System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to enter their information; a server for receiving and processing said information; said server comprising: means for generating a diet plan and an exercise menu based on said information; means for providing said generated plan and menu to the user; and means for storing said plan and menu in a format desired by the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] This invention relates to a system that efficiently supports dieting. With conventional dieting methods, many users are unsure of how to create a diet plan, and the target period is unclear, leading to frequent failure. It is also difficult to provide appropriate dietary restrictions and exercise plans tailored to individual users. Furthermore, the management and storage of various data is cumbersome, preventing users from continuing the diet over the long term. Therefore, the objective of this invention is to provide a system that solves these problems and enables users to diet effectively. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means.

[0006] The system includes a means for a user to input their own information, a server that receives and processes the information, a means for the server to generate a dietary restriction plan and exercise menu based on the information, a means for providing the generated plan and menu to the user, and a means for saving the plan and menu in a format desired by the user.

[0007] The system further includes means for a user to input daily data, means for receiving the daily data and managing progress, and means for adjusting the plan based on the progress and providing feedback.

[0008] The system also includes a means for displaying the plan and menu in a graph format, a means for providing the user with the graph format data, and a means for providing the data in a form that is easy to understand visually. These means allow the user to diet efficiently and make it easy to continuously manage their progress.

[0009] "User" refers to an individual or entity that inputs information and uses the system.

[0010] "Means for inputting information" refers to an interface that allows a user to input their own data (age, sex, weight, target weight, allergy information, etc.) into the system.

[0011] A "receiving and processing server" refers to a computer system that receives information sent by a user and performs data processing and analysis based on that information.

[0012] "Diet Plan" means a daily diet designed to help a user lose weight while maintaining a specific nutritional balance.

[0013] An "exercise menu" refers to a recommended exercise program for reaching a user's target weight.

[0014] "Means for providing" refers to a method or interface for notifying, displaying, or distributing the generated plan or menu to the user.

[0015] "Means for saving" refers to a method for saving the generated plan or menu in a format desired by the user (Word, Excel, PPT, PDF, etc.).

[0016] "Daily data" refers to data such as weight, diet, and exercise that the user inputs every day.

[0017] "Means for managing progress" refers to a method for analyzing daily data and monitoring and managing the user's progress toward their weight goal.

[0018] "Means for adjusting the plan and providing feedback" refers to a method for adjusting the diet plan or exercise menu based on the user's progress and providing appropriate advice and evaluation to the user.

[0019] "Means for displaying in graph format" refers to a method of displaying data such as weight trends and exercise volume as graphs so that the user can visually check their progress.

[0020] "Means of presenting information in a visually easy-to-understand format" refers to methods of presenting information in the form of icons, charts, graphs, etc., so that users can easily understand the data. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0029] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0042] As an embodiment of the present invention, a system is constructed as follows.

[0043] System Overview

[0044] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides real-time feedback. The generated data and progress information can also be saved in the user's preferred format.

[0045] Program processing

[0046] 1. User data entry

[0047] The user enters information such as age, gender, current weight, target weight, and allergy information into the application.

[0048] The terminal verifies the entered data and transmits it to the server.

[0049] 2. Data Receipt and Processing

[0050] The server receives the data sent by the user.

[0051] The server creates a user profile based on the received data.

[0052] 3. Create a diet plan and exercise menu

[0053] The server uses AI to generate a diet plan and exercise menu, taking into account the user's current weight, target weight, age, gender, and other factors to derive the optimal plan.

[0054] Example: If a user weighs 70kg and aims to lose 60kg, a plan will be generated that limits daily calorie intake to 1500kcal and recommends exercising five days a week.

[0055] 4. Providing the generated plan

[0056] The server compiles the generated diet plan and exercise menu in text and graph format.

[0057] The server saves this in the user's desired format (Word, Excel, PPT, PDF, etc.).

[0058] The terminal receives this data and displays it to the user.

[0059] 5. Daily progress input and management

[0060] Users enter their weight, diet, and exercise information into the application every day.

[0061] The terminal transmits the input data to the server.

[0062] The server analyzes the data daily and updates the progress.

[0063] 6. Real-time advice and plan adjustments

[0064] The server adjusts the plan as needed based on the user's progress and provides real-time feedback.

[0065] Example: If a user loses 1kg in a week, provide a message saying "You're making good progress! Keep it up!"

[0066] 7. Graphical display

[0067] The server generates data to display the user's progress in a graphical format.

[0068] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[0069] Specific examples

[0070] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg.

[0071] Users enter their age, gender, weight, target weight, and allergy information into the app.

[0072] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[0073] The plan is saved in Excel format and provided to the user.

[0074] Users input their daily weight and dietary information, and the server analyzes it and updates their progress.

[0075] The server generates a progress graph, which the terminal visually displays to the user.

[0076] In this way, the user can efficiently reach their target weight while checking their progress.

[0077] The processing flow will be explained below.

[0078] Step 1:

[0079] The user starts the application and enters personal data such as age, sex, current weight, target weight, allergy information, etc. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[0080] Step 2:

[0081] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[0082] Step 3:

[0083] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, and allergy information. The server stores this information in a database.

[0084] Step 4:

[0085] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile. For example, the generation process will design a calorie restriction and appropriate exercise menu to bring a 70kg user down to 60kg.

[0086] Step 5:

[0087] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[0088] Step 6:

[0089] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[0090] Step 7:

[0091] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[0092] Step 8:

[0093] Users enter their daily weight, diet, and exercise information into the application, which is then registered as daily data.

[0094] Step 9:

[0095] The terminal transmits the daily data entered by the user to the server, which receives it and stores it in a database.

[0096] Step 10:

[0097] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from reaching their goal weight.

[0098] Step 11:

[0099] The server adjusts the plan as needed based on the user's progress, for example generating advice to reset calorie levels or increase exercise if weight loss is slower than expected.

[0100] Step 12:

[0101] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[0102] Step 13:

[0103] The device receives the updates and feedback sent by the server and presents them to the user, who then takes the next step.

[0104] This series of steps helps users effectively diet, and the system provides ongoing progress monitoring and feedback.

[0105] Example 1

[0106] 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."

[0107] Previously, it was difficult for users to find appropriate diet plans and exercise menus based on their individual health conditions and goals. Additionally, there was a lack of systems that track daily progress and provide real-time feedback. Furthermore, there were limited ways to provide users with a visual understanding of their progress, making it difficult to support long-term goal achievement.

[0108] 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.

[0109] In this invention, the server includes a means for generating a diet plan and exercise menu using a generative AI model, a means for analyzing the user's daily data, updating the user's progress, and providing real-time feedback, and a means for generating data displaying the user's progress in a graphical format and providing the data to the user. This allows the user to obtain a customized diet plan and exercise menu based on their individual health condition and goals, allowing them to efficiently achieve their goals while managing their daily progress. Furthermore, providing progress in a format that is easy to understand visually can help the user maintain ongoing motivation.

[0110] "User information" refers to personal information such as age, sex, weight, target weight, and allergy information entered by the user.

[0111] A "terminal" is a device used by a user to enter information or view stored data, and includes smartphones, tablets, and personal computers with dedicated applications installed.

[0112] The "server" is a back-end system that receives and processes user information, generates diet plans and exercise menus, and provides them to users.

[0113] A "generative AI model" is an artificial intelligence model that generates appropriate diet plans and exercise menus based on input prompts.

[0114] A "prompt" is a textual instruction entered into a generative AI model, containing specific conditions and requirements.

[0115] A "dietary restriction plan" is a plan that includes recommended daily calorie intake and meal contents to achieve the user's health goals.

[0116] An "exercise menu" is a plan that includes the type and frequency of exercise recommended to achieve the user's health goals.

[0117] The "format" refers to the data format in which the diet plan or exercise menu is provided to the user, and examples include Word, Excel, PDF, etc.

[0118] "Progress data" refers to data such as weight, dietary details, and exercise details that are input by the user on a daily basis, and indicates the progress of the user in achieving their goals.

[0119] "Feedback" refers to advice and encouraging messages provided by the server based on analysis of the user's progress data.

[0120] "Graph-format data" refers to data such as line graphs and bar graphs that are generated to visually display the user's progress.

[0121] As an embodiment of the present invention, the following system is constructed. The system is designed to enable users to obtain a customized diet plan and exercise menu based on their individual health condition and goals. The user inputs daily data, and the system manages the progress in real time and provides feedback as needed. The system also displays the data in a graph format so that the user can visually grasp the progress toward achieving their goals.

[0122] System Overview and Configuration

[0123] Users install a dedicated application on their devices, such as smartphones, tablets, or PCs, to input data. The information entered by the user is verified by the device and securely sent to a server. The server processes the received information and generates a diet plan or exercise menu using a generative AI model (e.g., OpenAI's GPT-3.5).

[0124] The generated plan and menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and sent to the device. The user enters their daily weight, diet, and exercise details, and this data is sent to the server via the device. The server analyzes the progress data, adjusts the plan as needed, and provides feedback in real time. In addition, the server generates data that displays the user's progress in graph form and sends it to the device, allowing the user to check their progress in a format that is easy to understand visually.

[0125] Hardware and software used

[0126] 1. Devices: smartphones, tablets, computers

[0127] 2. Dedicated application: An application for users to enter data.

[0128] 3. Server: The back-end system that receives and processes data and generates plans using generative AI models.

[0129] 4. Generative AI models: Artificial intelligence models such as OpenAI's GPT-3.5

[0130] Specific examples

[0131] To illustrate each processing step, consider a scenario in which a 30-year-old female user wants to lose weight from 70 kg to a target weight of 60 kg. The user enters her age, gender, weight, target weight, and allergy information into the application. The device verifies this data and sends it to the server. The server uses the generated AI model to generate a plan that sets a daily calorie intake of 1500 kcal and includes five exercise sessions per week (strength training and aerobic exercise).

[0132] The generated plan is saved in the user's desired format (e.g., Excel format) and sent to the user's device. The user enters their daily weight, dietary habits, and exercise habits into the application, and this data is sent to the server. The server analyzes the progress data and provides real-time feedback, such as "You're making good progress. Keep it up!" The server also generates data that displays the progress in graph form, which the device displays to the user.

[0133] Prompt Sentence Examples

[0134] "Generate the optimal diet and exercise plan for a 30-year-old female user to lose weight from 70 kg to a target weight of 60 kg. The daily calorie intake should be set to 1500 kcal, and the user should exercise (strength training and aerobic exercise) five times a week."

[0135] By inputting this prompt into a generative AI model, a specific plan is generated.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] Step 1: Enter user data

[0138] The user launches a dedicated application and enters information such as age, gender, current weight, target weight, and allergy information.

[0139] Input: Age, gender, weight, target weight, allergy information

[0140] Output: User data is stored within the app and ready to be sent to the device.

[0141] Step 2: Validate and submit data

[0142] The terminal validates the data entered by the user, checking for missing information or improper formatting.

[0143] Input: Data entered by the user

[0144] Output: Validated data, if incomplete an error message is displayed to the user.

[0145] The terminal sends the verified data to the server.

[0146] Input: Validated Data

[0147] Output: The data is encrypted and sent to the server.

[0148] Step 3: Server receives data and creates profile

[0149] The server receives the data sent from the device and stores it in a database, creating a user profile.

[0150] Input: Validated Data

[0151] Output: The user profile is saved in the database.

[0152] Step 4: Generate plans and menus

[0153] The server uses the generative AI model to create prompts to generate a diet plan and exercise menu and sends them to the AI ​​model.

[0154] Input: User profile

[0155] Output: A prompt sentence is generated and sent to the AI ​​model.

[0156] The generative AI model generates an appropriate diet plan and exercise menu based on the prompt text and sends it back to the server.

[0157] Input: prompt statement

[0158] Output: The generated plan and exercise menu are sent back to the server.

[0159] Step 5: Save and serve your plans and menus

[0160] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[0161] Input: Generated plans and menus

[0162] Output: Saved in the specified format and sent to the device.

[0163] The terminal displays the received plans and menus to the user.

[0164] Input: Plans and menus saved in format

[0165] Output: What is displayed to the user in the application.

[0166] Step 6: Daily data entry and submission

[0167] Users enter their weight, diet, and exercise information into the application every day.

[0168] Input: Daily weight, diet, exercise

[0169] Output: Daily data is stored within the app and ready to be sent to your device.

[0170] The device sends daily data to the server.

[0171] Input: Daily data

[0172] Output: The data is sent to the server.

[0173] Step 7: Analyze progress data and receive real-time feedback

[0174] The server analyzes the daily data received and provides progress updates.

[0175] Input: Daily data

[0176] Output: Updated progress data is saved to the database.

[0177] The server generates a feedback message based on the progress data and sends it to the terminal.

[0178] Input: Progress data

[0179] Output: A feedback message is generated and sent to the terminal.

[0180] The terminal displays a feedback message to the user.

[0181] Input: Feedback message

[0182] Output: What is displayed to the user in the application.

[0183] Step 8: Graphical display of progress

[0184] The server generates and formats data to visually display the user's progress.

[0185] Input: Progress data

[0186] Output: Graphical data is generated.

[0187] The terminal displays the received data in the form of a graph to the user.

[0188] Input: Graph format data

[0189] Output: The output is displayed in an easy-to-understand visual format on the application.

[0190] (Application example 1)

[0191] 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."

[0192] In modern society, providing appropriate dietary plans and exercise menus based on individual health conditions and goals is an important issue. However, existing systems only generate plans based on user information, and few cover implementation and progress management, especially specific meal menus. In addition, they lack a function that allows users to easily order daily meals, making personalized health management difficult.

[0193] 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.

[0194] In this invention, the server includes means for a user to input their own information, means for receiving and processing the information, means for generating a dietary restriction plan and exercise menu based on the information, means for generating a meal menu based on the generated plan and menu using a generative AI model, means for allowing the user to select and order the generated meal menu, and means for saving the plan and menu in a format desired by the user. This allows the user to easily order a personalized meal menu based on their health information and receive real-time feedback on their progress.

[0195] The "means for inputting user information" is an interface for the user to input personal information such as age, sex, weight, target weight, and allergy information.

[0196] "Server that receives and processes information" refers to a computer system that centrally receives, analyzes, stores, and processes information entered by users.

[0197] The "means for generating a diet plan and exercise menu" refers to algorithms and processes for automatically generating a healthy diet plan and exercise menu based on user input information.

[0198] The "means for providing the generated plan and menu to the user" refers to an interface that provides the generated dietary restriction plan and exercise menu to the user in a visual or text format.

[0199] A "generative AI model" is an artificial intelligence model that generates appropriate meal menus based on user information and past data.

[0200] A "means for generating a meal menu" is a process and system that uses a generative AI model to automatically generate a meal menu based on a user's health information and goals.

[0201] The "means for enabling the user to select and order a meal menu" is an interface that displays the generated meal menu to the user, allows the user to select the meal they want from the menu, and confirms the order.

[0202] "Means for saving in a format desired by the user" is a function for saving the generated plan or menu in a format desired by the user, such as PDF, Excel, or Word.

[0203] The "means for inputting daily data" is an interface that allows the user to input data such as daily weight, dietary habits, and exercise habits.

[0204] "Means for receiving daily data and managing progress" refers to a system that receives daily data entered by the user and analyzes and manages the progress status.

[0205] The "means for adjusting the plan and providing feedback" is a function that adjusts the dietary restriction plan and exercise menu based on the user's progress data and provides the user with appropriate advice and feedback in real time.

[0206] The "means for managing order history and analyzing meal satisfaction data" is a system that stores the history of meal menus ordered by users and collects and analyzes user satisfaction data.

[0207] The "means for displaying in graph format" is a function for converting the user's progress and data into graph format and displaying it.

[0208] The "means for adjusting meal menus in real time" is a system that constantly optimizes the current meal menu based on the user's progress data and changes it as necessary.

[0209] MODE FOR CARRYING OUT THE INVENTION

[0210] As an embodiment of the present invention, a system is constructed as follows.

[0211] System Overview

[0212] The purpose of this system is to allow users to input their own health information and generate optimal dietary restriction plans and exercise menus based on that information.Furthermore, it provides a function to generate specific meal menus based on these plans and allow users to select and order.

[0213] Hardware Configuration

[0214] Server: Cloud-based server (e.g., Amazon Web Services, Google Cloud Platform)

[0215] Smartphone: iOS or Android compatible device

[0216] Software Configuration

[0217] Server side: Python (Framework: Flask)

[0218] Generative AI models: Python libraries (e.g., Scikit-learn, TensorFlow)

[0219] Client Side: React Native

[0220] Data Processing Procedures

[0221] 1. Entering and receiving user data

[0222] Users use a smartphone application to input their age, gender, current weight, target weight, allergy information, etc. The device verifies the input data and sends it to a cloud-based server.

[0223] 2. User Data Processing and Plan Generation

[0224] The server receives the information sent by the user and creates a user profile based on that data, analyzing data such as age, gender, weight, target weight, and allergy information, and then uses a generative AI model to generate an optimal diet plan and exercise menu.

[0225] 3. Generating and presenting a meal menu

[0226] The server automatically generates a meal menu using a generative AI model based on existing plans and menus. The generated menu is presented to the user via a smartphone application, and the user selects the desired menu and confirms their order.

[0227] 4. Daily progress input and management

[0228] Users enter their daily weight, diet, exercise, etc. into the application. The device sends this data to a cloud server, which analyzes it and manages the user's progress.

[0229] 5. Real-time advice and menu adjustments

[0230] The server adjusts the plan as needed and provides real-time feedback based on the user's progress, and also adjusts the meal menu in real time.

[0231] 6. Graphical progress display

[0232] The server generates data to display the user's progress in a graph format and provides this to the user via a smartphone application, allowing the user to visually grasp their progress.

[0233] Specific examples

[0234] Consider a case where a 30-year-old male user currently weighs 80 kg and creates a plan to bring his target weight down to 70 kg.

[0235] Users enter their age, gender, weight, target weight, and allergy information into the app.

[0236] Based on this data, the server generates a plan that sets a daily calorie intake of 1,600 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[0237] The generative AI model then generates a specific meal menu based on this (e.g., grilled chicken salad, whole wheat bread).

[0238] Users select and order from this menu on the app and receive their meal via food delivery.

[0239] Example prompt sentence:

[0240] Prompt: I'm 30 years old, my current weight is 80kg, and my goal weight is 70kg. I have no allergies. Please provide a healthy meal plan.

[0241] Example output: Breakfast: Oatmeal with fruit and unsweetened yogurt. Lunch: Grilled chicken with salad and whole wheat bread. Dinner: Steamed fish with stewing vegetables.

[0242] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0243] Step 1:

[0244] Entering and Receiving User Data

[0245] Users enter their age, gender, current weight, target weight, allergy information, etc. using a smartphone application.

[0246] The terminal validates the entered data and sends it to a cloud-based server in JSON format.

[0247] Input: Age, gender, current weight, target weight, allergy information

[0248] Output: Sending user data to the server

[0249] Step 2:

[0250] Processing of User Data

[0251] The server receives the information sent by the user and creates a user profile based on that data.

[0252] At this time, the data is formatted and saved.

[0253] Input: User data (age, gender, current weight, target weight, allergy information)

[0254] Output: Create and save user profile

[0255] Step 3:

[0256] Generate plans and exercise menus

[0257] The server uses a generative AI model to generate an optimal diet plan and exercise menu based on the user profile.

[0258] Specifically, the system calculates calorie intake and exercise frequency, taking into account the user's target weight and current weight.

[0259] Input: User profile

[0260] Output: Generated diet plan and exercise menu

[0261] Step 4:

[0262] Generate and present a meal menu

[0263] The server automatically generates meal menus using a generative AI model based on existing plans and menus.

[0264] The terminal displays the received data to the user through the application.

[0265] The user selects a menu item and confirms the order.

[0266] Input: Generated diet plan and exercise menu

[0267] Output: Meal menu presented to the user, order information

[0268] Step 5:

[0269] Daily progress input and management

[0270] Users input their daily weight, diet, exercise, etc. into the application.

[0271] The device sends this data to a cloud server.

[0272] The server analyzes the data and manages the user's progress.

[0273] Input: Daily weight, diet, exercise

[0274] Output: Progress management data

[0275] Step 6:

[0276] Real-time advice and menu adjustments

[0277] The server adjusts the plan as needed and provides real-time feedback based on the user's progress data.

