system

Abstract

Provide a system. The system includes a means for a user to input information such as dietary preferences, allergies, and health goals; A means for users to input food logs and exercise logs; means for transmitting the input data to a server; a means for storing the user data received by the server; A means for the server to use AI to generate a meal plan suitable for the user; means for transmitting the generated meal plan from the server to the terminal and displaying it to the user; A system including:

Description

[Technical Field]

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

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

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

[0004] In modern society, it is important to provide appropriate meal plans to maintain and improve the health of individuals. However, creating meal plans that take into account each user's preferences, allergies, and health goals is extremely difficult. Many existing services only provide general nutritional information and lack individualized support. This leaves users with a tendency to plan their meals in their own way, resulting in poor progress in improving their health. To address this issue, the present invention provides a system that provides optimal meal plans based on the user's individual information. [Means for solving the problem]

[0005] The present invention provides a system including means for users to input information such as food preferences, allergies, and health goals, means for users to input food logs and exercise logs, means for transmitting the input data to a server, means for the server to store the received user data, means for the server to use AI to generate a meal plan suited to the user, and means for transmitting the generated meal plan from the server to a terminal and displaying it to the user. The system of the present invention provides an optimized meal plan for each user, enabling effective maintenance and improvement of health.

[0006] A "user" is an individual who uses the system to input meal plans and exercise logs for the purpose of maintaining and improving their own health.

[0007] "Dietary preferences" refers to information that indicates an individual's likes and dislikes regarding specific ingredients and dishes.

[0008] An "allergy" is information that indicates that the immune system may overreact to certain foods, potentially causing adverse health effects.

[0009] "Health goals" are user inputs that refer to specific health goals that users want to achieve, such as weight loss, muscle gain, or blood sugar management.

[0010] A "food log" is information in which a user records their daily meals, including details such as the ingredients consumed, portions, and calories.

[0011] An "exercise log" is information in which a user records their daily exercise, including details such as the type of exercise performed, the time, and calories burned.

[0012] "Server" means a central processing unit for receiving, storing, and analyzing data sent by users.

[0013] "Analysis" is the process of evaluating the user's health status based on the data received by the server and identifying necessary nutrients and areas for improvement.

[0014] "Generative AI" is an artificial intelligence technology that takes a user's individual data as input parameters and generates an optimal meal plan.

[0015] A "meal plan" is a proposal that includes a specific meal menu and cooking instructions, generated by the AI ​​taking into account the user's preferences, allergies, and health goals.

[0016] A "terminal" is a hardware device, such as a smartphone, tablet, or wearable device, through which a user interfaces with the system. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention relates to a system for providing a meal plan for the purpose of maintaining and improving the health of a user. Specific embodiments of the system will be described below.

[0039] System Overview

[0040] This system consists of three main components: the user, the device, and the server. The user inputs their health data and preferences and sends them to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, which is then presented to the user via their device.

[0041] Program processing flow

[0042] 1. User enters basic information and goals

[0043] The user launches the application and creates an account.

[0044] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0045] 2. The user enters their daily diet and exercise log

[0046] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[0047] Users also record their exercise details (type of exercise, duration, and calories burned).

[0048] 3. The device sends the data to the server

[0049] The data entered by the user is sent from the device (smartphone or tablet) to the server.

[0050] 4. The server analyzes the data

[0051] The server stores the received user data in storage.

[0052] The server retrieves the user's past data from the database and evaluates and analyzes their current health condition.

[0053] 5. The server generates the meal plan

[0054] The server calls the generating AI and uses the user's dietary history, allergy information, and health goals as input parameters.

[0055] Generative AI generates optimal meal plans, taking into account nutritional balance and user preferences.

[0056] 6. Server notifies meal plan

[0057] The server sends the generated meal plan to the terminal.

[0058] 7. The device will display your plan.

[0059] The device (smartphone or tablet) displays the meal plan received from the server.

[0060] The user is provided with a specific meal menu and cooking instructions.

[0061] Specific examples

[0062] Enter user information

[0063] For example, User A creates an account and enters the following information:

[0064] Age: 30

[0065] Gender: Female

[0066] Height: 165 cm

[0067] Weight: 60 kg

[0068] Food preferences: Likes chicken and broccoli, dislikes eggplant

[0069] Allergies: Nut allergies

[0070] Health goal: weight loss

[0071] Daily Record

[0072] At the end of the day, User A opens the app and records the oatmeal and banana he ate for breakfast, the salad and grilled chicken for lunch, and the salmon steak and stir-fried vegetables for dinner. He also records a 30-minute run.

[0073] Server Analysis

[0074] The server analyzes User A's current nutritional intake and calorie consumption status based on their past data and newly entered data. Based on this, it identifies any nutrients that are lacking or elements that are being consumed in excess.

