML and CSS.

[0547] Combining Emotion Engines

[0548] User: The system collects voice and facial expressions.

[0549] On the device: The emotion engine analyzes the data and recognizes the user's emotions using the Python EmotionRecognition library.

[0550] Server: Receives the results of the emotion engine and provides feedback to the AI ​​model to adjust the training plan and feedback content in real time.

[0551] Terminal: The adjusted plan and feedback from the server are displayed to the user in HTML and CSS.

[0552] Examples and prompts

[0553] 1. Training plan and emotion recognition example:

[0554] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[0555] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[0556] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[0557] Device: User A sees the adjusted plan.

[0558] Example prompt sentence:

[0559] User A's goal is to increase muscle strength and would like to do high-intensity training three times a week. Please generate the optimal training plan.

[0560] 2. Video guide and emotion recognition example:

[0561] User: User B films and uploads a squat video.

[0562] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[0563] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[0564] Device: Feedback is displayed to User B.

[0565] Example prompt sentence:

[0566] User B uploads a video of themselves squatting. Perform motion analysis and generate feedback if their knees are too far forward. If any insecurity is detected, provide gentle feedback.

[0567] This allows the system to provide training and nutritional management tailored to the individual needs of the user, and utilizes emotion recognition technology to provide optimal feedback. By receiving feedback and plans tailored to their emotional state, users can more easily maintain their motivation.

[0568] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0569] Step 1: Enter your user information

[0570] User: A user logs into the system and enters their account information and goals.

[0571] Input: User's age, gender, exercise experience, and goals

[0572] Output: A JSON request containing the user's input data

[0573] What it does: It displays an HTML form, allows the user to enter information, validates the input with JavaScript, and prepares the data to be sent to the server.

[0574] Step 2: Submit your input

[0575] Terminal: Sends the information the user enters into the form to the server.

[0576] Input: User-entered account information and goals

[0577] Output: User data sent to the server in JSON format

[0578] Specific operation: Uses JavaScript's Ajax function to send information in JSON format to the server.

[0579] Step 3: Generate a training plan

[0580] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[0581] Input: User account information and goals sent to the server

[0582] Output: User-optimized training plan

[0583] How it works: Using a TensorFlow model developed in Python, it generates a training plan based on user input, including calculations for exercises, repetitions, sets, and rest periods.

[0584] Step 4: View your training plan

[0585] Device: Displays the training plan received from the server to the user.

[0586] Input: Training plan sent from the server

[0587] Output: A visual representation of the training plan to the user

[0588] What it does: Uses HTML and CSS to display training plans in a user-friendly format.

[0589] Step 5: Record and upload your video

[0590] User: Records videos of themselves training and uploads them to the system.

[0591] Input: Training video data

[0592] Output: Video file for uploading

[0593] Specific actions: Take a video using your smartphone or PC camera and click the upload button.

[0594] Step 6: Submit your video

[0595] Device: Sends uploaded videos to the server.

[0596] Input: User uploaded video file

[0597] Output: Video data sent to the server

[0598] Specific operation: Use the REST API to send video data to the server.

[0599] Step 7: Analyze the video and generate feedback

[0600] Server: Receives the video and the AI ​​module analyzes the training form and movements. It generates specific form corrections and improvement suggestions as feedback.

[0601] Input: Training video sent to the server

[0602] Output: Feedback and suggestions for corrections and improvements

[0603] Specific operation: Uses Python and OpenCV to analyze videos and generate suggestions for improving form.

[0604] Step 8: View your feedback

[0605] Terminal: Displays the feedback received from the server to the user.

[0606] Input: Feedback data sent from the server

[0607] Output: Visual feedback displayed to the user

[0608] What it does: Uses HTML and CSS to display feedback in a user-friendly way.

[0609] Step 9: Enter your meal information

[0610] User: Enters dietary history, preferences, and allergy information.

[0611] Input: User's dietary history, preferences, and allergy information

[0612] Output: JSON data of the entered user information

[0613] Specific behavior: Enter information into an HTML form and validate it with JavaScript.

[0614] Step 10: Submit your meal information

[0615] Terminal: Sends the entered data to the server.

[0616] Input: Meal information entered by the user

[0617] Output: JSON data sent to the server

[0618] Specific operation: Send data in JSON format via Ajax.

[0619] Step 11: Generate a meal plan

[0620] Server: Receives the data, and AI analyzes the nutritional balance and generates a meal plan.

[0621] Input: Meal information sent to the server

[0622] Output: A nutritionally balanced meal plan

[0623] Specific operation: Uses a TensorFlow model to generate a nutritionally balanced meal plan.

[0624] Step 12: View your meal plan

[0625] Terminal: Displays the meal plan sent from the server to the user.

[0626] Input: Meal plan received from the server

[0627] Output: A concrete meal menu visually displayed to the user

[0628] What it does: Uses HTML and CSS to display meal plans in a user-friendly format.

[0629] Step 13: Implementing the reward system

[0630] Server: Evaluates training results, calculates points, and generates rewards when a certain number of points are reached.

[0631] Input: User-entered training results

[0632] Output: Points and generated rewards (gacha and coupons)

[0633] What it does: A Python script evaluates the data, calculates points, and generates rewards.

[0634] Step 14: View your rewards

[0635] Terminal: Displays the reward information sent from the server to the user.

[0636] Input: Reward information sent from the server

[0637] Output: Reward details visually displayed to the user

[0638] What it does: Displays reward information using HTML and CSS.

[0639] Step 15: Collect emotion data

[0640] User: The system collects voice and facial expressions.

[0641] Input: User voice and facial expression data

[0642] Output: Collected speech and facial expression data

[0643] What it does: Collects data using the camera and microphone on your smartphone or PC.

[0644] Step 16: Sentiment Analysis

[0645] On the device: The emotion engine analyzes the data and recognizes the user's emotions.

[0646] Input: Collected voice and facial expression data

[0647] Output: User's emotional state (fatigue, anxiety, etc.)

[0648] What it does: Analyzes data using Python's EmotionRecognition library.

[0649] Step 17: Adjust your plan and feedback

[0650] Server: Receives the results of the emotion engine and adjusts the training plan and feedback content in real time.

[0651] Input: Emotion engine output (user's emotional state)

[0652] Output: Tailored training plans and feedback

[0653] Specific operation: Feeds analysis results back to the AI ​​model and updates plans and feedback.

[0654] Step 18: View adjusted plans and feedback

[0655] Terminal: Displays adjusted plans and feedback from the server to the user.

[0656] Input: Adjusted plan and feedback sent from the server

[0657] Output: The adjusted content visually displayed to the user

[0658] Specific behavior: Display the adjustment results using HTML and CSS.

[0659] (Application example 2)

[0660] 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."

[0661] Many people today, especially young women, who are trying to maintain their health and shape, are looking for training plans, video guides and feedback, and nutritional management and meal plans. However, traditional systems often provide these functions separately, making it difficult for them to work together to provide optimal feedback to users. Furthermore, traditional systems do not take into account the user's emotions, which can lead to training and meal plans that do not adapt to the user's condition, which can decrease motivation. Therefore, a comprehensive training support system that meets the individual needs of each user is needed.

[0662] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating an optimal training plan based on the user's goals and personal information, means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions, means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information, and means for analyzing the user's emotional data and adjusting the training plan and feedback content based on the user's emotions. This allows users to receive individually optimized training plans in real time, enabling them to maintain their health and physique while staying motivated.

[0663] "User" refers to anyone who uses this system to maintain their health and shape.

[0664] "Goal" refers to the specific objectives regarding exercise and health management that a user wishes to achieve through the system.

[0665] "Personal information" refers to information about an individual, such as the user's age, gender, and exercise experience.

[0666] "Training plan" refers to a specific exercise instruction plan provided by the system, including the exercise menu, number of repetitions, number of sets, and rest time.

[0667] "Training video" refers to video data of a user training.

[0668] "Form corrections" refer to areas in your posture or movements that need improvement during training.

[0669] "Improvement suggestions" refer to specific corrective guidance provided by the system to help users train more efficiently.

[0670] "Dietary history" refers to a record of the contents and amounts of food a user has consumed to date.

[0671] "Physical information" refers to data about a user's body, such as weight, height, and body fat percentage.

[0672] A "nutritional balanced meal plan" refers to a meal menu with a properly balanced nutrient content.

[0673] "Emotional data" refers to information about the emotional state of a user analyzed from their voice, facial expressions, etc.

[0674] "Feedback content" refers to the specific advice and guidance on training and diet that the system provides to users.

[0675] "Terminal" refers to electronic devices such as smartphones, tablets, and personal computers that users use to operate the system.

[0676] "Server" refers to a central computer that allows a system to process and store data and provide services to users.

[0677] The specific configuration and operation procedures for the embodiment of this invention are described below. This system provides several main functions to comprehensively support users in achieving their goals and managing their health.

[0678] Providing training plans

[0679] First, the user enters personal information such as age, gender, exercise experience, and goals. This data is sent from the device (smartphone or tablet) to the server. The server uses an AI algorithm to generate an optimal training plan based on the entered information. This AI algorithm can use the OpenAI API. The generated training plan is sent to the device and displayed to the user.

[0680] Video Guides and Feedback

[0681] Users film themselves training and upload the video to their device. The video is then sent to a server where it is analyzed using AI tools such as TensorFlow.js and Azure Cognitive Services. The AI ​​analyzes the video and generates corrections and suggestions for improvement. This feedback is then sent to the device and displayed to the user.

[0682] Nutritional management and meal plans provided

[0683] The user inputs their own dietary history and physical information (e.g., weight, height, body fat percentage, etc.). This data is also sent from the device to the server. The server uses AI to analyze nutritional balance and generate an optimal meal plan. The generated meal plan is sent to the device and displayed to the user.

[0684] Emotional data analysis and plan adjustment

[0685] A distinctive feature of this system is its emotional data analysis. The device collects emotional data, such as the user's voice and facial expressions, and sends it to the server. The server then analyzes the user's emotions using emotion recognition APIs such as Amazon Rekognition and Azure Cognitive Services. Based on the analysis results, the training plan and feedback content are adjusted in real time and sent to the device for display.

[0686] Specific examples

[0687] For example, consider the case where User A sets the goal of "beautiful legs and maintaining good health" and wishes to do high-intensity training three times a week. When User A inputs the information, the AI ​​generates a plan that includes "high-intensity interval training (HIIT)." Furthermore, when User A films and uploads a video of themselves training, the AI ​​analyzes the video and provides specific feedback such as "your form is correct." Furthermore, if User A's voice analysis detects fatigue, the AI ​​adjusts the training intensity appropriately and provides the plan again.

[0688] An example of a prompt using an industry-standard generative AI model might look like this:

[0689] text

[0690] The user entered the following information:

[0691] Age: 25

[0692] Gender: Female

[0693] Exercise experience: Intermediate

[0694] Goal: Beautiful legs and good health

[0695] Generate the best training plan for you based on:

[0696] Training frequency: 3 times a week

[0697] Available equipment: dumbbells, yoga mats

[0698] Favorite exercise: HIIT, yoga

[0699] This allows users to receive optimal feedback and plans tailored to their emotional state, making it easier for them to maintain their motivation.

[0700] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0701] Step 1:

[0702] The user enters personal information such as age, gender, exercise experience, and goals into the device and presses the send button. This input data is sent from the device to the server. The server receives this data and passes it to an AI algorithm to generate a training plan. The generated training plan is sent to the device and displayed to the user.

[0703] Step 2:

[0704] Users record videos of themselves training, which are then uploaded from their devices to a server. The server then analyzes the videos using AI tools such as TensorFlow.js and Azure Cognitive Services. The analysis results, including corrections and suggestions for improvement, are sent to the device and displayed to the user.

[0705] Step 3:

[0706] The user enters their diet history and physical information (e.g., weight, height, body fat percentage, etc.) into the device and presses the send button. This input data is also sent from the device to the server. The server receives this data and uses AI to analyze the nutritional balance. Based on the analysis results, an optimal meal plan is generated, sent to the device, and displayed to the user.

[0707] Step 4:

[0708] The device collects emotional data such as the user's voice and facial expressions. This emotional data is sent from the device to a server. The server then analyzes the emotions using emotion recognition APIs such as Amazon Rekognition and Azure Cognitive Services. Based on the results of this analysis, the training plan and feedback content are adjusted in real time. The adjusted content is sent to the device and displayed to the user.

[0709] Specific examples

[0710] Example: User A

[0711] User A's goal is to have beautiful legs and maintain good health, and he / she wishes to train three times a week. Personal information is entered into the device and sent to the server. The server uses AI to generate a training plan that combines HIIT and yoga, and sends it to the device. User A films and uploads a training video, which the server analyzes using an AI tool. Feedback is given that the form is "correct." If User A's voice analysis detects fatigue, the intensity is adjusted appropriately, and the adjustment results are displayed on the device.

[0712] 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.

[0713] 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.

[0714] 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.

[0715] [Second embodiment]

[0716] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0717] 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.

[0718] 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).

[0719] 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.

[0720] 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.

[0721] 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).

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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."

[0728] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, and nutritional management and meal plans. Specific embodiments of the present invention that provide these functions to users are described below.

[0729] 1. Providing training plans

[0730] User: First, the user logs in to their account through the system login screen, then enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.).

[0731] Terminal: The terminal provides this information to the user as an input form and displays a button to send the form to the server after the user has entered the information.

[0732] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan tailored to the user's goals.

[0733] Device: Receives the generated training plan from the server and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[0734] 2. Video guide and feedback

[0735] User: The user records a training video and uploads it to the system via their device.

[0736] Device: Sends the uploaded video to the server and waits for feedback.

[0737] Server: The server passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[0738] Device: Receives feedback from the server and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[0739] 3. Nutritional management and meal plans

[0740] User: The user enters their dietary history, food preferences, allergy information, etc.

[0741] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[0742] Server: The server uses AI to analyze the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[0743] Device: Receives the meal plan sent from the server and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[0744] 4. Reward System

[0745] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[0746] Terminal: Sends this data to the server and waits for the reward to be calculated.

[0747] Server: The server evaluates the user's input data, calculates points and rewards, and generates rewards such as gacha tickets or coupon codes when the points exceed a certain threshold.

[0748] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[0749] Specific examples

[0750] 1. Examples of training plans provided:

[0751] User: User A enters a goal of "building muscle" and wants to do high-intensity training three times a week.

[0752] Server: AI generates a plan based on the data, including high-intensity interval training (HIIT).

[0753] Terminal: The generated plan is displayed on User A's terminal.

[0754] 2. Video guide and feedback example:

[0755] User: User B records a video of himself doing squats and uploads it to the system.

[0756] Server: AI analyzes the video and detects areas for improvement, such as "knees are too far forward."

[0757] Terminal: User B is shown specific form correction guidelines as a result of the analysis.

[0758] As a result, by using the system of the present invention, users can not only carry out an effective and personalized training plan, but also maintain proper form and consume a nutritionally balanced diet, thereby achieving sustained health and physique maintenance.

[0759] The processing flow will be explained below.

[0760] 1. Providing training plans

[0761] Step 1:

[0762] User: A user logs into the system and enters their account information.

[0763] Step 2:

[0764] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[0765] Step 3:

[0766] User: The user enters their information into the form and clicks the submit button.

[0767] Step 4:

[0768] Terminal: The terminal sends the entered information to the server.

[0769] Step 5:

[0770] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[0771] Step 6:

[0772] Server: The server sends the generated training plan to the device.

[0773] Step 7:

[0774] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[0775] 2. Video guide and feedback

[0776] Step 1:

[0777] User: The user records a video of themselves training.

[0778] Step 2:

[0779] User: The user uploads the video they have taken to the system via their device.

[0780] Step 3:

[0781] Device: Sends uploaded videos to the server.

[0782] Step 4:

[0783] Server: The server passes the received video to the AI ​​module.

[0784] Step 5:

[0785] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[0786] Step 6:

[0787] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[0788] Step 7:

[0789] Server: The server sends the generated feedback to the device.

[0790] Step 8:

[0791] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[0792] 3. Nutritional management and meal plans

[0793] Step 1:

[0794] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[0795] Step 2:

[0796] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[0797] Step 3:

[0798] User: The user clicks the submit button.

[0799] Step 4:

[0800] Terminal: The terminal sends the entered meal data to the server.

[0801] Step 5:

[0802] Server: The server uses AI to analyze the nutritional balance based on the data received.

[0803] Step 6:

[0804] Server: AI generates meal plans tailored to the user's goals.

[0805] Step 7:

[0806] Server: The server sends the generated meal plan to the device.

[0807] Step 8:

[0808] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[0809] 4. Reward System

[0810] Step 1:

[0811] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[0812] Step 2:

[0813] Terminal: The terminal sends this data to the server.

[0814] Step 3:

[0815] Server: The server evaluates the data received and calculates points.

[0816] Step 4:

[0817] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[0818] Step 5:

[0819] Server: The server sends the generated reward information to the terminal.

[0820] Step 6:

[0821] Terminal: The terminal displays the sent reward information to the user.

[0822] Example 1

[0823] 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."

[0824] In recent years, the importance of maintaining health and physique has increased, especially among young people. However, it is difficult to effectively provide individual training and meal plans and maintain high motivation. Furthermore, the lack of systems that provide accurate advice on proper training form and nutritional balance makes it difficult for users to sustainably manage their health. Therefore, there is a need to provide users with effective and efficient training and meal plans, as well as a reward system, to increase their motivation.

[0825] 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.