[0278] Using generative AI models, new menus and exercise plans are generated and provided to users through the application.

[0279] Input: Progress management data

[0280] Output: Adjusted plan, real-time feedback

[0281] Step 7:

[0282] Progress display in graphical format

[0283] The server generates data to display the user's progress in a graph format and provides this to the user through a smartphone application.

[0284] Users can visually grasp their progress.

[0285] Input: Progress management data

[0286] Output: Progress data in graphical format

[0287] 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.

[0288] As an embodiment of the present invention, a system is constructed as follows.

[0289] System Overview

[0290] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. The generated data and progress information can also be saved in the format desired by the user.

[0291] Program processing

[0292] 1. User data entry

[0293] The user enters their age, gender, current weight, target weight, allergy information, and emotional data (e.g., self-reported or obtained through emotion recognition technology) into the application. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[0294] 2. Data Receipt and Processing

[0295] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[0296] 3. Creating a profile on the server

[0297] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[0298] 4. Analysis by Emotion Engine

[0299] The server analyzes the user's emotional data using an emotion engine, which evaluates the user's emotional state, such as whether the user is stressed or motivated.

[0300] 5. Create a diet plan and exercise menu

[0301] The server generates a diet plan and exercise menu based on the analysis results of the generative AI and emotion engine, according to the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress.

[0302] 6. Providing the generated plan

[0303] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[0304] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[0305] 7. Offering and Display of Offers

[0306] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[0307] 8. Daily progress input and emotional data collection

[0308] Users enter their weight, diet, exercise, and emotional state into the application every day, and the data is registered as daily data.

[0309] The terminal transmits the entered daily data to the server, which receives it and stores it in a database.

[0310] 9. Progress data analysis and management

[0311] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from their goal weight. It also analyzes emotional data to assess the user's emotional state.

[0312] 10. Real-time advice and plan adjustments

[0313] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling depressed, it generates encouraging messages and dietary and exercise advice to reduce stress. This feedback is provided in real time.

[0314] 11. Graphical display

[0315] The server generates data for displaying the user's progress and emotion data in a graph format.

[0316] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[0317] Specific examples

[0318] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. The user also reports that she feels stressed.

[0319] Users enter their age, gender, weight, goal weight, allergy information and emotional state into the app.

[0320] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also adds a meal menu suitable for stress relief.

[0321] The plan is saved in Excel format and provided to the user.

[0322] Users input their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[0323] The server generates a progress graph and emotion data as graphs, which are then visually displayed to the user on the device.

[0324] This series of steps allows users to track their progress and emotional state while efficiently reaching their goal weight, and the combined emotional engine provides more personalized plans and feedback.

[0325] The processing flow will be explained below.

[0326] Step 1:

[0327] The user starts the application and inputs their age, gender, current weight, target weight, allergy information, and emotional data (e.g., data obtained through a form to input their emotional state or through emotion recognition technology). The user enters this data and confirms it by pressing the submit button.

[0328] Step 2:

[0329] The device receives the data entered by the user and verifies whether the data is appropriate: specifically, whether the age is within a reasonable range, whether the gender is selected correctly, whether the weight and target weight are reasonable, and whether the emotional data is entered accurately. After verification, the device sends the data to the server.

[0330] Step 3:

[0331] The server receives the data sent from the device and creates a user profile, which includes age, gender, current weight, target weight, allergy information, and emotional state. The server stores this information in a database and updates the data as needed.

[0332] Step 4:

[0333] The server uses an emotion engine to analyze the user's emotional data. The emotion engine uses emotion analysis algorithms to analyze the emotional data entered by the user and sensor data to determine the user's emotional state, such as whether they are feeling stressed or highly motivated.

[0334] Step 5:

[0335] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress. On the other hand, if the user is highly motivated, it will recommend a slightly more strenuous exercise menu.

[0336] Step 6:

[0337] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume, making it easier to visually grasp the user's progress.

[0338] Step 7:

[0339] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[0340] Step 8:

[0341] The terminal receives the plan file sent from the server and presents it to the user, who can then download it and view it on their device.

[0342] Step 9:

[0343] Every day, users enter their weight, diet, exercise, and emotional state into the application, which then sends the data to the system as daily data.

[0344] Step 10:

[0345] The device sends daily data entered by the user to a server, including weight, food intake, exercise, emotional state, etc.

[0346] Step 11:

[0347] The server receives and analyzes daily data, evaluating weight fluctuations, calorie intake, and activity levels to determine whether the user is approaching their weight goal and how their emotional state is evolving.

[0348] Step 12:

[0349] The server updates the progress based on the analysis of the daily data, which means adding the latest information to the user profile.

[0350] Step 13:

[0351] The server reevaluates the plan based on the user's progress and emotional data and makes adjustments as needed. For example, if the user is feeling emotionally down, it may provide encouraging messages or advice to help relieve stress.

[0352] Step 14:

[0353] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[0354] Step 15:

[0355] The device receives the feedback and updates sent by the server and presents them to the user, who then takes the next step.

[0356] As a concrete example, consider a 30-year-old female user who wants to lose weight from 70 kg to 60 kg, and who reports feeling stressed.

[0357] The user inputs their age, gender, current weight, goal weight, allergy information, and emotional state.

[0358] The server generates a plan that sets a daily calorie intake of 1500 kcal and recommends five exercise sessions per week. Because the user is under stress, it recommends foods that are effective in relieving stress and light exercise.

[0359] The plan is saved in Excel format and provided to the user.

[0360] Users input their daily weight, diet, exercise and emotional state, and the server analyzes this and updates their progress.

[0361] The server generates a progress graph and emotion data, which the device visually displays to the user.

[0362] In this way, the system takes into account the user's emotional state and provides more personalized guidance and feedback to support dieting success.

[0363] Example 2

[0364] 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."

[0365] Conventional health management systems only provide fixed dietary restriction plans and exercise menus based on basic information entered by users, making it difficult to provide dynamic feedback that corresponds to the user's emotional state or daily progress.In addition, there was a lack of a way for users to easily understand plans and progress data visually, which resulted in a tendency for users to find it difficult to maintain motivation.

[0366] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing emotional data and adjusting the plan and menu, a means for providing feedback in real time, and a means for visually displaying the emotional data and progress data. This not only enables dynamic feedback according to the user's emotional state and daily progress, but also makes it easier to maintain the user's motivation by providing the feedback in a visually easy-to-understand format.

[0367] A "user" is an individual who utilizes the system to input their own health care data and receive feedback.

[0368] "Information" refers to all data input by the user, including age, sex, current weight, target weight, allergy information, and emotional data.

[0369] "Computer" refers to the entire device or system that receives, processes, and stores information entered by a user in a database.

[0370] "Means for generating" refers to a process or algorithm that generates a diet plan and exercise menu based on input information.

[0371] "Means for providing" refers to a method or system for presenting the generated diet plan and exercise menu to the user.

[0372] "Means for saving" refers to a function or process for saving the generated plans and menus in a format desired by the user.

[0373] "Emotion data" is data that reflects the user's emotional state, including stress, motivation, and the like.

[0374] "Means for analyzing" refers to a function or algorithm that processes emotional data to assess the user's emotional state.

[0375] "Means for adjusting" refers to a function or process that modifies plans and menus based on the user's emotional state and progress data.

[0376] "Means for providing feedback" refers to a function or system that provides appropriate advice or information to users in real time.

[0377] "Graphical format" refers to a format used to visualize data, such as a line graph, bar graph, or pie chart.

[0378] "Progress Data" refers to data regarding a user's daily weight, diet, exercise, and emotional state.

[0379] "Visual display means" refers to a function or system that displays data in a form such as a graph so that the user can easily understand the information.

[0380] This invention is a system that generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. In addition, the generated data and progress information can be saved in the format desired by the user.

[0381] System Overview

[0382] The system begins with the user entering their age, gender, current weight, goal weight, allergy information, and emotional data. The entered data is sent to the server via the device. The server creates a user profile based on the received data and uses a generative AI model and emotional engine to generate a dietary restriction plan and exercise menu tailored to each individual user. The generated plan is saved in the user's desired format and provided via the device.

[0383] When users enter their daily progress data (weight, diet, exercise, emotional state), this data is sent back to the server, where it is analyzed and the plan is adjusted as needed. Furthermore, the analysis results are fed back to the user in real time, allowing them to easily visualize their progress in the form of statistical data and graphs.

[0384] Hardware and software used

[0385] Terminal: A device on which a user inputs data and receives data from a server. This includes smartphones, tablets, and PCs.

[0386] Server: A central computer system that receives data, creates profiles, analyzes them, generates plans, and provides feedback. It is where the generative AI models and emotion engines run.

[0387] The generative AI model includes an algorithm to suggest optimal diet and exercise plans based on the user's basic information and emotional data, while the emotional engine analyzes the user's emotional data and provides information necessary to adjust the plan.

[0388] Specific examples

[0389] For example, a 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. This user reports that she feels stressed.

[0390] 1. The user enters their age, gender, weight, target weight, allergy information, and emotional state into the application's input form.

[0391] 2. Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also suggests additional meal menus suitable for stress relief.

[0392] 3. The plan is saved in Excel format and provided to the user, who can view it on their device.

[0393] 4. Users enter their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[0394] 5. The server generates a progress graph and emotion data, which are then visually displayed on the device.

[0395] Example prompt sentence:

[0396] "A 30-year-old woman currently weighs 70 kg and has a goal weight of 60 kg. She reports feeling stressed. Based on these conditions, please suggest a balanced diet plan and a five-day weekly exercise routine."

[0397] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0398] Step 1: User Data Entry

[0399] The user enters age, gender, current weight, target weight, allergy information, and emotional data into the application's input form. The entered data is confirmed when the user presses the send button. This data is sent to the terminal as input information (age, gender, current weight, target weight, allergy information, emotional data).

[0400] Step 2: Receiving and processing data

[0401] The terminal receives the data entered by the user. At this stage, the terminal checks the integrity of the data, for example, whether the age is within a reasonable range and whether the numerical data is in the correct format. After verification, the terminal sends the appropriate data to the server. The sent data becomes information for creating a user profile.

[0402] Step 3: Create a profile on the server

[0403] The server receives the data sent from the device and creates a user profile based on this data. The profile includes age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[0404] Step 4: Analysis by Emotion Engine

[0405] The server uses an emotion engine to analyze the user's emotion data. For example, it evaluates the user's emotional state, such as whether they are feeling stressed or highly motivated. The analysis results are added to the user profile and used to generate the next plan. The input is emotion data, and the output is the analysis results of the emotion engine.

[0406] Step 5: Create a diet plan and exercise menu

[0407] The server generates a dietary restriction plan and exercise menu based on the analysis results of the generative AI model and emotion engine according to the user profile. For example, if the user is feeling stressed, it will suggest meals and light exercise menus that are effective in relieving stress. The input is the user profile and the analysis results of the emotion engine, and the output is a dietary restriction plan and exercise menu.

[0408] Step 6: Serving the generated plan

[0409] The server compiles the generated diet plan and exercise menu in text and graph format. The generated plan is saved in the user's desired format (e.g., Word, Excel, PPT, PDF) and sent to the device. The input is the generated plan and menu, and the output is the saved file.

[0410] Step 7: Offer and display your plan

[0411] The terminal receives the plan file sent from the server. The user can download this file and view it on their device. The input is the plan file from the server, and the output is the presentation to the user.

[0412] Step 8: Daily progress input and emotional data collection

[0413] Every day, users input their weight, diet, exercise, and emotional state into the application. This data is registered as daily data. The input data is sent to the server via the device, and the server stores it in a database. The input is daily progress data, and the output is the stored daily data.

[0414] Step 9: Analyze and manage progress data

[0415] The server analyzes the data entered daily and updates the user's progress. This analysis evaluates how close or far the user is from reaching their goal weight. Emotional data is also analyzed to evaluate the user's emotional state. The input is daily progress data and emotional data, and the output is the progress analysis results.

[0416] Step 10: Real-time advice and plan adjustments

[0417] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling emotionally down, it generates encouraging messages and diet and exercise advice to reduce stress. This feedback is provided in real time. The input is progress and emotional data, and the output is the adjusted plan and feedback.

[0418] Step 11: Display in graphical format

[0419] The server generates data to display the user's progress and emotional data in a graph format, allowing the user to visually grasp their own progress and emotional state. The device receives this data and displays it in a form that is easy for the user to understand visually. The input is the generated graph data, and the output is the visual display.

[0420] (Application example 2)

[0421] 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."

[0422] Traditional health management systems only provide basic dietary and exercise plans based on user input, but they lack the ability to adjust plans to take into account the user's emotional state or provide real-time feedback. This can lead to a decrease in user motivation and an increase in stress, making it difficult to achieve goals. They also lack tools for visualizing progress.

[0423] 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 analyzing the user's emotional data using emotion recognition technology, means for adjusting the diet plan and exercise menu based on the user's emotional state, and means for generating data for visually displaying daily progress and emotional state. This makes it possible to provide an individualized plan according to the user's emotional state and provide real-time feedback.

[0424] "Means for users to input their own information" refers to a device or system that provides an interface for users to input information such as age, sex, current weight, target weight, allergy information, and emotional data.

[0425] The "server that receives and processes the information" refers to a server system that receives information entered by users and analyzes, stores, and processes that information.

[0426] The "means for generating a dietary restriction plan and exercise menu" refers to an algorithm or program for automatically generating an appropriate dietary restriction plan and exercise menu based on input user information.

[0427] "Means for providing the generated plan and menu to the user" refers to means for presenting the generated dietary restriction plan and exercise menu to the user, including providing them in text format or graphical format.

[0428] "Means for saving in a format desired by the user" refers to a function for saving the generated plan or menu in a file format (e.g., Word, Excel, PDF) specified by the user.

[0429] "Means for analyzing user emotional data using emotion recognition technology" refers to technology for identifying and analyzing a user's current emotional state using the user's input data and biometric data.

[0430] "Means for adjusting dietary plans and exercise menus based on the user's emotional state" refers to means for individually adjusting and optimizing existing plans and menus by taking into account the user's emotional state.

[0431] "Means for generating data for visually displaying daily progress and emotional state" refers to means for converting a user's progress data and emotional data into a visual format such as a graph, and providing it to the user in a way that is easy to understand.

[0432] MODE FOR CARRYING OUT THE INVENTION

[0433] DETAILED DESCRIPTION OF THE INVENTION The following describes an embodiment of the present invention.

[0434] System Overview

[0435] This system allows users to input their personal information and generates a balanced diet plan and exercise menu based on that information, and further adjusts the plan in real time according to the user's emotional state. It also allows users to visually grasp their daily progress and emotional data, providing personalized health management support.

[0436] Program Implementation

[0437] The system uses the following key tools and technologies:

[0438] User information input interface

[0439] Central Server

[0440] emotion recognition technology

[0441] Meal restriction plan generation algorithm

[0442] Exercise menu generation algorithm

[0443] Data Visualization Techniques

[0444] Specific examples

[0445] The user inputs their age, gender, weight, target weight, allergy information, and emotional data into the health management app. The central server receives this information and analyzes the user's emotional state using emotion recognition technology. Based on this information, an individualized plan is generated using a dietary restriction plan generation algorithm and an exercise menu generation algorithm. The generated plan and menu are saved in the user's desired format and displayed visually.

[0446] Step-by-step process overview

[0447] User Data Entry

[0448] The user inputs age, gender, weight, target weight, allergy information, and emotional data into the application. This data is sent to the server through the application's input form.

[0449] Data reception and processing

[0450] The server receives the input data, verifies it, and then stores it. In particular, emotional data is analyzed using emotion recognition technology.

[0451] Plan Generation

[0452] The server generates a diet plan and exercise menu based on the user's profile and the results of emotion analysis. A generative AI model is used to generate an appropriate plan.

[0453] Plan delivery and visualization

[0454] The generated diet plan and exercise menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and provided to the user. The user's progress and emotional data are also displayed in a visually easy-to-understand format.

[0455] The specific hardware and software used

[0456] Hardware

[0457] Central server: Stores data and performs calculations.

[0458] Client terminal: A device (PC, smartphone, tablet, etc.) through which a user enters data.

[0459] software

[0460] Emotion recognition technology: Analyzes user emotion data.

[0461] Diet Plan Generation Algorithm: Generates a meal plan based on input data.

[0462] Exercise menu generation algorithm: Generate an exercise menu.

[0463] Data visualization tools: Visually display user progress data.

[0464] Prompt Sentence Examples

[0465] markdown

[0466] Prompt for employee wellness app:

[0467] Enter the user profile:

[0468] Age: 30

[0469] Gender: Female

[0470] Current weight: 70kg

[0471] Target weight: 60kg

[0472] Allergy Information: Nuts

[0473] Emotional state: Stress

[0474] Example of a generated meal plan:

[0475] Breakfast: Oatmeal and fruit

[0476] Lunch: Grilled chicken salad

[0477] Dinner: Salmon and vegetables

[0478] An example of a generated exercise menu:

[0479] Light stretching

[0480] 30 minutes of walking every day

[0481] Three yoga sessions per week

[0482] conclusion

[0483] This allows users to obtain a personalized health management plan based on their own information, and effectively manage their health through real-time adjustments and visualizations according to their emotional state, while also solving the problems faced by traditional health management systems.

[0484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0485] Processing Steps

[0486] Step 1: User Data Entry

[0487] The user inputs information such as age, sex, weight, target weight, allergy information, emotional data, etc. through the input interface. After completing the input, the user presses the send button to confirm the data and send it from the terminal to the server.

[0488] Input: Age, gender, weight, target weight, allergy information, emotional data

[0489] Output: User information data sent to the server

[0490] Step 2: Data reception and verification

[0491] The server receives the user information sent from the terminal and then verifies whether the format of the received data is correct and within a reasonable range.

[0492] Input: User information data sent from the device

[0493] Output: Validated user information data, error message (if invalid data)

[0494] Step 3: Create a profile

[0495] The server creates a user profile based on the verified user information and stores it in a database.

[0496] Input: Verified user information data

[0497] Output: User profile stored in the database

[0498] Step 4: Analyze the sentiment data

[0499] The server analyzes the user's emotional data using emotion recognition technology. An emotion engine processes the data and identifies the user's emotional state (e.g., stress, motivation).

[0500] Input: User emotion data

[0501] Output: Parsed emotional state

[0502] Step 5: Create a diet plan and exercise menu

[0503] The server generates a plan based on the user's profile and emotional state using a diet plan generation algorithm and an exercise menu generation algorithm. The generative AI model proposes the optimal plan for each user.

[0504] Input: User profile, analyzed emotional state

[0505] Output: Generated diet plan and exercise menu

[0506] Step 6: Save and serve your plan

[0507] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[0508] Input: Generated diet plan and exercise menu, user's desired format

[0509] Output: Plan file saved in desired format

[0510] Step 7: View your plan

[0511] The terminal receives the plan file sent from the server and proposes it to the user, who can visually confirm it.

[0512] Input: Plan file sent from the server

[0513] Output: Plans and menus displayed to the user

[0514] Step 8: Collect daily progress and sentiment data

[0515] Every day, users enter their weight, diet, exercise, emotional data, etc. into the application and send that data to the server.

[0516] Input: Daily weight, diet, exercise, emotional data

[0517] Output: Daily progress data stored on the server

[0518] Step 9: Analyze progress data

[0519] The server analyzes the daily progress data, evaluates the user's progress and emotional state, and updates the database.

[0520] Input: Daily progress data, emotional data

[0521] Output: Parsed progress, updated user profile

[0522] Step 10: Real-time feedback and plan adjustments

[0523] Based on the analyzed progress and emotional state, the server adjusts the plan as needed and provides real-time feedback, generating encouraging messages or new advice depending on the user's emotional state.

[0524] Input: Parsed progress, emotional state

[0525] Output: Real-time feedback, tailored plans and advice

[0526] Step 11: Visualize the data

[0527] The server generates graph data for visually displaying the user's progress data and emotion data, and transmits it to the device, which receives it and visually displays it to the user.

[0528] Input: Progress data, emotion data

[0529] Output: visualized graph data, graph displayed to user

[0530] In this way, the system helps users manage their health and provides personalized plans tailored to their emotional state.

[0531] 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.

[0532] 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.

[0533] 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.

[0534] [Second embodiment]

[0535] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0536] 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.

[0537] 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).

[0538] 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.

[0539] 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.

[0540] 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).