[0075] Generate a meal plan

[0076] The Generator AI takes User A's data as input parameters and generates the following meal plan:

[0077] Breakfast: Avocado toast and scrambled eggs

[0078] Lunch: Grilled chicken salad (broccoli, tomato, lettuce, creamy dressing)

[0079] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[0080] Notification and implementation of the plan

[0081] The meal plan generated by the server is sent to User A's device, and the app displays the plan. User A follows the suggested menu while looking at the app.

[0082] The above is a specific embodiment for carrying out the present invention. By using this system, a meal plan suited to each individual user can be provided, helping to maintain and improve health.

[0083] The processing flow will be explained below.

[0084] Step 1:

[0085] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0086] Step 2:

[0087] The user records their daily diet, specifically the names of ingredients, amounts, cooking methods, and calorie intake. At the same time, the user also records their exercise, including the type of exercise, duration, and calories burned.

[0088] Step 3:

[0089] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[0090] Step 4:

[0091] The server stores the received user data in a database. The server also stores the user's past data, and combines the new data with the past data for analysis.

[0092] Step 5:

[0093] The server retrieves the user's past data from the database and evaluates their current health status, comparing the data previously entered by the user with their current data to analyze their current nutritional intake and calorie consumption.

[0094] Step 6:

[0095] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The server evaluates the user's nutritional balance based on data supervised by nutritionists and general nutritional rules.

[0096] Step 7:

[0097] The server calls the AI ​​generator and passes the user's dietary history, allergy information, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[0098] Step 8:

[0099] The AI ​​generative system considers nutritional balance and proposes a different menu each day that matches the user's preferences. Specifically, it designs a meal plan that meets the user's needs for protein, vitamins, minerals, etc.

[0100] Step 9:

[0101] The server then formats the generated meal plan and sends it to the user's device as encrypted data, again using a secure protocol to keep the data safe.

[0102] Step 10:

[0103] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow.

[0104] Step 11:

[0105] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[0106] Step 12:

[0107] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[0108] In this way, this system works in cooperation between the server and the terminal based on the user's input data, and utilizes generative AI to provide the optimal meal plan for each individual user.

[0109] Example 1

[0110] 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."

[0111] Conventional meal plan providing systems have difficulty in fully considering the user's individual health condition, preferences, and allergy information. Furthermore, the quality and accuracy of the meal plans are low, making it difficult to provide optimal meal plans for users and achieving results. Furthermore, meal plans rarely change from day to day, making it difficult for users to maintain motivation to continue using the system.

[0112] 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.

[0113] In this invention, the server includes a means for analyzing the user's past data and newly acquired data, a means for generating a meal plan based on prompts using a generative AI model, and a means for assessing the user's health status using multiple data science techniques. This allows for the provision of highly accurate meal plans optimized for the user's health status. Furthermore, by proposing meal plans that change daily, the server can maintain the user's motivation and efficiently manage their health.

[0114] "Health information" refers to basic health data such as the user's age, gender, height, weight, allergies, and health goals.

[0115] "Dietary preferences" is information about the user's preferred ingredients, cooking methods, and ingredients to avoid.

[0116] "Allergy" is information indicating that the user has an allergic reaction to a specific food ingredient or component.

[0117] A "health goal" is a health-related goal that a user wants to achieve (e.g., weight loss, muscle gain, blood sugar management).

[0118] A "meal log" is data recorded by a user about the contents of their daily meals (food ingredients, portions, cooking methods, calorie intake).

[0119] An "exercise log" is data recorded by a user regarding the details of their daily exercise (type of exercise, duration, calories burned).

[0120] A "terminal" is a device (e.g., a smartphone or tablet) that a user uses to input data or receive data from a server.

[0121] A "server" is a computing device that analyzes data received from users and generates meal plans.

[0122] A "database" is an information management system that stores a user's past data and retrieves it as needed.

[0123] A "generative AI model" is an artificial intelligence technology that generates optimal meal plans based on user data.

[0124] A "prompt sentence" is an explanatory sentence that describes the user's health information, dietary history, etc. to be input into the generative AI model.

[0125] "Data science techniques" are statistical and machine learning methods used to assess and analyze a user's health status.

[0126] A "meal plan" is a specific meal menu and cooking instructions created taking into account the user's health condition and preferences.

[0127] This invention relates to a system that provides meal plans for users to maintain and improve their health. The system consists of three main components: a user, a terminal, and a server.

[0128] Users enter their health information, preferences, allergies, and health goals via their device. For example, a user uses a device (smartphone or tablet) to launch a health application and enter their age, gender, height, weight, food preferences, allergies, and health goals. Next, the user enters their daily food and exercise logs. For example, if they eat oatmeal for breakfast and go running, they record that information in the application. This data is sent from the device to the server. An HTTP POST request is used for transmission, and HTTPS communication is used to ensure data security.