[0826] In this invention, the server includes: a means for a user to log in to the system and input personal information and goals; a means for generating an optimal training plan using an AI algorithm based on the input information; a means for uploading training videos filmed by the user to the system and analyzing form corrections and improvement suggestions using an AI module; a means for inputting the user's dietary history, food preferences, and allergy information and using an AI platform to suggest a nutritionally balanced meal plan based on the input; and a means for evaluating the user's training results and calculating and providing points and rewards. This makes it possible to provide individually optimized training and meal plans, and the accurate feedback and reward system further motivates users, enabling them to maintain their health and shape.

[0827] A "server" is a computing device that provides data and services to client terminals via the Internet or a local network.

[0828] "User" refers to an individual who uses the System to receive training plans, video feedback, meal plans, and rewards systems.

[0829] "Terminal" means a computing device or device that a user operates to input information or receive and display information from a server.

[0830] "Login" refers to the authentication procedure required for a user to access a system.

[0831] "Personal information" refers to information that can be used to identify a specific individual, such as a user's age, gender, and exercise experience.

[0832] "Goal" refers to the specific purpose that a user wants to achieve when using the system (e.g., maintaining health, losing weight, gaining muscle, etc.).

[0833] An "AI algorithm" is a calculation method that uses artificial intelligence to input user information and generate optimal training and meal plans.

[0834] A "training plan" is a plan that includes specific exercise content, number of repetitions, number of sets, and rest times, generated based on the user's goals.

[0835] "Training video" refers to video data that a user has filmed of their own training.

[0836] The "AI module" is a computing unit that uses artificial intelligence to analyze training videos and provide form corrections and improvement suggestions.

[0837] "Dietary history" refers to a record of the meals a user has eaten up to now.

[0838] "Allergy information" refers to information indicating that a user has an allergic reaction to a particular food or substance.

[0839] A "meal plan" is a plan that includes specific nutritionally balanced menus and a list of ingredients that are suggested based on information entered by the user.

[0840] "Points" are evaluation units that are added up within the system based on a user's activities and achievements.

[0841] "Rewards" refer to incentives (e.g., gacha tickets, bonus coupons, etc.) provided based on the user's training results and continuation status.

[0842] The invention provides users looking to stay healthy and in shape with personalized training plans, video guides and feedback, nutritional management and meal plans, and a rewards system, all optimized using user input and AI algorithms.

[0843] Hardware and Software Configuration

[0844] Server: The server is a high-performance computing device that uses deep learning frameworks such as TensorFlow and PyTorch to generate training and meal plans, and video analysis libraries such as OpenCV and MediaPipe to analyze the training videos.

[0845] Terminal: A terminal is a smartphone or PC operated by a user, and information is input and displayed via a browser or mobile application.

[0846] User: The user accesses the system, logs in, and enters the necessary information to receive personalized training and meal plans.

[0847] Providing training plans

[0848] User: A user logs in to the system and enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, building muscle, etc.). For example, User A enters "building muscle" as their goal and wishes to do high-intensity training three times a week.

[0849] Terminal: The terminal provides this information as an input form, performs error checking, and then sends the information to the server.

[0850] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan. For example, the AI ​​might generate a plan that includes high-intensity interval training (HIIT).

[0851] On your device: The generated training plan will be displayed on your device, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[0852] Video Guides and Feedback

[0853] User: A user records a training video and uploads it to the system. For example, User B records a video of himself doing squats and uploads it to the system.

[0854] Device: The device sends the video to the server.

[0855] Server: The server passes the video to an AI module, which analyzes the form and movements. For example, the AI ​​can detect areas for improvement, such as "the knees are too far forward."

[0856] Device: The analysis results are displayed to the user, and the feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[0857] Nutritional management and meal plans provided

[0858] User: The user enters their dietary history, dietary preferences, and allergy information. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[0859] Terminal: The terminal sends this information to the server.

[0860] Server: The server uses an AI platform to analyze the nutritional balance based on the data and generate a meal plan tailored to the user's goals.

[0861] On your device: The generated meal plan will be displayed on your device, including the specific menu, list of ingredients, and cooking instructions.

[0862] Reward System

[0863] User: The user performs training and enters the results (exercise type, calories burned, number of days continued, etc.).

[0864] Terminal: The terminal sends the entered data to the server.

[0865] Server: The server evaluates the data and calculates points and rewards. For example, when points exceed a certain threshold, gacha tickets or bonus coupons are generated.

[0866] Device: Display generated reward information on your device. Rewards include perks to motivate you to stick to your training and meal plans.

[0867] Examples of prompt statements

[0868] "Create a strength training plan three times a week."

[0869] "Analyze the correct form of the squat and suggest areas for improvement."

[0870] "Create a weekly meal plan to help you stay healthy."

[0871] "Provide rewards based on the number of calories burned by the user in a week."

[0872] As described above, the system of the present invention allows users to implement effective and personalized training plans, while also enabling them to maintain their health and physique on an ongoing basis.

[0873] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0874] Providing training plans

[0875] Step 1:

[0876] User: The user opens the system's login screen and enters their username and password to log into their account. The information they enter is sent to the server via HTTPS.

[0877] Input: Username, Password

[0878] Output: Authentication token

[0879] Step 2:

[0880] Terminal: If authentication is successful, the terminal displays a form for entering age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.). The user enters the information and presses the "Submit" button.

[0881] Input: Age, Gender, Exercise Experience, Goal

[0882] Output: Validation result of user input data

[0883] Step 3:

[0884] Terminal: The entered information is checked for errors, and if there are no problems, it is sent to the server via HTTPS.

[0885] Input: User-entered data

[0886] Output: Data to send to the server

[0887] Step 4:

[0888] Server: The server stores the received information in a database and inputs it into the AI ​​algorithm, which is built using TensorFlow and PyTorch to process the data and perform calculations to generate the optimal training plan.

[0889] Input: User-entered data

[0890] Output: Training plan

[0891] Step 5:

[0892] Device: The device receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[0893] Input: Training Plan

[0894] Output: what is displayed to the user

[0895] ---

[0896] Video Guides and Feedback

[0897] Step 1:

[0898] User: The user uses a smartphone or digital camera to record a training video, for example, recording their squat form.

[0899] Input: Recorded video file

[0900] Output: Video file saved on device

[0901] Step 2:

[0902] Terminal: The terminal provides an interface for selecting a video file and uploading it to the system. The user presses the "Upload" button.

[0903] Input: Select video file

[0904] Output: Data to send to server

[0905] Step 3:

[0906] Server: The server stores the received video file in temporary storage and passes it to the AI ​​module, which uses libraries such as OpenCV and MediaPipe to perform video analysis.

[0907] Input: Video data

[0908] Output: Analysis results (form corrections, improvement suggestions)

[0909] Step 4:

[0910] Terminal: Receives the analysis results sent from the server and displays them to the user. Feedback includes specific form corrections and suggestions for improvement.

[0911] Input: Analysis results

[0912] Output: what is displayed to the user

[0913] ---

[0914] Nutritional management and meal plans provided

[0915] Step 1:

[0916] User: The user enters their dietary history, food preferences, allergy information, etc. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[0917] Input: dietary history, food preferences, allergy information

[0918] Output: User data stored on the device

[0919] Step 2:

[0920] Terminal: The terminal displays this information in a form and provides a button to send it to the server once the user has completed the form.

[0921] Input: User data

[0922] Output: Data to send to server

[0923] Step 3:

[0924] Server: The server uses an AI platform, such as Amazon SageMaker or Google Cloud AI Platform, to analyze the nutritional balance based on the data and generate an optimal meal plan.

[0925] Input: User data

[0926] Output: Meal plan

[0927] Step 4:

[0928] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[0929] Enter: meal plan

[0930] Output: what is displayed to the user

[0931] ---

[0932] Reward System

[0933] Step 1:

[0934] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[0935] Input: Training results

[0936] Output: Data entered into the terminal

[0937] Step 2:

[0938] Terminal: The terminal sends the entered data to the server.

[0939] Input: Training data

[0940] Output: Data to send to server

[0941] Step 3:

[0942] Server: The server evaluates the received data, calculates points and rewards, and generates gacha tickets and bonus coupons when points exceed a certain threshold.

[0943] Input: Training data

[0944] Output: Points, rewards

[0945] Step 4:

[0946] Device: Receives generated reward information and displays it to the user. Rewards include perks to motivate them to continue their next workout or meal plan.

[0947] Input: Remuneration information

[0948] Output: what is displayed to the user

[0949] The above are the specific processing steps of this system, which allows users to implement effective and personalized training plans and maintain their health and physique on a continuous basis.

[0950] (Application example 1)

[0951] 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."

[0952] Conventional healthy lifestyle support systems lack the ability to provide individually customized training and meal plans, and lack adequate feedback on users' actual training form. As a result, it has been difficult to effectively maintain health and shape. Furthermore, food delivery services, in particular, do not offer menus tailored to users' health goals, limiting the means by which users can easily obtain meals that align with their health goals.

[0953] 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.

[0954] In this invention, the server includes: a means for generating an optimal training plan based on the user's goals and personal information; a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions; a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information; a means for providing rewards based on goal achievement and training continuity; a means for generating and providing a customized healthy food menu based on user data; and a means for analyzing exercise videos filmed by the user and providing feedback on form improvements. This allows users to easily obtain effective training and meal plans tailored to their health goals and receive feedback on training form corrections and improvements. Furthermore, particularly in the case of food delivery services, this allows for the provision of menus tailored to the user's health goals, providing a convenient way for users to obtain healthy meals.

[0955] "User goals" are specific goals that users want to achieve, such as maintaining their health or maintaining their figure.

[0956] "Personal information" refers to personal data such as a user's age, gender, and exercise experience.

[0957] A "training plan" is a customized exercise schedule based on a user's goals.

[0958] A "training video" is a video file that records the exercise performed by a user.

[0959] "Form corrections" refer to problems with body movement or posture that need to be improved during training.

[0960] "Improvement suggestions" are specific correction methods and advice provided based on the corrections made to the form.

[0961] "Dietary history" refers to a record of the meals a user has eaten to date.

[0962] "Physical information" refers to data about a user's body, such as weight, height, and body fat percentage.

[0963] A "nutritional balanced meal plan" is a meal plan that includes a balanced amount of nutrients necessary to maintain health, based on the user's physical information and dietary history.

[0964] "Rewards" are incentives provided to users based on goal achievement and training continuity.

[0965] A "customized healthy food menu" is a specific meal plan generated by AI based on a user's health goals and dietary preferences.

[0966] "Analyzing exercise videos" refers to the process of using AI technology to analyze exercise videos taken by users and identify areas for improvement in their form.

[0967] "Feedback" refers to specific corrections and advice provided based on the analysis results.

[0968] A "server" is a central processing unit that analyzes data and manages generated information.

[0969] "Terminal" refers to the computer or smartphone used by the user to enter data or view generated information.

[0970] The present invention is a system that provides optimal training plans, video guides and feedback, nutritional management, and meal plans to support users who are trying to maintain their health and shape. This system is composed of a server, a terminal, and a user. Each component and its specific processing are described below.

[0971] 1. Providing training plans

[0972] User: First, log in to the system and enter their age, gender, exercise experience, and goals (maintaining health, losing weight, building muscle, etc.).

[0973] Terminal: This information is provided as an input form, and a button is displayed to send the form to the server after input.

[0974] Server: Runs AI algorithms based on the received information to generate an optimal training plan tailored to the user's goals.

[0975] Device: Receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[0976] 2. Video guide and feedback

[0977] User: Records training videos and uploads them to the system via a device.

[0978] Device: Sends the uploaded video to the server and waits for feedback.

[0979] Server: Passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[0980] The device receives feedback and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knees are at the wrong angle" or "Stand up straighter."

[0981] 3. Nutritional management and meal plans

[0982] User: Enter their dietary history, food preferences, allergy information, etc.

[0983] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[0984] Server: AI analyzes the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[0985] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[0986] 4. Reward System

[0987] User: Performs training and enters the results (exercise type, calories burned, number of days continued, etc.) into the device.

[0988] Terminal: Sends this data to the server and waits for the reward to be calculated.

[0989] Server: Evaluates user input data and calculates points and rewards. When points exceed a certain threshold, it generates rewards such as gacha tickets or coupon codes.

[0990] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[0991] 5. Healthy food delivery

[0992] User: Enter their health goals and dietary preferences.

[0993] Server: Generates customized healthy food menus and meal plans based on user data.

[0994] Device: Receives the provided meal plan and displays it to the user. The menu includes specific meal contents and ingredient information.

[0995] Hardware used: Cloud servers (e.g., AWS, Google Cloud), user devices (smartphones: iOS or Android)

[0996] Software used: Flask (web framework), TensorFlow and Keras (AI model framework), OpenCV (video analysis)

[0997] For example, a user can access the app and set a goal of "building muscle," and the AI ​​will generate a training plan that includes "high-intensity interval training (HIIT)." When a user films themselves doing squats and uploads them to the system, the AI ​​will provide feedback on areas for improvement, such as "your knees are too far forward." Furthermore, when a user types in "I want to know what healthy breakfast menu items are," the AI ​​will suggest specific customized menu items, such as "Smoothie Bowl."

[0998] In this way, users can easily obtain training and meal plans tailored to their health goals, and receive feedback on correcting and improving their training form.

[0999] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1000] Step 1:

[1001] The user logs into the system and enters personal information such as their age, gender, exercise experience, and goals.

[1002] Input: Age, Gender, Exercise Experience, Goal (e.g., Maintaining Health, Losing Weight, Gaining Muscle, etc.)

[1003] Action: Fill out the form on your device and press the "Submit" button.

[1004] Output: Input information is sent from the device to the server.

[1005] Step 2:

[1006] The server runs an AI algorithm based on the personal information it receives and generates an optimal training plan tailored to the user's goals.

[1007] Input: Age, Gender, Exercise Experience, Goal

[1008] How it works: An AI model (using TensorFlow and Keras) processes the data and generates a personalized training plan.

[1009] Output: Generated training plan

[1010] Step 3:

[1011] The terminal receives the generated training plan from the server and displays it to the user.

[1012] Input: Generated training plan

[1013] Operation: The plan details (exercise content, number of repetitions and sets, rest time) will be displayed on the device screen.

[1014] Output: A training plan that users can view

[1015] Step 4:

[1016] Users film their training videos and upload them to the system via their devices.

[1017] Input: Filmed training video

[1018] How it works: Uses the device's camera to take a video and upload it to the system.

[1019] Output: Uploaded training videos

[1020] Step 5:

[1021] The server passes the received training video to the AI ​​module, which analyzes the video.

[1022] Input: Uploaded training video

[1023] Movement: Video analysis is performed using OpenCV to detect and evaluate form and movement.

[1024] Output: Form corrections and improvement suggestions as a result of the diagnosis

[1025] Step 6:

[1026] The terminal displays the feedback received from the server to the user.

[1027] Input: Feedback (form corrections, improvement suggestions)

[1028] How it works: Feedback is displayed on the device screen, including specific advice.

[1029] Output: Feedback that users can see

[1030] Step 7:

[1031] Users enter their dietary history, food preferences, allergy information, etc.

[1032] Input: dietary history, food preferences, allergy information

[1033] Action: Fill out the form on your device and press the "Submit" button.

[1034] Output: Input information is sent from the device to the server.

[1035] Step 8:

[1036] Based on the data received by the server, the AI ​​analyzes nutritional balance and generates a meal plan.

[1037] Input: dietary history, food preferences, allergy information

[1038] How it works: An AI model processes the data and generates a customized meal plan.

[1039] Output: Generated meal plan

[1040] Step 9:

[1041] The terminal receives the generated meal plan from the server and displays it to the user.

[1042] Input: Generated meal plan

[1043] How it works: The meal plan details (specific menu, ingredients, and cooking instructions) will be displayed on the device screen.

[1044] Output: Meal plan available for user review

[1045] Step 10:

[1046] The user inputs the results of their training and diet into the terminal.

[1047] Input: Training content, calories burned, number of days, meal content

[1048] Action: Enter the results into the input form on your device and press the "Submit" button.

[1049] Output: Input information is sent from the device to the server.

[1050] Step 11:

[1051] The server evaluates the received information and calculates the reward.

[1052] Input: Training content, calories burned, number of days, meal content

[1053] What it does: Evaluates data and generates rewards (points, gacha tickets, coupon codes, etc.) if it exceeds a certain threshold.

[1054] Output: Generated rewards

[1055] Step 12:

[1056] The terminal displays the reward information received from the server to the user.

[1057] Input: Remuneration information

[1058] Operation: The reward details (points, gacha tickets, coupon codes, etc.) will be displayed on the device screen.

[1059] Output: Reward details that users can check

[1060] Step 13:

[1061] The user views and orders a customized healthy food menu.

[1062] Input: User's health goals and dietary preferences

[1063] What it does: View the healthy food menu provided on the device and complete your order using your smartphone.

[1064] Output: Healthy food ordered

[1065] 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.

[1066] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, nutritional management and meal plans, and an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention that provide these functions to users are described below.

[1067] 1. Providing training plans

[1068] User: A user logs into the system and enters their account information and goals.

[1069] Terminal: The terminal displays a form for the user to enter information such as age, gender, exercise experience, and goals.

[1070] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[1071] Device: Displays the training plan received from the server to the user. The plan includes specific exercises, number of repetitions and sets, and rest periods.

[1072] 2. Video guide and feedback

[1073] User: The user records a video of themselves training and uploads it to the system.

[1074] Device: Sends uploaded videos to the server.

[1075] Server: The server receives the video and the AI ​​module analyzes the training form and movements.