[0541] 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.

[0542] 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.

[0543] 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.

[0544] 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.

[0545] In the smart glasses 214, 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.

[0546] 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."

[0547] As an embodiment of the present invention, a system is constructed as follows.

[0548] System Overview

[0549] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides real-time feedback. The generated data and progress information can also be saved in the user's preferred format.

[0550] Program processing

[0551] 1. User data entry

[0552] The user enters information such as age, gender, current weight, target weight, and allergy information into the application.

[0553] The terminal verifies the entered data and transmits it to the server.

[0554] 2. Data Receipt and Processing

[0555] The server receives the data sent by the user.

[0556] The server creates a user profile based on the received data.

[0557] 3. Create a diet plan and exercise menu

[0558] The server uses AI to generate a diet plan and exercise menu, taking into account the user's current weight, target weight, age, gender, and other factors to derive the optimal plan.

[0559] Example: If a user weighs 70kg and aims to lose 60kg, a plan will be generated that limits daily calorie intake to 1500kcal and recommends exercising five days a week.

[0560] 4. Providing the generated plan

[0561] The server compiles the generated diet plan and exercise menu in text and graph format.

[0562] The server saves this in the user's desired format (Word, Excel, PPT, PDF, etc.).

[0563] The terminal receives this data and displays it to the user.

[0564] 5. Daily progress input and management

[0565] Users enter their weight, diet, and exercise information into the application every day.

[0566] The terminal transmits the input data to the server.

[0567] The server analyzes the data daily and updates the progress.

[0568] 6. Real-time advice and plan adjustments

[0569] The server adjusts the plan as needed based on the user's progress and provides real-time feedback.

[0570] Example: If a user loses 1kg in a week, provide a message saying "You're making good progress! Keep it up!"

[0571] 7. Graphical display

[0572] The server generates data to display the user's progress in a graphical format.

[0573] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[0574] Specific examples

[0575] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg.

[0576] Users enter their age, gender, weight, target weight, and allergy information into the app.

[0577] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[0578] The plan is saved in Excel format and provided to the user.

[0579] Users input their daily weight and dietary information, and the server analyzes it and updates their progress.

[0580] The server generates a progress graph, which the terminal visually displays to the user.

[0581] In this way, the user can efficiently reach their target weight while checking their progress.

[0582] The processing flow will be explained below.

[0583] Step 1:

[0584] The user starts the application and enters personal data such as age, sex, current weight, target weight, allergy information, etc. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[0585] Step 2:

[0586] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[0587] Step 3:

[0588] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, and allergy information. The server stores this information in a database.

[0589] Step 4:

[0590] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile. For example, the generation process will design a calorie restriction and appropriate exercise menu to bring a 70kg user down to 60kg.

[0591] Step 5:

[0592] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[0593] Step 6:

[0594] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[0595] Step 7:

[0596] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[0597] Step 8:

[0598] Users enter their daily weight, diet, and exercise information into the application, which is then registered as daily data.

[0599] Step 9:

[0600] The terminal transmits the daily data entered by the user to the server, which receives it and stores it in a database.

[0601] Step 10:

[0602] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from reaching their goal weight.

[0603] Step 11:

[0604] The server adjusts the plan as needed based on the user's progress, for example generating advice to reset calorie levels or increase exercise if weight loss is slower than expected.

[0605] Step 12:

[0606] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[0607] Step 13:

[0608] The device receives the updates and feedback sent by the server and presents them to the user, who then takes the next step.

[0609] This series of steps helps users effectively diet, and the system provides ongoing progress monitoring and feedback.

[0610] Example 1

[0611] 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."

[0612] Previously, it was difficult for users to find appropriate diet plans and exercise menus based on their individual health conditions and goals. Additionally, there was a lack of systems that track daily progress and provide real-time feedback. Furthermore, there were limited ways to provide users with a visual understanding of their progress, making it difficult to support long-term goal achievement.

[0613] 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.

[0614] In this invention, the server includes a means for generating a diet plan and exercise menu using a generative AI model, a means for analyzing the user's daily data, updating the user's progress, and providing real-time feedback, and a means for generating data displaying the user's progress in a graphical format and providing the data to the user. This allows the user to obtain a customized diet plan and exercise menu based on their individual health condition and goals, allowing them to efficiently achieve their goals while managing their daily progress. Furthermore, providing progress in a format that is easy to understand visually can help the user maintain ongoing motivation.

[0615] "User information" refers to personal information such as age, sex, weight, target weight, and allergy information entered by the user.

[0616] A "terminal" is a device used by a user to enter information or view stored data, and includes smartphones, tablets, and personal computers with dedicated applications installed.

[0617] The "server" is a back-end system that receives and processes user information, generates diet plans and exercise menus, and provides them to users.

[0618] A "generative AI model" is an artificial intelligence model that generates appropriate diet plans and exercise menus based on input prompts.

[0619] A "prompt" is a textual instruction entered into a generative AI model, containing specific conditions and requirements.

[0620] A "dietary restriction plan" is a plan that includes recommended daily calorie intake and meal contents to achieve the user's health goals.

[0621] An "exercise menu" is a plan that includes the type and frequency of exercise recommended to achieve the user's health goals.

[0622] The "format" refers to the data format in which the diet plan or exercise menu is provided to the user, and examples include Word, Excel, PDF, etc.

[0623] "Progress data" refers to data such as weight, dietary details, and exercise details that are input by the user on a daily basis, and indicates the progress of the user in achieving their goals.

[0624] "Feedback" refers to advice and encouraging messages provided by the server based on analysis of the user's progress data.

[0625] "Graph-format data" refers to data such as line graphs and bar graphs that are generated to visually display the user's progress.

[0626] As an embodiment of the present invention, the following system is constructed. The system is designed to enable users to obtain a customized diet plan and exercise menu based on their individual health condition and goals. The user inputs daily data, and the system manages the progress in real time and provides feedback as needed. The system also displays the data in a graph format so that the user can visually grasp the progress toward achieving their goals.

[0627] System Overview and Configuration

[0628] Users install a dedicated application on their devices, such as smartphones, tablets, or PCs, to input data. The information entered by the user is verified by the device and securely sent to a server. The server processes the received information and generates a diet plan or exercise menu using a generative AI model (e.g., OpenAI's GPT-3.5).

[0629] The generated plan and menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and sent to the device. The user enters their daily weight, diet, and exercise details, and this data is sent to the server via the device. The server analyzes the progress data, adjusts the plan as needed, and provides feedback in real time. In addition, the server generates data that displays the user's progress in graph form and sends it to the device, allowing the user to check their progress in a format that is easy to understand visually.

[0630] Hardware and software used

[0631] 1. Devices: smartphones, tablets, computers

[0632] 2. Dedicated application: An application for users to enter data.

[0633] 3. Server: The back-end system that receives and processes data and generates plans using generative AI models.

[0634] 4. Generative AI models: Artificial intelligence models such as OpenAI's GPT-3.5

[0635] Specific examples

[0636] To illustrate each processing step, consider a scenario in which a 30-year-old female user wants to lose weight from 70 kg to a target weight of 60 kg. The user enters her age, gender, weight, target weight, and allergy information into the application. The device verifies this data and sends it to the server. The server uses the generated AI model to generate a plan that sets a daily calorie intake of 1500 kcal and includes five exercise sessions per week (strength training and aerobic exercise).

[0637] The generated plan is saved in the user's desired format (e.g., Excel format) and sent to the user's device. The user enters their daily weight, dietary habits, and exercise habits into the application, and this data is sent to the server. The server analyzes the progress data and provides real-time feedback, such as "You're making good progress. Keep it up!" The server also generates data that displays the progress in graph form, which the device displays to the user.

[0638] Prompt Sentence Examples

[0639] "Generate the optimal diet and exercise plan for a 30-year-old female user to lose weight from 70 kg to a target weight of 60 kg. The daily calorie intake should be set to 1500 kcal, and the user should exercise (strength training and aerobic exercise) five times a week."

[0640] By inputting this prompt into a generative AI model, a specific plan is generated.

[0641] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0642] Step 1: Enter user data

[0643] The user launches a dedicated application and enters information such as age, gender, current weight, target weight, and allergy information.

[0644] Input: Age, gender, weight, target weight, allergy information

[0645] Output: User data is stored within the app and ready to be sent to the device.

[0646] Step 2: Validate and submit data

[0647] The terminal validates the data entered by the user, checking for missing information or improper formatting.

[0648] Input: Data entered by the user

[0649] Output: Validated data, if incomplete an error message is displayed to the user.

[0650] The terminal sends the verified data to the server.

[0651] Input: Validated Data

[0652] Output: The data is encrypted and sent to the server.

[0653] Step 3: Server receives data and creates profile

[0654] The server receives the data sent from the device and stores it in a database, creating a user profile.

[0655] Input: Validated Data

[0656] Output: The user profile is saved in the database.

[0657] Step 4: Generate plans and menus

[0658] The server uses the generative AI model to create prompts to generate a diet plan and exercise menu and sends them to the AI ​​model.

[0659] Input: User profile

[0660] Output: A prompt sentence is generated and sent to the AI ​​model.

[0661] The generative AI model generates an appropriate diet plan and exercise menu based on the prompt text and sends it back to the server.

[0662] Input: prompt statement

[0663] Output: The generated plan and exercise menu are sent back to the server.

[0664] Step 5: Save and serve your plans and menus

[0665] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[0666] Input: Generated plans and menus

[0667] Output: Saved in the specified format and sent to the device.

[0668] The terminal displays the received plans and menus to the user.

[0669] Input: Plans and menus saved in format

[0670] Output: What is displayed to the user in the application.

[0671] Step 6: Daily data entry and submission

[0672] Users enter their weight, diet, and exercise information into the application every day.

[0673] Input: Daily weight, diet, exercise

[0674] Output: Daily data is stored within the app and ready to be sent to your device.

[0675] The device sends daily data to the server.

[0676] Input: Daily data

[0677] Output: The data is sent to the server.

[0678] Step 7: Analyze progress data and receive real-time feedback

[0679] The server analyzes the daily data received and provides progress updates.

[0680] Input: Daily data

[0681] Output: Updated progress data is saved to the database.

[0682] The server generates a feedback message based on the progress data and sends it to the terminal.

[0683] Input: Progress data

[0684] Output: A feedback message is generated and sent to the terminal.

[0685] The terminal displays a feedback message to the user.

[0686] Input: Feedback message

[0687] Output: What is displayed to the user in the application.

[0688] Step 8: Graphical display of progress

[0689] The server generates and formats data to visually display the user's progress.

[0690] Input: Progress data

[0691] Output: Graphical data is generated.

[0692] The terminal displays the received data in the form of a graph to the user.

[0693] Input: Graph format data

[0694] Output: The output is displayed in an easy-to-understand visual format on the application.

[0695] (Application example 1)

[0696] 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."

[0697] In modern society, providing appropriate dietary plans and exercise menus based on individual health conditions and goals is an important issue. However, existing systems only generate plans based on user information, and few cover implementation and progress management, especially specific meal menus. In addition, they lack a function that allows users to easily order daily meals, making personalized health management difficult.

[0698] 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.

[0699] In this invention, the server includes means for a user to input their own information, means for receiving and processing the information, means for generating a dietary restriction plan and exercise menu based on the information, means for generating a meal menu based on the generated plan and menu using a generative AI model, means for allowing the user to select and order the generated meal menu, and means for saving the plan and menu in a format desired by the user. This allows the user to easily order a personalized meal menu based on their health information and receive real-time feedback on their progress.

[0700] The "means for inputting user information" is an interface for the user to input personal information such as age, sex, weight, target weight, and allergy information.

[0701] "Server that receives and processes information" refers to a computer system that centrally receives, analyzes, stores, and processes information entered by users.

[0702] The "means for generating a diet plan and exercise menu" refers to algorithms and processes for automatically generating a healthy diet plan and exercise menu based on user input information.

[0703] The "means for providing the generated plan and menu to the user" refers to an interface that provides the generated dietary restriction plan and exercise menu to the user in a visual or text format.

[0704] A "generative AI model" is an artificial intelligence model that generates appropriate meal menus based on user information and past data.

[0705] A "means for generating a meal menu" is a process and system that uses a generative AI model to automatically generate a meal menu based on a user's health information and goals.

[0706] The "means for enabling the user to select and order a meal menu" is an interface that displays the generated meal menu to the user, allows the user to select the meal they want from the menu, and confirms the order.

[0707] "Means for saving in a format desired by the user" is a function for saving the generated plan or menu in a format desired by the user, such as PDF, Excel, or Word.

[0708] The "means for inputting daily data" is an interface that allows the user to input data such as daily weight, dietary habits, and exercise habits.

[0709] "Means for receiving daily data and managing progress" refers to a system that receives daily data entered by the user and analyzes and manages the progress status.

[0710] The "means for adjusting the plan and providing feedback" is a function that adjusts the dietary restriction plan and exercise menu based on the user's progress data and provides the user with appropriate advice and feedback in real time.

[0711] The "means for managing order history and analyzing meal satisfaction data" is a system that stores the history of meal menus ordered by users and collects and analyzes user satisfaction data.

[0712] The "means for displaying in graph format" is a function for converting the user's progress and data into graph format and displaying it.

[0713] The "means for adjusting meal menus in real time" is a system that constantly optimizes the current meal menu based on the user's progress data and changes it as necessary.

[0714] MODE FOR CARRYING OUT THE INVENTION

[0715] As an embodiment of the present invention, a system is constructed as follows.

[0716] System Overview

[0717] The purpose of this system is to allow users to input their own health information and generate optimal dietary restriction plans and exercise menus based on that information.Furthermore, it provides a function to generate specific meal menus based on these plans and allow users to select and order.

[0718] Hardware Configuration

[0719] Server: Cloud-based server (e.g., Amazon Web Services, Google Cloud Platform)

[0720] Smartphone: iOS or Android compatible device

[0721] Software Configuration

[0722] Server side: Python (Framework: Flask)

[0723] Generative AI models: Python libraries (e.g., Scikit-learn, TensorFlow)

[0724] Client Side: React Native

[0725] Data Processing Procedures

[0726] 1. Entering and receiving user data

[0727] Users use a smartphone application to input their age, gender, current weight, target weight, allergy information, etc. The device verifies the input data and sends it to a cloud-based server.

[0728] 2. User Data Processing and Plan Generation

[0729] The server receives the information sent by the user and creates a user profile based on that data, analyzing data such as age, gender, weight, target weight, and allergy information, and then uses a generative AI model to generate an optimal diet plan and exercise menu.

[0730] 3. Generating and presenting a meal menu

[0731] The server automatically generates a meal menu using a generative AI model based on existing plans and menus. The generated menu is presented to the user via a smartphone application, and the user selects the desired menu and confirms their order.

[0732] 4. Daily progress input and management

[0733] Users enter their daily weight, diet, exercise, etc. into the application. The device sends this data to a cloud server, which analyzes it and manages the user's progress.

[0734] 5. Real-time advice and menu adjustments

[0735] The server adjusts the plan as needed and provides real-time feedback based on the user's progress, and also adjusts the meal menu in real time.

[0736] 6. Graphical progress display

[0737] The server generates data to display the user's progress in a graph format and provides this to the user via a smartphone application, allowing the user to visually grasp their progress.

[0738] Specific examples

[0739] Consider a case where a 30-year-old male user currently weighs 80 kg and creates a plan to bring his target weight down to 70 kg.

[0740] Users enter their age, gender, weight, target weight, and allergy information into the app.

[0741] Based on this data, the server generates a plan that sets a daily calorie intake of 1,600 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[0742] The generative AI model then generates a specific meal menu based on this (e.g., grilled chicken salad, whole wheat bread).

[0743] Users select and order from this menu on the app and receive their meal via food delivery.

[0744] Example prompt sentence:

[0745] Prompt: I'm 30 years old, my current weight is 80kg, and my goal weight is 70kg. I have no allergies. Please provide a healthy meal plan.

[0746] Example output: Breakfast: Oatmeal with fruit and unsweetened yogurt. Lunch: Grilled chicken with salad and whole wheat bread. Dinner: Steamed fish with stewing vegetables.

[0747] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0748] Step 1:

[0749] Entering and Receiving User Data

[0750] Users enter their age, gender, current weight, target weight, allergy information, etc. using a smartphone application.

[0751] The terminal validates the entered data and sends it to a cloud-based server in JSON format.

[0752] Input: Age, gender, current weight, target weight, allergy information

[0753] Output: Sending user data to the server

[0754] Step 2:

[0755] Processing of User Data

[0756] The server receives the information sent by the user and creates a user profile based on that data.

[0757] At this time, the data is formatted and saved.

[0758] Input: User data (age, gender, current weight, target weight, allergy information)

[0759] Output: Create and save user profile

[0760] Step 3:

[0761] Generate plans and exercise menus

[0762] The server uses a generative AI model to generate an optimal diet plan and exercise menu based on the user profile.

[0763] Specifically, the system calculates calorie intake and exercise frequency, taking into account the user's target weight and current weight.

[0764] Input: User profile

[0765] Output: Generated diet plan and exercise menu

[0766] Step 4:

[0767] Generate and present a meal menu

[0768] The server automatically generates meal menus using a generative AI model based on existing plans and menus.

[0769] The terminal displays the received data to the user through the application.

[0770] The user selects a menu item and confirms the order.

[0771] Input: Generated diet plan and exercise menu

[0772] Output: Meal menu presented to the user, order information

[0773] Step 5:

[0774] Daily progress input and management

[0775] Users input their daily weight, diet, exercise, etc. into the application.

[0776] The device sends this data to a cloud server.

[0777] The server analyzes the data and manages the user's progress.

[0778] Input: Daily weight, diet, exercise

[0779] Output: Progress management data

[0780] Step 6:

[0781] Real-time advice and menu adjustments

[0782] The server adjusts the plan as needed and provides real-time feedback based on the user's progress data.

[0783] Using generative AI models, new menus and exercise plans are generated and provided to users through the application.

[0784] Input: Progress management data

[0785] Output: Adjusted plan, real-time feedback

[0786] Step 7:

[0787] Progress display in graphical format

[0788] The server generates data to display the user's progress in a graph format and provides this to the user through a smartphone application.

[0789] Users can visually grasp their progress.

[0790] Input: Progress management data

[0791] Output: Progress data in graphical format

[0792] 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.

[0793] As an embodiment of the present invention, a system is constructed as follows.

[0794] System Overview

[0795] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. The generated data and progress information can also be saved in the format desired by the user.

[0796] Program processing

[0797] 1. User data entry

[0798] The user enters their age, gender, current weight, target weight, allergy information, and emotional data (e.g., self-reported or obtained through emotion recognition technology) into the application. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[0799] 2. Data Receipt and Processing

[0800] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[0801] 3. Creating a profile on the server

[0802] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[0803] 4. Analysis by Emotion Engine

[0804] The server analyzes the user's emotional data using an emotion engine, which evaluates the user's emotional state, such as whether the user is stressed or motivated.

[0805] 5. Create a diet plan and exercise menu

[0806] The server generates a diet plan and exercise menu based on the analysis results of the generative AI and emotion engine, according to the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress.

[0807] 6. Providing the generated plan

[0808] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[0809] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[0810] 7. Offering and Display of Offers

[0811] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[0812] 8. Daily progress input and emotional data collection

[0813] Users enter their weight, diet, exercise, and emotional state into the application every day, and the data is registered as daily data.

[0814] The terminal transmits the entered daily data to the server, which receives it and stores it in a database.

[0815] 9. Progress data analysis and management

[0816] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from their goal weight. It also analyzes emotional data to assess the user's emotional state.

[0817] 10. Real-time advice and plan adjustments

[0818] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling depressed, it generates encouraging messages and dietary and exercise advice to reduce stress. This feedback is provided in real time.

[0819] 11. Graphical display

[0820] The server generates data for displaying the user's progress and emotion data in a graph format.

[0821] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[0822] Specific examples

[0823] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. The user also reports that she feels stressed.

[0824] Users enter their age, gender, weight, goal weight, allergy information and emotional state into the app.

[0825] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also adds a meal menu suitable for stress relief.

[0826] The plan is saved in Excel format and provided to the user.

[0827] Users input their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[0828] The server generates a progress graph and emotion data as graphs, which are then visually displayed to the user on the device.

[0829] This series of steps allows users to track their progress and emotional state while efficiently reaching their goal weight, and the combined emotional engine provides more personalized plans and feedback.