[0129] The server stores the received data in a database and analyzes the user's past data and newly acquired data. Data analysis uses data science techniques such as Python and R. The server uses a generative AI model based on the analysis results to create prompts and generate a meal plan. Generative AI models such as ChatGPT (registered trademark) and OpenAI (registered trademark)'s GPT-4 (registered trademark) are used.

[0130] Here is an example prompt:

[0131] User Basic Information:

[0132] Age: 30

[0133] Gender: Female

[0134] Height: 165 cm

[0135] Weight: 60 kg

[0136] Food preferences: Likes chicken and broccoli, dislikes eggplant

[0137] Allergies: Nut allergies

[0138] Health goal: weight loss

[0139] User's diet history:

[0140] Breakfast: oatmeal and banana

[0141] Lunch: Salad, grilled chicken

[0142] Dinner: Salmon steak, stir-fried vegetables

[0143] User's exercise history:

[0144] Exercise: Running for 30 minutes

[0145] Based on this prompt, the generative AI model generates the optimal meal plan for the user. For example, the following meal plan might be generated:

[0146] Breakfast: Avocado toast and scrambled eggs

[0147] Lunch: Grilled Chin Salad (broccoli, tomato, lettuce, creamy dressing)

[0148] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[0149] The generated meal plan is sent from the server to the device, which then displays it to the user, along with specific meal menus and cooking instructions, allowing the user to prepare the meal.

[0150] By using this system, users can easily obtain the optimal meal plan for themselves and efficiently manage their health. Because the server performs the analysis and generation, the processing load is not placed on the device, providing a comfortable environment for users.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Step 1:

[0153] The user enters health information and goals.

[0154] Users launch a health application on their smartphone or tablet and enter their age, gender, height, weight, food preferences, allergies, and health goals. This data is collected using an input form on the device. The entered data is temporarily stored in local storage.

[0155] Input: Age, gender, height, weight, food preferences, allergies, health goals

[0156] Output: Health information data, goal data

[0157] Step 2:

[0158] The user inputs a daily food log and exercise log.

[0159] Users log in to the application to record their daily diet and exercise. For example, if they had oatmeal and a banana for breakfast and then went for a run, they would enter that information. The food log includes the ingredients, portion sizes, cooking methods, and calorie intake. The exercise log includes the type of exercise, time, and calories burned.

[0160] Input: Ingredient name, amount, cooking method, calorie intake, type of exercise, time, calories burned

[0161] Output: Food log data, exercise log data

[0162] Step 3:

[0163] The device sends the data to the server.

[0164] The device sends the data entered by the user to the server using an HTTP POST request, using HTTPS for secure communication. This request includes health information data, goal data, meal log data, and exercise log data.

[0165] Input: Health information data, goal data, food log data, exercise log data

[0166] Output: Data sent to the server

[0167] Step 4:

[0168] The server analyzes the data.

[0169] The server stores the received data in a database. It then compares the user's past data with the newly acquired data to assess their current health status. This is done using data science techniques such as Python and R. The server calculates nutrient deficiencies and excesses, as well as calorie balance.

[0170] Input: Data sent to the server, historical data

[0171] Output: Analysis result data (nutrient surplus / deficiency, calorie balance)

[0172] Step 5:

[0173] The server generates the meal plan.

[0174] The server calls the generative AI model and creates a prompt based on the analysis results. This prompt is then input into the generative AI model to generate the optimal meal plan for the user. ChatGPT and OpenAI's GPT-4 are used as generative AI models.

[0175] Input: Analysis result data

[0176] Output: Meal plan prompt, generated meal plan

[0177] Step 6:

[0178] The server will notify you of the meal plan.

[0179] The server sends the generated meal plan to the device using an HTTP POST request, allowing the user to receive the updated meal plan.

[0180] Input: Generated meal plan

[0181] Output: Meal plan sent to device

[0182] Step 7:

[0183] The device will display the plan.

[0184] The device displays the meal plan received from the server to the user, and when the user opens the application, a specific menu and cooking instructions are displayed on the screen.

[0185] Input: Meal plan sent to device

[0186] Output: A specific meal plan and cooking instructions displayed to the user

[0187] The above are the specific processing steps of the system program, which allow users to efficiently obtain a meal plan that suits them and manage their health.

[0188] (Application example 1)

[0189] 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."

[0190] In modern society, the growing health consciousness has led to an increased importance of personalized dietary management. However, there is no easy way to obtain a meal plan that suits each individual's dietary preferences, allergies, and health goals, and then easily implement the meals based on that plan. Furthermore, there is a lack of sufficient coordination between the proposal of a meal plan and the actual delivery of the meal, which requires users to go through complicated procedures. Furthermore, there are insufficient means for users to track the progress of their meal or the delivery status.

[0191] 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.