[1076] Server: Generates specific form corrections and improvement proposals as analysis results.

[1077] On the device: Displays the feedback received from the server to the user and provides specific advice.

[1078] 3. Nutritional management and meal plans

[1079] User: The user enters their dietary history, preferences, and allergy information.

[1080] Terminal: The terminal displays the input form and sends the data to the server.

[1081] Server: The server receives the data and the AI ​​analyzes the nutritional balance. It then generates a meal plan based on the analysis.

[1082] Device: The meal plan sent from the server is displayed to the user, including the specific menu and ingredients used.

[1083] 4. Reward System

[1084] User: The user enters the training results.

[1085] Terminal: The terminal sends data to the server.

[1086] Server: The server evaluates the data and calculates points. When a certain number of points is reached, it generates a reward.

[1087] Terminal: Displays reward information sent from the server to the user, including gacha tickets and coupons.

[1088] 5. Combining Emotion Engines

[1089] User: The system collects the user's voice and facial expressions.

[1090] On the device: The emotion engine analyzes the data and recognizes the user's emotions.

[1091] Server: The server receives the results of the emotion engine and adjusts the training plan and feedback content in real time.

[1092] Terminal: Displays adjusted plans and feedback from the server to the user.

[1093] Specific examples

[1094] 1. Training plan and emotion recognition example:

[1095] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[1096] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[1097] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[1098] Device: User A sees the adjusted plan.

[1099] 2. Video guide and emotion recognition example:

[1100] User: User B films and uploads a squat video.

[1101] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[1102] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[1103] Device: Feedback is displayed to User B.

[1104] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[1105] The processing flow will be explained below.

[1106] 1. Providing training plans

[1107] Step 1:

[1108] User: A user logs into the system and enters their account information.

[1109] Step 2:

[1110] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[1111] Step 3:

[1112] User: The user enters their information into the form and clicks the submit button.

[1113] Step 4:

[1114] Terminal: The terminal sends the entered information to the server.

[1115] Step 5:

[1116] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[1117] Step 6:

[1118] Server: The server sends the generated training plan to the device.

[1119] Step 7:

[1120] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[1121] 2. Video guide and feedback

[1122] Step 1:

[1123] User: The user records a video of themselves training.

[1124] Step 2:

[1125] User: The user uploads the video they have taken to the system via their device.

[1126] Step 3:

[1127] Device: Sends uploaded videos to the server.

[1128] Step 4:

[1129] Server: The server passes the received video to the AI ​​module.

[1130] Step 5:

[1131] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[1132] Step 6:

[1133] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[1134] Step 7:

[1135] Server: The server sends the generated feedback to the device.

[1136] Step 8:

[1137] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[1138] 3. Nutritional management and meal plans

[1139] Step 1:

[1140] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[1141] Step 2:

[1142] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[1143] Step 3:

[1144] User: The user clicks the submit button.

[1145] Step 4:

[1146] Terminal: The terminal sends the entered meal data to the server.

[1147] Step 5:

[1148] Server: The server uses AI to analyze the nutritional balance based on the data received.

[1149] Step 6:

[1150] Server: AI generates meal plans tailored to the user's goals.

[1151] Step 7:

[1152] Server: The server sends the generated meal plan to the device.

[1153] Step 8:

[1154] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[1155] 4. Reward System

[1156] Step 1:

[1157] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[1158] Step 2:

[1159] Terminal: The terminal sends this data to the server.

[1160] Step 3:

[1161] Server: The server evaluates the data received and calculates points.

[1162] Step 4:

[1163] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[1164] Step 5:

[1165] Server: The server sends the generated reward information to the terminal.

[1166] Step 6:

[1167] Terminal: The terminal displays the sent reward information to the user.

[1168] 5. Combining Emotion Engines

[1169] Step 1:

[1170] User: The device collects the user's voice and facial expressions.

[1171] Step 2:

[1172] On the device: The emotion engine analyzes the collected data and identifies the user's emotions.

[1173] Step 3:

[1174] Server: The server receives the results from the emotion engine and adjusts the training plan and feedback in real time.

[1175] Step 4:

[1176] Server: Sends adjusted training plans and feedback to the device.

[1177] Step 5:

[1178] Device: The device displays the adjusted plan and feedback to the user, including personalized messages and training advice based on the user's emotions.

[1179] Specific examples

[1180] 1. Training plan and emotion recognition example:

[1181] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[1182] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[1183] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[1184] Device: User A sees the adjusted plan.

[1185] 2. Video guide and emotion recognition example:

[1186] User: User B films and uploads a squat video.

[1187] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[1188] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[1189] Device: Feedback is displayed to User B.

[1190] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[1191] Example 2

[1192] 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."

[1193] In today's busy lifestyles, personalized training plans and nutritional management are important for effectively maintaining health and physique. However, few systems offer optimal plans tailored to individual needs, and coaching users on proper form and maintaining motivation during training can be challenging. Furthermore, there are few systems that provide feedback based on the user's emotions. This makes it difficult for many users to effectively and sustainably manage their health.

[1194] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1195] In this invention, the server includes a means for generating an optimal training plan based on the user's goals and personal information, a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions, a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information, and a means for recognizing the user's emotions and adjusting the training plan and feedback content based on the results. This allows users to receive training and nutritional management tailored to their individual needs, while providing accurate form guidance and maintaining motivation during the process. Furthermore, providing feedback based on emotions enables more effective and sustainable health management.

[1196] "User" refers to an individual who uses the system to maintain their health and fitness.

[1197] "Goals" refer to the specific objectives that users aim to achieve in order to maintain their health and physique.

[1198] "Personal information" refers to data relating to an individual user, such as age, gender, exercise experience, and physical characteristics.

[1199] "Training Plan" refers to a plan that includes customized exercise content, number of repetitions, number of sets, rest times, etc. to help a user achieve their goals.

[1200] "Video" refers to video data that users film while training and upload to the system.

[1201] "Form" refers to the user's body movements and posture during training.

[1202] "Areas to be corrected" refers to areas in the user's training form that need improvement.

[1203] "Improvement suggestions" refer to specific methods and advice to make the user's training form more effective.

[1204] "Dietary history" refers to a record of the foods and dietary content that a user has consumed in the past.

[1205] "Physical information" refers to health-related data such as a user's height, weight, and allergy information.

[1206] "Nutritional balance" refers to the proper distribution of nutrients necessary to maintain physical health.

[1207] "Meal plan" refers to the specific meal contents proposed taking into consideration the user's nutritional balance.

[1208] "Rewards" refers to incentives that users can receive based on achieving their goals and continuing their training.

[1209] "Emotion" refers to the psychological state recognized from the user's voice and facial expression.

[1210] "Feedback" refers to providing appropriate advice and information regarding the user's training and diet.

[1211] "Server" refers to the computer system that processes user data and generates various plans and feedback.

[1212] "Terminal" refers to a device (e.g., a smartphone or PC) that a user uses to access the system, input data, and display results.

[1213] The present invention is a system that provides users who are aiming to maintain their health and physique with personalized training plans, video guides and feedback, nutritional management and meal plans, and feedback using an emotion engine.

[1214] Providing training plans

[1215] User: A user logs into the system and enters their account information and goals.

[1216] Device: The device (e.g., a smartphone or PC) uses HTML and JavaScript to display a form for the user to enter information such as age, gender, exercise experience, and goals.

[1217] Server: The server receives the input information and generates an optimal training plan using a TensorFlow model developed in Python.

[1218] Device: The training plan received from the server is displayed to the user using HTML and CSS. The training plan includes specific exercises, number of repetitions and sets, and rest periods.

[1219] Video Guides and Feedback

[1220] User: Records videos of themselves training and uploads them to the system.

[1221] Device: Uploaded videos are sent to the server using the REST API.

[1222] Server: The server receives the video and analyzes it using Python and OpenCV. As a result of the analysis, it generates corrections and improvement suggestions for the player's form.

[1223] Terminal: Feedback received from the server is displayed to the user using HTML and CSS.

[1224] Nutritional management and meal plans provided

[1225] User: Enters dietary history, preferences, and allergy information.

[1226] Terminal: Displays input forms created with HTML and JavaScript and sends data to the server.

[1227] Server: Receives the data, analyzes nutritional balance using a TensorFlow model developed in Python, and generates a meal plan.

[1228] Device: The meal plan sent from the server is displayed to the user using HTML and CSS, including the specific menu and ingredients used.

[1229] Reward System

[1230] User: Enter training results.

[1231] Terminal: The input results are sent to the server using JavaScript's Ajax function.

[1232] Server: The server evaluates the data, calculates points using a Python script, and generates rewards when a certain number of points are reached. Rewards include perks and coupons for gacha and avatar acquisition.

[1233] Terminal: Reward information sent from the server is displayed to the user using HTML and CSS.

[1234] Combining Emotion Engines

[1235] User: The system collects voice and facial expressions.

[1236] On the device: The emotion engine analyzes the data and recognizes the user's emotions using the Python EmotionRecognition library.

[1237] Server: Receives the results of the emotion engine and provides feedback to the AI ​​model to adjust the training plan and feedback content in real time.

[1238] Terminal: The adjusted plan and feedback from the server are displayed to the user in HTML and CSS.

[1239] Examples and prompts

[1240] 1. Training plan and emotion recognition example:

[1241] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[1242] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[1243] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[1244] Device: User A sees the adjusted plan.

[1245] Example prompt sentence:

[1246] User A's goal is to increase muscle strength and would like to do high-intensity training three times a week. Please generate the optimal training plan.

[1247] 2. Video guide and emotion recognition example:

[1248] User: User B films and uploads a squat video.

[1249] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[1250] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[1251] Device: Feedback is displayed to User B.

[1252] Example prompt sentence:

[1253] User B uploads a video of themselves squatting. Perform motion analysis and generate feedback if their knees are too far forward. If any insecurity is detected, provide gentle feedback.

[1254] This allows the system to provide training and nutritional management tailored to the individual needs of the user, and utilizes emotion recognition technology to provide optimal feedback. By receiving feedback and plans tailored to their emotional state, users can more easily maintain their motivation.

[1255] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1256] Step 1: Enter your user information

[1257] User: A user logs into the system and enters their account information and goals.

[1258] Input: User's age, gender, exercise experience, and goals

[1259] Output: A JSON request containing the user's input data

[1260] What it does: It displays an HTML form, allows the user to enter information, validates the input with JavaScript, and prepares the data to be sent to the server.

[1261] Step 2: Submit your input

[1262] Terminal: Sends the information the user enters into the form to the server.

[1263] Input: User-entered account information and goals

[1264] Output: User data sent to the server in JSON format

[1265] Specific operation: Uses JavaScript's Ajax function to send information in JSON format to the server.

[1266] Step 3: Generate a training plan

[1267] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[1268] Input: User account information and goals sent to the server

[1269] Output: User-optimized training plan

[1270] How it works: Using a TensorFlow model developed in Python, it generates a training plan based on user input, including calculations for exercises, repetitions, sets, and rest periods.

[1271] Step 4: View your training plan

[1272] Device: Displays the training plan received from the server to the user.

[1273] Input: Training plan sent from the server

[1274] Output: A visual representation of the training plan to the user

[1275] What it does: Uses HTML and CSS to display training plans in a user-friendly format.

[1276] Step 5: Record and upload your video

[1277] User: Records videos of themselves training and uploads them to the system.

[1278] Input: Training video data

[1279] Output: Video file for uploading

[1280] Specific actions: Take a video using your smartphone or PC camera and click the upload button.

[1281] Step 6: Submit your video

[1282] Device: Sends uploaded videos to the server.

[1283] Input: User uploaded video file

[1284] Output: Video data sent to the server

[1285] Specific operation: Use the REST API to send video data to the server.

[1286] Step 7: Analyze the video and generate feedback

[1287] Server: Receives the video and the AI ​​module analyzes the training form and movements. It generates specific form corrections and improvement suggestions as feedback.

[1288] Input: Training video sent to the server

[1289] Output: Feedback and suggestions for corrections and improvements

[1290] Specific operation: Uses Python and OpenCV to analyze videos and generate suggestions for improving form.

[1291] Step 8: View your feedback

[1292] Terminal: Displays the feedback received from the server to the user.

[1293] Input: Feedback data sent from the server

[1294] Output: Visual feedback displayed to the user

[1295] What it does: Uses HTML and CSS to display feedback in a user-friendly way.

[1296] Step 9: Enter your meal information

[1297] User: Enters dietary history, preferences, and allergy information.

[1298] Input: User's dietary history, preferences, and allergy information

[1299] Output: JSON data of the entered user information

[1300] Specific behavior: Enter information into an HTML form and validate it with JavaScript.

[1301] Step 10: Submit your meal information

[1302] Terminal: Sends the entered data to the server.

[1303] Input: Meal information entered by the user

[1304] Output: JSON data sent to the server

[1305] Specific operation: Send data in JSON format via Ajax.

[1306] Step 11: Generate a meal plan

[1307] Server: Receives the data, and AI analyzes the nutritional balance and generates a meal plan.

[1308] Input: Meal information sent to the server

[1309] Output: A nutritionally balanced meal plan

[1310] Specific operation: Uses a TensorFlow model to generate a nutritionally balanced meal plan.

[1311] Step 12: View your meal plan

[1312] Terminal: Displays the meal plan sent from the server to the user.

[1313] Input: Meal plan received from the server

[1314] Output: A concrete meal menu visually displayed to the user

[1315] What it does: Uses HTML and CSS to display meal plans in a user-friendly format.

[1316] Step 13: Implementing the reward system

[1317] Server: Evaluates training results, calculates points, and generates rewards when a certain number of points are reached.

[1318] Input: User-entered training results

[1319] Output: Points and generated rewards (gacha and coupons)

[1320] What it does: A Python script evaluates the data, calculates points, and generates rewards.

[1321] Step 14: View your rewards

[1322] Terminal: Displays the reward information sent from the server to the user.

[1323] Input: Reward information sent from the server

[1324] Output: Reward details visually displayed to the user

[1325] What it does: Displays reward information using HTML and CSS.

[1326] Step 15: Collect emotion data

[1327] User: The system collects voice and facial expressions.

[1328] Input: User voice and facial expression data

[1329] Output: Collected speech and facial expression data

[1330] What it does: Collects data using the camera and microphone on your smartphone or PC.

[1331] Step 16: Sentiment Analysis

[1332] On the device: The emotion engine analyzes the data and recognizes the user's emotions.

[1333] Input: Collected voice and facial expression data

[1334] Output: User's emotional state (fatigue, anxiety, etc.)

[1335] What it does: Analyzes data using Python's EmotionRecognition library.

[1336] Step 17: Adjust your plan and feedback

[1337] Server: Receives the results of the emotion engine and adjusts the training plan and feedback content in real time.

[1338] Input: Emotion engine output (user's emotional state)

[1339] Output: Tailored training plans and feedback

[1340] Specific operation: Feeds analysis results back to the AI ​​model and updates plans and feedback.

[1341] Step 18: View adjusted plans and feedback

[1342] Terminal: Displays adjusted plans and feedback from the server to the user.

[1343] Input: Adjusted plan and feedback sent from the server

[1344] Output: The adjusted content visually displayed to the user

[1345] Specific behavior: Display the adjustment results using HTML and CSS.

[1346] (Application example 2)

[1347] 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."

[1348] Many people today, especially young women, who are trying to maintain their health and shape, are looking for training plans, video guides and feedback, and nutritional management and meal plans. However, traditional systems often provide these functions separately, making it difficult for them to work together to provide optimal feedback to users. Furthermore, traditional systems do not take into account the user's emotions, which can lead to training and meal plans that do not adapt to the user's condition, which can decrease motivation. Therefore, a comprehensive training support system that meets the individual needs of each user is needed.

[1349] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating an optimal training plan based on the user's goals and personal information, means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions, means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information, and means for analyzing the user's emotional data and adjusting the training plan and feedback content based on the user's emotions. This allows users to receive individually optimized training plans in real time, enabling them to maintain their health and physique while staying motivated.

[1350] "User" refers to anyone who uses this system to maintain their health and shape.

[1351] "Goal" refers to the specific objectives regarding exercise and health management that a user wishes to achieve through the system.

[1352] "Personal information" refers to information about an individual, such as the user's age, gender, and exercise experience.

[1353] "Training plan" refers to a specific exercise instruction plan provided by the system, including the exercise menu, number of repetitions, number of sets, and rest time.

[1354] "Training video" refers to video data of a user training.

[1355] "Form corrections" refer to areas in your posture or movements that need improvement during training.

[1356] "Improvement suggestions" refer to specific corrective guidance provided by the system to help users train more efficiently.

[1357] "Dietary history" refers to a record of the contents and amounts of food a user has consumed to date.

[1358] "Physical information" refers to data about a user's body, such as weight, height, and body fat percentage.

[1359] A "nutritional balanced meal plan" refers to a meal menu with a properly balanced nutrient content.

[1360] "Emotional data" refers to information about the emotional state of a user analyzed from their voice, facial expressions, etc.

[1361] "Feedback content" refers to the specific advice and guidance on training and diet that the system provides to users.

[1362] "Terminal" refers to electronic devices such as smartphones, tablets, and personal computers that users use to operate the system.

[1363] "Server" refers to a central computer that allows a system to process and store data and provide services to users.

[1364] The specific configuration and operation procedures for the embodiment of this invention are described below. This system provides several main functions to comprehensively support users in achieving their goals and managing their health.