[0830] The processing flow will be explained below.

[0831] Step 1:

[0832] The user starts the application and inputs their age, gender, current weight, target weight, allergy information, and emotional data (e.g., data obtained through a form to input their emotional state or through emotion recognition technology). The user enters this data and confirms it by pressing the submit button.

[0833] Step 2:

[0834] The device receives the data entered by the user and verifies whether the data is appropriate: specifically, whether the age is within a reasonable range, whether the gender is selected correctly, whether the weight and target weight are reasonable, and whether the emotional data is entered accurately. After verification, the device sends the data to the server.

[0835] Step 3:

[0836] The server receives the data sent from the device and creates a user profile, which includes age, gender, current weight, target weight, allergy information, and emotional state. The server stores this information in a database and updates the data as needed.

[0837] Step 4:

[0838] The server uses an emotion engine to analyze the user's emotional data. The emotion engine uses emotion analysis algorithms to analyze the emotional data entered by the user and sensor data to determine the user's emotional state, such as whether they are feeling stressed or highly motivated.

[0839] Step 5:

[0840] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress. On the other hand, if the user is highly motivated, it will recommend a slightly more strenuous exercise menu.

[0841] Step 6:

[0842] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume, making it easier to visually grasp the user's progress.

[0843] Step 7:

[0844] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[0845] Step 8:

[0846] The terminal receives the plan file sent from the server and presents it to the user, who can then download it and view it on their device.

[0847] Step 9:

[0848] Every day, users enter their weight, diet, exercise, and emotional state into the application, which then sends the data to the system as daily data.

[0849] Step 10:

[0850] The device sends daily data entered by the user to a server, including weight, food intake, exercise, emotional state, etc.

[0851] Step 11:

[0852] The server receives and analyzes daily data, evaluating weight fluctuations, calorie intake, and activity levels to determine whether the user is approaching their weight goal and how their emotional state is evolving.

[0853] Step 12:

[0854] The server updates the progress based on the analysis of the daily data, which means adding the latest information to the user profile.

[0855] Step 13:

[0856] The server reevaluates the plan based on the user's progress and emotional data and makes adjustments as needed. For example, if the user is feeling emotionally down, it may provide encouraging messages or advice to help relieve stress.

[0857] Step 14:

[0858] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[0859] Step 15:

[0860] The device receives the feedback and updates sent by the server and presents them to the user, who then takes the next step.

[0861] As a concrete example, consider a 30-year-old female user who wants to lose weight from 70 kg to 60 kg, and who reports feeling stressed.

[0862] The user inputs their age, gender, current weight, goal weight, allergy information, and emotional state.

[0863] The server generates a plan that sets a daily calorie intake of 1500 kcal and recommends five exercise sessions per week. Because the user is under stress, it recommends foods that are effective in relieving stress and light exercise.

[0864] The plan is saved in Excel format and provided to the user.

[0865] Users input their daily weight, diet, exercise and emotional state, and the server analyzes this and updates their progress.

[0866] The server generates a progress graph and emotion data, which the device visually displays to the user.

[0867] In this way, the system takes into account the user's emotional state and provides more personalized guidance and feedback to support dieting success.

[0868] Example 2

[0869] 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."

[0870] Conventional health management systems only provide fixed dietary restriction plans and exercise menus based on basic information entered by users, making it difficult to provide dynamic feedback that corresponds to the user's emotional state or daily progress.In addition, there was a lack of a way for users to easily understand plans and progress data visually, which resulted in a tendency for users to find it difficult to maintain motivation.

[0871] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing emotional data and adjusting the plan and menu, a means for providing feedback in real time, and a means for visually displaying the emotional data and progress data. This not only enables dynamic feedback according to the user's emotional state and daily progress, but also makes it easier to maintain the user's motivation by providing the feedback in a visually easy-to-understand format.

[0872] A "user" is an individual who utilizes the system to input their own health care data and receive feedback.

[0873] "Information" refers to all data input by the user, including age, sex, current weight, target weight, allergy information, and emotional data.

[0874] "Computer" refers to the entire device or system that receives, processes, and stores information entered by a user in a database.

[0875] "Means for generating" refers to a process or algorithm that generates a diet plan and exercise menu based on input information.

[0876] "Means for providing" refers to a method or system for presenting the generated diet plan and exercise menu to the user.

[0877] "Means for saving" refers to a function or process for saving the generated plans and menus in a format desired by the user.

[0878] "Emotion data" is data that reflects the user's emotional state, including stress, motivation, and the like.

[0879] "Means for analyzing" refers to a function or algorithm that processes emotional data to assess the user's emotional state.

[0880] "Means for adjusting" refers to a function or process that modifies plans and menus based on the user's emotional state and progress data.

[0881] "Means for providing feedback" refers to a function or system that provides appropriate advice or information to users in real time.

[0882] "Graphical format" refers to a format used to visualize data, such as a line graph, bar graph, or pie chart.

[0883] "Progress Data" refers to data regarding a user's daily weight, diet, exercise, and emotional state.

[0884] "Visual display means" refers to a function or system that displays data in a form such as a graph so that the user can easily understand the information.

[0885] This invention is a system that generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. In addition, the generated data and progress information can be saved in the format desired by the user.

[0886] System Overview

[0887] The system begins with the user entering their age, gender, current weight, goal weight, allergy information, and emotional data. The entered data is sent to the server via the device. The server creates a user profile based on the received data and uses a generative AI model and emotional engine to generate a dietary restriction plan and exercise menu tailored to each individual user. The generated plan is saved in the user's desired format and provided via the device.

[0888] When users enter their daily progress data (weight, diet, exercise, emotional state), this data is sent back to the server, where it is analyzed and the plan is adjusted as needed. Furthermore, the analysis results are fed back to the user in real time, allowing them to easily visualize their progress in the form of statistical data and graphs.

[0889] Hardware and software used

[0890] Terminal: A device on which a user inputs data and receives data from a server. This includes smartphones, tablets, and PCs.

[0891] Server: A central computer system that receives data, creates profiles, analyzes them, generates plans, and provides feedback. It is where the generative AI models and emotion engines run.

[0892] The generative AI model includes an algorithm to suggest optimal diet and exercise plans based on the user's basic information and emotional data, while the emotional engine analyzes the user's emotional data and provides information necessary to adjust the plan.

[0893] Specific examples

[0894] For example, a 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. This user reports that she feels stressed.

[0895] 1. The user enters their age, gender, weight, target weight, allergy information, and emotional state into the application's input form.

[0896] 2. Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also suggests additional meal menus suitable for stress relief.

[0897] 3. The plan is saved in Excel format and provided to the user, who can view it on their device.

[0898] 4. Users enter their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[0899] 5. The server generates a progress graph and emotion data, which are then visually displayed on the device.

[0900] Example prompt sentence:

[0901] "A 30-year-old woman currently weighs 70 kg and has a goal weight of 60 kg. She reports feeling stressed. Based on these conditions, please suggest a balanced diet plan and a five-day weekly exercise routine."

[0902] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0903] Step 1: User Data Entry

[0904] The user enters age, gender, current weight, target weight, allergy information, and emotional data into the application's input form. The entered data is confirmed when the user presses the send button. This data is sent to the terminal as input information (age, gender, current weight, target weight, allergy information, emotional data).

[0905] Step 2: Receiving and processing data

[0906] The terminal receives the data entered by the user. At this stage, the terminal checks the integrity of the data, for example, whether the age is within a reasonable range and whether the numerical data is in the correct format. After verification, the terminal sends the appropriate data to the server. The sent data becomes information for creating a user profile.

[0907] Step 3: Create a profile on the server

[0908] The server receives the data sent from the device and creates a user profile based on this data. The profile includes age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[0909] Step 4: Analysis by Emotion Engine

[0910] The server uses an emotion engine to analyze the user's emotion data. For example, it evaluates the user's emotional state, such as whether they are feeling stressed or highly motivated. The analysis results are added to the user profile and used to generate the next plan. The input is emotion data, and the output is the analysis results of the emotion engine.

[0911] Step 5: Create a diet plan and exercise menu

[0912] The server generates a dietary restriction plan and exercise menu based on the analysis results of the generative AI model and emotion engine according to the user profile. For example, if the user is feeling stressed, it will suggest meals and light exercise menus that are effective in relieving stress. The input is the user profile and the analysis results of the emotion engine, and the output is a dietary restriction plan and exercise menu.

[0913] Step 6: Serving the generated plan

[0914] The server compiles the generated diet plan and exercise menu in text and graph format. The generated plan is saved in the user's desired format (e.g., Word, Excel, PPT, PDF) and sent to the device. The input is the generated plan and menu, and the output is the saved file.

[0915] Step 7: Offer and display your plan

[0916] The terminal receives the plan file sent from the server. The user can download this file and view it on their device. The input is the plan file from the server, and the output is the presentation to the user.

[0917] Step 8: Daily progress input and emotional data collection

[0918] Every day, users input their weight, diet, exercise, and emotional state into the application. This data is registered as daily data. The input data is sent to the server via the device, and the server stores it in a database. The input is daily progress data, and the output is the stored daily data.

[0919] Step 9: Analyze and manage progress data

[0920] The server analyzes the data entered daily and updates the user's progress. This analysis evaluates how close or far the user is from reaching their goal weight. Emotional data is also analyzed to evaluate the user's emotional state. The input is daily progress data and emotional data, and the output is the progress analysis results.

[0921] Step 10: Real-time advice and plan adjustments

[0922] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling emotionally down, it generates encouraging messages and diet and exercise advice to reduce stress. This feedback is provided in real time. The input is progress and emotional data, and the output is the adjusted plan and feedback.

[0923] Step 11: Display in graphical format

[0924] The server generates data to display the user's progress and emotional data in a graph format, allowing the user to visually grasp their own progress and emotional state. The device receives this data and displays it in a form that is easy for the user to understand visually. The input is the generated graph data, and the output is the visual display.

[0925] (Application example 2)

[0926] 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."

[0927] Traditional health management systems only provide basic dietary and exercise plans based on user input, but they lack the ability to adjust plans to take into account the user's emotional state or provide real-time feedback. This can lead to a decrease in user motivation and an increase in stress, making it difficult to achieve goals. They also lack tools for visualizing progress.

[0928] 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 analyzing the user's emotional data using emotion recognition technology, means for adjusting the diet plan and exercise menu based on the user's emotional state, and means for generating data for visually displaying daily progress and emotional state. This makes it possible to provide an individualized plan according to the user's emotional state and provide real-time feedback.

[0929] "Means for users to input their own information" refers to a device or system that provides an interface for users to input information such as age, sex, current weight, target weight, allergy information, and emotional data.

[0930] The "server that receives and processes the information" refers to a server system that receives information entered by users and analyzes, stores, and processes that information.

[0931] The "means for generating a dietary restriction plan and exercise menu" refers to an algorithm or program for automatically generating an appropriate dietary restriction plan and exercise menu based on input user information.

[0932] "Means for providing the generated plan and menu to the user" refers to means for presenting the generated dietary restriction plan and exercise menu to the user, including providing them in text format or graphical format.

[0933] "Means for saving in a format desired by the user" refers to a function for saving the generated plan or menu in a file format (e.g., Word, Excel, PDF) specified by the user.

[0934] "Means for analyzing user emotional data using emotion recognition technology" refers to technology for identifying and analyzing a user's current emotional state using the user's input data and biometric data.

[0935] "Means for adjusting dietary plans and exercise menus based on the user's emotional state" refers to means for individually adjusting and optimizing existing plans and menus by taking into account the user's emotional state.

[0936] "Means for generating data for visually displaying daily progress and emotional state" refers to means for converting a user's progress data and emotional data into a visual format such as a graph, and providing it to the user in a way that is easy to understand.

[0937] MODE FOR CARRYING OUT THE INVENTION

[0938] DETAILED DESCRIPTION OF THE INVENTION The following describes an embodiment of the present invention.

[0939] System Overview

[0940] This system allows users to input their personal information and generates a balanced diet plan and exercise menu based on that information, and further adjusts the plan in real time according to the user's emotional state. It also allows users to visually grasp their daily progress and emotional data, providing personalized health management support.

[0941] Program Implementation

[0942] The system uses the following key tools and technologies:

[0943] User information input interface

[0944] Central Server

[0945] emotion recognition technology

[0946] Meal restriction plan generation algorithm

[0947] Exercise menu generation algorithm

[0948] Data Visualization Techniques

[0949] Specific examples

[0950] The user inputs their age, gender, weight, target weight, allergy information, and emotional data into the health management app. The central server receives this information and analyzes the user's emotional state using emotion recognition technology. Based on this information, an individualized plan is generated using a dietary restriction plan generation algorithm and an exercise menu generation algorithm. The generated plan and menu are saved in the user's desired format and displayed visually.

[0951] Step-by-step process overview

[0952] User Data Entry

[0953] The user inputs age, gender, weight, target weight, allergy information, and emotional data into the application. This data is sent to the server through the application's input form.

[0954] Data reception and processing

[0955] The server receives the input data, verifies it, and then stores it. In particular, emotional data is analyzed using emotion recognition technology.

[0956] Plan Generation

[0957] The server generates a diet plan and exercise menu based on the user's profile and the results of emotion analysis. A generative AI model is used to generate an appropriate plan.

[0958] Plan delivery and visualization

[0959] The generated diet plan and exercise menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and provided to the user. The user's progress and emotional data are also displayed in a visually easy-to-understand format.

[0960] The specific hardware and software used

[0961] Hardware

[0962] Central server: Stores data and performs calculations.

[0963] Client terminal: A device (PC, smartphone, tablet, etc.) through which a user enters data.

[0964] software

[0965] Emotion recognition technology: Analyzes user emotion data.

[0966] Diet Plan Generation Algorithm: Generates a meal plan based on input data.

[0967] Exercise menu generation algorithm: Generate an exercise menu.

[0968] Data visualization tools: Visually display user progress data.

[0969] Prompt Sentence Examples

[0970] markdown

[0971] Prompt for employee wellness app:

[0972] Enter the user profile:

[0973] Age: 30

[0974] Gender: Female

[0975] Current weight: 70kg

[0976] Target weight: 60kg

[0977] Allergy Information: Nuts

[0978] Emotional state: Stress

[0979] Example of a generated meal plan:

[0980] Breakfast: Oatmeal and fruit

[0981] Lunch: Grilled chicken salad

[0982] Dinner: Salmon and vegetables

[0983] An example of a generated exercise menu:

[0984] Light stretching

[0985] 30 minutes of walking every day

[0986] Three yoga sessions per week

[0987] conclusion

[0988] This allows users to obtain a personalized health management plan based on their own information, and effectively manage their health through real-time adjustments and visualizations according to their emotional state, while also solving the problems faced by traditional health management systems.

[0989] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0990] Processing Steps

[0991] Step 1: User Data Entry

[0992] The user inputs information such as age, sex, weight, target weight, allergy information, emotional data, etc. through the input interface. After completing the input, the user presses the send button to confirm the data and send it from the terminal to the server.

[0993] Input: Age, gender, weight, target weight, allergy information, emotional data

[0994] Output: User information data sent to the server

[0995] Step 2: Data reception and verification

[0996] The server receives the user information sent from the terminal and then verifies whether the format of the received data is correct and within a reasonable range.

[0997] Input: User information data sent from the device

[0998] Output: Validated user information data, error message (if invalid data)

[0999] Step 3: Create a profile

[1000] The server creates a user profile based on the verified user information and stores it in a database.

[1001] Input: Verified user information data

[1002] Output: User profile stored in the database

[1003] Step 4: Analyze the sentiment data

[1004] The server analyzes the user's emotional data using emotion recognition technology. An emotion engine processes the data and identifies the user's emotional state (e.g., stress, motivation).

[1005] Input: User emotion data

[1006] Output: Parsed emotional state

[1007] Step 5: Create a diet plan and exercise menu

[1008] The server generates a plan based on the user's profile and emotional state using a diet plan generation algorithm and an exercise menu generation algorithm. The generative AI model proposes the optimal plan for each user.

[1009] Input: User profile, analyzed emotional state

[1010] Output: Generated diet plan and exercise menu

[1011] Step 6: Save and serve your plan

[1012] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[1013] Input: Generated diet plan and exercise menu, user's desired format

[1014] Output: Plan file saved in desired format

[1015] Step 7: View your plan

[1016] The terminal receives the plan file sent from the server and proposes it to the user, who can visually confirm it.

[1017] Input: Plan file sent from the server

[1018] Output: Plans and menus displayed to the user

[1019] Step 8: Collect daily progress and sentiment data

[1020] Every day, users enter their weight, diet, exercise, emotional data, etc. into the application and send that data to the server.

[1021] Input: Daily weight, diet, exercise, emotional data

[1022] Output: Daily progress data stored on the server

[1023] Step 9: Analyze progress data

[1024] The server analyzes the daily progress data, evaluates the user's progress and emotional state, and updates the database.

[1025] Input: Daily progress data, emotional data

[1026] Output: Parsed progress, updated user profile

[1027] Step 10: Real-time feedback and plan adjustments

[1028] Based on the analyzed progress and emotional state, the server adjusts the plan as needed and provides real-time feedback, generating encouraging messages or new advice depending on the user's emotional state.

[1029] Input: Parsed progress, emotional state

[1030] Output: Real-time feedback, tailored plans and advice

[1031] Step 11: Visualize the data

[1032] The server generates graph data for visually displaying the user's progress data and emotion data, and transmits it to the device, which receives it and visually displays it to the user.

[1033] Input: Progress data, emotion data

[1034] Output: visualized graph data, graph displayed to user

[1035] In this way, the system helps users manage their health and provides personalized plans tailored to their emotional state.

[1036] 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.

[1037] 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.

[1038] 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.

[1039] [Third embodiment]

[1040] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1041] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1042] 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).

[1043] 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.

[1044] 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.

[1045] 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).

[1046] 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.

[1047] 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.

[1048] 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.

[1049] 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.

[1050] 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.

[1051] 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."

[1052] As an embodiment of the present invention, a system is constructed as follows.

[1053] System Overview

[1054] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides real-time feedback. The generated data and progress information can also be saved in the user's preferred format.

[1055] Program processing

[1056] 1. User data entry

[1057] The user enters information such as age, gender, current weight, target weight, and allergy information into the application.

[1058] The terminal verifies the entered data and transmits it to the server.

[1059] 2. Data Receipt and Processing

[1060] The server receives the data sent by the user.

[1061] The server creates a user profile based on the received data.

[1062] 3. Create a diet plan and exercise menu

[1063] The server uses AI to generate a diet plan and exercise menu, taking into account the user's current weight, target weight, age, gender, and other factors to derive the optimal plan.

[1064] Example: If a user weighs 70kg and aims to lose 60kg, a plan will be generated that limits daily calorie intake to 1500kcal and recommends exercising five days a week.

[1065] 4. Providing the generated plan

[1066] The server compiles the generated diet plan and exercise menu in text and graph format.

[1067] The server saves this in the user's desired format (Word, Excel, PPT, PDF, etc.).

[1068] The terminal receives this data and displays it to the user.

[1069] 5. Daily progress input and management

[1070] Users enter their weight, diet, and exercise information into the application every day.

[1071] The terminal transmits the input data to the server.

[1072] The server analyzes the data daily and updates the progress.

[1073] 6. Real-time advice and plan adjustments

[1074] The server adjusts the plan as needed based on the user's progress and provides real-time feedback.

[1075] Example: If a user loses 1kg in a week, provide a message saying "You're making good progress! Keep it up!"

[1076] 7. Graphical display

[1077] The server generates data to display the user's progress in a graphical format.

[1078] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[1079] Specific examples

[1080] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg.

[1081] Users enter their age, gender, weight, target weight, and allergy information into the app.

[1082] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[1083] The plan is saved in Excel format and provided to the user.

[1084] Users input their daily weight and dietary information, and the server analyzes it and updates their progress.

[1085] The server generates a progress graph, which the terminal visually displays to the user.

[1086] In this way, the user can efficiently reach their target weight while checking their progress.

[1087] The processing flow will be explained below.

[1088] Step 1:

[1089] The user starts the application and enters personal data such as age, sex, current weight, target weight, allergy information, etc. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[1090] Step 2:

[1091] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[1092] Step 3:

[1093] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, and allergy information. The server stores this information in a database.