[0192] In this invention, the server includes: a means for a user to input information such as dietary preferences, allergies, and health goals; a means for the user to input a meal log and exercise log; a means for transmitting the input data to a data center; a means for the data center to store the received user data; a means for the data center to generate a meal plan suitable for the user using a generative AI model; a means for transmitting the generated meal plan from the data center to a terminal and displaying it to the user; a means for a delivery service to suggest an optimal menu based on the generated meal plan; and a means for tracking delivery progress in real time and notifying the user. This allows users to quickly obtain an individually optimized meal plan and easily purchase meals based on it. Furthermore, knowing the delivery progress in real time improves convenience.

[0193] "User" refers to an individual who intends to use the system to manage their health.

[0194] "Dietary preferences" is information about ingredients and dishes that the user likes.

[0195] "Allergy" refers to a food ingredient or ingredient that is harmful to the user's health if ingested.

[0196] "Health goal" refers to a specific health or fitness goal that a user wishes to achieve.

[0197] A "meal log" is data that allows a user to record the contents of their daily meals.

[0198] An "exercise log" is data that allows a user to record the details of their daily exercise.

[0199] "Data Center" refers to a computer system for storing user data and for performing analysis and plan generation.

[0200] "Generative AI model" refers to artificial intelligence technology that automatically generates optimal meal plans based on user information.

[0201] A "meal plan" is a plan that takes into consideration specific meal menus and nutritional balance proposed to the user.

[0202] "Terminal" refers to the device through which a user enters information and receives meal plans.

[0203] "Delivery Service" refers to the logistics and distribution system for delivering meals to users.

[0204] "Delivery progress" refers to the process and progress of the meal being delivered to the user.

[0205] The present invention is a system for generating an individually optimized meal plan based on a user's health condition and preferences, and then reliably providing meals based on that plan. This system is mainly composed of three elements: the user, a terminal, and a data center.

[0206] Hardware and Software

[0207] Hardware:

[0208] Device: refers to a smartphone or tablet, which is the device through which the user enters information and receives the meal plan.

[0209] Data center: A group of servers that processes and analyzes information, and typically uses cloud services (e.g., AWS (registered trademark) or Google (registered trademark) Cloud Platform).

[0210] software:

[0211] Generative AI models: Use artificial intelligence (e.g., generative AI models such as GPT-4) to generate personalized, optimized meal plans.

[0212] Database: Use a database such as SQL or NoSQL to manage and store user information.

[0213] Process Overview

[0214] 1. The user enters basic information, preferences, and allergies

[0215] Users enter basic information such as age, gender, height, weight, food preferences, allergies, and health goals through the terminal, which is then sent to a data center.

[0216] 2. Enter your daily food log

[0217] Users record their daily diet and exercise logs, and this data is also sent to a data center.

[0218] 3. Data storage and analysis

[0219] The data center stores and analyzes the received user data, including the user's past data, to assess the user's health status.

[0220] 4. Generative AI Meal Plan Generation

[0221] The data center generates an individually optimized meal plan by inputting user data into a generative AI model, specifically using prompts such as:

[0222] (Example of a prompt)

[0223] Generate a daily meal plan based on your health data.

[0224] Age: 30

[0225] Gender: Female

[0226] Height: 165 cm

[0227] Weight: 60 kg

[0228] Preferences: Likes chicken and broccoli, dislikes eggplant

[0229] Allergies: Nut allergies

[0230] Health goal: weight loss

[0231] 5. Send and view your meal plan

[0232] The generated meal plan is sent from the data center to the user's device, where the user can review it. The delivery service also suggests optimal menus based on the meal plan.

[0233] 6. Track delivery progress

[0234] Users can track delivery progress in real time and check the progress on their devices.

[0235] This system allows users to easily obtain individually optimized meal plans and efficiently manage their health based on those plans. In addition, delivery progress can be monitored in real time, improving user convenience.

[0236] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0237] Step 1:

[0238] The user enters basic information, preferences, and allergies.

[0239] Input: Age, Gender, Height, Weight, Food Preferences, Allergies, Health Goals.

[0240] How it works: The user enters this information into the application through a terminal.

[0241] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[0242] Step 2:

[0243] The user inputs a daily food log and exercise log.

[0244] Input: Daily dietary information (ingredients, amounts, cooking methods), calorie intake, exercise information (type of exercise, time, calories burned).

[0245] How it works: The user uses the device to record and enter their daily diet and exercise log.

[0246] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[0247] Step 3:

[0248] The device sends the data to the data center.

[0249] Input: User data entered in step 1 and step 2.

[0250] How it works: The device sends stored user data over the internet to a data center.

[0251] Output: The data center receives the user data and stores it in a database.

[0252] Step 4:

[0253] The server evaluates the current health status based on the data received.

[0254] Input: User's basic information, preferences, allergies, daily food log, and exercise log.