[1365] Providing training plans

[1366] First, the user enters personal information such as age, gender, exercise experience, and goals. This data is sent from the device (smartphone or tablet) to the server. The server uses an AI algorithm to generate an optimal training plan based on the entered information. This AI algorithm can use the OpenAI API. The generated training plan is sent to the device and displayed to the user.

[1367] Video Guides and Feedback

[1368] Users film themselves training and upload the video to their device. The video is then sent to a server where it is analyzed using AI tools such as TensorFlow.js and Azure Cognitive Services. The AI ​​analyzes the video and generates corrections and suggestions for improvement. This feedback is then sent to the device and displayed to the user.

[1369] Nutritional management and meal plans provided

[1370] The user inputs their own dietary history and physical information (e.g., weight, height, body fat percentage, etc.). This data is also sent from the device to the server. The server uses AI to analyze nutritional balance and generate an optimal meal plan. The generated meal plan is sent to the device and displayed to the user.

[1371] Emotional data analysis and plan adjustment

[1372] A distinctive feature of this system is its emotional data analysis. The device collects emotional data, such as the user's voice and facial expressions, and sends it to the server. The server then analyzes the user's emotions using emotion recognition APIs such as Amazon Rekognition and Azure Cognitive Services. Based on the analysis results, the training plan and feedback content are adjusted in real time and sent to the device for display.

[1373] Specific examples

[1374] For example, consider the case where User A sets the goal of "beautiful legs and maintaining good health" and wishes to do high-intensity training three times a week. When User A inputs the information, the AI ​​generates a plan that includes "high-intensity interval training (HIIT)." Furthermore, when User A films and uploads a video of themselves training, the AI ​​analyzes the video and provides specific feedback such as "your form is correct." Furthermore, if User A's voice analysis detects fatigue, the AI ​​adjusts the training intensity appropriately and provides the plan again.

[1375] An example of a prompt using an industry-standard generative AI model might look like this:

[1376] text

[1377] The user entered the following information:

[1378] Age: 25

[1379] Gender: Female

[1380] Exercise experience: Intermediate

[1381] Goal: Beautiful legs and good health

[1382] Generate the best training plan for you based on:

[1383] Training frequency: 3 times a week

[1384] Available equipment: dumbbells, yoga mats

[1385] Favorite exercise: HIIT, yoga

[1386] This allows users to receive optimal feedback and plans tailored to their emotional state, making it easier for them to maintain their motivation.

[1387] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1388] Step 1:

[1389] The user enters personal information such as age, gender, exercise experience, and goals into the device and presses the send button. This input data is sent from the device to the server. The server receives this data and passes it to an AI algorithm to generate a training plan. The generated training plan is sent to the device and displayed to the user.

[1390] Step 2:

[1391] Users record videos of themselves training, which are then uploaded from their devices to a server. The server then analyzes the videos using AI tools such as TensorFlow.js and Azure Cognitive Services. The analysis results, including corrections and suggestions for improvement, are sent to the device and displayed to the user.

[1392] Step 3:

[1393] The user enters their diet history and physical information (e.g., weight, height, body fat percentage, etc.) into the device and presses the send button. This input data is also sent from the device to the server. The server receives this data and uses AI to analyze the nutritional balance. Based on the analysis results, an optimal meal plan is generated, sent to the device, and displayed to the user.

[1394] Step 4:

[1395] The device collects emotional data such as the user's voice and facial expressions. This emotional data is sent from the device to a server. The server then analyzes the emotions using emotion recognition APIs such as Amazon Rekognition and Azure Cognitive Services. Based on the results of this analysis, the training plan and feedback content are adjusted in real time. The adjusted content is sent to the device and displayed to the user.

[1396] Specific examples

[1397] Example: User A

[1398] User A's goal is to have beautiful legs and maintain good health, and he / she wishes to train three times a week. Personal information is entered into the device and sent to the server. The server uses AI to generate a training plan that combines HIIT and yoga, and sends it to the device. User A films and uploads a training video, which the server analyzes using an AI tool. Feedback is given that the form is "correct." If User A's voice analysis detects fatigue, the intensity is adjusted appropriately, and the adjustment results are displayed on the device.

[1399] 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.

[1400] 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.

[1401] 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.

[1402] [Third embodiment]

[1403] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1404] 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.

[1405] 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).

[1406] 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.

[1407] 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.

[1408] 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).

[1409] 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.

[1410] 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.

[1411] 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.

[1412] 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.

[1413] 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.

[1414] 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."

[1415] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, and nutritional management and meal plans. Specific embodiments of the present invention that provide these functions to users are described below.

[1416] 1. Providing training plans

[1417] User: First, the user logs in to their account through the system login screen, then enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.).

[1418] Terminal: The terminal provides this information to the user as an input form and displays a button to send the form to the server after the user has entered the information.

[1419] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan tailored to the user's goals.

[1420] Device: Receives the generated training plan from the server and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[1421] 2. Video guide and feedback

[1422] User: The user records a training video and uploads it to the system via their device.

[1423] Device: Sends the uploaded video to the server and waits for feedback.

[1424] Server: The server passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[1425] Device: Receives feedback from the server and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[1426] 3. Nutritional management and meal plans

[1427] User: The user enters their dietary history, food preferences, allergy information, etc.

[1428] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[1429] Server: The server uses AI to analyze the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[1430] Device: Receives the meal plan sent from the server and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[1431] 4. Reward System

[1432] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[1433] Terminal: Sends this data to the server and waits for the reward to be calculated.

[1434] Server: The server evaluates the user's input data, calculates points and rewards, and generates rewards such as gacha tickets or coupon codes when the points exceed a certain threshold.

[1435] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[1436] Specific examples

[1437] 1. Examples of training plans provided:

[1438] User: User A enters a goal of "building muscle" and wants to do high-intensity training three times a week.

[1439] Server: AI generates a plan based on the data, including high-intensity interval training (HIIT).

[1440] Terminal: The generated plan is displayed on User A's terminal.

[1441] 2. Video guide and feedback example:

[1442] User: User B records a video of himself doing squats and uploads it to the system.

[1443] Server: AI analyzes the video and detects areas for improvement, such as "knees are too far forward."

[1444] Terminal: User B is shown specific form correction guidelines as a result of the analysis.

[1445] As a result, by using the system of the present invention, users can not only carry out an effective and personalized training plan, but also maintain proper form and consume a nutritionally balanced diet, thereby achieving sustained health and physique maintenance.

[1446] The processing flow will be explained below.

[1447] 1. Providing training plans

[1448] Step 1:

[1449] User: A user logs into the system and enters their account information.

[1450] Step 2:

[1451] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[1452] Step 3:

[1453] User: The user enters their information into the form and clicks the submit button.

[1454] Step 4:

[1455] Terminal: The terminal sends the entered information to the server.

[1456] Step 5:

[1457] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[1458] Step 6:

[1459] Server: The server sends the generated training plan to the device.

[1460] Step 7:

[1461] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[1462] 2. Video guide and feedback

[1463] Step 1:

[1464] User: The user records a video of themselves training.

[1465] Step 2:

[1466] User: The user uploads the video they have taken to the system via their device.

[1467] Step 3:

[1468] Device: Sends uploaded videos to the server.

[1469] Step 4:

[1470] Server: The server passes the received video to the AI ​​module.

[1471] Step 5:

[1472] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[1473] Step 6:

[1474] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[1475] Step 7:

[1476] Server: The server sends the generated feedback to the device.

[1477] Step 8:

[1478] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[1479] 3. Nutritional management and meal plans

[1480] Step 1:

[1481] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[1482] Step 2:

[1483] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[1484] Step 3:

[1485] User: The user clicks the submit button.

[1486] Step 4:

[1487] Terminal: The terminal sends the entered meal data to the server.

[1488] Step 5:

[1489] Server: The server uses AI to analyze the nutritional balance based on the data received.

[1490] Step 6:

[1491] Server: AI generates meal plans tailored to the user's goals.

[1492] Step 7:

[1493] Server: The server sends the generated meal plan to the device.

[1494] Step 8:

[1495] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[1496] 4. Reward System

[1497] Step 1:

[1498] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[1499] Step 2:

[1500] Terminal: The terminal sends this data to the server.

[1501] Step 3:

[1502] Server: The server evaluates the data received and calculates points.

[1503] Step 4:

[1504] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[1505] Step 5:

[1506] Server: The server sends the generated reward information to the terminal.

[1507] Step 6:

[1508] Terminal: The terminal displays the sent reward information to the user.

[1509] Example 1

[1510] 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."

[1511] In recent years, the importance of maintaining health and physique has increased, especially among young people. However, it is difficult to effectively provide individual training and meal plans and maintain high motivation. Furthermore, the lack of systems that provide accurate advice on proper training form and nutritional balance makes it difficult for users to sustainably manage their health. Therefore, there is a need to provide users with effective and efficient training and meal plans, as well as a reward system, to increase their motivation.

[1512] 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.

[1513] In this invention, the server includes: a means for a user to log in to the system and input personal information and goals; a means for generating an optimal training plan using an AI algorithm based on the input information; a means for uploading training videos filmed by the user to the system and analyzing form corrections and improvement suggestions using an AI module; a means for inputting the user's dietary history, food preferences, and allergy information and using an AI platform to suggest a nutritionally balanced meal plan based on the input; and a means for evaluating the user's training results and calculating and providing points and rewards. This makes it possible to provide individually optimized training and meal plans, and the accurate feedback and reward system further motivates users, enabling them to maintain their health and shape.

[1514] A "server" is a computing device that provides data and services to client terminals via the Internet or a local network.

[1515] "User" refers to an individual who uses the System to receive training plans, video feedback, meal plans, and rewards systems.

[1516] "Terminal" means a computing device or device that a user operates to input information or receive and display information from a server.

[1517] "Login" refers to the authentication procedure required for a user to access a system.

[1518] "Personal information" refers to information that can be used to identify a specific individual, such as a user's age, gender, and exercise experience.

[1519] "Goal" refers to the specific purpose that a user wants to achieve when using the system (e.g., maintaining health, losing weight, gaining muscle, etc.).

[1520] An "AI algorithm" is a calculation method that uses artificial intelligence to input user information and generate optimal training and meal plans.

[1521] A "training plan" is a plan that includes specific exercise content, number of repetitions, number of sets, and rest times, generated based on the user's goals.

[1522] "Training video" refers to video data that a user has filmed of their own training.

[1523] The "AI module" is a computing unit that uses artificial intelligence to analyze training videos and provide form corrections and improvement suggestions.

[1524] "Dietary history" refers to a record of the meals a user has eaten up to now.

[1525] "Allergy information" refers to information indicating that a user has an allergic reaction to a particular food or substance.

[1526] A "meal plan" is a plan that includes specific nutritionally balanced menus and a list of ingredients that are suggested based on information entered by the user.

[1527] "Points" are evaluation units that are added up within the system based on a user's activities and achievements.

[1528] "Rewards" refer to incentives (e.g., gacha tickets, bonus coupons, etc.) provided based on the user's training results and continuation status.

[1529] The invention provides users looking to stay healthy and in shape with personalized training plans, video guides and feedback, nutritional management and meal plans, and a rewards system, all optimized using user input and AI algorithms.

[1530] Hardware and Software Configuration

[1531] Server: The server is a high-performance computing device that uses deep learning frameworks such as TensorFlow and PyTorch to generate training and meal plans, and video analysis libraries such as OpenCV and MediaPipe to analyze the training videos.

[1532] Terminal: A terminal is a smartphone or PC operated by a user, and information is input and displayed via a browser or mobile application.

[1533] User: The user accesses the system, logs in, and enters the necessary information to receive personalized training and meal plans.

[1534] Providing training plans

[1535] User: A user logs in to the system and enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, building muscle, etc.). For example, User A enters "building muscle" as their goal and wishes to do high-intensity training three times a week.

[1536] Terminal: The terminal provides this information as an input form, performs error checking, and then sends the information to the server.

[1537] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan. For example, the AI ​​might generate a plan that includes high-intensity interval training (HIIT).

[1538] On your device: The generated training plan will be displayed on your device, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[1539] Video Guides and Feedback

[1540] User: A user records a training video and uploads it to the system. For example, User B records a video of himself doing squats and uploads it to the system.

[1541] Device: The device sends the video to the server.

[1542] Server: The server passes the video to an AI module, which analyzes the form and movements. For example, the AI ​​can detect areas for improvement, such as "the knees are too far forward."

[1543] Device: The analysis results are displayed to the user, and the feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[1544] Nutritional management and meal plans provided

[1545] User: The user enters their dietary history, dietary preferences, and allergy information. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[1546] Terminal: The terminal sends this information to the server.

[1547] Server: The server uses an AI platform to analyze the nutritional balance based on the data and generate a meal plan tailored to the user's goals.

[1548] On your device: The generated meal plan will be displayed on your device, including the specific menu, list of ingredients, and cooking instructions.

[1549] Reward System

[1550] User: The user performs training and enters the results (exercise type, calories burned, number of days continued, etc.).

[1551] Terminal: The terminal sends the entered data to the server.

[1552] Server: The server evaluates the data and calculates points and rewards. For example, when points exceed a certain threshold, gacha tickets or bonus coupons are generated.

[1553] Device: Display generated reward information on your device. Rewards include perks to motivate you to stick to your training and meal plans.

[1554] Examples of prompt statements

[1555] "Create a strength training plan three times a week."

[1556] "Analyze the correct form of the squat and suggest areas for improvement."

[1557] "Create a weekly meal plan to help you stay healthy."

[1558] "Provide rewards based on the number of calories burned by the user in a week."

[1559] As described above, the system of the present invention allows users to implement effective and personalized training plans, while also enabling them to maintain their health and physique on an ongoing basis.

[1560] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1561] Providing training plans

[1562] Step 1:

[1563] User: The user opens the system's login screen and enters their username and password to log into their account. The information they enter is sent to the server via HTTPS.

[1564] Input: Username, Password

[1565] Output: Authentication token

[1566] Step 2:

[1567] Terminal: If authentication is successful, the terminal displays a form for entering age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.). The user enters the information and presses the "Submit" button.

[1568] Input: Age, Gender, Exercise Experience, Goal

[1569] Output: Validation result of user input data

[1570] Step 3:

[1571] Terminal: The entered information is checked for errors, and if there are no problems, it is sent to the server via HTTPS.

[1572] Input: User-entered data

[1573] Output: Data to send to the server

[1574] Step 4:

[1575] Server: The server stores the received information in a database and inputs it into the AI ​​algorithm, which is built using TensorFlow and PyTorch to process the data and perform calculations to generate the optimal training plan.

[1576] Input: User-entered data

[1577] Output: Training plan

[1578] Step 5:

[1579] Device: The device receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[1580] Input: Training Plan

[1581] Output: what is displayed to the user

[1582] ---

[1583] Video Guides and Feedback

[1584] Step 1:

[1585] User: The user uses a smartphone or digital camera to record a training video, for example, recording their squat form.

[1586] Input: Recorded video file

[1587] Output: Video file saved on device

[1588] Step 2:

[1589] Terminal: The terminal provides an interface for selecting a video file and uploading it to the system. The user presses the "Upload" button.

[1590] Input: Select video file

[1591] Output: Data to send to server

[1592] Step 3:

[1593] Server: The server stores the received video file in temporary storage and passes it to the AI ​​module, which uses libraries such as OpenCV and MediaPipe to perform video analysis.

[1594] Input: Video data

[1595] Output: Analysis results (form corrections, improvement suggestions)

[1596] Step 4:

[1597] Terminal: Receives the analysis results sent from the server and displays them to the user. Feedback includes specific form corrections and suggestions for improvement.

[1598] Input: Analysis results

[1599] Output: what is displayed to the user

[1600] ---

[1601] Nutritional management and meal plans provided

[1602] Step 1:

[1603] User: The user enters their dietary history, food preferences, allergy information, etc. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[1604] Input: dietary history, food preferences, allergy information

[1605] Output: User data stored on the device

[1606] Step 2:

[1607] Terminal: The terminal displays this information in a form and provides a button to send it to the server once the user has completed the form.

[1608] Input: User data

[1609] Output: Data to send to server

[1610] Step 3:

[1611] Server: The server uses an AI platform, such as Amazon SageMaker or Google Cloud AI Platform, to analyze the nutritional balance based on the data and generate an optimal meal plan.

[1612] Input: User data

[1613] Output: Meal plan

[1614] Step 4:

[1615] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[1616] Enter: meal plan

[1617] Output: what is displayed to the user

[1618] ---

[1619] Reward System

[1620] Step 1:

[1621] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[1622] Input: Training results

[1623] Output: Data entered into the terminal

[1624] Step 2:

[1625] Terminal: The terminal sends the entered data to the server.

[1626] Input: Training data

[1627] Output: Data to send to server

[1628] Step 3:

[1629] Server: The server evaluates the received data, calculates points and rewards, and generates gacha tickets and bonus coupons when points exceed a certain threshold.

[1630] Input: Training data

[1631] Output: Points, rewards

[1632] Step 4:

[1633] Device: Receives generated reward information and displays it to the user. Rewards include perks to motivate them to continue their next workout or meal plan.

[1634] Input: Remuneration information

[1635] Output: what is displayed to the user

[1636] The above are the specific processing steps of this system, which allows users to implement effective and personalized training plans and maintain their health and physique on a continuous basis.

[1637] (Application example 1)

[1638] 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."

[1639] Conventional healthy lifestyle support systems lack the ability to provide individually customized training and meal plans, and lack adequate feedback on users' actual training form. As a result, it has been difficult to effectively maintain health and shape. Furthermore, food delivery services, in particular, do not offer menus tailored to users' health goals, limiting the means by which users can easily obtain meals that align with their health goals.