[1094] Step 4:

[1095] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile. For example, the generation process will design a calorie restriction and appropriate exercise menu to bring a 70kg user down to 60kg.

[1096] Step 5:

[1097] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[1098] Step 6:

[1099] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[1100] Step 7:

[1101] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[1102] Step 8:

[1103] Users enter their daily weight, diet, and exercise information into the application, which is then registered as daily data.

[1104] Step 9:

[1105] The terminal transmits the daily data entered by the user to the server, which receives it and stores it in a database.

[1106] Step 10:

[1107] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from reaching their goal weight.

[1108] Step 11:

[1109] The server adjusts the plan as needed based on the user's progress, for example generating advice to reset calorie levels or increase exercise if weight loss is slower than expected.

[1110] Step 12:

[1111] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[1112] Step 13:

[1113] The device receives the updates and feedback sent by the server and presents them to the user, who then takes the next step.

[1114] This series of steps helps users effectively diet, and the system provides ongoing progress monitoring and feedback.

[1115] Example 1

[1116] 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."

[1117] Previously, it was difficult for users to find appropriate diet plans and exercise menus based on their individual health conditions and goals. Additionally, there was a lack of systems that track daily progress and provide real-time feedback. Furthermore, there were limited ways to provide users with a visual understanding of their progress, making it difficult to support long-term goal achievement.

[1118] 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.

[1119] In this invention, the server includes a means for generating a diet plan and exercise menu using a generative AI model, a means for analyzing the user's daily data, updating the user's progress, and providing real-time feedback, and a means for generating data displaying the user's progress in a graphical format and providing the data to the user. This allows the user to obtain a customized diet plan and exercise menu based on their individual health condition and goals, allowing them to efficiently achieve their goals while managing their daily progress. Furthermore, providing progress in a format that is easy to understand visually can help the user maintain ongoing motivation.

[1120] "User information" refers to personal information such as age, sex, weight, target weight, and allergy information entered by the user.

[1121] A "terminal" is a device used by a user to enter information or view stored data, and includes smartphones, tablets, and personal computers with dedicated applications installed.

[1122] The "server" is a back-end system that receives and processes user information, generates diet plans and exercise menus, and provides them to users.

[1123] A "generative AI model" is an artificial intelligence model that generates appropriate diet plans and exercise menus based on input prompts.

[1124] A "prompt" is a textual instruction entered into a generative AI model, containing specific conditions and requirements.

[1125] A "dietary restriction plan" is a plan that includes recommended daily calorie intake and meal contents to achieve the user's health goals.

[1126] An "exercise menu" is a plan that includes the type and frequency of exercise recommended to achieve the user's health goals.

[1127] The "format" refers to the data format in which the diet plan or exercise menu is provided to the user, and examples include Word, Excel, PDF, etc.

[1128] "Progress data" refers to data such as weight, dietary details, and exercise details that are input by the user on a daily basis, and indicates the progress of the user in achieving their goals.

[1129] "Feedback" refers to advice and encouraging messages provided by the server based on analysis of the user's progress data.

[1130] "Graph-format data" refers to data such as line graphs and bar graphs that are generated to visually display the user's progress.

[1131] As an embodiment of the present invention, the following system is constructed. The system is designed to enable users to obtain a customized diet plan and exercise menu based on their individual health condition and goals. The user inputs daily data, and the system manages the progress in real time and provides feedback as needed. The system also displays the data in a graph format so that the user can visually grasp the progress toward achieving their goals.

[1132] System Overview and Configuration

[1133] Users install a dedicated application on their devices, such as smartphones, tablets, or PCs, to input data. The information entered by the user is verified by the device and securely sent to a server. The server processes the received information and generates a diet plan or exercise menu using a generative AI model (e.g., OpenAI's GPT-3.5).

[1134] The generated plan and menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and sent to the device. The user enters their daily weight, diet, and exercise details, and this data is sent to the server via the device. The server analyzes the progress data, adjusts the plan as needed, and provides feedback in real time. In addition, the server generates data that displays the user's progress in graph form and sends it to the device, allowing the user to check their progress in a format that is easy to understand visually.

[1135] Hardware and software used

[1136] 1. Devices: smartphones, tablets, computers

[1137] 2. Dedicated application: An application for users to enter data.

[1138] 3. Server: The back-end system that receives and processes data and generates plans using generative AI models.

[1139] 4. Generative AI models: Artificial intelligence models such as OpenAI's GPT-3.5

[1140] Specific examples

[1141] To illustrate each processing step, consider a scenario in which a 30-year-old female user wants to lose weight from 70 kg to a target weight of 60 kg. The user enters her age, gender, weight, target weight, and allergy information into the application. The device verifies this data and sends it to the server. The server uses the generated AI model to generate a plan that sets a daily calorie intake of 1500 kcal and includes five exercise sessions per week (strength training and aerobic exercise).

[1142] The generated plan is saved in the user's desired format (e.g., Excel format) and sent to the user's device. The user enters their daily weight, dietary habits, and exercise habits into the application, and this data is sent to the server. The server analyzes the progress data and provides real-time feedback, such as "You're making good progress. Keep it up!" The server also generates data that displays the progress in graph form, which the device displays to the user.

[1143] Prompt Sentence Examples

[1144] "Generate the optimal diet and exercise plan for a 30-year-old female user to lose weight from 70 kg to a target weight of 60 kg. The daily calorie intake should be set to 1500 kcal, and the user should exercise (strength training and aerobic exercise) five times a week."

[1145] By inputting this prompt into a generative AI model, a specific plan is generated.

[1146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1147] Step 1: Enter user data

[1148] The user launches a dedicated application and enters information such as age, gender, current weight, target weight, and allergy information.

[1149] Input: Age, gender, weight, target weight, allergy information

[1150] Output: User data is stored within the app and ready to be sent to the device.

[1151] Step 2: Validate and submit data

[1152] The terminal validates the data entered by the user, checking for missing information or improper formatting.

[1153] Input: Data entered by the user

[1154] Output: Validated data, if incomplete an error message is displayed to the user.

[1155] The terminal sends the verified data to the server.

[1156] Input: Validated Data

[1157] Output: The data is encrypted and sent to the server.

[1158] Step 3: Server receives data and creates profile

[1159] The server receives the data sent from the device and stores it in a database, creating a user profile.

[1160] Input: Validated Data

[1161] Output: The user profile is saved in the database.

[1162] Step 4: Generate plans and menus

[1163] The server uses the generative AI model to create prompts to generate a diet plan and exercise menu and sends them to the AI ​​model.

[1164] Input: User profile

[1165] Output: A prompt sentence is generated and sent to the AI ​​model.

[1166] The generative AI model generates an appropriate diet plan and exercise menu based on the prompt text and sends it back to the server.

[1167] Input: prompt statement

[1168] Output: The generated plan and exercise menu are sent back to the server.

[1169] Step 5: Save and serve your plans and menus

[1170] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[1171] Input: Generated plans and menus

[1172] Output: Saved in the specified format and sent to the device.

[1173] The terminal displays the received plans and menus to the user.

[1174] Input: Plans and menus saved in format

[1175] Output: What is displayed to the user in the application.

[1176] Step 6: Daily data entry and submission

[1177] Users enter their weight, diet, and exercise information into the application every day.

[1178] Input: Daily weight, diet, exercise

[1179] Output: Daily data is stored within the app and ready to be sent to your device.

[1180] The device sends daily data to the server.

[1181] Input: Daily data

[1182] Output: The data is sent to the server.

[1183] Step 7: Analyze progress data and receive real-time feedback

[1184] The server analyzes the daily data received and provides progress updates.

[1185] Input: Daily data

[1186] Output: Updated progress data is saved to the database.

[1187] The server generates a feedback message based on the progress data and sends it to the terminal.

[1188] Input: Progress data

[1189] Output: A feedback message is generated and sent to the terminal.

[1190] The terminal displays a feedback message to the user.

[1191] Input: Feedback message

[1192] Output: What is displayed to the user in the application.

[1193] Step 8: Graphical display of progress

[1194] The server generates and formats data to visually display the user's progress.

[1195] Input: Progress data

[1196] Output: Graphical data is generated.

[1197] The terminal displays the received data in the form of a graph to the user.

[1198] Input: Graph format data

[1199] Output: The output is displayed in an easy-to-understand visual format on the application.

[1200] (Application example 1)

[1201] 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."

[1202] In modern society, providing appropriate dietary plans and exercise menus based on individual health conditions and goals is an important issue. However, existing systems only generate plans based on user information, and few cover implementation and progress management, especially specific meal menus. In addition, they lack a function that allows users to easily order daily meals, making personalized health management difficult.

[1203] 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.

[1204] In this invention, the server includes means for a user to input their own information, means for receiving and processing the information, means for generating a dietary restriction plan and exercise menu based on the information, means for generating a meal menu based on the generated plan and menu using a generative AI model, means for allowing the user to select and order the generated meal menu, and means for saving the plan and menu in a format desired by the user. This allows the user to easily order a personalized meal menu based on their health information and receive real-time feedback on their progress.

[1205] The "means for inputting user information" is an interface for the user to input personal information such as age, sex, weight, target weight, and allergy information.

[1206] "Server that receives and processes information" refers to a computer system that centrally receives, analyzes, stores, and processes information entered by users.

[1207] The "means for generating a diet plan and exercise menu" refers to algorithms and processes for automatically generating a healthy diet plan and exercise menu based on user input information.

[1208] The "means for providing the generated plan and menu to the user" refers to an interface that provides the generated dietary restriction plan and exercise menu to the user in a visual or text format.

[1209] A "generative AI model" is an artificial intelligence model that generates appropriate meal menus based on user information and past data.

[1210] A "means for generating a meal menu" is a process and system that uses a generative AI model to automatically generate a meal menu based on a user's health information and goals.

[1211] The "means for enabling the user to select and order a meal menu" is an interface that displays the generated meal menu to the user, allows the user to select the meal they want from the menu, and confirms the order.

[1212] "Means for saving in a format desired by the user" is a function for saving the generated plan or menu in a format desired by the user, such as PDF, Excel, or Word.

[1213] The "means for inputting daily data" is an interface that allows the user to input data such as daily weight, dietary habits, and exercise habits.

[1214] "Means for receiving daily data and managing progress" refers to a system that receives daily data entered by the user and analyzes and manages the progress status.

[1215] The "means for adjusting the plan and providing feedback" is a function that adjusts the dietary restriction plan and exercise menu based on the user's progress data and provides the user with appropriate advice and feedback in real time.

[1216] The "means for managing order history and analyzing meal satisfaction data" is a system that stores the history of meal menus ordered by users and collects and analyzes user satisfaction data.

[1217] The "means for displaying in graph format" is a function for converting the user's progress and data into graph format and displaying it.

[1218] The "means for adjusting meal menus in real time" is a system that constantly optimizes the current meal menu based on the user's progress data and changes it as necessary.

[1219] MODE FOR CARRYING OUT THE INVENTION

[1220] As an embodiment of the present invention, a system is constructed as follows.

[1221] System Overview

[1222] The purpose of this system is to allow users to input their own health information and generate optimal dietary restriction plans and exercise menus based on that information.Furthermore, it provides a function to generate specific meal menus based on these plans and allow users to select and order.

[1223] Hardware Configuration

[1224] Server: Cloud-based server (e.g., Amazon Web Services, Google Cloud Platform)

[1225] Smartphone: iOS or Android compatible device

[1226] Software Configuration

[1227] Server side: Python (Framework: Flask)

[1228] Generative AI models: Python libraries (e.g., Scikit-learn, TensorFlow)

[1229] Client Side: React Native

[1230] Data Processing Procedures

[1231] 1. Entering and receiving user data

[1232] Users use a smartphone application to input their age, gender, current weight, target weight, allergy information, etc. The device verifies the input data and sends it to a cloud-based server.

[1233] 2. User Data Processing and Plan Generation

[1234] The server receives the information sent by the user and creates a user profile based on that data, analyzing data such as age, gender, weight, target weight, and allergy information, and then uses a generative AI model to generate an optimal diet plan and exercise menu.

[1235] 3. Generating and presenting a meal menu

[1236] The server automatically generates a meal menu using a generative AI model based on existing plans and menus. The generated menu is presented to the user via a smartphone application, and the user selects the desired menu and confirms their order.

[1237] 4. Daily progress input and management

[1238] Users enter their daily weight, diet, exercise, etc. into the application. The device sends this data to a cloud server, which analyzes it and manages the user's progress.

[1239] 5. Real-time advice and menu adjustments

[1240] The server adjusts the plan as needed and provides real-time feedback based on the user's progress, and also adjusts the meal menu in real time.

[1241] 6. Graphical progress display

[1242] The server generates data to display the user's progress in a graph format and provides this to the user via a smartphone application, allowing the user to visually grasp their progress.

[1243] Specific examples

[1244] Consider a case where a 30-year-old male user currently weighs 80 kg and creates a plan to bring his target weight down to 70 kg.

[1245] Users enter their age, gender, weight, target weight, and allergy information into the app.

[1246] Based on this data, the server generates a plan that sets a daily calorie intake of 1,600 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[1247] The generative AI model then generates a specific meal menu based on this (e.g., grilled chicken salad, whole wheat bread).

[1248] Users select and order from this menu on the app and receive their meal via food delivery.

[1249] Example prompt sentence:

[1250] Prompt: I'm 30 years old, my current weight is 80kg, and my goal weight is 70kg. I have no allergies. Please provide a healthy meal plan.

[1251] Example output: Breakfast: Oatmeal with fruit and unsweetened yogurt. Lunch: Grilled chicken with salad and whole wheat bread. Dinner: Steamed fish with stewing vegetables.

[1252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1253] Step 1:

[1254] Entering and Receiving User Data

[1255] Users enter their age, gender, current weight, target weight, allergy information, etc. using a smartphone application.

[1256] The terminal validates the entered data and sends it to a cloud-based server in JSON format.

[1257] Input: Age, gender, current weight, target weight, allergy information

[1258] Output: Sending user data to the server

[1259] Step 2:

[1260] Processing of User Data

[1261] The server receives the information sent by the user and creates a user profile based on that data.

[1262] At this time, the data is formatted and saved.

[1263] Input: User data (age, gender, current weight, target weight, allergy information)

[1264] Output: Create and save user profile

[1265] Step 3:

[1266] Generate plans and exercise menus

[1267] The server uses a generative AI model to generate an optimal diet plan and exercise menu based on the user profile.

[1268] Specifically, the system calculates calorie intake and exercise frequency, taking into account the user's target weight and current weight.

[1269] Input: User profile

[1270] Output: Generated diet plan and exercise menu

[1271] Step 4:

[1272] Generate and present a meal menu

[1273] The server automatically generates meal menus using a generative AI model based on existing plans and menus.

[1274] The terminal displays the received data to the user through the application.

[1275] The user selects a menu item and confirms the order.

[1276] Input: Generated diet plan and exercise menu

[1277] Output: Meal menu presented to the user, order information

[1278] Step 5:

[1279] Daily progress input and management

[1280] Users input their daily weight, diet, exercise, etc. into the application.

[1281] The device sends this data to a cloud server.

[1282] The server analyzes the data and manages the user's progress.

[1283] Input: Daily weight, diet, exercise

[1284] Output: Progress management data

[1285] Step 6:

[1286] Real-time advice and menu adjustments

[1287] The server adjusts the plan as needed and provides real-time feedback based on the user's progress data.

[1288] Using generative AI models, new menus and exercise plans are generated and provided to users through the application.

[1289] Input: Progress management data

[1290] Output: Adjusted plan, real-time feedback

[1291] Step 7:

[1292] Progress display in graphical format

[1293] The server generates data to display the user's progress in a graph format and provides this to the user through a smartphone application.

[1294] Users can visually grasp their progress.

[1295] Input: Progress management data

[1296] Output: Progress data in graphical format

[1297] 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.

[1298] As an embodiment of the present invention, a system is constructed as follows.

[1299] System Overview

[1300] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. The generated data and progress information can also be saved in the format desired by the user.

[1301] Program processing

[1302] 1. User data entry

[1303] The user enters their age, gender, current weight, target weight, allergy information, and emotional data (e.g., self-reported or obtained through emotion recognition technology) into the application. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[1304] 2. Data Receipt and Processing

[1305] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[1306] 3. Creating a profile on the server

[1307] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[1308] 4. Analysis by Emotion Engine

[1309] The server analyzes the user's emotional data using an emotion engine, which evaluates the user's emotional state, such as whether the user is stressed or motivated.

[1310] 5. Create a diet plan and exercise menu

[1311] The server generates a diet plan and exercise menu based on the analysis results of the generative AI and emotion engine, according to the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress.

[1312] 6. Providing the generated plan

[1313] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[1314] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[1315] 7. Offering and Display of Offers

[1316] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[1317] 8. Daily progress input and emotional data collection

[1318] Users enter their weight, diet, exercise, and emotional state into the application every day, and the data is registered as daily data.

[1319] The terminal transmits the entered daily data to the server, which receives it and stores it in a database.

[1320] 9. Progress data analysis and management

[1321] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from their goal weight. It also analyzes emotional data to assess the user's emotional state.

[1322] 10. Real-time advice and plan adjustments

[1323] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling depressed, it generates encouraging messages and dietary and exercise advice to reduce stress. This feedback is provided in real time.

[1324] 11. Graphical display

[1325] The server generates data for displaying the user's progress and emotion data in a graph format.

[1326] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[1327] Specific examples

[1328] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. The user also reports that she feels stressed.

[1329] Users enter their age, gender, weight, goal weight, allergy information and emotional state into the app.

[1330] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also adds a meal menu suitable for stress relief.

[1331] The plan is saved in Excel format and provided to the user.

[1332] Users input their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[1333] The server generates a progress graph and emotion data as graphs, which are then visually displayed to the user on the device.

[1334] This series of steps allows users to track their progress and emotional state while efficiently reaching their goal weight, and the combined emotional engine provides more personalized plans and feedback.

[1335] The processing flow will be explained below.

[1336] Step 1:

[1337] The user starts the application and inputs their age, gender, current weight, target weight, allergy information, and emotional data (e.g., data obtained through a form to input their emotional state or through emotion recognition technology). The user enters this data and confirms it by pressing the submit button.

[1338] Step 2:

[1339] The device receives the data entered by the user and verifies whether the data is appropriate: specifically, whether the age is within a reasonable range, whether the gender is selected correctly, whether the weight and target weight are reasonable, and whether the emotional data is entered accurately. After verification, the device sends the data to the server.

[1340] Step 3:

[1341] The server receives the data sent from the device and creates a user profile, which includes age, gender, current weight, target weight, allergy information, and emotional state. The server stores this information in a database and updates the data as needed.

[1342] Step 4:

[1343] The server uses an emotion engine to analyze the user's emotional data. The emotion engine uses emotion analysis algorithms to analyze the emotional data entered by the user and sensor data to determine the user's emotional state, such as whether they are feeling stressed or highly motivated.

[1344] Step 5:

[1345] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress. On the other hand, if the user is highly motivated, it will recommend a slightly more strenuous exercise menu.

[1346] Step 6:

[1347] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume, making it easier to visually grasp the user's progress.

[1348] Step 7:

[1349] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[1350] Step 8:

[1351] The terminal receives the plan file sent from the server and presents it to the user, who can then download it and view it on their device.

[1352] Step 9:

[1353] Every day, users enter their weight, diet, exercise, and emotional state into the application, which then sends the data to the system as daily data.

[1354] Step 10:

[1355] The device sends daily data entered by the user to a server, including weight, food intake, exercise, emotional state, etc.

[1356] Step 11:

[1357] The server receives and analyzes daily data, evaluating weight fluctuations, calorie intake, and activity levels to determine whether the user is approaching their weight goal and how their emotional state is evolving.

[1358] Step 12:

[1359] The server updates the progress based on the analysis of the daily data, which means adding the latest information to the user profile.

[1360] Step 13:

[1361] The server reevaluates the plan based on the user's progress and emotional data and makes adjustments as needed. For example, if the user is feeling emotionally down, it may provide encouraging messages or advice to help relieve stress.

[1362] Step 14:

[1363] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[1364] Step 15:

[1365] The device receives the feedback and updates sent by the server and presents them to the user, who then takes the next step.

[1366] As a concrete example, consider a 30-year-old female user who wants to lose weight from 70 kg to 60 kg, and who reports feeling stressed.