[0255] How it works: The server analyzes your current nutritional intake and calorie consumption status based on past data stored in a database. Specifically, it retrieves the data using SQL queries and applies analysis algorithms.

[0256] Output: An assessment of the user's current health status and nutrient and calorie needs.

[0257] Step 5:

[0258] Generate meal plans using generative AI models.

[0259] Input: Health assessment results, user demographics, preferences, allergies, and health goals.

[0260] How it works: The server sends prompts to a generative AI model (e.g., GPT-4) to generate an optimal meal plan.

[0261] Example prompt sentence:

[0262] Generate a daily meal plan based on your health data.

[0263] Age: 30

[0264] Gender: Female

[0265] Height: 165 cm

[0266] Weight: 60 kg

[0267] Preferences: Likes chicken and broccoli, dislikes eggplant

[0268] Allergies: Nut allergies

[0269] Health goal: weight loss

[0270] Output: A specific meal plan tailored to the user (e.g., breakfast, lunch, and dinner menus).

[0271] Step 6:

[0272] The generated meal plan is sent to the terminal and displayed to the user.

[0273] Input: A meal plan generated from a generative AI model.

[0274] Operation: The server sends the generated meal plan to the device.

[0275] Output: The meal plan is displayed on the user's device. The user confirms the suggested menu.

[0276] Step 7:

[0277] The delivery service will suggest the best menu based on the generated meal plan.

[0278] Input: Meal plan and delivery preferences set by the user.

[0279] How it works: Based on your meal plan, the server will select and suggest the best items from the menu offered by the delivery service.

[0280] Output: Delivery menu suggestions are displayed on the user's device.

[0281] Step 8:

[0282] Track delivery progress in real time and notify users.

[0283] Input: The progress of the delivery ordered by the user.

[0284] How it works: The server receives progress information from the delivery service and notifies the device.

[0285] Output: Delivery progress is displayed in real time on the user's device.

[0286] 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.

[0287] The present invention combines an emotion engine with a system that provides meal plans aimed at maintaining and improving the user's health. Specific embodiments of the system are described below.

[0288] System Overview

[0289] This system consists of three main components: the user, the device, and the server. The user inputs their health data, preferences, and emotional state, which are then sent to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, then adjusts the plan using an emotion engine. The plan is then finally presented to the user via their device.

[0290] Program processing flow

[0291] 1. Enter user information

[0292] The user launches the application and creates an account.

[0293] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0294] 2. Entering Emotion Data

[0295] Users input their emotional state in real time, based on their reactions to daily events and meals.

[0296] Emotions come in categories such as happy, sad, stressed, and relaxed.

[0297] 3. The user enters their daily diet and exercise log

[0298] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[0299] Users also record their exercise details (type of exercise, duration, and calories burned).

[0300] 4. Data Transmission

[0301] The terminal encrypts the data entered by the user and sends it to the server. All communication is carried out using a secure protocol to ensure data confidentiality.

[0302] 5. Server Analysis

[0303] The server stores the received user data in a database and analyzes it.

[0304] The server retrieves the user's past data from the database and uses it to evaluate their current health condition.

[0305] 6. Meal plan generation

[0306] The server calls the generation AI and passes the user's dietary history, allergy information, emotional state, and health goals as input parameters.

[0307] Generative AI uses this data to generate an optimal meal plan.

[0308] 7. Use of Emotion Engines

[0309] An emotion engine analyzes the user's emotional data and adjusts the generated meal plan.

[0310] For example, if a user is feeling stressed, a menu containing ingredients with a high relaxing effect is suggested.

[0311] The emotion engine assesses the user's motivation to achieve their health goals and stress level, and provides encouraging messages and advice accordingly.

[0312] 8. Transmission and Display

[0313] The server then sends the final adjusted meal plan to the device, again using a secure protocol.

[0314] The device displays the received meal plan and encouraging messages to the user.

[0315] Specific examples

[0316] Enter user information

[0317] For example, User B creates an account and enters the following information:

[0318] Age: 28

[0319] Gender: Male

[0320] Height: 175 cm

[0321] Weight: 70 kg

[0322] Favorite ingredients: chicken, spinach, tomatoes

[0323] Disliked food: Celery

[0324] Allergens: Wheat

[0325] Health Goal: Muscle Gain

[0326] Entering emotion data

[0327] User B enters their daily physical and emotional state in categories such as "stress," "relaxation," and "happiness."

[0328] Daily Record

[0329] User B records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner. He also trains at the gym and records his exercise schedule.

[0330] Server Analysis and Plan Generation

[0331] The server analyzes nutritional balance based on User B's data, and the AI ​​generates a meal plan. Based on this, the emotion engine suggests additional menu items with a relaxing effect on days when the user feels stressed.

[0332] Meal plan notification and implementation

[0333] The generated plan and advice based on emotions are sent to the device and displayed in User B's app. User B follows this advice and eats accordingly, then enters feedback.