[1640] 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.

[1641] In this invention, the server includes: a means for generating an optimal training plan based on the user's goals and personal information; a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions; a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information; a means for providing rewards based on goal achievement and training continuity; a means for generating and providing a customized healthy food menu based on user data; and a means for analyzing exercise videos filmed by the user and providing feedback on form improvements. This allows users to easily obtain effective training and meal plans tailored to their health goals and receive feedback on training form corrections and improvements. Furthermore, particularly in the case of food delivery services, this allows for the provision of menus tailored to the user's health goals, providing a convenient way for users to obtain healthy meals.

[1642] "User goals" are specific goals that users want to achieve, such as maintaining their health or maintaining their figure.

[1643] "Personal information" refers to personal data such as a user's age, gender, and exercise experience.

[1644] A "training plan" is a customized exercise schedule based on a user's goals.

[1645] A "training video" is a video file that records the exercise performed by a user.

[1646] "Form corrections" refer to problems with body movement or posture that need to be improved during training.

[1647] "Improvement suggestions" are specific correction methods and advice provided based on the corrections made to the form.

[1648] "Dietary history" refers to a record of the meals a user has eaten to date.

[1649] "Physical information" refers to data about a user's body, such as weight, height, and body fat percentage.

[1650] A "nutritional balanced meal plan" is a meal plan that includes a balanced amount of nutrients necessary to maintain health, based on the user's physical information and dietary history.

[1651] "Rewards" are incentives provided to users based on goal achievement and training continuity.

[1652] A "customized healthy food menu" is a specific meal plan generated by AI based on a user's health goals and dietary preferences.

[1653] "Analyzing exercise videos" refers to the process of using AI technology to analyze exercise videos taken by users and identify areas for improvement in their form.

[1654] "Feedback" refers to specific corrections and advice provided based on the analysis results.

[1655] A "server" is a central processing unit that analyzes data and manages generated information.

[1656] "Terminal" refers to the computer or smartphone used by the user to enter data or view generated information.

[1657] The present invention is a system that provides optimal training plans, video guides and feedback, nutritional management, and meal plans to support users who are trying to maintain their health and shape. This system is composed of a server, a terminal, and a user. Each component and its specific processing are described below.

[1658] 1. Providing training plans

[1659] User: First, log in to the system and enter their age, gender, exercise experience, and goals (maintaining health, losing weight, building muscle, etc.).

[1660] Terminal: This information is provided as an input form, and a button is displayed to send the form to the server after input.

[1661] Server: Runs AI algorithms based on the received information to generate an optimal training plan tailored to the user's goals.

[1662] Device: Receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[1663] 2. Video guide and feedback

[1664] User: Records training videos and uploads them to the system via a device.

[1665] Device: Sends the uploaded video to the server and waits for feedback.

[1666] Server: Passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[1667] The device receives feedback and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knees are at the wrong angle" or "Stand up straighter."

[1668] 3. Nutritional management and meal plans

[1669] User: Enter their dietary history, food preferences, allergy information, etc.

[1670] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[1671] Server: AI analyzes the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[1672] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[1673] 4. Reward System

[1674] User: Performs training and enters the results (exercise type, calories burned, number of days continued, etc.) into the device.

[1675] Terminal: Sends this data to the server and waits for the reward to be calculated.

[1676] Server: Evaluates user input data and calculates points and rewards. When points exceed a certain threshold, it generates rewards such as gacha tickets or coupon codes.

[1677] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[1678] 5. Healthy food delivery

[1679] User: Enter their health goals and dietary preferences.

[1680] Server: Generates customized healthy food menus and meal plans based on user data.

[1681] Device: Receives the provided meal plan and displays it to the user. The menu includes specific meal contents and ingredient information.

[1682] Hardware used: Cloud servers (e.g., AWS, Google Cloud), user devices (smartphones: iOS or Android)

[1683] Software used: Flask (web framework), TensorFlow and Keras (AI model framework), OpenCV (video analysis)

[1684] For example, a user can access the app and set a goal of "building muscle," and the AI ​​will generate a training plan that includes "high-intensity interval training (HIIT)." When a user films themselves doing squats and uploads them to the system, the AI ​​will provide feedback on areas for improvement, such as "your knees are too far forward." Furthermore, when a user types in "I want to know what healthy breakfast menu items are," the AI ​​will suggest specific customized menu items, such as "Smoothie Bowl."

[1685] In this way, users can easily obtain training and meal plans tailored to their health goals, and receive feedback on correcting and improving their training form.

[1686] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1687] Step 1:

[1688] The user logs into the system and enters personal information such as their age, gender, exercise experience, and goals.

[1689] Input: Age, Gender, Exercise Experience, Goal (e.g., Maintaining Health, Losing Weight, Gaining Muscle, etc.)

[1690] Action: Fill out the form on your device and press the "Submit" button.

[1691] Output: Input information is sent from the device to the server.

[1692] Step 2:

[1693] The server runs an AI algorithm based on the personal information it receives and generates an optimal training plan tailored to the user's goals.

[1694] Input: Age, Gender, Exercise Experience, Goal

[1695] How it works: An AI model (using TensorFlow and Keras) processes the data and generates a personalized training plan.

[1696] Output: Generated training plan

[1697] Step 3:

[1698] The terminal receives the generated training plan from the server and displays it to the user.

[1699] Input: Generated training plan

[1700] Operation: The plan details (exercise content, number of repetitions and sets, rest time) will be displayed on the device screen.

[1701] Output: A training plan that users can view

[1702] Step 4:

[1703] Users film their training videos and upload them to the system via their devices.

[1704] Input: Filmed training video

[1705] How it works: Uses the device's camera to take a video and upload it to the system.

[1706] Output: Uploaded training videos

[1707] Step 5:

[1708] The server passes the received training video to the AI ​​module, which analyzes the video.

[1709] Input: Uploaded training video

[1710] Movement: Video analysis is performed using OpenCV to detect and evaluate form and movement.

[1711] Output: Form corrections and improvement suggestions as a result of the diagnosis

[1712] Step 6:

[1713] The terminal displays the feedback received from the server to the user.

[1714] Input: Feedback (form corrections, improvement suggestions)

[1715] How it works: Feedback is displayed on the device screen, including specific advice.

[1716] Output: Feedback that users can see

[1717] Step 7:

[1718] Users enter their dietary history, food preferences, allergy information, etc.

[1719] Input: dietary history, food preferences, allergy information

[1720] Action: Fill out the form on your device and press the "Submit" button.

[1721] Output: Input information is sent from the device to the server.

[1722] Step 8:

[1723] Based on the data received by the server, the AI ​​analyzes nutritional balance and generates a meal plan.

[1724] Input: dietary history, food preferences, allergy information

[1725] How it works: An AI model processes the data and generates a customized meal plan.

[1726] Output: Generated meal plan

[1727] Step 9:

[1728] The terminal receives the generated meal plan from the server and displays it to the user.

[1729] Input: Generated meal plan

[1730] How it works: The meal plan details (specific menu, ingredients, and cooking instructions) will be displayed on the device screen.

[1731] Output: Meal plan available for user review

[1732] Step 10:

[1733] The user inputs the results of their training and diet into the terminal.

[1734] Input: Training content, calories burned, number of days, meal content

[1735] Action: Enter the results into the input form on your device and press the "Submit" button.

[1736] Output: Input information is sent from the device to the server.

[1737] Step 11:

[1738] The server evaluates the received information and calculates the reward.

[1739] Input: Training content, calories burned, number of days, meal content

[1740] What it does: Evaluates data and generates rewards (points, gacha tickets, coupon codes, etc.) if it exceeds a certain threshold.

[1741] Output: Generated rewards

[1742] Step 12:

[1743] The terminal displays the reward information received from the server to the user.

[1744] Input: Remuneration information

[1745] Operation: The reward details (points, gacha tickets, coupon codes, etc.) will be displayed on the device screen.

[1746] Output: Reward details that users can check

[1747] Step 13:

[1748] The user views and orders a customized healthy food menu.

[1749] Input: User's health goals and dietary preferences

[1750] What it does: View the healthy food menu provided on the device and complete your order using your smartphone.

[1751] Output: Healthy food ordered

[1752] 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.

[1753] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, nutritional management and meal plans, and an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention that provide these functions to users are described below.

[1754] 1. Providing training plans

[1755] User: A user logs into the system and enters their account information and goals.

[1756] Terminal: The terminal displays a form for the user to enter information such as age, gender, exercise experience, and goals.

[1757] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[1758] Device: Displays the training plan received from the server to the user. The plan includes specific exercises, number of repetitions and sets, and rest periods.

[1759] 2. Video guide and feedback

[1760] User: The user records a video of themselves training and uploads it to the system.

[1761] Device: Sends uploaded videos to the server.

[1762] Server: The server receives the video and the AI ​​module analyzes the training form and movements.

[1763] Server: Generates specific form corrections and improvement proposals as analysis results.

[1764] On the device: Displays the feedback received from the server to the user and provides specific advice.

[1765] 3. Nutritional management and meal plans

[1766] User: The user enters their dietary history, preferences, and allergy information.

[1767] Terminal: The terminal displays the input form and sends the data to the server.

[1768] Server: The server receives the data and the AI ​​analyzes the nutritional balance. It then generates a meal plan based on the analysis.

[1769] Device: The meal plan sent from the server is displayed to the user, including the specific menu and ingredients used.

[1770] 4. Reward System

[1771] User: The user enters the training results.

[1772] Terminal: The terminal sends data to the server.

[1773] Server: The server evaluates the data and calculates points. When a certain number of points is reached, it generates a reward.

[1774] Terminal: Displays reward information sent from the server to the user, including gacha tickets and coupons.

[1775] 5. Combining Emotion Engines

[1776] User: The system collects the user's voice and facial expressions.

[1777] On the device: The emotion engine analyzes the data and recognizes the user's emotions.

[1778] Server: The server receives the results of the emotion engine and adjusts the training plan and feedback content in real time.

[1779] Terminal: Displays adjusted plans and feedback from the server to the user.

[1780] Specific examples

[1781] 1. Training plan and emotion recognition example:

[1782] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[1783] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[1784] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[1785] Device: User A sees the adjusted plan.

[1786] 2. Video guide and emotion recognition example:

[1787] User: User B films and uploads a squat video.

[1788] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[1789] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[1790] Device: Feedback is displayed to User B.

[1791] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[1792] The processing flow will be explained below.

[1793] 1. Providing training plans

[1794] Step 1:

[1795] User: A user logs into the system and enters their account information.

[1796] Step 2:

[1797] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[1798] Step 3:

[1799] User: The user enters their information into the form and clicks the submit button.

[1800] Step 4:

[1801] Terminal: The terminal sends the entered information to the server.

[1802] Step 5:

[1803] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[1804] Step 6:

[1805] Server: The server sends the generated training plan to the device.

[1806] Step 7:

[1807] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[1808] 2. Video guide and feedback

[1809] Step 1:

[1810] User: The user records a video of themselves training.

[1811] Step 2:

[1812] User: The user uploads the video they have taken to the system via their device.

[1813] Step 3:

[1814] Device: Sends uploaded videos to the server.

[1815] Step 4:

[1816] Server: The server passes the received video to the AI ​​module.

[1817] Step 5:

[1818] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[1819] Step 6:

[1820] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[1821] Step 7:

[1822] Server: The server sends the generated feedback to the device.

[1823] Step 8:

[1824] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[1825] 3. Nutritional management and meal plans

[1826] Step 1:

[1827] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[1828] Step 2:

[1829] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[1830] Step 3:

[1831] User: The user clicks the submit button.

[1832] Step 4:

[1833] Terminal: The terminal sends the entered meal data to the server.

[1834] Step 5:

[1835] Server: The server uses AI to analyze the nutritional balance based on the data received.

[1836] Step 6:

[1837] Server: AI generates meal plans tailored to the user's goals.

[1838] Step 7:

[1839] Server: The server sends the generated meal plan to the device.

[1840] Step 8:

[1841] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[1842] 4. Reward System

[1843] Step 1:

[1844] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[1845] Step 2:

[1846] Terminal: The terminal sends this data to the server.

[1847] Step 3:

[1848] Server: The server evaluates the data received and calculates points.

[1849] Step 4:

[1850] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[1851] Step 5:

[1852] Server: The server sends the generated reward information to the terminal.

[1853] Step 6:

[1854] Terminal: The terminal displays the sent reward information to the user.

[1855] 5. Combining Emotion Engines

[1856] Step 1:

[1857] User: The device collects the user's voice and facial expressions.

[1858] Step 2:

[1859] On the device: The emotion engine analyzes the collected data and identifies the user's emotions.

[1860] Step 3:

[1861] Server: The server receives the results from the emotion engine and adjusts the training plan and feedback in real time.

[1862] Step 4:

[1863] Server: Sends adjusted training plans and feedback to the device.

[1864] Step 5:

[1865] Device: The device displays the adjusted plan and feedback to the user, including personalized messages and training advice based on the user's emotions.

[1866] Specific examples

[1867] 1. Training plan and emotion recognition example:

[1868] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[1869] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[1870] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[1871] Device: User A sees the adjusted plan.

[1872] 2. Video guide and emotion recognition example:

[1873] User: User B films and uploads a squat video.

[1874] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[1875] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[1876] Device: Feedback is displayed to User B.

[1877] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[1878] Example 2

[1879] 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."

[1880] In today's busy lifestyles, personalized training plans and nutritional management are important for effectively maintaining health and physique. However, few systems offer optimal plans tailored to individual needs, and coaching users on proper form and maintaining motivation during training can be challenging. Furthermore, there are few systems that provide feedback based on the user's emotions. This makes it difficult for many users to effectively and sustainably manage their health.

[1881] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1882] In this invention, the server includes a means for generating an optimal training plan based on the user's goals and personal information, a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions, a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information, and a means for recognizing the user's emotions and adjusting the training plan and feedback content based on the results. This allows users to receive training and nutritional management tailored to their individual needs, while providing accurate form guidance and maintaining motivation during the process. Furthermore, providing feedback based on emotions enables more effective and sustainable health management.

[1883] "User" refers to an individual who uses the system to maintain their health and fitness.

[1884] "Goals" refer to the specific objectives that users aim to achieve in order to maintain their health and physique.

[1885] "Personal information" refers to data relating to an individual user, such as age, gender, exercise experience, and physical characteristics.

[1886] "Training Plan" refers to a plan that includes customized exercise content, number of repetitions, number of sets, rest times, etc. to help a user achieve their goals.

[1887] "Video" refers to video data that users film while training and upload to the system.

[1888] "Form" refers to the user's body movements and posture during training.

[1889] "Areas to be corrected" refers to areas in the user's training form that need improvement.

[1890] "Improvement suggestions" refer to specific methods and advice to make the user's training form more effective.

[1891] "Dietary history" refers to a record of the foods and dietary content that a user has consumed in the past.

[1892] "Physical information" refers to health-related data such as a user's height, weight, and allergy information.

[1893] "Nutritional balance" refers to the proper distribution of nutrients necessary to maintain physical health.

[1894] "Meal plan" refers to the specific meal contents proposed taking into consideration the user's nutritional balance.

[1895] "Rewards" refers to incentives that users can receive based on achieving their goals and continuing their training.

[1896] "Emotion" refers to the psychological state recognized from the user's voice and facial expression.

[1897] "Feedback" refers to providing appropriate advice and information regarding the user's training and diet.

[1898] "Server" refers to the computer system that processes user data and generates various plans and feedback.

[1899] "Terminal" refers to a device (e.g., a smartphone or PC) that a user uses to access the system, input data, and display results.

[1900] The present invention is a system that provides users who are aiming to maintain their health and physique with personalized training plans, video guides and feedback, nutritional management and meal plans, and feedback using an emotion engine.

[1901] Providing training plans

[1902] User: A user logs into the system and enters their account information and goals.

[1903] Device: The device (e.g., a smartphone or PC) uses HTML and JavaScript to display a form for the user to enter information such as age, gender, exercise experience, and goals.

[1904] Server: The server receives the input information and generates an optimal training plan using a TensorFlow model developed in Python.

[1905] Device: The training plan received from the server is displayed to the user using HTML and CSS. The training plan includes specific exercises, number of repetitions and sets, and rest periods.

[1906] Video Guides and Feedback

[1907] User: Records videos of themselves training and uploads them to the system.

[1908] Device: Uploaded videos are sent to the server using the REST API.

[1909] Server: The server receives the video and analyzes it using Python and OpenCV. As a result of the analysis, it generates corrections and improvement suggestions for the player's form.

[1910] Terminal: Feedback received from the server is displayed to the user using HTML and CSS.

[1911] Nutritional management and meal plans provided

[1912] User: Enters dietary history, preferences, and allergy information.

[1913] Terminal: Displays input forms created with HTML and JavaScript and sends data to the server.

[1914] Server: Receives the data, analyzes nutritional balance using a TensorFlow model developed in Python, and generates a meal plan.

[1915] Device: The meal plan sent from the server is displayed to the user using HTML and CSS, including the specific menu and ingredients used.

[1916] Reward System

[1917] User: Enter training results.

[1918] Terminal: The input results are sent to the server using JavaScript's Ajax function.

[1919] Server: The server evaluates the data, calculates points using a Python script, and generates rewards when a certain number of points are reached. Rewards include perks and coupons for gacha and avatar acquisition.

[1920] Terminal: Reward information sent from the server is displayed to the user using HTML and CSS.