[1367] The user inputs their age, gender, current weight, goal weight, allergy information, and emotional state.

[1368] The server generates a plan that sets a daily calorie intake of 1500 kcal and recommends five exercise sessions per week. Because the user is under stress, it recommends foods that are effective in relieving stress and light exercise.

[1369] The plan is saved in Excel format and provided to the user.

[1370] Users input their daily weight, diet, exercise and emotional state, and the server analyzes this and updates their progress.

[1371] The server generates a progress graph and emotion data, which the device visually displays to the user.

[1372] In this way, the system takes into account the user's emotional state and provides more personalized guidance and feedback to support dieting success.

[1373] Example 2

[1374] 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."

[1375] Conventional health management systems only provide fixed dietary restriction plans and exercise menus based on basic information entered by users, making it difficult to provide dynamic feedback that corresponds to the user's emotional state or daily progress.In addition, there was a lack of a way for users to easily understand plans and progress data visually, which resulted in a tendency for users to find it difficult to maintain motivation.

[1376] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing emotional data and adjusting the plan and menu, a means for providing feedback in real time, and a means for visually displaying the emotional data and progress data. This not only enables dynamic feedback according to the user's emotional state and daily progress, but also makes it easier to maintain the user's motivation by providing the feedback in a visually easy-to-understand format.

[1377] A "user" is an individual who utilizes the system to input their own health care data and receive feedback.

[1378] "Information" refers to all data input by the user, including age, sex, current weight, target weight, allergy information, and emotional data.

[1379] "Computer" refers to the entire device or system that receives, processes, and stores information entered by a user in a database.

[1380] "Means for generating" refers to a process or algorithm that generates a diet plan and exercise menu based on input information.

[1381] "Means for providing" refers to a method or system for presenting the generated diet plan and exercise menu to the user.

[1382] "Means for saving" refers to a function or process for saving the generated plans and menus in a format desired by the user.

[1383] "Emotion data" is data that reflects the user's emotional state, including stress, motivation, and the like.

[1384] "Means for analyzing" refers to a function or algorithm that processes emotional data to assess the user's emotional state.

[1385] "Means for adjusting" refers to a function or process that modifies plans and menus based on the user's emotional state and progress data.

[1386] "Means for providing feedback" refers to a function or system that provides appropriate advice or information to users in real time.

[1387] "Graphical format" refers to a format used to visualize data, such as a line graph, bar graph, or pie chart.

[1388] "Progress Data" refers to data regarding a user's daily weight, diet, exercise, and emotional state.

[1389] "Visual display means" refers to a function or system that displays data in a form such as a graph so that the user can easily understand the information.

[1390] This invention is a system that generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. In addition, the generated data and progress information can be saved in the format desired by the user.

[1391] System Overview

[1392] The system begins with the user entering their age, gender, current weight, goal weight, allergy information, and emotional data. The entered data is sent to the server via the device. The server creates a user profile based on the received data and uses a generative AI model and emotional engine to generate a dietary restriction plan and exercise menu tailored to each individual user. The generated plan is saved in the user's desired format and provided via the device.

[1393] When users enter their daily progress data (weight, diet, exercise, emotional state), this data is sent back to the server, where it is analyzed and the plan is adjusted as needed. Furthermore, the analysis results are fed back to the user in real time, allowing them to easily visualize their progress in the form of statistical data and graphs.

[1394] Hardware and software used

[1395] Terminal: A device on which a user inputs data and receives data from a server. This includes smartphones, tablets, and PCs.

[1396] Server: A central computer system that receives data, creates profiles, analyzes them, generates plans, and provides feedback. It is where the generative AI models and emotion engines run.

[1397] The generative AI model includes an algorithm to suggest optimal diet and exercise plans based on the user's basic information and emotional data, while the emotional engine analyzes the user's emotional data and provides information necessary to adjust the plan.

[1398] Specific examples

[1399] For example, a 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. This user reports that she feels stressed.

[1400] 1. The user enters their age, gender, weight, target weight, allergy information, and emotional state into the application's input form.

[1401] 2. Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also suggests additional meal menus suitable for stress relief.

[1402] 3. The plan is saved in Excel format and provided to the user, who can view it on their device.

[1403] 4. Users enter their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[1404] 5. The server generates a progress graph and emotion data, which are then visually displayed on the device.

[1405] Example prompt sentence:

[1406] "A 30-year-old woman currently weighs 70 kg and has a goal weight of 60 kg. She reports feeling stressed. Based on these conditions, please suggest a balanced diet plan and a five-day weekly exercise routine."

[1407] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1408] Step 1: User Data Entry

[1409] The user enters age, gender, current weight, target weight, allergy information, and emotional data into the application's input form. The entered data is confirmed when the user presses the send button. This data is sent to the terminal as input information (age, gender, current weight, target weight, allergy information, emotional data).

[1410] Step 2: Receiving and processing data

[1411] The terminal receives the data entered by the user. At this stage, the terminal checks the integrity of the data, for example, whether the age is within a reasonable range and whether the numerical data is in the correct format. After verification, the terminal sends the appropriate data to the server. The sent data becomes information for creating a user profile.

[1412] Step 3: Create a profile on the server

[1413] The server receives the data sent from the device and creates a user profile based on this data. The profile includes age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[1414] Step 4: Analysis by Emotion Engine

[1415] The server uses an emotion engine to analyze the user's emotion data. For example, it evaluates the user's emotional state, such as whether they are feeling stressed or highly motivated. The analysis results are added to the user profile and used to generate the next plan. The input is emotion data, and the output is the analysis results of the emotion engine.

[1416] Step 5: Create a diet plan and exercise menu

[1417] The server generates a dietary restriction plan and exercise menu based on the analysis results of the generative AI model and emotion engine according to the user profile. For example, if the user is feeling stressed, it will suggest meals and light exercise menus that are effective in relieving stress. The input is the user profile and the analysis results of the emotion engine, and the output is a dietary restriction plan and exercise menu.

[1418] Step 6: Serving the generated plan

[1419] The server compiles the generated diet plan and exercise menu in text and graph format. The generated plan is saved in the user's desired format (e.g., Word, Excel, PPT, PDF) and sent to the device. The input is the generated plan and menu, and the output is the saved file.

[1420] Step 7: Offer and display your plan

[1421] The terminal receives the plan file sent from the server. The user can download this file and view it on their device. The input is the plan file from the server, and the output is the presentation to the user.

[1422] Step 8: Daily progress input and emotional data collection

[1423] Every day, users input their weight, diet, exercise, and emotional state into the application. This data is registered as daily data. The input data is sent to the server via the device, and the server stores it in a database. The input is daily progress data, and the output is the stored daily data.

[1424] Step 9: Analyze and manage progress data

[1425] The server analyzes the data entered daily and updates the user's progress. This analysis evaluates how close or far the user is from reaching their goal weight. Emotional data is also analyzed to evaluate the user's emotional state. The input is daily progress data and emotional data, and the output is the progress analysis results.

[1426] Step 10: Real-time advice and plan adjustments

[1427] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling emotionally down, it generates encouraging messages and diet and exercise advice to reduce stress. This feedback is provided in real time. The input is progress and emotional data, and the output is the adjusted plan and feedback.

[1428] Step 11: Display in graphical format

[1429] The server generates data to display the user's progress and emotional data in a graph format, allowing the user to visually grasp their own progress and emotional state. The device receives this data and displays it in a form that is easy for the user to understand visually. The input is the generated graph data, and the output is the visual display.

[1430] (Application example 2)

[1431] 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."

[1432] Traditional health management systems only provide basic dietary and exercise plans based on user input, but they lack the ability to adjust plans to take into account the user's emotional state or provide real-time feedback. This can lead to a decrease in user motivation and an increase in stress, making it difficult to achieve goals. They also lack tools for visualizing progress.

[1433] 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 analyzing the user's emotional data using emotion recognition technology, means for adjusting the diet plan and exercise menu based on the user's emotional state, and means for generating data for visually displaying daily progress and emotional state. This makes it possible to provide an individualized plan according to the user's emotional state and provide real-time feedback.

[1434] "Means for users to input their own information" refers to a device or system that provides an interface for users to input information such as age, sex, current weight, target weight, allergy information, and emotional data.

[1435] The "server that receives and processes the information" refers to a server system that receives information entered by users and analyzes, stores, and processes that information.

[1436] The "means for generating a dietary restriction plan and exercise menu" refers to an algorithm or program for automatically generating an appropriate dietary restriction plan and exercise menu based on input user information.

[1437] "Means for providing the generated plan and menu to the user" refers to means for presenting the generated dietary restriction plan and exercise menu to the user, including providing them in text format or graphical format.

[1438] "Means for saving in a format desired by the user" refers to a function for saving the generated plan or menu in a file format (e.g., Word, Excel, PDF) specified by the user.

[1439] "Means for analyzing user emotional data using emotion recognition technology" refers to technology for identifying and analyzing a user's current emotional state using the user's input data and biometric data.

[1440] "Means for adjusting dietary plans and exercise menus based on the user's emotional state" refers to means for individually adjusting and optimizing existing plans and menus by taking into account the user's emotional state.

[1441] "Means for generating data for visually displaying daily progress and emotional state" refers to means for converting a user's progress data and emotional data into a visual format such as a graph, and providing it to the user in a way that is easy to understand.

[1442] MODE FOR CARRYING OUT THE INVENTION

[1443] DETAILED DESCRIPTION OF THE INVENTION The following describes an embodiment of the present invention.

[1444] System Overview

[1445] This system allows users to input their personal information and generates a balanced diet plan and exercise menu based on that information, and further adjusts the plan in real time according to the user's emotional state. It also allows users to visually grasp their daily progress and emotional data, providing personalized health management support.

[1446] Program Implementation

[1447] The system uses the following key tools and technologies:

[1448] User information input interface

[1449] Central Server

[1450] emotion recognition technology

[1451] Meal restriction plan generation algorithm

[1452] Exercise menu generation algorithm

[1453] Data Visualization Techniques

[1454] Specific examples

[1455] The user inputs their age, gender, weight, target weight, allergy information, and emotional data into the health management app. The central server receives this information and analyzes the user's emotional state using emotion recognition technology. Based on this information, an individualized plan is generated using a dietary restriction plan generation algorithm and an exercise menu generation algorithm. The generated plan and menu are saved in the user's desired format and displayed visually.

[1456] Step-by-step process overview

[1457] User Data Entry

[1458] The user inputs age, gender, weight, target weight, allergy information, and emotional data into the application. This data is sent to the server through the application's input form.

[1459] Data reception and processing

[1460] The server receives the input data, verifies it, and then stores it. In particular, emotional data is analyzed using emotion recognition technology.

[1461] Plan Generation

[1462] The server generates a diet plan and exercise menu based on the user's profile and the results of emotion analysis. A generative AI model is used to generate an appropriate plan.

[1463] Plan delivery and visualization

[1464] The generated diet plan and exercise menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and provided to the user. The user's progress and emotional data are also displayed in a visually easy-to-understand format.

[1465] The specific hardware and software used

[1466] Hardware

[1467] Central server: Stores data and performs calculations.

[1468] Client terminal: A device (PC, smartphone, tablet, etc.) through which a user enters data.

[1469] software

[1470] Emotion recognition technology: Analyzes user emotion data.

[1471] Diet Plan Generation Algorithm: Generates a meal plan based on input data.

[1472] Exercise menu generation algorithm: Generate an exercise menu.

[1473] Data visualization tools: Visually display user progress data.

[1474] Prompt Sentence Examples

[1475] markdown

[1476] Prompt for employee wellness app:

[1477] Enter the user profile:

[1478] Age: 30

[1479] Gender: Female

[1480] Current weight: 70kg

[1481] Target weight: 60kg

[1482] Allergy Information: Nuts

[1483] Emotional state: Stress

[1484] Example of a generated meal plan:

[1485] Breakfast: Oatmeal and fruit

[1486] Lunch: Grilled chicken salad

[1487] Dinner: Salmon and vegetables

[1488] An example of a generated exercise menu:

[1489] Light stretching

[1490] 30 minutes of walking every day

[1491] Three yoga sessions per week

[1492] conclusion

[1493] This allows users to obtain a personalized health management plan based on their own information, and effectively manage their health through real-time adjustments and visualizations according to their emotional state, while also solving the problems faced by traditional health management systems.

[1494] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1495] Processing Steps

[1496] Step 1: User Data Entry

[1497] The user inputs information such as age, sex, weight, target weight, allergy information, emotional data, etc. through the input interface. After completing the input, the user presses the send button to confirm the data and send it from the terminal to the server.

[1498] Input: Age, gender, weight, target weight, allergy information, emotional data

[1499] Output: User information data sent to the server

[1500] Step 2: Data reception and verification

[1501] The server receives the user information sent from the terminal and then verifies whether the format of the received data is correct and within a reasonable range.

[1502] Input: User information data sent from the device

[1503] Output: Validated user information data, error message (if invalid data)

[1504] Step 3: Create a profile

[1505] The server creates a user profile based on the verified user information and stores it in a database.

[1506] Input: Verified user information data

[1507] Output: User profile stored in the database

[1508] Step 4: Analyze the sentiment data

[1509] The server analyzes the user's emotional data using emotion recognition technology. An emotion engine processes the data and identifies the user's emotional state (e.g., stress, motivation).

[1510] Input: User emotion data

[1511] Output: Parsed emotional state

[1512] Step 5: Create a diet plan and exercise menu

[1513] The server generates a plan based on the user's profile and emotional state using a diet plan generation algorithm and an exercise menu generation algorithm. The generative AI model proposes the optimal plan for each user.

[1514] Input: User profile, analyzed emotional state

[1515] Output: Generated diet plan and exercise menu

[1516] Step 6: Save and serve your plan

[1517] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[1518] Input: Generated diet plan and exercise menu, user's desired format

[1519] Output: Plan file saved in desired format

[1520] Step 7: View your plan

[1521] The terminal receives the plan file sent from the server and proposes it to the user, who can visually confirm it.

[1522] Input: Plan file sent from the server

[1523] Output: Plans and menus displayed to the user

[1524] Step 8: Collect daily progress and sentiment data

[1525] Every day, users enter their weight, diet, exercise, emotional data, etc. into the application and send that data to the server.

[1526] Input: Daily weight, diet, exercise, emotional data

[1527] Output: Daily progress data stored on the server

[1528] Step 9: Analyze progress data

[1529] The server analyzes the daily progress data, evaluates the user's progress and emotional state, and updates the database.

[1530] Input: Daily progress data, emotional data

[1531] Output: Parsed progress, updated user profile

[1532] Step 10: Real-time feedback and plan adjustments

[1533] Based on the analyzed progress and emotional state, the server adjusts the plan as needed and provides real-time feedback, generating encouraging messages or new advice depending on the user's emotional state.

[1534] Input: Parsed progress, emotional state

[1535] Output: Real-time feedback, tailored plans and advice

[1536] Step 11: Visualize the data

[1537] The server generates graph data for visually displaying the user's progress data and emotion data, and transmits it to the device, which receives it and visually displays it to the user.

[1538] Input: Progress data, emotion data

[1539] Output: visualized graph data, graph displayed to user

[1540] In this way, the system helps users manage their health and provides personalized plans tailored to their emotional state.

[1541] 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.

[1542] 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.

[1543] 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.

[1544] [Fourth embodiment]

[1545] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1546] 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.

[1547] 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).

[1548] 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.

[1549] 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.

[1550] 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).

[1551] 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.

[1552] 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.

[1553] 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.

[1554] 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.

[1555] 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.

[1556] 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.

[1557] 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."

[1558] As an embodiment of the present invention, a system is constructed as follows.

[1559] System Overview

[1560] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides real-time feedback. The generated data and progress information can also be saved in the user's preferred format.

[1561] Program processing

[1562] 1. User data entry

[1563] The user enters information such as age, gender, current weight, target weight, and allergy information into the application.

[1564] The terminal verifies the entered data and transmits it to the server.

[1565] 2. Data Receipt and Processing

[1566] The server receives the data sent by the user.

[1567] The server creates a user profile based on the received data.

[1568] 3. Create a diet plan and exercise menu

[1569] The server uses AI to generate a diet plan and exercise menu, taking into account the user's current weight, target weight, age, gender, and other factors to derive the optimal plan.

[1570] Example: If a user weighs 70kg and aims to lose 60kg, a plan will be generated that limits daily calorie intake to 1500kcal and recommends exercising five days a week.

[1571] 4. Providing the generated plan

[1572] The server compiles the generated diet plan and exercise menu in text and graph format.

[1573] The server saves this in the user's desired format (Word, Excel, PPT, PDF, etc.).

[1574] The terminal receives this data and displays it to the user.

[1575] 5. Daily progress input and management

[1576] Users enter their weight, diet, and exercise information into the application every day.

[1577] The terminal transmits the input data to the server.

[1578] The server analyzes the data daily and updates the progress.

[1579] 6. Real-time advice and plan adjustments

[1580] The server adjusts the plan as needed based on the user's progress and provides real-time feedback.

[1581] Example: If a user loses 1kg in a week, provide a message saying "You're making good progress! Keep it up!"

[1582] 7. Graphical display

[1583] The server generates data to display the user's progress in a graphical format.

[1584] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[1585] Specific examples

[1586] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg.

[1587] Users enter their age, gender, weight, target weight, and allergy information into the app.

[1588] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[1589] The plan is saved in Excel format and provided to the user.

[1590] Users input their daily weight and dietary information, and the server analyzes it and updates their progress.

[1591] The server generates a progress graph, which the terminal visually displays to the user.

[1592] In this way, the user can efficiently reach their target weight while checking their progress.

[1593] The processing flow will be explained below.

[1594] Step 1:

[1595] The user starts the application and enters personal data such as age, sex, current weight, target weight, allergy information, etc. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[1596] Step 2:

[1597] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[1598] Step 3:

[1599] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, and allergy information. The server stores this information in a database.

[1600] Step 4:

[1601] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile. For example, the generation process will design a calorie restriction and appropriate exercise menu to bring a 70kg user down to 60kg.

[1602] Step 5:

[1603] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[1604] Step 6:

[1605] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[1606] Step 7:

[1607] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[1608] Step 8:

[1609] Users enter their daily weight, diet, and exercise information into the application, which is then registered as daily data.

[1610] Step 9:

[1611] The terminal transmits the daily data entered by the user to the server, which receives it and stores it in a database.

[1612] Step 10:

[1613] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from reaching their goal weight.

[1614] Step 11:

[1615] The server adjusts the plan as needed based on the user's progress, for example generating advice to reset calorie levels or increase exercise if weight loss is slower than expected.

[1616] Step 12:

[1617] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[1618] Step 13:

[1619] The device receives the updates and feedback sent by the server and presents them to the user, who then takes the next step.

[1620] This series of steps helps users effectively diet, and the system provides ongoing progress monitoring and feedback.

[1621] Example 1

[1622] 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."

[1623] Previously, it was difficult for users to find appropriate diet plans and exercise menus based on their individual health conditions and goals. Additionally, there was a lack of systems that track daily progress and provide real-time feedback. Furthermore, there were limited ways to provide users with a visual understanding of their progress, making it difficult to support long-term goal achievement.

[1624] 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.

[1625] In this invention, the server includes a means for generating a diet plan and exercise menu using a generative AI model, a means for analyzing the user's daily data, updating the user's progress, and providing real-time feedback, and a means for generating data displaying the user's progress in a graphical format and providing the data to the user. This allows the user to obtain a customized diet plan and exercise menu based on their individual health condition and goals, allowing them to efficiently achieve their goals while managing their daily progress. Furthermore, providing progress in a format that is easy to understand visually can help the user maintain ongoing motivation.

[1626] "User information" refers to personal information such as age, sex, weight, target weight, and allergy information entered by the user.

[1627] A "terminal" is a device used by a user to enter information or view stored data, and includes smartphones, tablets, and personal computers with dedicated applications installed.

[1628] The "server" is a back-end system that receives and processes user information, generates diet plans and exercise menus, and provides them to users.

[1629] A "generative AI model" is an artificial intelligence model that generates appropriate diet plans and exercise menus based on input prompts.

[1630] A "prompt" is a textual instruction entered into a generative AI model, containing specific conditions and requirements.

[1631] A "dietary restriction plan" is a plan that includes recommended daily calorie intake and meal contents to achieve the user's health goals.