[0334] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to provide an appropriate and effective meal plan that also takes into account the emotional state of each individual user.

[0335] The processing flow will be explained below.

[0336] Step 1:

[0337] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0338] Step 2:

[0339] The user inputs their emotional state, specifically their reactions to daily events and meals, in categories such as "happy," "sad," "stressed," and "relaxed."

[0340] Step 3:

[0341] The user records the contents of their daily meals, specifically the names of ingredients, amounts, cooking methods, calorie intake, etc. They also record exercise, entering the type, duration, and calories burned.

[0342] Step 4:

[0343] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[0344] Step 5:

[0345] The server stores the received user data in a database, and then integrates the user's past data with new data for analysis.

[0346] Step 6:

[0347] The server retrieves the user's past data from the database and evaluates their current health condition, which is then used to analyze their current nutritional intake and calorie consumption.

[0348] Step 7:

[0349] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The analysis uses data supervised by nutritionists and general nutritional rules.

[0350] Step 8:

[0351] The server calls the AI ​​generator, which uses the user's dietary history, allergy information, emotional state, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[0352] Step 9:

[0353] The emotion engine analyzes the user's emotional data. Specifically, the emotion engine evaluates the user's emotional state and adjusts the generated meal plan as needed. For example, if the user is feeling stressed, the engine will suggest a menu containing ingredients that will reduce stress.

[0354] Step 10:

[0355] The server then formats the meal plan tailored by the emotion engine and sends it to the device as encrypted data, again using a secure protocol to keep the data safe.

[0356] Step 11:

[0357] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow. Encouraging messages and advice generated by the emotion engine are also displayed.

[0358] Step 12:

[0359] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[0360] Step 13:

[0361] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[0362] This process allows the system to provide appropriate and effective meal plans that take into account each user's emotional state.

[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] Many people today find it difficult to balance health management and diet. It is also difficult to independently determine the optimal meal plan that corresponds to one's health and emotional state. Even if a meal plan is appropriate, it can be difficult to adhere to due to the influence of emotions and stress. To solve these problems, a system is needed that takes into account each user's health data and daily emotional state and provides the optimal meal plan.

[0366] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0367] In this invention, the server includes: means for the user to input information such as food preferences, allergies, and health goals; means for the user to input daily emotional data and a meal log and exercise log; means for encrypting the input data and sending it to the server; means for the server to store the user data received; means for the server to generate a meal plan suitable for the user using an artificial intelligence model; means for the emotion engine to adjust the meal plan based on the user's emotional data; and means for sending the generated meal plan from the server to a terminal and displaying it to the user. This makes it possible to provide an optimal meal plan that takes into consideration the health and emotional state of each individual user.

[0368] A "user" is an individual who uses the system and inputs health data and emotion data.

[0369] "Dietary preferences" refers to the types of ingredients and dishes that a user likes to eat.

[0370] "Allergy" refers to a health problem that occurs when a user ingests a particular food ingredient.

[0371] A "health goal" refers to a specific health goal that a user wants to achieve, such as losing weight or gaining muscle.

[0372] "Emotion data" is data that indicates the user's daily emotional state, including states such as stress, relaxation, and happiness.

[0373] A "meal log" is data in which a user records the contents of their daily meals, and includes the names of ingredients, portions, calories, etc.

[0374] An "exercise log" is data in which a user records the details of their daily exercise, including the type of exercise, time, calories burned, and so on.

[0375] "Encryption" refers to a technique for converting transmitted data into a format that cannot be deciphered by third parties.

[0376] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates and sends meal plans.

[0377] An "artificial intelligence model" refers to a computational model that learns from large amounts of data and generates meal plans that are suitable for the user.

[0378] "Emotion engine" refers to a system that analyzes a user's emotional data and adjusts meal plans based on the results.

[0379] "Terminal" refers to a device through which a user can input data and display meal plans received from a server.

[0380] This invention is a system that provides meal plans for users to maintain and improve their health, and is combined with an emotion engine. In this embodiment, it operates through three main elements: the user, the terminal, and the server.

[0381] System Configuration

[0382] Enter user information

[0383] First, users install the dedicated application and create an account. The information they enter includes basic information (age, gender, height, weight), food preferences, allergies, and health goals. The application collects this information through a GUI.

[0384] Entering emotion data

[0385] Next, users input their daily emotional data into the application. Emotional states are presented in categories such as "stress," "relaxed," and "happy," and users can select their daily emotional state and add comments.

[0386] Enter your daily diet and exercise log

[0387] Users input their daily dietary information (ingredients, portions, calories, cooking methods) and exercise information (type of exercise, time, calories burned) into the application, which updates the user's health data daily.