[1921] Combining Emotion Engines

[1922] User: The system collects voice and facial expressions.

[1923] On the device: The emotion engine analyzes the data and recognizes the user's emotions using the Python EmotionRecognition library.

[1924] Server: Receives the results of the emotion engine and provides feedback to the AI ​​model to adjust the training plan and feedback content in real time.

[1925] Terminal: The adjusted plan and feedback from the server are displayed to the user in HTML and CSS.

[1926] Examples and prompts

[1927] 1. Training plan and emotion recognition example:

[1928] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[1929] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[1930] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[1931] Device: User A sees the adjusted plan.

[1932] Example prompt sentence:

[1933] User A's goal is to increase muscle strength and would like to do high-intensity training three times a week. Please generate the optimal training plan.

[1934] 2. Video guide and emotion recognition example:

[1935] User: User B films and uploads a squat video.

[1936] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[1937] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[1938] Device: Feedback is displayed to User B.

[1939] Example prompt sentence:

[1940] User B uploads a video of themselves squatting. Perform motion analysis and generate feedback if their knees are too far forward. If any insecurity is detected, provide gentle feedback.

[1941] This allows the system to provide training and nutritional management tailored to the individual needs of the user, and utilizes emotion recognition technology to provide optimal feedback. By receiving feedback and plans tailored to their emotional state, users can more easily maintain their motivation.

[1942] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1943] Step 1: Enter your user information

[1944] User: A user logs into the system and enters their account information and goals.

[1945] Input: User's age, gender, exercise experience, and goals

[1946] Output: A JSON request containing the user's input data

[1947] What it does: It displays an HTML form, allows the user to enter information, validates the input with JavaScript, and prepares the data to be sent to the server.

[1948] Step 2: Submit your input

[1949] Terminal: Sends the information the user enters into the form to the server.

[1950] Input: User-entered account information and goals

[1951] Output: User data sent to the server in JSON format

[1952] Specific operation: Uses JavaScript's Ajax function to send information in JSON format to the server.

[1953] Step 3: Generate a training plan

[1954] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[1955] Input: User account information and goals sent to the server

[1956] Output: User-optimized training plan

[1957] How it works: Using a TensorFlow model developed in Python, it generates a training plan based on user input, including calculations for exercises, repetitions, sets, and rest periods.

[1958] Step 4: View your training plan

[1959] Device: Displays the training plan received from the server to the user.

[1960] Input: Training plan sent from the server

[1961] Output: A visual representation of the training plan to the user

[1962] What it does: Uses HTML and CSS to display training plans in a user-friendly format.

[1963] Step 5: Record and upload your video

[1964] User: Records videos of themselves training and uploads them to the system.

[1965] Input: Training video data

[1966] Output: Video file for uploading

[1967] Specific actions: Take a video using your smartphone or PC camera and click the upload button.

[1968] Step 6: Submit your video

[1969] Device: Sends uploaded videos to the server.

[1970] Input: User uploaded video file

[1971] Output: Video data sent to the server

[1972] Specific operation: Use the REST API to send video data to the server.

[1973] Step 7: Analyze the video and generate feedback

[1974] Server: Receives the video and the AI ​​module analyzes the training form and movements. It generates specific form corrections and improvement suggestions as feedback.

[1975] Input: Training video sent to the server

[1976] Output: Feedback and suggestions for corrections and improvements

[1977] Specific operation: Uses Python and OpenCV to analyze videos and generate suggestions for improving form.

[1978] Step 8: View your feedback

[1979] Terminal: Displays the feedback received from the server to the user.

[1980] Input: Feedback data sent from the server

[1981] Output: Visual feedback displayed to the user

[1982] What it does: Uses HTML and CSS to display feedback in a user-friendly way.

[1983] Step 9: Enter your meal information

[1984] User: Enters dietary history, preferences, and allergy information.

[1985] Input: User's dietary history, preferences, and allergy information

[1986] Output: JSON data of the entered user information

[1987] Specific behavior: Enter information into an HTML form and validate it with JavaScript.

[1988] Step 10: Submit your meal information

[1989] Terminal: Sends the entered data to the server.

[1990] Input: Meal information entered by the user

[1991] Output: JSON data sent to the server

[1992] Specific operation: Send data in JSON format via Ajax.

[1993] Step 11: Generate a meal plan

[1994] Server: Receives the data, and AI analyzes the nutritional balance and generates a meal plan.

[1995] Input: Meal information sent to the server

[1996] Output: A nutritionally balanced meal plan

[1997] Specific operation: Uses a TensorFlow model to generate a nutritionally balanced meal plan.

[1998] Step 12: View your meal plan

[1999] Terminal: Displays the meal plan sent from the server to the user.

[2000] Input: Meal plan received from the server

[2001] Output: A concrete meal menu visually displayed to the user

[2002] What it does: Uses HTML and CSS to display meal plans in a user-friendly format.

[2003] Step 13: Implementing the reward system

[2004] Server: Evaluates training results, calculates points, and generates rewards when a certain number of points are reached.

[2005] Input: User-entered training results

[2006] Output: Points and generated rewards (gacha and coupons)

[2007] What it does: A Python script evaluates the data, calculates points, and generates rewards.

[2008] Step 14: View your rewards

[2009] Terminal: Displays the reward information sent from the server to the user.

[2010] Input: Reward information sent from the server

[2011] Output: Reward details visually displayed to the user

[2012] What it does: Displays reward information using HTML and CSS.

[2013] Step 15: Collect emotion data

[2014] User: The system collects voice and facial expressions.

[2015] Input: User voice and facial expression data

[2016] Output: Collected speech and facial expression data

[2017] What it does: Collects data using the camera and microphone on your smartphone or PC.

[2018] Step 16: Sentiment Analysis

[2019] On the device: The emotion engine analyzes the data and recognizes the user's emotions.

[2020] Input: Collected voice and facial expression data

[2021] Output: User's emotional state (fatigue, anxiety, etc.)

[2022] What it does: Analyzes data using Python's EmotionRecognition library.

[2023] Step 17: Adjust your plan and feedback

[2024] Server: Receives the results of the emotion engine and adjusts the training plan and feedback content in real time.

[2025] Input: Emotion engine output (user's emotional state)

[2026] Output: Tailored training plans and feedback

[2027] Specific operation: Feeds analysis results back to the AI ​​model and updates plans and feedback.

[2028] Step 18: View adjusted plans and feedback

[2029] Terminal: Displays adjusted plans and feedback from the server to the user.

[2030] Input: Adjusted plan and feedback sent from the server

[2031] Output: The adjusted content visually displayed to the user

[2032] Specific behavior: Display the adjustment results using HTML and CSS.

[2033] (Application example 2)

[2034] 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."

[2035] Many people today, especially young women, who are trying to maintain their health and shape, are looking for training plans, video guides and feedback, and nutritional management and meal plans. However, traditional systems often provide these functions separately, making it difficult for them to work together to provide optimal feedback to users. Furthermore, traditional systems do not take into account the user's emotions, which can lead to training and meal plans that do not adapt to the user's condition, which can decrease motivation. Therefore, a comprehensive training support system that meets the individual needs of each user is needed.

[2036] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for generating an optimal training plan based on the user's goals and personal information, means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions, means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information, and means for analyzing the user's emotional data and adjusting the training plan and feedback content based on the user's emotions. This allows users to receive individually optimized training plans in real time, enabling them to maintain their health and physique while staying motivated.

[2037] "User" refers to anyone who uses this system to maintain their health and shape.

[2038] "Goal" refers to the specific objectives regarding exercise and health management that a user wishes to achieve through the system.

[2039] "Personal information" refers to information about an individual, such as the user's age, gender, and exercise experience.

[2040] "Training plan" refers to a specific exercise instruction plan provided by the system, including the exercise menu, number of repetitions, number of sets, and rest time.

[2041] "Training video" refers to video data of a user training.

[2042] "Form corrections" refer to areas in your posture or movements that need improvement during training.

[2043] "Improvement suggestions" refer to specific corrective guidance provided by the system to help users train more efficiently.

[2044] "Dietary history" refers to a record of the contents and amounts of food a user has consumed to date.

[2045] "Physical information" refers to data about a user's body, such as weight, height, and body fat percentage.

[2046] A "nutritional balanced meal plan" refers to a meal menu with a properly balanced nutrient content.

[2047] "Emotional data" refers to information about the emotional state of a user analyzed from their voice, facial expressions, etc.

[2048] "Feedback content" refers to the specific advice and guidance on training and diet that the system provides to users.

[2049] "Terminal" refers to electronic devices such as smartphones, tablets, and personal computers that users use to operate the system.

[2050] "Server" refers to a central computer that allows a system to process and store data and provide services to users.

[2051] The specific configuration and operation procedures for the embodiment of this invention are described below. This system provides several main functions to comprehensively support users in achieving their goals and managing their health.

[2052] Providing training plans

[2053] First, the user enters personal information such as age, gender, exercise experience, and goals. This data is sent from the device (smartphone or tablet) to the server. The server uses an AI algorithm to generate an optimal training plan based on the entered information. This AI algorithm can use the OpenAI API. The generated training plan is sent to the device and displayed to the user.

[2054] Video Guides and Feedback

[2055] Users film themselves training and upload the video to their device. The video is then sent to a server where it is analyzed using AI tools such as TensorFlow.js and Azure Cognitive Services. The AI ​​analyzes the video and generates corrections and suggestions for improvement. This feedback is then sent to the device and displayed to the user.

[2056] Nutritional management and meal plans provided

[2057] The user inputs their own dietary history and physical information (e.g., weight, height, body fat percentage, etc.). This data is also sent from the device to the server. The server uses AI to analyze nutritional balance and generate an optimal meal plan. The generated meal plan is sent to the device and displayed to the user.

[2058] Emotional data analysis and plan adjustment

[2059] A distinctive feature of this system is its emotional data analysis. The device collects emotional data, such as the user's voice and facial expressions, and sends it to the server. The server then analyzes the user's emotions using emotion recognition APIs such as Amazon Rekognition and Azure Cognitive Services. Based on the analysis results, the training plan and feedback content are adjusted in real time and sent to the device for display.

[2060] Specific examples

[2061] For example, consider the case where User A sets the goal of "beautiful legs and maintaining good health" and wishes to do high-intensity training three times a week. When User A inputs the information, the AI ​​generates a plan that includes "high-intensity interval training (HIIT)." Furthermore, when User A films and uploads a video of themselves training, the AI ​​analyzes the video and provides specific feedback such as "your form is correct." Furthermore, if User A's voice analysis detects fatigue, the AI ​​adjusts the training intensity appropriately and provides the plan again.

[2062] An example of a prompt using an industry-standard generative AI model might look like this:

[2063] text

[2064] The user entered the following information:

[2065] Age: 25

[2066] Gender: Female

[2067] Exercise experience: Intermediate

[2068] Goal: Beautiful legs and good health

[2069] Generate the best training plan for you based on:

[2070] Training frequency: 3 times a week

[2071] Available equipment: dumbbells, yoga mats

[2072] Favorite exercise: HIIT, yoga

[2073] This allows users to receive optimal feedback and plans tailored to their emotional state, making it easier for them to maintain their motivation.

[2074] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2075] Step 1:

[2076] The user enters personal information such as age, gender, exercise experience, and goals into the device and presses the send button. This input data is sent from the device to the server. The server receives this data and passes it to an AI algorithm to generate a training plan. The generated training plan is sent to the device and displayed to the user.

[2077] Step 2:

[2078] Users record videos of themselves training, which are then uploaded from their devices to a server. The server then analyzes the videos using AI tools such as TensorFlow.js and Azure Cognitive Services. The analysis results, including corrections and suggestions for improvement, are sent to the device and displayed to the user.

[2079] Step 3:

[2080] The user enters their diet history and physical information (e.g., weight, height, body fat percentage, etc.) into the device and presses the send button. This input data is also sent from the device to the server. The server receives this data and uses AI to analyze the nutritional balance. Based on the analysis results, an optimal meal plan is generated, sent to the device, and displayed to the user.

[2081] Step 4:

[2082] The device collects emotional data such as the user's voice and facial expressions. This emotional data is sent from the device to a server. The server then analyzes the emotions using emotion recognition APIs such as Amazon Rekognition and Azure Cognitive Services. Based on the results of this analysis, the training plan and feedback content are adjusted in real time. The adjusted content is sent to the device and displayed to the user.

[2083] Specific examples

[2084] Example: User A

[2085] User A's goal is to have beautiful legs and maintain good health, and he / she wishes to train three times a week. Personal information is entered into the device and sent to the server. The server uses AI to generate a training plan that combines HIIT and yoga, and sends it to the device. User A films and uploads a training video, which the server analyzes using an AI tool. Feedback is given that the form is "correct." If User A's voice analysis detects fatigue, the intensity is adjusted appropriately, and the adjustment results are displayed on the device.

[2086] 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.

[2087] 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.

[2088] 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.

[2089] [Fourth embodiment]

[2090] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2091] 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.

[2092] 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).

[2093] 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.

[2094] 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.

[2095] 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).

[2096] 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.

[2097] 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.

[2098] 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.

[2099] 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.

[2100] 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.

[2101] 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.

[2102] 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."

[2103] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, and nutritional management and meal plans. Specific embodiments of the present invention that provide these functions to users are described below.

[2104] 1. Providing training plans

[2105] User: First, the user logs in to their account through the system login screen, then enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.).

[2106] Terminal: The terminal provides this information to the user as an input form and displays a button to send the form to the server after the user has entered the information.

[2107] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan tailored to the user's goals.

[2108] Device: Receives the generated training plan from the server and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[2109] 2. Video guide and feedback

[2110] User: The user records a training video and uploads it to the system via their device.

[2111] Device: Sends the uploaded video to the server and waits for feedback.

[2112] Server: The server passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[2113] Device: Receives feedback from the server and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[2114] 3. Nutritional management and meal plans

[2115] User: The user enters their dietary history, food preferences, allergy information, etc.

[2116] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[2117] Server: The server uses AI to analyze the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[2118] Device: Receives the meal plan sent from the server and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[2119] 4. Reward System

[2120] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[2121] Terminal: Sends this data to the server and waits for the reward to be calculated.

[2122] Server: The server evaluates the user's input data, calculates points and rewards, and generates rewards such as gacha tickets or coupon codes when the points exceed a certain threshold.

[2123] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[2124] Specific examples

[2125] 1. Examples of training plans provided:

[2126] User: User A enters a goal of "building muscle" and wants to do high-intensity training three times a week.

[2127] Server: AI generates a plan based on the data, including high-intensity interval training (HIIT).

[2128] Terminal: The generated plan is displayed on User A's terminal.

[2129] 2. Video guide and feedback example:

[2130] User: User B records a video of himself doing squats and uploads it to the system.

[2131] Server: AI analyzes the video and detects areas for improvement, such as "knees are too far forward."

[2132] Terminal: User B is shown specific form correction guidelines as a result of the analysis.

[2133] As a result, by using the system of the present invention, users can not only carry out an effective and personalized training plan, but also maintain proper form and consume a nutritionally balanced diet, thereby achieving sustained health and physique maintenance.

[2134] The processing flow will be explained below.

[2135] 1. Providing training plans

[2136] Step 1:

[2137] User: A user logs into the system and enters their account information.

[2138] Step 2:

[2139] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[2140] Step 3:

[2141] User: The user enters their information into the form and clicks the submit button.

[2142] Step 4:

[2143] Terminal: The terminal sends the entered information to the server.

[2144] Step 5:

[2145] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[2146] Step 6:

[2147] Server: The server sends the generated training plan to the device.

[2148] Step 7:

[2149] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[2150] 2. Video guide and feedback

[2151] Step 1:

[2152] User: The user records a video of themselves training.

[2153] Step 2:

[2154] User: The user uploads the video they have taken to the system via their device.

[2155] Step 3:

[2156] Device: Sends uploaded videos to the server.

[2157] Step 4:

[2158] Server: The server passes the received video to the AI ​​module.

[2159] Step 5:

[2160] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[2161] Step 6:

[2162] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[2163] Step 7:

[2164] Server: The server sends the generated feedback to the device.

[2165] Step 8:

[2166] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[2167] 3. Nutritional management and meal plans

[2168] Step 1:

[2169] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[2170] Step 2:

[2171] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[2172] Step 3:

[2173] User: The user clicks the submit button.

[2174] Step 4:

[2175] Terminal: The terminal sends the entered meal data to the server.

[2176] Step 5:

[2177] Server: The server uses AI to analyze the nutritional balance based on the data received.

[2178] Step 6:

[2179] Server: AI generates meal plans tailored to the user's goals.

[2180] Step 7:

[2181] Server: The server sends the generated meal plan to the device.

[2182] Step 8:

[2183] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[2184] 4. Reward System

[2185] Step 1:

[2186] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[2187] Step 2:

[2188] Terminal: The terminal sends this data to the server.

[2189] Step 3:

[2190] Server: The server evaluates the data received and calculates points.

[2191] Step 4:

[2192] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[2193] Step 5:

[2194] Server: The server sends the generated reward information to the terminal.

[2195] Step 6:

[2196] Terminal: The terminal displays the sent reward information to the user.

[2197] Example 1

[2198] 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."

[2199] In recent years, the importance of maintaining health and physique has increased, especially among young people. However, it is difficult to effectively provide individual training and meal plans and maintain high motivation. Furthermore, the lack of systems that provide accurate advice on proper training form and nutritional balance makes it difficult for users to sustainably manage their health. Therefore, there is a need to provide users with effective and efficient training and meal plans, as well as a reward system, to increase their motivation.