[1632] An "exercise menu" is a plan that includes the type and frequency of exercise recommended to achieve the user's health goals.

[1633] The "format" refers to the data format in which the diet plan or exercise menu is provided to the user, and examples include Word, Excel, PDF, etc.

[1634] "Progress data" refers to data such as weight, dietary details, and exercise details that are input by the user on a daily basis, and indicates the progress of the user in achieving their goals.

[1635] "Feedback" refers to advice and encouraging messages provided by the server based on analysis of the user's progress data.

[1636] "Graph-format data" refers to data such as line graphs and bar graphs that are generated to visually display the user's progress.

[1637] As an embodiment of the present invention, the following system is constructed. The system is designed to enable users to obtain a customized diet plan and exercise menu based on their individual health condition and goals. The user inputs daily data, and the system manages the progress in real time and provides feedback as needed. The system also displays the data in a graph format so that the user can visually grasp the progress toward achieving their goals.

[1638] System Overview and Configuration

[1639] Users install a dedicated application on their devices, such as smartphones, tablets, or PCs, to input data. The information entered by the user is verified by the device and securely sent to a server. The server processes the received information and generates a diet plan or exercise menu using a generative AI model (e.g., OpenAI's GPT-3.5).

[1640] The generated plan and menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and sent to the device. The user enters their daily weight, diet, and exercise details, and this data is sent to the server via the device. The server analyzes the progress data, adjusts the plan as needed, and provides feedback in real time. In addition, the server generates data that displays the user's progress in graph form and sends it to the device, allowing the user to check their progress in a format that is easy to understand visually.

[1641] Hardware and software used

[1642] 1. Devices: smartphones, tablets, computers

[1643] 2. Dedicated application: An application for users to enter data.

[1644] 3. Server: The back-end system that receives and processes data and generates plans using generative AI models.

[1645] 4. Generative AI models: Artificial intelligence models such as OpenAI's GPT-3.5

[1646] Specific examples

[1647] To illustrate each processing step, consider a scenario in which a 30-year-old female user wants to lose weight from 70 kg to a target weight of 60 kg. The user enters her age, gender, weight, target weight, and allergy information into the application. The device verifies this data and sends it to the server. The server uses the generated AI model to generate a plan that sets a daily calorie intake of 1500 kcal and includes five exercise sessions per week (strength training and aerobic exercise).

[1648] The generated plan is saved in the user's desired format (e.g., Excel format) and sent to the user's device. The user enters their daily weight, dietary habits, and exercise habits into the application, and this data is sent to the server. The server analyzes the progress data and provides real-time feedback, such as "You're making good progress. Keep it up!" The server also generates data that displays the progress in graph form, which the device displays to the user.

[1649] Prompt Sentence Examples

[1650] "Generate the optimal diet and exercise plan for a 30-year-old female user to lose weight from 70 kg to a target weight of 60 kg. The daily calorie intake should be set to 1500 kcal, and the user should exercise (strength training and aerobic exercise) five times a week."

[1651] By inputting this prompt into a generative AI model, a specific plan is generated.

[1652] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1653] Step 1: Enter user data

[1654] The user launches a dedicated application and enters information such as age, gender, current weight, target weight, and allergy information.

[1655] Input: Age, gender, weight, target weight, allergy information

[1656] Output: User data is stored within the app and ready to be sent to the device.

[1657] Step 2: Validate and submit data

[1658] The terminal validates the data entered by the user, checking for missing information or improper formatting.

[1659] Input: Data entered by the user

[1660] Output: Validated data, if incomplete an error message is displayed to the user.

[1661] The terminal sends the verified data to the server.

[1662] Input: Validated Data

[1663] Output: The data is encrypted and sent to the server.

[1664] Step 3: Server receives data and creates profile

[1665] The server receives the data sent from the device and stores it in a database, creating a user profile.

[1666] Input: Validated Data

[1667] Output: The user profile is saved in the database.

[1668] Step 4: Generate plans and menus

[1669] The server uses the generative AI model to create prompts to generate a diet plan and exercise menu and sends them to the AI ​​model.

[1670] Input: User profile

[1671] Output: A prompt sentence is generated and sent to the AI ​​model.

[1672] The generative AI model generates an appropriate diet plan and exercise menu based on the prompt text and sends it back to the server.

[1673] Input: prompt statement

[1674] Output: The generated plan and exercise menu are sent back to the server.

[1675] Step 5: Save and serve your plans and menus

[1676] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[1677] Input: Generated plans and menus

[1678] Output: Saved in the specified format and sent to the device.

[1679] The terminal displays the received plans and menus to the user.

[1680] Input: Plans and menus saved in format

[1681] Output: What is displayed to the user in the application.

[1682] Step 6: Daily data entry and submission

[1683] Users enter their weight, diet, and exercise information into the application every day.

[1684] Input: Daily weight, diet, exercise

[1685] Output: Daily data is stored within the app and ready to be sent to your device.

[1686] The device sends daily data to the server.

[1687] Input: Daily data

[1688] Output: The data is sent to the server.

[1689] Step 7: Analyze progress data and receive real-time feedback

[1690] The server analyzes the daily data received and provides progress updates.

[1691] Input: Daily data

[1692] Output: Updated progress data is saved to the database.

[1693] The server generates a feedback message based on the progress data and sends it to the terminal.

[1694] Input: Progress data

[1695] Output: A feedback message is generated and sent to the terminal.

[1696] The terminal displays a feedback message to the user.

[1697] Input: Feedback message

[1698] Output: What is displayed to the user in the application.

[1699] Step 8: Graphical display of progress

[1700] The server generates and formats data to visually display the user's progress.

[1701] Input: Progress data

[1702] Output: Graphical data is generated.

[1703] The terminal displays the received data in the form of a graph to the user.

[1704] Input: Graph format data

[1705] Output: The output is displayed in an easy-to-understand visual format on the application.

[1706] (Application example 1)

[1707] 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."

[1708] In modern society, providing appropriate dietary plans and exercise menus based on individual health conditions and goals is an important issue. However, existing systems only generate plans based on user information, and few cover implementation and progress management, especially specific meal menus. In addition, they lack a function that allows users to easily order daily meals, making personalized health management difficult.

[1709] 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.

[1710] In this invention, the server includes means for a user to input their own information, means for receiving and processing the information, means for generating a dietary restriction plan and exercise menu based on the information, means for generating a meal menu based on the generated plan and menu using a generative AI model, means for allowing the user to select and order the generated meal menu, and means for saving the plan and menu in a format desired by the user. This allows the user to easily order a personalized meal menu based on their health information and receive real-time feedback on their progress.

[1711] The "means for inputting user information" is an interface for the user to input personal information such as age, sex, weight, target weight, and allergy information.

[1712] "Server that receives and processes information" refers to a computer system that centrally receives, analyzes, stores, and processes information entered by users.

[1713] The "means for generating a diet plan and exercise menu" refers to algorithms and processes for automatically generating a healthy diet plan and exercise menu based on user input information.

[1714] The "means for providing the generated plan and menu to the user" refers to an interface that provides the generated dietary restriction plan and exercise menu to the user in a visual or text format.

[1715] A "generative AI model" is an artificial intelligence model that generates appropriate meal menus based on user information and past data.

[1716] A "means for generating a meal menu" is a process and system that uses a generative AI model to automatically generate a meal menu based on a user's health information and goals.

[1717] The "means for enabling the user to select and order a meal menu" is an interface that displays the generated meal menu to the user, allows the user to select the meal they want from the menu, and confirms the order.

[1718] "Means for saving in a format desired by the user" is a function for saving the generated plan or menu in a format desired by the user, such as PDF, Excel, or Word.

[1719] The "means for inputting daily data" is an interface that allows the user to input data such as daily weight, dietary habits, and exercise habits.

[1720] "Means for receiving daily data and managing progress" refers to a system that receives daily data entered by the user and analyzes and manages the progress status.

[1721] The "means for adjusting the plan and providing feedback" is a function that adjusts the dietary restriction plan and exercise menu based on the user's progress data and provides the user with appropriate advice and feedback in real time.

[1722] The "means for managing order history and analyzing meal satisfaction data" is a system that stores the history of meal menus ordered by users and collects and analyzes user satisfaction data.

[1723] The "means for displaying in graph format" is a function for converting the user's progress and data into graph format and displaying it.

[1724] The "means for adjusting meal menus in real time" is a system that constantly optimizes the current meal menu based on the user's progress data and changes it as necessary.

[1725] MODE FOR CARRYING OUT THE INVENTION

[1726] As an embodiment of the present invention, a system is constructed as follows.

[1727] System Overview

[1728] The purpose of this system is to allow users to input their own health information and generate optimal dietary restriction plans and exercise menus based on that information.Furthermore, it provides a function to generate specific meal menus based on these plans and allow users to select and order.

[1729] Hardware Configuration

[1730] Server: Cloud-based server (e.g., Amazon Web Services, Google Cloud Platform)

[1731] Smartphone: iOS or Android compatible device

[1732] Software Configuration

[1733] Server side: Python (Framework: Flask)

[1734] Generative AI models: Python libraries (e.g., Scikit-learn, TensorFlow)

[1735] Client Side: React Native

[1736] Data Processing Procedures

[1737] 1. Entering and receiving user data

[1738] Users use a smartphone application to input their age, gender, current weight, target weight, allergy information, etc. The device verifies the input data and sends it to a cloud-based server.

[1739] 2. User Data Processing and Plan Generation

[1740] The server receives the information sent by the user and creates a user profile based on that data, analyzing data such as age, gender, weight, target weight, and allergy information, and then uses a generative AI model to generate an optimal diet plan and exercise menu.

[1741] 3. Generating and presenting a meal menu

[1742] The server automatically generates a meal menu using a generative AI model based on existing plans and menus. The generated menu is presented to the user via a smartphone application, and the user selects the desired menu and confirms their order.

[1743] 4. Daily progress input and management

[1744] Users enter their daily weight, diet, exercise, etc. into the application. The device sends this data to a cloud server, which analyzes it and manages the user's progress.

[1745] 5. Real-time advice and menu adjustments

[1746] The server adjusts the plan as needed and provides real-time feedback based on the user's progress, and also adjusts the meal menu in real time.

[1747] 6. Graphical progress display

[1748] The server generates data to display the user's progress in a graph format and provides this to the user via a smartphone application, allowing the user to visually grasp their progress.

[1749] Specific examples

[1750] Consider a case where a 30-year-old male user currently weighs 80 kg and creates a plan to bring his target weight down to 70 kg.

[1751] Users enter their age, gender, weight, target weight, and allergy information into the app.

[1752] Based on this data, the server generates a plan that sets a daily calorie intake of 1,600 kcal and recommends five exercise sessions per week (strength training and aerobic exercise).

[1753] The generative AI model then generates a specific meal menu based on this (e.g., grilled chicken salad, whole wheat bread).

[1754] Users select and order from this menu on the app and receive their meal via food delivery.

[1755] Example prompt sentence:

[1756] Prompt: I'm 30 years old, my current weight is 80kg, and my goal weight is 70kg. I have no allergies. Please provide a healthy meal plan.

[1757] Example output: Breakfast: Oatmeal with fruit and unsweetened yogurt. Lunch: Grilled chicken with salad and whole wheat bread. Dinner: Steamed fish with stewing vegetables.

[1758] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1759] Step 1:

[1760] Entering and Receiving User Data

[1761] Users enter their age, gender, current weight, target weight, allergy information, etc. using a smartphone application.

[1762] The terminal validates the entered data and sends it to a cloud-based server in JSON format.

[1763] Input: Age, gender, current weight, target weight, allergy information

[1764] Output: Sending user data to the server

[1765] Step 2:

[1766] Processing of User Data

[1767] The server receives the information sent by the user and creates a user profile based on that data.

[1768] At this time, the data is formatted and saved.

[1769] Input: User data (age, gender, current weight, target weight, allergy information)

[1770] Output: Create and save user profile

[1771] Step 3:

[1772] Generate plans and exercise menus

[1773] The server uses a generative AI model to generate an optimal diet plan and exercise menu based on the user profile.

[1774] Specifically, the system calculates calorie intake and exercise frequency, taking into account the user's target weight and current weight.

[1775] Input: User profile

[1776] Output: Generated diet plan and exercise menu

[1777] Step 4:

[1778] Generate and present a meal menu

[1779] The server automatically generates meal menus using a generative AI model based on existing plans and menus.

[1780] The terminal displays the received data to the user through the application.

[1781] The user selects a menu item and confirms the order.

[1782] Input: Generated diet plan and exercise menu

[1783] Output: Meal menu presented to the user, order information

[1784] Step 5:

[1785] Daily progress input and management

[1786] Users input their daily weight, diet, exercise, etc. into the application.

[1787] The device sends this data to a cloud server.

[1788] The server analyzes the data and manages the user's progress.

[1789] Input: Daily weight, diet, exercise

[1790] Output: Progress management data

[1791] Step 6:

[1792] Real-time advice and menu adjustments

[1793] The server adjusts the plan as needed and provides real-time feedback based on the user's progress data.

[1794] Using generative AI models, new menus and exercise plans are generated and provided to users through the application.

[1795] Input: Progress management data

[1796] Output: Adjusted plan, real-time feedback

[1797] Step 7:

[1798] Progress display in graphical format

[1799] The server generates data to display the user's progress in a graph format and provides this to the user through a smartphone application.

[1800] Users can visually grasp their progress.

[1801] Input: Progress management data

[1802] Output: Progress data in graphical format

[1803] 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.

[1804] As an embodiment of the present invention, a system is constructed as follows.

[1805] System Overview

[1806] This system generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. The generated data and progress information can also be saved in the format desired by the user.

[1807] Program processing

[1808] 1. User data entry

[1809] The user enters their age, gender, current weight, target weight, allergy information, and emotional data (e.g., self-reported or obtained through emotion recognition technology) into the application. The entered data is written in the application's input form, and the user confirms the data by pressing the submit button.

[1810] 2. Data Receipt and Processing

[1811] The terminal receives the data entered by the user and verifies that the data is appropriate (for example, ensuring that the age is within a reasonable range and checking that numerical data is in the correct format). After verification, the terminal sends the data to the server.

[1812] 3. Creating a profile on the server

[1813] The server receives the data sent from the device and creates a user profile, which includes the user's age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[1814] 4. Analysis by Emotion Engine

[1815] The server analyzes the user's emotional data using an emotion engine, which evaluates the user's emotional state, such as whether the user is stressed or motivated.

[1816] 5. Create a diet plan and exercise menu

[1817] The server generates a diet plan and exercise menu based on the analysis results of the generative AI and emotion engine, according to the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress.

[1818] 6. Providing the generated plan

[1819] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume over time, making it easier to visually grasp the user's progress.

[1820] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[1821] 7. Offering and Display of Offers

[1822] The terminal receives the plan file sent from the server and presents it to the user, who can then download the file and view it on their device.

[1823] 8. Daily progress input and emotional data collection

[1824] Users enter their weight, diet, exercise, and emotional state into the application every day, and the data is registered as daily data.

[1825] The terminal transmits the entered daily data to the server, which receives it and stores it in a database.

[1826] 9. Progress data analysis and management

[1827] The server analyzes the daily data and updates the user's progress, assessing how close or far away the user is from their goal weight. It also analyzes emotional data to assess the user's emotional state.

[1828] 10. Real-time advice and plan adjustments

[1829] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling depressed, it generates encouraging messages and dietary and exercise advice to reduce stress. This feedback is provided in real time.

[1830] 11. Graphical display

[1831] The server generates data for displaying the user's progress and emotion data in a graph format.

[1832] The terminal receives this data and displays it in a form that is easy for the user to visually understand.

[1833] Specific examples

[1834] A 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. The user also reports that she feels stressed.

[1835] Users enter their age, gender, weight, goal weight, allergy information and emotional state into the app.

[1836] Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also adds a meal menu suitable for stress relief.

[1837] The plan is saved in Excel format and provided to the user.

[1838] Users input their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[1839] The server generates a progress graph and emotion data as graphs, which are then visually displayed to the user on the device.

[1840] This series of steps allows users to track their progress and emotional state while efficiently reaching their goal weight, and the combined emotional engine provides more personalized plans and feedback.

[1841] The processing flow will be explained below.

[1842] Step 1:

[1843] The user starts the application and inputs their age, gender, current weight, target weight, allergy information, and emotional data (e.g., data obtained through a form to input their emotional state or through emotion recognition technology). The user enters this data and confirms it by pressing the submit button.

[1844] Step 2:

[1845] The device receives the data entered by the user and verifies whether the data is appropriate: specifically, whether the age is within a reasonable range, whether the gender is selected correctly, whether the weight and target weight are reasonable, and whether the emotional data is entered accurately. After verification, the device sends the data to the server.

[1846] Step 3:

[1847] The server receives the data sent from the device and creates a user profile, which includes age, gender, current weight, target weight, allergy information, and emotional state. The server stores this information in a database and updates the data as needed.

[1848] Step 4:

[1849] The server uses an emotion engine to analyze the user's emotional data. The emotion engine uses emotion analysis algorithms to analyze the emotional data entered by the user and sensor data to determine the user's emotional state, such as whether they are feeling stressed or highly motivated.

[1850] Step 5:

[1851] The server uses generative AI to generate a diet plan and exercise menu based on the user's profile and emotional state. For example, if the user is feeling stressed, it will suggest foods and light exercise that are effective in relieving stress. On the other hand, if the user is highly motivated, it will recommend a slightly more strenuous exercise menu.

[1852] Step 6:

[1853] The server then compiles the generated diet plan and exercise menu in text and graph format, and in the process creates graphs showing the progress of calorie intake and exercise volume, making it easier to visually grasp the user's progress.

[1854] Step 7:

[1855] The server saves the generated plan and graph data in the user's desired format (Word, Excel, PPT, PDF, etc.) and sends it to the terminal.

[1856] Step 8:

[1857] The terminal receives the plan file sent from the server and presents it to the user, who can then download it and view it on their device.

[1858] Step 9:

[1859] Every day, users enter their weight, diet, exercise, and emotional state into the application, which then sends the data to the system as daily data.

[1860] Step 10:

[1861] The device sends daily data entered by the user to a server, including weight, food intake, exercise, emotional state, etc.

[1862] Step 11:

[1863] The server receives and analyzes daily data, evaluating weight fluctuations, calorie intake, and activity levels to determine whether the user is approaching their weight goal and how their emotional state is evolving.

[1864] Step 12:

[1865] The server updates the progress based on the analysis of the daily data, which means adding the latest information to the user profile.

[1866] Step 13:

[1867] The server reevaluates the plan based on the user's progress and emotional data and makes adjustments as needed. For example, if the user is feeling emotionally down, it may provide encouraging messages or advice to help relieve stress.

[1868] Step 14:

[1869] The server displays progress data and new advice in a graphical format, providing real-time feedback to the user.

[1870] Step 15:

[1871] The device receives the feedback and updates sent by the server and presents them to the user, who then takes the next step.

[1872] As a concrete example, consider a 30-year-old female user who wants to lose weight from 70 kg to 60 kg, and who reports feeling stressed.

[1873] The user inputs their age, gender, current weight, goal weight, allergy information, and emotional state.

[1874] The server generates a plan that sets a daily calorie intake of 1500 kcal and recommends five exercise sessions per week. Because the user is under stress, it recommends foods that are effective in relieving stress and light exercise.

[1875] The plan is saved in Excel format and provided to the user.

[1876] Users input their daily weight, diet, exercise and emotional state, and the server analyzes this and updates their progress.

[1877] The server generates a progress graph and emotion data, which the device visually displays to the user.

[1878] In this way, the system takes into account the user's emotional state and provides more personalized guidance and feedback to support dieting success.

[1879] Example 2

[1880] 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."

[1881] Conventional health management systems only provide fixed dietary restriction plans and exercise menus based on basic information entered by users, making it difficult to provide dynamic feedback that corresponds to the user's emotional state or daily progress.In addition, there was a lack of a way for users to easily understand plans and progress data visually, which resulted in a tendency for users to find it difficult to maintain motivation.

[1882] The specification process by the specification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing emotional data and adjusting the plan and menu, a means for providing feedback in real time, and a means for visually displaying the emotional data and progress data. This not only enables dynamic feedback according to the user's emotional state and daily progress, but also makes it easier to maintain the user's motivation by providing the feedback in a visually easy-to-understand format.

[1883] A "user" is an individual who utilizes the system to input their own health care data and receive feedback.