[0388] Data transmission

[0389] The device encrypts the collected data using AES encryption and transmits it securely to the server via the HTTPS protocol, ensuring the confidentiality of the data.

[0390] Server Analysis

[0391] The server stores the received data in a database and analyzes the user's current health status based on their past data. The server also uses an artificial intelligence (AI) model to generate an optimal meal plan for the user. The generated plan is adjusted according to the user's stress level and relaxation state by analyzing the user's emotional data using an emotion engine.

[0392] View Meal Plans

[0393] Finally, the server sends the tailored meal plan to the device, where the application displays it to the user, including encouraging messages and advice tailored to the user's emotional state.

[0394] Specific examples

[0395] User B creates an account and enters the following information:

[0396] Age: 28

[0397] Gender: Male

[0398] Height: 175 cm

[0399] Weight: 70 kg

[0400] Favorite ingredients: chicken, spinach, tomatoes

[0401] Disliked food: Celery

[0402] Allergens: Wheat

[0403] Health Goal: Muscle Gain

[0404] When inputting daily emotional data, User B inputs his / her daily emotional state such as "stress," "relaxation," or "happiness."

[0405] I eat oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner, and I record each of them in the app. I also enter my gym workouts.

[0406] The server analyzes this data, and a generative AI model generates a meal plan. The emotion engine suggests additional ingredients with a relaxing effect (e.g., herbal tea) on stressful days.

[0407] Finally, the adjusted meal plan and emotion-based advice are sent to the device and displayed in User B's app, where User B follows the plan and provides feedback.

[0408] Prompt Sentence Examples

[0409] Generate a meal plan that suggests foods that will have a relaxing effect on the user's stressful days. The user's information is: age 28, male, 175cm, 70kg, favorite foods are chicken, spinach, and tomato, dislikes are celery, wheat allergy, and health goal is to gain muscle.

[0410] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0411] Step 1:

[0412] A user creates an account and enters basic information.

[0413] Input: Install the application and enter user information (age, gender, height, weight, favorite ingredients, disliked ingredients, allergies, health goals).

[0414] Output: The user information is saved on the device.

[0415] Specific operation: The user downloads and installs the application, then creates an account by entering an email address and password, and enters basic information.

[0416] Step 2:

[0417] The user inputs daily emotion data.

[0418] Input: Enter your emotional state (stressed, relaxed, happy, etc.) and any related comments.

[0419] Output: Emotion data is saved on the device.

[0420] Specific operation: The user opens the application, selects their current emotional state on the emotion input screen, and optionally adds a comment.

[0421] Step 3:

[0422] The user inputs a daily food log and exercise log.

[0423] Input: Enter the meal details (ingredients, amount, cooking method, calories) and exercise details (type of exercise, time, calories burned).

[0424] Output: Food log and exercise log are saved on the device.

[0425] Specific operation: The user opens the application, enters the names of ingredients, amounts, cooking methods, and calories on the meal input screen, and enters the type of exercise, time, and calories burned on the exercise input screen.

[0426] Step 4:

[0427] The device encrypts the data and sends it to the server.

[0428] Input: Obtain user information, emotional data, food log, and exercise log.

[0429] Output: The encrypted data is sent to the server.

[0430] Specific operation: The terminal encrypts the data using the AES encryption algorithm and sends it to the server via the HTTPS protocol.

[0431] Step 5:

[0432] The server stores the received data in a database.

[0433] Input: Encrypted data is sent to the server.

[0434] Output: Encrypted data stored in the database.

[0435] Specific operation: The server decrypts the received data and stores it in a database, classifying it by user.

[0436] Step 6:

[0437] The server compares the current health status with past data and analyzes it.

[0438] Input: Retrieves past data in the database and newly received data.

[0439] Output: The analysis results are obtained.

[0440] How it works: The server compares past user data with new data and uses statistical algorithms to assess current health status.

[0441] Step 7:

[0442] The server calls the generation AI to generate a meal plan.

[0443] Input: Obtain user information, emotional data, food log, exercise log, and health status analysis results.

[0444] Output: An optimal meal plan is generated.

[0445] Specific operation: The server provides the necessary parameters to the generative AI model, allowing it to generate the optimal meal plan for the user.

[0446] Step 8:

[0447] An emotion engine adjusts meal plans based on the user's emotional data.

[0448] Input: Obtain the generated meal plan and the user's sentiment data.

[0449] Output: You get a tailored meal plan.

[0450] Specific operation: The emotion engine analyzes the user's emotional data and adds menus that have stress-reducing or relaxing effects as needed.

[0451] Step 9:

[0452] The server sends the final meal plan to the device.

[0453] Enter: Get your tailored meal plan.

[0454] Output: The encrypted meal plan is sent to the device.

[0455] How it works: The server encrypts the meal plan using AES encryption and sends it to the device via HTTPS protocol.

[0456] Step 10:

[0457] The device displays the meal plan to the user.