[2200] 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.

[2201] In this invention, the server includes: a means for a user to log in to the system and input personal information and goals; a means for generating an optimal training plan using an AI algorithm based on the input information; a means for uploading training videos filmed by the user to the system and analyzing form corrections and improvement suggestions using an AI module; a means for inputting the user's dietary history, food preferences, and allergy information and using an AI platform to suggest a nutritionally balanced meal plan based on the input; and a means for evaluating the user's training results and calculating and providing points and rewards. This makes it possible to provide individually optimized training and meal plans, and the accurate feedback and reward system further motivates users, enabling them to maintain their health and shape.

[2202] A "server" is a computing device that provides data and services to client terminals via the Internet or a local network.

[2203] "User" refers to an individual who uses the System to receive training plans, video feedback, meal plans, and rewards systems.

[2204] "Terminal" means a computing device or device that a user operates to input information or receive and display information from a server.

[2205] "Login" refers to the authentication procedure required for a user to access a system.

[2206] "Personal information" refers to information that can be used to identify a specific individual, such as a user's age, gender, and exercise experience.

[2207] "Goal" refers to the specific purpose that a user wants to achieve when using the system (e.g., maintaining health, losing weight, gaining muscle, etc.).

[2208] An "AI algorithm" is a calculation method that uses artificial intelligence to input user information and generate optimal training and meal plans.

[2209] A "training plan" is a plan that includes specific exercise content, number of repetitions, number of sets, and rest times, generated based on the user's goals.

[2210] "Training video" refers to video data that a user has filmed of their own training.

[2211] The "AI module" is a computing unit that uses artificial intelligence to analyze training videos and provide form corrections and improvement suggestions.

[2212] "Dietary history" refers to a record of the meals a user has eaten up to now.

[2213] "Allergy information" refers to information indicating that a user has an allergic reaction to a particular food or substance.

[2214] A "meal plan" is a plan that includes specific nutritionally balanced menus and a list of ingredients that are suggested based on information entered by the user.

[2215] "Points" are evaluation units that are added up within the system based on a user's activities and achievements.

[2216] "Rewards" refer to incentives (e.g., gacha tickets, bonus coupons, etc.) provided based on the user's training results and continuation status.

[2217] The invention provides users looking to stay healthy and in shape with personalized training plans, video guides and feedback, nutritional management and meal plans, and a rewards system, all optimized using user input and AI algorithms.

[2218] Hardware and Software Configuration

[2219] Server: The server is a high-performance computing device that uses deep learning frameworks such as TensorFlow and PyTorch to generate training and meal plans, and video analysis libraries such as OpenCV and MediaPipe to analyze the training videos.

[2220] Terminal: A terminal is a smartphone or PC operated by a user, and information is input and displayed via a browser or mobile application.

[2221] User: The user accesses the system, logs in, and enters the necessary information to receive personalized training and meal plans.

[2222] Providing training plans

[2223] User: A user logs in to the system and enters their age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, building muscle, etc.). For example, User A enters "building muscle" as their goal and wishes to do high-intensity training three times a week.

[2224] Terminal: The terminal provides this information as an input form, performs error checking, and then sends the information to the server.

[2225] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan. For example, the AI ​​might generate a plan that includes high-intensity interval training (HIIT).

[2226] On your device: The generated training plan will be displayed on your device, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[2227] Video Guides and Feedback

[2228] User: A user records a training video and uploads it to the system. For example, User B records a video of himself doing squats and uploads it to the system.

[2229] Device: The device sends the video to the server.

[2230] Server: The server passes the video to an AI module, which analyzes the form and movements. For example, the AI ​​can detect areas for improvement, such as "the knees are too far forward."

[2231] Device: The analysis results are displayed to the user, and the feedback includes specific advice such as "Your knee angle is incorrect" or "Stand up straighter."

[2232] Nutritional management and meal plans provided

[2233] User: The user enters their dietary history, dietary preferences, and allergy information. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[2234] Terminal: The terminal sends this information to the server.

[2235] Server: The server uses an AI platform to analyze the nutritional balance based on the data and generate a meal plan tailored to the user's goals.

[2236] On your device: The generated meal plan will be displayed on your device, including the specific menu, list of ingredients, and cooking instructions.

[2237] Reward System

[2238] User: The user performs training and enters the results (exercise type, calories burned, number of days continued, etc.).

[2239] Terminal: The terminal sends the entered data to the server.

[2240] Server: The server evaluates the data and calculates points and rewards. For example, when points exceed a certain threshold, gacha tickets or bonus coupons are generated.

[2241] Device: Display generated reward information on your device. Rewards include perks to motivate you to stick to your training and meal plans.

[2242] Examples of prompt statements

[2243] "Create a strength training plan three times a week."

[2244] "Analyze the correct form of the squat and suggest areas for improvement."

[2245] "Create a weekly meal plan to help you stay healthy."

[2246] "Provide rewards based on the number of calories burned by the user in a week."

[2247] As described above, the system of the present invention allows users to implement effective and personalized training plans, while also enabling them to maintain their health and physique on an ongoing basis.

[2248] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2249] Providing training plans

[2250] Step 1:

[2251] User: The user opens the system's login screen and enters their username and password to log into their account. The information they enter is sent to the server via HTTPS.

[2252] Input: Username, Password

[2253] Output: Authentication token

[2254] Step 2:

[2255] Terminal: If authentication is successful, the terminal displays a form for entering age, gender, exercise experience, and goals (e.g., maintaining health, losing weight, gaining muscle, etc.). The user enters the information and presses the "Submit" button.

[2256] Input: Age, Gender, Exercise Experience, Goal

[2257] Output: Validation result of user input data

[2258] Step 3:

[2259] Terminal: The entered information is checked for errors, and if there are no problems, it is sent to the server via HTTPS.

[2260] Input: User-entered data

[2261] Output: Data to send to the server

[2262] Step 4:

[2263] Server: The server stores the received information in a database and inputs it into the AI ​​algorithm, which is built using TensorFlow and PyTorch to process the data and perform calculations to generate the optimal training plan.

[2264] Input: User-entered data

[2265] Output: Training plan

[2266] Step 5:

[2267] Device: The device receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[2268] Input: Training Plan

[2269] Output: what is displayed to the user

[2270] ---

[2271] Video Guides and Feedback

[2272] Step 1:

[2273] User: The user uses a smartphone or digital camera to record a training video, for example, recording their squat form.

[2274] Input: Recorded video file

[2275] Output: Video file saved on device

[2276] Step 2:

[2277] Terminal: The terminal provides an interface for selecting a video file and uploading it to the system. The user presses the "Upload" button.

[2278] Input: Select video file

[2279] Output: Data to send to server

[2280] Step 3:

[2281] Server: The server stores the received video file in temporary storage and passes it to the AI ​​module, which uses libraries such as OpenCV and MediaPipe to perform video analysis.

[2282] Input: Video data

[2283] Output: Analysis results (form corrections, improvement suggestions)

[2284] Step 4:

[2285] Terminal: Receives the analysis results sent from the server and displays them to the user. Feedback includes specific form corrections and suggestions for improvement.

[2286] Input: Analysis results

[2287] Output: what is displayed to the user

[2288] ---

[2289] Nutritional management and meal plans provided

[2290] Step 1:

[2291] User: The user enters their dietary history, food preferences, allergy information, etc. For example, they may enter information such as "dairy allergy" or "high protein diet preference."

[2292] Input: dietary history, food preferences, allergy information

[2293] Output: User data stored on the device

[2294] Step 2:

[2295] Terminal: The terminal displays this information in a form and provides a button to send it to the server once the user has completed the form.

[2296] Input: User data

[2297] Output: Data to send to server

[2298] Step 3:

[2299] Server: The server uses an AI platform, such as Amazon SageMaker or Google Cloud AI Platform, to analyze the nutritional balance based on the data and generate an optimal meal plan.

[2300] Input: User data

[2301] Output: Meal plan

[2302] Step 4:

[2303] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[2304] Enter: meal plan

[2305] Output: what is displayed to the user

[2306] ---

[2307] Reward System

[2308] Step 1:

[2309] User: The user performs training and enters the results (exercise content, calories burned, number of days continued, etc.) into the device.

[2310] Input: Training results

[2311] Output: Data entered into the terminal

[2312] Step 2:

[2313] Terminal: The terminal sends the entered data to the server.

[2314] Input: Training data

[2315] Output: Data to send to server

[2316] Step 3:

[2317] Server: The server evaluates the received data, calculates points and rewards, and generates gacha tickets and bonus coupons when points exceed a certain threshold.

[2318] Input: Training data

[2319] Output: Points, rewards

[2320] Step 4:

[2321] Device: Receives generated reward information and displays it to the user. Rewards include perks to motivate them to continue their next workout or meal plan.

[2322] Input: Remuneration information

[2323] Output: what is displayed to the user

[2324] The above are the specific processing steps of this system, which allows users to implement effective and personalized training plans and maintain their health and physique on a continuous basis.

[2325] (Application example 1)

[2326] 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."

[2327] Conventional healthy lifestyle support systems lack the ability to provide individually customized training and meal plans, and lack adequate feedback on users' actual training form. As a result, it has been difficult to effectively maintain health and shape. Furthermore, food delivery services, in particular, do not offer menus tailored to users' health goals, limiting the means by which users can easily obtain meals that align with their health goals.

[2328] 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.

[2329] In this invention, the server includes: a means for generating an optimal training plan based on the user's goals and personal information; a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions; a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information; a means for providing rewards based on goal achievement and training continuity; a means for generating and providing a customized healthy food menu based on user data; and a means for analyzing exercise videos filmed by the user and providing feedback on form improvements. This allows users to easily obtain effective training and meal plans tailored to their health goals and receive feedback on training form corrections and improvements. Furthermore, particularly in the case of food delivery services, this allows for the provision of menus tailored to the user's health goals, providing a convenient way for users to obtain healthy meals.

[2330] "User goals" are specific goals that users want to achieve, such as maintaining their health or maintaining their figure.

[2331] "Personal information" refers to personal data such as a user's age, gender, and exercise experience.

[2332] A "training plan" is a customized exercise schedule based on a user's goals.

[2333] A "training video" is a video file that records the exercise performed by a user.

[2334] "Form corrections" refer to problems with body movement or posture that need to be improved during training.

[2335] "Improvement suggestions" are specific correction methods and advice provided based on the corrections made to the form.

[2336] "Dietary history" refers to a record of the meals a user has eaten to date.

[2337] "Physical information" refers to data about a user's body, such as weight, height, and body fat percentage.

[2338] A "nutritional balanced meal plan" is a meal plan that includes a balanced amount of nutrients necessary to maintain health, based on the user's physical information and dietary history.

[2339] "Rewards" are incentives provided to users based on goal achievement and training continuity.

[2340] A "customized healthy food menu" is a specific meal plan generated by AI based on a user's health goals and dietary preferences.

[2341] "Analyzing exercise videos" refers to the process of using AI technology to analyze exercise videos taken by users and identify areas for improvement in their form.

[2342] "Feedback" refers to specific corrections and advice provided based on the analysis results.

[2343] A "server" is a central processing unit that analyzes data and manages generated information.

[2344] "Terminal" refers to the computer or smartphone used by the user to enter data or view generated information.

[2345] The present invention is a system that provides optimal training plans, video guides and feedback, nutritional management, and meal plans to support users who are trying to maintain their health and shape. This system is composed of a server, a terminal, and a user. Each component and its specific processing are described below.

[2346] 1. Providing training plans

[2347] User: First, log in to the system and enter their age, gender, exercise experience, and goals (maintaining health, losing weight, building muscle, etc.).

[2348] Terminal: This information is provided as an input form, and a button is displayed to send the form to the server after input.

[2349] Server: Runs AI algorithms based on the received information to generate an optimal training plan tailored to the user's goals.

[2350] Device: Receives the generated training plan and displays it to the user. The plan includes specific exercises, number of repetitions and sets, and appropriate rest periods.

[2351] 2. Video guide and feedback

[2352] User: Records training videos and uploads them to the system via a device.

[2353] Device: Sends the uploaded video to the server and waits for feedback.

[2354] Server: Passes the received video to the AI ​​module, which analyzes the training form and movements. As a result of the analysis, it generates specific form corrections and improvement suggestions.

[2355] The device receives feedback and displays it to the user along with a video guide. The feedback includes specific advice such as "Your knees are at the wrong angle" or "Stand up straighter."

[2356] 3. Nutritional management and meal plans

[2357] User: Enter their dietary history, food preferences, allergy information, etc.

[2358] Terminal: This information is displayed in a form and a button is provided to send the completed information to the server.

[2359] Server: AI analyzes the nutritional balance based on the input data. Based on the analysis results, it generates a meal plan tailored to the user's goals.

[2360] Device: Receives the generated meal plan and displays it to the user. The plan includes specific menu items, a list of ingredients, and cooking instructions.

[2361] 4. Reward System

[2362] User: Performs training and enters the results (exercise type, calories burned, number of days continued, etc.) into the device.

[2363] Terminal: Sends this data to the server and waits for the reward to be calculated.

[2364] Server: Evaluates user input data and calculates points and rewards. When points exceed a certain threshold, it generates rewards such as gacha tickets or coupon codes.

[2365] Device: Receives reward information from the server and displays it to the user. Rewards include rewards and incentives to motivate them to continue their next workout or meal plan.

[2366] 5. Healthy food delivery

[2367] User: Enter their health goals and dietary preferences.

[2368] Server: Generates customized healthy food menus and meal plans based on user data.

[2369] Device: Receives the provided meal plan and displays it to the user. The menu includes specific meal contents and ingredient information.

[2370] Hardware used: Cloud servers (e.g., AWS, Google Cloud), user devices (smartphones: iOS or Android)

[2371] Software used: Flask (web framework), TensorFlow and Keras (AI model framework), OpenCV (video analysis)

[2372] For example, a user can access the app and set a goal of "building muscle," and the AI ​​will generate a training plan that includes "high-intensity interval training (HIIT)." When a user films themselves doing squats and uploads them to the system, the AI ​​will provide feedback on areas for improvement, such as "your knees are too far forward." Furthermore, when a user types in "I want to know what healthy breakfast menu items are," the AI ​​will suggest specific customized menu items, such as "Smoothie Bowl."

[2373] In this way, users can easily obtain training and meal plans tailored to their health goals, and receive feedback on correcting and improving their training form.

[2374] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2375] Step 1:

[2376] The user logs into the system and enters personal information such as their age, gender, exercise experience, and goals.

[2377] Input: Age, Gender, Exercise Experience, Goal (e.g., Maintaining Health, Losing Weight, Gaining Muscle, etc.)

[2378] Action: Fill out the form on your device and press the "Submit" button.

[2379] Output: Input information is sent from the device to the server.

[2380] Step 2:

[2381] The server runs an AI algorithm based on the personal information it receives and generates an optimal training plan tailored to the user's goals.

[2382] Input: Age, Gender, Exercise Experience, Goal

[2383] How it works: An AI model (using TensorFlow and Keras) processes the data and generates a personalized training plan.

[2384] Output: Generated training plan

[2385] Step 3:

[2386] The terminal receives the generated training plan from the server and displays it to the user.

[2387] Input: Generated training plan

[2388] Operation: The plan details (exercise content, number of repetitions and sets, rest time) will be displayed on the device screen.

[2389] Output: A training plan that users can view

[2390] Step 4:

[2391] Users film their training videos and upload them to the system via their devices.

[2392] Input: Filmed training video

[2393] How it works: Uses the device's camera to take a video and upload it to the system.

[2394] Output: Uploaded training videos

[2395] Step 5:

[2396] The server passes the received training video to the AI ​​module, which analyzes the video.

[2397] Input: Uploaded training video

[2398] Movement: Video analysis is performed using OpenCV to detect and evaluate form and movement.

[2399] Output: Form corrections and improvement suggestions as a result of the diagnosis

[2400] Step 6:

[2401] The terminal displays the feedback received from the server to the user.

[2402] Input: Feedback (form corrections, improvement suggestions)

[2403] How it works: Feedback is displayed on the device screen, including specific advice.

[2404] Output: Feedback that users can see

[2405] Step 7:

[2406] Users enter their dietary history, food preferences, allergy information, etc.

[2407] Input: dietary history, food preferences, allergy information

[2408] Action: Fill out the form on your device and press the "Submit" button.

[2409] Output: Input information is sent from the device to the server.

[2410] Step 8:

[2411] Based on the data received by the server, the AI ​​analyzes nutritional balance and generates a meal plan.

[2412] Input: dietary history, food preferences, allergy information

[2413] How it works: An AI model processes the data and generates a customized meal plan.

[2414] Output: Generated meal plan

[2415] Step 9:

[2416] The terminal receives the generated meal plan from the server and displays it to the user.

[2417] Input: Generated meal plan

[2418] How it works: The meal plan details (specific menu, ingredients, and cooking instructions) will be displayed on the device screen.

[2419] Output: Meal plan available for user review

[2420] Step 10:

[2421] The user inputs the results of their training and diet into the terminal.

[2422] Input: Training content, calories burned, number of days, meal content

[2423] Action: Enter the results into the input form on your device and press the "Submit" button.

[2424] Output: Input information is sent from the device to the server.

[2425] Step 11:

[2426] The server evaluates the received information and calculates the reward.

[2427] Input: Training content, calories burned, number of days, meal content

[2428] What it does: Evaluates data and generates rewards (points, gacha tickets, coupon codes, etc.) if it exceeds a certain threshold.