[1884] "Information" refers to all data input by the user, including age, sex, current weight, target weight, allergy information, and emotional data.

[1885] "Computer" refers to the entire device or system that receives, processes, and stores information entered by a user in a database.

[1886] "Means for generating" refers to a process or algorithm that generates a diet plan and exercise menu based on input information.

[1887] "Means for providing" refers to a method or system for presenting the generated diet plan and exercise menu to the user.

[1888] "Means for saving" refers to a function or process for saving the generated plans and menus in a format desired by the user.

[1889] "Emotion data" is data that reflects the user's emotional state, including stress, motivation, and the like.

[1890] "Means for analyzing" refers to a function or algorithm that processes emotional data to assess the user's emotional state.

[1891] "Means for adjusting" refers to a function or process that modifies plans and menus based on the user's emotional state and progress data.

[1892] "Means for providing feedback" refers to a function or system that provides appropriate advice or information to users in real time.

[1893] "Graphical format" refers to a format used to visualize data, such as a line graph, bar graph, or pie chart.

[1894] "Progress Data" refers to data regarding a user's daily weight, diet, exercise, and emotional state.

[1895] "Visual display means" refers to a function or system that displays data in a form such as a graph so that the user can easily understand the information.

[1896] This invention is a system that generates and provides a balanced diet plan and exercise menu based on information entered by the user. The user enters daily data, and the system manages the progress, adjusts the plan as needed, and provides feedback in real time. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to adjust the plan and provide feedback according to the user's emotional state. In addition, the generated data and progress information can be saved in the format desired by the user.

[1897] System Overview

[1898] The system begins with the user entering their age, gender, current weight, goal weight, allergy information, and emotional data. The entered data is sent to the server via the device. The server creates a user profile based on the received data and uses a generative AI model and emotional engine to generate a dietary restriction plan and exercise menu tailored to each individual user. The generated plan is saved in the user's desired format and provided via the device.

[1899] When users enter their daily progress data (weight, diet, exercise, emotional state), this data is sent back to the server, where it is analyzed and the plan is adjusted as needed. Furthermore, the analysis results are fed back to the user in real time, allowing them to easily visualize their progress in the form of statistical data and graphs.

[1900] Hardware and software used

[1901] Terminal: A device on which a user inputs data and receives data from a server. This includes smartphones, tablets, and PCs.

[1902] Server: A central computer system that receives data, creates profiles, analyzes them, generates plans, and provides feedback. It is where the generative AI models and emotion engines run.

[1903] The generative AI model includes an algorithm to suggest optimal diet and exercise plans based on the user's basic information and emotional data, while the emotional engine analyzes the user's emotional data and provides information necessary to adjust the plan.

[1904] Specific examples

[1905] For example, a 30-year-old female user currently weighs 70 kg and creates a plan to reduce her target weight to 60 kg. This user reports that she feels stressed.

[1906] 1. The user enters their age, gender, weight, target weight, allergy information, and emotional state into the application's input form.

[1907] 2. Based on the received data, the server generates a plan that sets a daily calorie intake of 1,500 kcal and recommends five exercise sessions per week (muscle training and aerobic exercise). It also suggests additional meal menus suitable for stress relief.

[1908] 3. The plan is saved in Excel format and provided to the user, who can view it on their device.

[1909] 4. Users enter their daily weight, dietary habits, and emotional state, and the server analyzes this information and updates their progress.

[1910] 5. The server generates a progress graph and emotion data, which are then visually displayed on the device.

[1911] Example prompt sentence:

[1912] "A 30-year-old woman currently weighs 70 kg and has a goal weight of 60 kg. She reports feeling stressed. Based on these conditions, please suggest a balanced diet plan and a five-day weekly exercise routine."

[1913] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1914] Step 1: User Data Entry

[1915] The user enters age, gender, current weight, target weight, allergy information, and emotional data into the application's input form. The entered data is confirmed when the user presses the send button. This data is sent to the terminal as input information (age, gender, current weight, target weight, allergy information, emotional data).

[1916] Step 2: Receiving and processing data

[1917] The terminal receives the data entered by the user. At this stage, the terminal checks the integrity of the data, for example, whether the age is within a reasonable range and whether the numerical data is in the correct format. After verification, the terminal sends the appropriate data to the server. The sent data becomes information for creating a user profile.

[1918] Step 3: Create a profile on the server

[1919] The server receives the data sent from the device and creates a user profile based on this data. The profile includes age, gender, current weight, target weight, allergy information, and emotional data. The server stores this information in a database.

[1920] Step 4: Analysis by Emotion Engine

[1921] The server uses an emotion engine to analyze the user's emotion data. For example, it evaluates the user's emotional state, such as whether they are feeling stressed or highly motivated. The analysis results are added to the user profile and used to generate the next plan. The input is emotion data, and the output is the analysis results of the emotion engine.

[1922] Step 5: Create a diet plan and exercise menu

[1923] The server generates a dietary restriction plan and exercise menu based on the analysis results of the generative AI model and emotion engine according to the user profile. For example, if the user is feeling stressed, it will suggest meals and light exercise menus that are effective in relieving stress. The input is the user profile and the analysis results of the emotion engine, and the output is a dietary restriction plan and exercise menu.

[1924] Step 6: Serving the generated plan

[1925] The server compiles the generated diet plan and exercise menu in text and graph format. The generated plan is saved in the user's desired format (e.g., Word, Excel, PPT, PDF) and sent to the device. The input is the generated plan and menu, and the output is the saved file.

[1926] Step 7: Offer and display your plan

[1927] The terminal receives the plan file sent from the server. The user can download this file and view it on their device. The input is the plan file from the server, and the output is the presentation to the user.

[1928] Step 8: Daily progress input and emotional data collection

[1929] Every day, users input their weight, diet, exercise, and emotional state into the application. This data is registered as daily data. The input data is sent to the server via the device, and the server stores it in a database. The input is daily progress data, and the output is the stored daily data.

[1930] Step 9: Analyze and manage progress data

[1931] The server analyzes the data entered daily and updates the user's progress. This analysis evaluates how close or far the user is from reaching their goal weight. Emotional data is also analyzed to evaluate the user's emotional state. The input is daily progress data and emotional data, and the output is the progress analysis results.

[1932] Step 10: Real-time advice and plan adjustments

[1933] The server adjusts the plan as needed based on the user's progress and emotional data. For example, if the user is feeling emotionally down, it generates encouraging messages and diet and exercise advice to reduce stress. This feedback is provided in real time. The input is progress and emotional data, and the output is the adjusted plan and feedback.

[1934] Step 11: Display in graphical format

[1935] The server generates data to display the user's progress and emotional data in a graph format, allowing the user to visually grasp their own progress and emotional state. The device receives this data and displays it in a form that is easy for the user to understand visually. The input is the generated graph data, and the output is the visual display.

[1936] (Application example 2)

[1937] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1938] Traditional health management systems only provide basic dietary and exercise plans based on user input, but they lack the ability to adjust plans to take into account the user's emotional state or provide real-time feedback. This can lead to a decrease in user motivation and an increase in stress, making it difficult to achieve goals. They also lack tools for visualizing progress.

[1939] 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 analyzing the user's emotional data using emotion recognition technology, means for adjusting the diet plan and exercise menu based on the user's emotional state, and means for generating data for visually displaying daily progress and emotional state. This makes it possible to provide an individualized plan according to the user's emotional state and provide real-time feedback.

[1940] "Means for users to input their own information" refers to a device or system that provides an interface for users to input information such as age, sex, current weight, target weight, allergy information, and emotional data.

[1941] The "server that receives and processes the information" refers to a server system that receives information entered by users and analyzes, stores, and processes that information.

[1942] The "means for generating a dietary restriction plan and exercise menu" refers to an algorithm or program for automatically generating an appropriate dietary restriction plan and exercise menu based on input user information.

[1943] "Means for providing the generated plan and menu to the user" refers to means for presenting the generated dietary restriction plan and exercise menu to the user, including providing them in text format or graphical format.

[1944] "Means for saving in a format desired by the user" refers to a function for saving the generated plan or menu in a file format (e.g., Word, Excel, PDF) specified by the user.

[1945] "Means for analyzing user emotional data using emotion recognition technology" refers to technology for identifying and analyzing a user's current emotional state using the user's input data and biometric data.

[1946] "Means for adjusting dietary plans and exercise menus based on the user's emotional state" refers to means for individually adjusting and optimizing existing plans and menus by taking into account the user's emotional state.

[1947] "Means for generating data for visually displaying daily progress and emotional state" refers to means for converting a user's progress data and emotional data into a visual format such as a graph, and providing it to the user in a way that is easy to understand.

[1948] MODE FOR CARRYING OUT THE INVENTION

[1949] DETAILED DESCRIPTION OF THE INVENTION The following describes an embodiment of the present invention.

[1950] System Overview

[1951] This system allows users to input their personal information and generates a balanced diet plan and exercise menu based on that information, and further adjusts the plan in real time according to the user's emotional state. It also allows users to visually grasp their daily progress and emotional data, providing personalized health management support.

[1952] Program Implementation

[1953] The system uses the following key tools and technologies:

[1954] User information input interface

[1955] Central Server

[1956] emotion recognition technology

[1957] Meal restriction plan generation algorithm

[1958] Exercise menu generation algorithm

[1959] Data Visualization Techniques

[1960] Specific examples

[1961] The user inputs their age, gender, weight, target weight, allergy information, and emotional data into the health management app. The central server receives this information and analyzes the user's emotional state using emotion recognition technology. Based on this information, an individualized plan is generated using a dietary restriction plan generation algorithm and an exercise menu generation algorithm. The generated plan and menu are saved in the user's desired format and displayed visually.

[1962] Step-by-step process overview

[1963] User Data Entry

[1964] The user inputs age, gender, weight, target weight, allergy information, and emotional data into the application. This data is sent to the server through the application's input form.

[1965] Data reception and processing

[1966] The server receives the input data, verifies it, and then stores it. In particular, emotional data is analyzed using emotion recognition technology.

[1967] Plan Generation

[1968] The server generates a diet plan and exercise menu based on the user's profile and the results of emotion analysis. A generative AI model is used to generate an appropriate plan.

[1969] Plan delivery and visualization

[1970] The generated diet plan and exercise menu are saved in the user's preferred format (e.g., Word, Excel, PDF) and provided to the user. The user's progress and emotional data are also displayed in a visually easy-to-understand format.

[1971] The specific hardware and software used

[1972] Hardware

[1973] Central server: Stores data and performs calculations.

[1974] Client terminal: A device (PC, smartphone, tablet, etc.) through which a user enters data.

[1975] software

[1976] Emotion recognition technology: Analyzes user emotion data.

[1977] Diet Plan Generation Algorithm: Generates a meal plan based on input data.

[1978] Exercise menu generation algorithm: Generate an exercise menu.

[1979] Data visualization tools: Visually display user progress data.

[1980] Prompt Sentence Examples

[1981] markdown

[1982] Prompt for employee wellness app:

[1983] Enter the user profile:

[1984] Age: 30

[1985] Gender: Female

[1986] Current weight: 70kg

[1987] Target weight: 60kg

[1988] Allergy Information: Nuts

[1989] Emotional state: Stress

[1990] Example of a generated meal plan:

[1991] Breakfast: Oatmeal and fruit

[1992] Lunch: Grilled chicken salad

[1993] Dinner: Salmon and vegetables

[1994] An example of a generated exercise menu:

[1995] Light stretching

[1996] 30 minutes of walking every day

[1997] Three yoga sessions per week

[1998] conclusion

[1999] This allows users to obtain a personalized health management plan based on their own information, and effectively manage their health through real-time adjustments and visualizations according to their emotional state, while also solving the problems faced by traditional health management systems.

[2000] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2001] Processing Steps

[2002] Step 1: User Data Entry

[2003] The user inputs information such as age, sex, weight, target weight, allergy information, emotional data, etc. through the input interface. After completing the input, the user presses the send button to confirm the data and send it from the terminal to the server.

[2004] Input: Age, gender, weight, target weight, allergy information, emotional data

[2005] Output: User information data sent to the server

[2006] Step 2: Data reception and verification

[2007] The server receives the user information sent from the terminal and then verifies whether the format of the received data is correct and within a reasonable range.

[2008] Input: User information data sent from the device

[2009] Output: Validated user information data, error message (if invalid data)

[2010] Step 3: Create a profile

[2011] The server creates a user profile based on the verified user information and stores it in a database.

[2012] Input: Verified user information data

[2013] Output: User profile stored in the database

[2014] Step 4: Analyze the sentiment data

[2015] The server analyzes the user's emotional data using emotion recognition technology. An emotion engine processes the data and identifies the user's emotional state (e.g., stress, motivation).

[2016] Input: User emotion data

[2017] Output: Parsed emotional state

[2018] Step 5: Create a diet plan and exercise menu

[2019] The server generates a plan based on the user's profile and emotional state using a diet plan generation algorithm and an exercise menu generation algorithm. The generative AI model proposes the optimal plan for each user.

[2020] Input: User profile, analyzed emotional state

[2021] Output: Generated diet plan and exercise menu

[2022] Step 6: Save and serve your plan

[2023] The server saves the generated plan and menu in the user's desired format (e.g., Word, Excel, PDF) and sends it to the terminal.

[2024] Input: Generated diet plan and exercise menu, user's desired format

[2025] Output: Plan file saved in desired format

[2026] Step 7: View your plan

[2027] The terminal receives the plan file sent from the server and proposes it to the user, who can visually confirm it.

[2028] Input: Plan file sent from the server

[2029] Output: Plans and menus displayed to the user

[2030] Step 8: Collect daily progress and sentiment data

[2031] Every day, users enter their weight, diet, exercise, emotional data, etc. into the application and send that data to the server.

[2032] Input: Daily weight, diet, exercise, emotional data

[2033] Output: Daily progress data stored on the server

[2034] Step 9: Analyze progress data

[2035] The server analyzes the daily progress data, evaluates the user's progress and emotional state, and updates the database.

[2036] Input: Daily progress data, emotional data

[2037] Output: Parsed progress, updated user profile

[2038] Step 10: Real-time feedback and plan adjustments

[2039] Based on the analyzed progress and emotional state, the server adjusts the plan as needed and provides real-time feedback, generating encouraging messages or new advice depending on the user's emotional state.

[2040] Input: Parsed progress, emotional state

[2041] Output: Real-time feedback, tailored plans and advice

[2042] Step 11: Visualize the data

[2043] The server generates graph data for visually displaying the user's progress data and emotion data, and transmits it to the device, which receives it and visually displays it to the user.

[2044] Input: Progress data, emotion data

[2045] Output: visualized graph data, graph displayed to user

[2046] In this way, the system helps users manage their health and provides personalized plans tailored to their emotional state.

[2047] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2048] 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.

[2049] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2050] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2051] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2052] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2053] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2054] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2055] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2056] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2057] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2058] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2059] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2060] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2061] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2062] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2063] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2064] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2065] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2066] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2067] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2068] The following is further disclosed regarding the above embodiment.

[2069] (Claim 1)

[2070] a means for users to input their information;

[2071] a system including a server that receives and processes the information;

[2072] means for generating a diet plan and an exercise menu based on the information;

[2073] means for providing the generated plans and menus to a user;

[2074] The system includes means for saving said plans and menus in a user-desired format.

[2075] (Claim 2)

[2076] means for said user to input daily data;

[2077] means for receiving the daily data and managing progress;

[2078] means for adjusting the plan based on said progress and providing feedback;

[2079] 10. The system of claim 1.

[2080] (Claim 3)

[2081] means for displaying said plans and menus in a graphical format;

[2082] means for providing said graphical data to a user;

[2083] means for providing the data in a form that is easy to visually understand;

[2084] 10. The system of claim 1.

[2085] "Example 1"

[2086] (Claim 1)

[2087] a means for users to input their information;

[2088] means for receiving, verifying and transmitting said information to a server;

[2089] means for the server to create a user profile based on the information;

[2090] A means for the server to generate a diet plan and an exercise menu using a generative AI model;

[2091] means for saving and providing the generated plans and menus in a format desired by the user;

[2092] means for the server to analyze the user's daily data, update progress, and provide feedback in real time;

[2093] means for generating data in the form of a graph showing the user's progress and providing the data to the user;

[2094] A system including:

[2095] (Claim 2)

[2096] A means for the user to input daily weight, dietary details, and exercise details;

[2097] means for receiving the daily data and transmitting it to a server;

[2098] means for the server to adjust plans based on the daily data and provide feedback;

[2099] means for the server to generate data that displays the user's progress in a graph format and transmit the data to the terminal;

[2100] 10. The system of claim 1, comprising:

[2101] (Claim 3)

[2102] a means for the server to analyze the user's progress data and provide it in a format that is easy to visually understand;

[2103] means for visually displaying the data in a graph format to a user on the terminal;

[2104] 10. The system of claim 1, comprising:

[2105] "Application Example 1"

[2106] (Claim 1)

[2107] a means for users to input their information;

[2108] a system including a server that receives and processes the information;

[2109] means for generating a diet plan and an exercise menu based on the information;

[2110] means for providing the generated plans and menus to a user;

[2111] means for generating a meal menu based on the plan and menu using a generative AI model;

[2112] means for enabling a user to select and order the generated meal menu;

[2113] The system includes means for saving said plans and menus in a user-desired format.

[2114] (Claim 2)

[2115] means for said user to input daily data;

[2116] means for receiving the daily data and managing progress;

[2117] means for adjusting the plan based on said progress and providing feedback;

[2118] means for managing an order history of the generated meal menu and analyzing meal satisfaction data;

[2119] 10. The system of claim 1.

[2120] (Claim 3)

[2121] means for displaying said plans and menus in a graphical format;

[2122] means for providing said graphical data to a user;

[2123] A means for providing the data in a form that is easy to visually understand;

[2124] means for adjusting the meal menu in real time based on the progress data;

[2125] 10. The system of claim 1.

[2126] "Example 2: Combining Emotion Engines"

[2127] (Claim 1)

[2128] a means for users to input their information;

[2129] a system including a computer that receives and processes the information;

[2130] means for generating a diet plan and an exercise menu based on the information;

[2131] means for providing the generated plans and menus to a user;

[2132] means for saving said plans and menus in a format desired by the user;

[2133] means for analyzing emotion data and adjusting said plans and menus;

[2134] A way to provide real-time feedback

[2135] Including system.

[2136] (Claim 2)

[2137] means for said user to input daily data;

[2138] means for receiving the daily data and managing progress;

[2139] means for adjusting the plan based on said progress and providing feedback;

[2140] 10. The system of claim 1.

[2141] (Claim 3)

[2142] means for displaying said plans and menus in a graphical format;

[2143] means for providing said graphical data to a user;

[2144] means for providing the data in a form that is easy to visually understand;

[2145] 10. The system of claim 1.

[2146] "Application example 2 when combining emotion engines"

[2147] (Claim 1)

[2148] a means for users to input their information;

[2149] a system including a server that receives and processes the information;

[2150] means for generating a diet plan and an exercise menu based on the information;

[2151] means for providing the generated plans and menus to a user;

[2152] means for saving said plans and menus in a format desired by the user;

[2153] A means for analyzing user emotion data using emotion recognition technology;

[2154] means for adjusting a diet plan and exercise menu based on the user's emotional state;

[2155] A system including means for generating data for visually displaying daily progress and emotional state.

[2156] (Claim 2)

[2157] means for said user to input daily data;

[2158] means for receiving the daily data and managing progress;

[2159] means for adjusting the plan based on said progress and providing real-time feedback;

[2160] 10. The system of claim 1.

[2161] (Claim 3)

[2162] means for displaying said plans and menus in a graphical format;

[2163] means for providing said graphical data to a user;

[2164] means for providing the data in a form that is easy to visually understand;

[2165] 10. The system of claim 1. [Explanation of symbols]

[2166] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for users to input their information; a system including a server that receives and processes the information; means for generating a diet plan and an exercise menu based on the information; means for providing the generated plans and menus to a user; The system includes means for saving said plans and menus in a user-desired format.

2. means for said user to input daily data; means for receiving the daily data and managing progress; means for adjusting the plan based on said progress and providing feedback; The system of claim 1 .

3. means for displaying said plans and menus in a graphical format; means for providing said graphical data to a user; means for providing the data in a form that is easy to visually understand; The system of claim 1 .

Images