[2429] Output: Generated rewards

[2430] Step 12:

[2431] The terminal displays the reward information received from the server to the user.

[2432] Input: Remuneration information

[2433] Operation: The reward details (points, gacha tickets, coupon codes, etc.) will be displayed on the device screen.

[2434] Output: Reward details that users can check

[2435] Step 13:

[2436] The user views and orders a customized healthy food menu.

[2437] Input: User's health goals and dietary preferences

[2438] What it does: View the healthy food menu provided on the device and complete your order using your smartphone.

[2439] Output: Healthy food ordered

[2440] 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.

[2441] The present invention is a system primarily targeted at women in their early to mid-twenties who are looking to maintain their health and shape, and provides personalized training plans, video guides and feedback, nutritional management and meal plans, and an emotion engine that recognizes the user's emotions. Specific embodiments of the present invention that provide these functions to users are described below.

[2442] 1. Providing training plans

[2443] User: A user logs into the system and enters their account information and goals.

[2444] Terminal: The terminal displays a form for the user to enter information such as age, gender, exercise experience, and goals.

[2445] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[2446] Device: Displays the training plan received from the server to the user. The plan includes specific exercises, number of repetitions and sets, and rest periods.

[2447] 2. Video guide and feedback

[2448] User: The user records a video of themselves training and uploads it to the system.

[2449] Device: Sends uploaded videos to the server.

[2450] Server: The server receives the video and the AI ​​module analyzes the training form and movements.

[2451] Server: Generates specific form corrections and improvement proposals as analysis results.

[2452] On the device: Displays the feedback received from the server to the user and provides specific advice.

[2453] 3. Nutritional management and meal plans

[2454] User: The user enters their dietary history, preferences, and allergy information.

[2455] Terminal: The terminal displays the input form and sends the data to the server.

[2456] Server: The server receives the data and the AI ​​analyzes the nutritional balance. It then generates a meal plan based on the analysis.

[2457] Device: The meal plan sent from the server is displayed to the user, including the specific menu and ingredients used.

[2458] 4. Reward System

[2459] User: The user enters the training results.

[2460] Terminal: The terminal sends data to the server.

[2461] Server: The server evaluates the data and calculates points. When a certain number of points is reached, it generates a reward.

[2462] Terminal: Displays reward information sent from the server to the user, including gacha tickets and coupons.

[2463] 5. Combining Emotion Engines

[2464] User: The system collects the user's voice and facial expressions.

[2465] On the device: The emotion engine analyzes the data and recognizes the user's emotions.

[2466] Server: The server receives the results of the emotion engine and adjusts the training plan and feedback content in real time.

[2467] Terminal: Displays adjusted plans and feedback from the server to the user.

[2468] Specific examples

[2469] 1. Training plan and emotion recognition example:

[2470] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[2471] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[2472] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[2473] Device: User A sees the adjusted plan.

[2474] 2. Video guide and emotion recognition example:

[2475] User: User B films and uploads a squat video.

[2476] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[2477] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[2478] Device: Feedback is displayed to User B.

[2479] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[2480] The processing flow will be explained below.

[2481] 1. Providing training plans

[2482] Step 1:

[2483] User: A user logs into the system and enters their account information.

[2484] Step 2:

[2485] Device: The device provides the user with an input form for information such as age, gender, exercise experience, and goals.

[2486] Step 3:

[2487] User: The user enters their information into the form and clicks the submit button.

[2488] Step 4:

[2489] Terminal: The terminal sends the entered information to the server.

[2490] Step 5:

[2491] Server: The server runs an AI algorithm based on the received information to generate an optimal training plan based on the user's goals and physical information.

[2492] Step 6:

[2493] Server: The server sends the generated training plan to the device.

[2494] Step 7:

[2495] Device: The device displays a training plan to the user, including specific exercises, number of repetitions and sets, and appropriate rest periods.

[2496] 2. Video guide and feedback

[2497] Step 1:

[2498] User: The user records a video of themselves training.

[2499] Step 2:

[2500] User: The user uploads the video they have taken to the system via their device.

[2501] Step 3:

[2502] Device: Sends uploaded videos to the server.

[2503] Step 4:

[2504] Server: The server passes the received video to the AI ​​module.

[2505] Step 5:

[2506] Server: The AI ​​module analyzes the video and evaluates training form and movements.

[2507] Step 6:

[2508] Server: The AI ​​module generates corrections and improvement suggestions for the form.

[2509] Step 7:

[2510] Server: The server sends the generated feedback to the device.

[2511] Step 8:

[2512] Device: The device displays feedback to the user, including specific advice and suggestions for improvement.

[2513] 3. Nutritional management and meal plans

[2514] Step 1:

[2515] User: The user fills out a form with their dietary history, dietary preferences, and allergy information.

[2516] Step 2:

[2517] Terminal: The terminal displays this information and provides a button to send it to the server once you have completed entering it.

[2518] Step 3:

[2519] User: The user clicks the submit button.

[2520] Step 4:

[2521] Terminal: The terminal sends the entered meal data to the server.

[2522] Step 5:

[2523] Server: The server uses AI to analyze the nutritional balance based on the data received.

[2524] Step 6:

[2525] Server: AI generates meal plans tailored to the user's goals.

[2526] Step 7:

[2527] Server: The server sends the generated meal plan to the device.

[2528] Step 8:

[2529] Device: The device displays the meal plan to the user, including specific menu items, a list of ingredients, and cooking instructions.

[2530] 4. Reward System

[2531] Step 1:

[2532] User: The user enters training results (exercise content, calories burned, number of days continued, etc.) into the device.

[2533] Step 2:

[2534] Terminal: The terminal sends this data to the server.

[2535] Step 3:

[2536] Server: The server evaluates the data received and calculates points.

[2537] Step 4:

[2538] Server: Generates rewards when points exceed a certain threshold. Rewards include, for example, gacha tickets or coupon codes.

[2539] Step 5:

[2540] Server: The server sends the generated reward information to the terminal.

[2541] Step 6:

[2542] Terminal: The terminal displays the sent reward information to the user.

[2543] 5. Combining Emotion Engines

[2544] Step 1:

[2545] User: The device collects the user's voice and facial expressions.

[2546] Step 2:

[2547] On the device: The emotion engine analyzes the collected data and identifies the user's emotions.

[2548] Step 3:

[2549] Server: The server receives the results from the emotion engine and adjusts the training plan and feedback in real time.

[2550] Step 4:

[2551] Server: Sends adjusted training plans and feedback to the device.

[2552] Step 5:

[2553] Device: The device displays the adjusted plan and feedback to the user, including personalized messages and training advice based on the user's emotions.

[2554] Specific examples

[2555] 1. Training plan and emotion recognition example:

[2556] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[2557] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[2558] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[2559] Device: User A sees the adjusted plan.

[2560] 2. Video guide and emotion recognition example:

[2561] User: User B films and uploads a squat video.

[2562] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[2563] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[2564] Device: Feedback is displayed to User B.

[2565] This allows the system of the present invention to utilize emotion recognition technology to provide training and nutritional management tailored to the individual needs of each user. By receiving optimal feedback and plans based on their emotional state, users can more easily maintain their motivation.

[2566] Example 2

[2567] 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."

[2568] In today's busy lifestyles, personalized training plans and nutritional management are important for effectively maintaining health and physique. However, few systems offer optimal plans tailored to individual needs, and coaching users on proper form and maintaining motivation during training can be challenging. Furthermore, there are few systems that provide feedback based on the user's emotions. This makes it difficult for many users to effectively and sustainably manage their health.

[2569] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2570] In this invention, the server includes a means for generating an optimal training plan based on the user's goals and personal information, a means for analyzing training videos uploaded by the user and providing form corrections and improvement suggestions, a means for proposing a nutritionally balanced meal plan based on the user's diet history and physical information, and a means for recognizing the user's emotions and adjusting the training plan and feedback content based on the results. This allows users to receive training and nutritional management tailored to their individual needs, while providing accurate form guidance and maintaining motivation during the process. Furthermore, providing feedback based on emotions enables more effective and sustainable health management.

[2571] "User" refers to an individual who uses the system to maintain their health and fitness.

[2572] "Goals" refer to the specific objectives that users aim to achieve in order to maintain their health and physique.

[2573] "Personal information" refers to data relating to an individual user, such as age, gender, exercise experience, and physical characteristics.

[2574] "Training Plan" refers to a plan that includes customized exercise content, number of repetitions, number of sets, rest times, etc. to help a user achieve their goals.

[2575] "Video" refers to video data that users film while training and upload to the system.

[2576] "Form" refers to the user's body movements and posture during training.

[2577] "Areas to be corrected" refers to areas in the user's training form that need improvement.

[2578] "Improvement suggestions" refer to specific methods and advice to make the user's training form more effective.

[2579] "Dietary history" refers to a record of the foods and dietary content that a user has consumed in the past.

[2580] "Physical information" refers to health-related data such as a user's height, weight, and allergy information.

[2581] "Nutritional balance" refers to the proper distribution of nutrients necessary to maintain physical health.

[2582] "Meal plan" refers to the specific meal contents proposed taking into consideration the user's nutritional balance.

[2583] "Rewards" refers to incentives that users can receive based on achieving their goals and continuing their training.

[2584] "Emotion" refers to the psychological state recognized from the user's voice and facial expression.

[2585] "Feedback" refers to providing appropriate advice and information regarding the user's training and diet.

[2586] "Server" refers to the computer system that processes user data and generates various plans and feedback.

[2587] "Terminal" refers to a device (e.g., a smartphone or PC) that a user uses to access the system, input data, and display results.

[2588] The present invention is a system that provides users who are aiming to maintain their health and physique with personalized training plans, video guides and feedback, nutritional management and meal plans, and feedback using an emotion engine.

[2589] Providing training plans

[2590] User: A user logs into the system and enters their account information and goals.

[2591] Device: The device (e.g., a smartphone or PC) uses HTML and JavaScript to display a form for the user to enter information such as age, gender, exercise experience, and goals.

[2592] Server: The server receives the input information and generates an optimal training plan using a TensorFlow model developed in Python.

[2593] Device: The training plan received from the server is displayed to the user using HTML and CSS. The training plan includes specific exercises, number of repetitions and sets, and rest periods.

[2594] Video Guides and Feedback

[2595] User: Records videos of themselves training and uploads them to the system.

[2596] Device: Uploaded videos are sent to the server using the REST API.

[2597] Server: The server receives the video and analyzes it using Python and OpenCV. As a result of the analysis, it generates corrections and improvement suggestions for the player's form.

[2598] Terminal: Feedback received from the server is displayed to the user using HTML and CSS.

[2599] Nutritional management and meal plans provided

[2600] User: Enters dietary history, preferences, and allergy information.

[2601] Terminal: Displays input forms created with HTML and JavaScript and sends data to the server.

[2602] Server: Receives the data, analyzes nutritional balance using a TensorFlow model developed in Python, and generates a meal plan.

[2603] Device: The meal plan sent from the server is displayed to the user using HTML and CSS, including the specific menu and ingredients used.

[2604] Reward System

[2605] User: Enter training results.

[2606] Terminal: The input results are sent to the server using JavaScript's Ajax function.

[2607] Server: The server evaluates the data, calculates points using a Python script, and generates rewards when a certain number of points are reached. Rewards include perks and coupons for gacha and avatar acquisition.

[2608] Terminal: Reward information sent from the server is displayed to the user using HTML and CSS.

[2609] Combining Emotion Engines

[2610] User: The system collects voice and facial expressions.

[2611] On the device: The emotion engine analyzes the data and recognizes the user's emotions using the Python EmotionRecognition library.

[2612] Server: Receives the results of the emotion engine and provides feedback to the AI ​​model to adjust the training plan and feedback content in real time.

[2613] Terminal: The adjusted plan and feedback from the server are displayed to the user in HTML and CSS.

[2614] Examples and prompts

[2615] 1. Training plan and emotion recognition example:

[2616] User: User A sets the goal of "building muscle strength" and wants to do high-intensity training three times a week.

[2617] Server: AI generates a plan that includes "High Intensity Interval Training (HIIT)."

[2618] Emotion engine: If user A's voice analysis detects fatigue, the training intensity is adjusted accordingly.

[2619] Device: User A sees the adjusted plan.

[2620] Example prompt sentence:

[2621] User A's goal is to increase muscle strength and would like to do high-intensity training three times a week. Please generate the optimal training plan.

[2622] 2. Video guide and emotion recognition example:

[2623] User: User B films and uploads a squat video.

[2624] Server: The AI ​​analyzes the video and gives feedback such as, "Your knees are too far forward."

[2625] Emotion engine: If User B's facial expression analysis detects anxiety, the feedback is softened.

[2626] Device: Feedback is displayed to User B.

[2627] Example prompt sentence:

[2628] User B uploads a video of themselves squatting. Perform motion analysis and generate feedback if their knees are too far forward. If any insecurity is detected, provide gentle feedback.

[2629] This allows the system to provide training and nutritional management tailored to the individual needs of the user, and utilizes emotion recognition technology to provide optimal feedback. By receiving feedback and plans tailored to their emotional state, users can more easily maintain their motivation.

[2630] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2631] Step 1: Enter your user information

[2632] User: A user logs into the system and enters their account information and goals.

[2633] Input: User's age, gender, exercise experience, and goals

[2634] Output: A JSON request containing the user's input data

[2635] What it does: It displays an HTML form, allows the user to enter information, validates the input with JavaScript, and prepares the data to be sent to the server.

[2636] Step 2: Submit your input

[2637] Terminal: Sends the information the user enters into the form to the server.

[2638] Input: User-entered account information and goals

[2639] Output: User data sent to the server in JSON format

[2640] Specific operation: Uses JavaScript's Ajax function to send information in JSON format to the server.

[2641] Step 3: Generate a training plan

[2642] Server: The server receives the input information and runs an AI algorithm to generate the optimal training plan.

[2643] Input: User account information and goals sent to the server

[2644] Output: User-optimized training plan

[2645] How it works: Using a TensorFlow model developed in Python, it generates a training plan based on user input, including calculations for exercises, repetitions, sets, and rest periods.

[2646] Step 4: View your training plan

[2647] Device: Displays the training plan received from the server to the user.

[2648] Input: Training plan sent from the server

[2649] Output: A visual representation of the training plan to the user

[2650] What it does: Uses HTML and CSS to display training plans in a user-friendly format.

[2651] Step 5: Record and upload your video

[2652] User: Records videos of themselves training and uploads them to the system.

[2653] Input: Training video data

[2654] Output: Video file for uploading

[2655] Specific actions: Take a video using your smartphone or PC camera and click the upload button.

[2656] Step 6: Submit your video

[2657] Device: Sends uploaded videos to the server.

[2658] Input: User uploaded video file

[2659] Output: Video data sent to the server

[2660] Specific operation: Use the REST API to send video data to the server.

[2661] Step 7: Analyze the video and generate feedback

[2662] Server: Receives the video and the AI ​​module analyzes the training form and movements. It generates specific form corrections and improvement suggestions as feedback.

[2663] Input: Training video sent to the server

[2664] Output: Feedback and suggestions for corrections and improvements

[2665] Specific operation: Uses Python and OpenCV to analyze videos and generate suggestions for improving form.

[2666] Step 8: View your feedback

[2667] Terminal: Displays the feedback received from the server to the user.

[2668] Input: Feedback data sent from the server

[2669] Output: Visual feedback displayed to the user

[2670] What it does: Uses HTML and CSS to display feedback in a user-friendly way.

[2671] Step 9: Enter your meal information

[2672] User: Enters dietary history, preferences, and allergy information.

[2673] Input: User's dietary history, preferences, and allergy information

[2674] Output: JSON data of the entered user information

[2675] Specific behavior: Enter information into an HTML form and validate it with JavaScript.

[2676] Step 10: Submit your meal information

[2677] Terminal: Sends the entered data to the server.

[2678] Input: Meal information entered by the user

[2679] Output: JSON data sent to the server

[2680] Specific operation: Send data in JSON format via Ajax.

[2681] Step 11: Generate a meal plan

[2682] Server: Receives the data, and AI analyzes the nutritional balance and generates a meal plan.

[2683] Input: Meal information sent to the server

[2684] Output: A nutritionally balanced meal plan

[2685] Specific operation: Uses a TensorFlow model to generate a nutritionally balanced meal plan.

[2686] Step 12: View your meal plan

[2687] Terminal: Displays the meal plan sent from the server to the user.

[2688] Input: Meal plan received from the server

[2689] Output: A concrete meal menu visually displayed to the user

[2690] What it does: Uses HTML and CSS to display meal plans in a user-friendly format.

[2691] Step 13: Implementing the reward system

[2692] Server: Evaluates training results, calculates points, and generates rewards when a certain number of points are reached.

[2693] Input: User-entered training results

[2694] Output: Points and generated rewards (gacha and coupons)

[2695] What it does: A Python script evaluates the data, calculates points, and generates rewards.

[2696] Step 14: View your rewards

[2697] Terminal: Displays the reward information ...

Claims

1. A means for generating an optimal training plan based on the user's goals and personal information; A means to analyze training videos uploaded by users and provide corrections and improvement suggestions for their form; A means for proposing a nutritionally balanced meal plan based on the user's dietary history and physical information; A means of providing rewards based on goal achievement and training persistence; A system including:

2. The system according to claim 1, wherein the reward means includes issuing bonuses and coupons for gacha and avatar acquisition.

3. 2. The system according to claim 1, wherein each of the means for providing the training plan, video feedback, and meal plan cooperates with a means for transmitting the user's data to a server and displaying the generated information on a terminal.

Images