[0458] Enter: Get your encrypted meal plan.

[0459] Output: The meal plan is displayed to the user.

[0460] Specific operation: The device decodes the received data and displays the meal plan in an easy-to-understand format for the user in the application.

[0461] (Application example 2)

[0462] 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."

[0463] While conventional meal plan providing systems can take into account a user's health condition and preferences, they have the problem of not being able to incorporate the user's emotional state. As a result, it is difficult to provide an appropriate meal plan even when the user is feeling stressed or tired. Furthermore, there has been no system that seamlessly links to providing specific meal menus based on the generated meal plan. This makes it difficult for users to easily incorporate optimal meals and to continuously manage their health.

[0464] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0465] In this invention, the server includes means for generating a meal plan suitable for the user using a generative AI model, means for adjusting the meal plan using an emotion engine, and means for providing a menu based on the meal plan to the user in cooperation with an external service. This makes it possible to generate an optimal meal plan that takes the user's emotional state into consideration, and to seamlessly present and provide a specific menu based on the meal plan.

[0466] "User" means an individual who uses the System to receive a Meal Plan.

[0467] "Dietary preferences" refers to information about the ingredients and dishes that a user likes to eat.

[0468] "Allergy" refers to information that indicates a user has an allergic reaction to a particular food ingredient.

[0469] "Health Goal" means a health or fitness goal that a User wishes to achieve.

[0470] "Data" refers to information entered by the user, such as food preferences, allergies, health goals, food logs, and exercise logs.

[0471] "Food log" refers to data used by a user to record the meals they eat each day.

[0472] "Exercise log" refers to data that records the exercise a user has performed and the calories they have burned.

[0473] "Generative AI model" refers to an artificial intelligence model that generates optimal meal plans based on user data.

[0474] "Emotion Engine" refers to an algorithm that analyzes a user's emotional state and adjusts their meal plan.

[0475] "External Services" refers to service providers and stores that cooperate with us to provide specific menus based on the meal plan.

[0476] "Server" refers to the computing resources that store the data submitted by the user and generate meal plans using the generative AI model and emotion engine.

[0477] "Terminal" means the electronic device used by a User to enter data and view meal plans.

[0478] System Overview

[0479] The system of the present invention is composed of three main elements: a user, a terminal, and a server. The details of each element and their roles are explained below.

[0480] User

[0481] Users input information such as their food preferences, allergies, and health goals through the device, as well as daily food and exercise logs. Furthermore, their emotional state is recorded and sent to the system.

[0482] Terminal

[0483] The terminal functions as a user interface and is an electronic device such as a smartphone or tablet. A dedicated application is available on the terminal, allowing the user to input and send their own data. The input data is encrypted and sent to the server. The terminal also displays meal plans and related messages sent from the server.

[0484] server

[0485] The server is responsible for storing and analyzing data received from users. The server has the following main functions:

[0486] Generative AI model: Generates optimal meal plans based on a user's dietary history, allergy information, and health goals.

[0487] Emotion engine: Analyzes the user's emotional data and adjusts the generated meal plan. For example, if the user is feeling stressed, the generative AI model will add menu items containing ingredients with a relaxing effect to the plan it suggests.

[0488] External service integration: Collaborate with a food delivery service to provide specific menus based on the generated meal plan.

[0489] Program processing

[0490] The server analyzes the data using AI models and emotion engines. Specifically, it performs the following steps:

[0491] 1. Receiving and storing data: We receive and securely store data sent by users.

[0492] 2. Health status assessment: Retrieve historical data from the database and assess current health status.

[0493] 3. Meal plan generation: Have the generative AI model generate an optimal meal plan using a prompt, such as:

[0494] "

[0495] Age: 28

[0496] Gender: Male

[0497] Health Goal: Muscle Gain

[0498] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[0499] Emotional state: Stress

[0500] Allergens: Wheat

[0501] Favorites: Chicken, spinach, tomatoes

[0502] Dislikes: Celery

[0503] "

[0504] 4. Adjustment by the emotion engine: The emotion engine further adjusts the generated plan, for example, adding ingredients that have a relaxing effect if you are feeling stressed.

[0505] 5. Send Final Plan: The final, adjusted meal plan is sent to the device, again using secure protocols for all communications.

[0506] 6. Notification and Display: The device displays the received meal plan and encouraging messages to the user.

[0507] Specific examples

[0508] As a real-world example, User B creates an account and enters the following information:

[0509] Age: 28

[0510] Gender: Male

[0511] Height: 175 cm

[0512] Weight: 70 kg

[0513] Favorite ingredients: Chicken, spinach, tomatoes

[0514] Disliked food: Celery

[0515] Allergens: Wheat

[0516] Health Goal: Muscle Gain

[0517] User B enters "stress" as his emotional state and records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner in his food log. Based on this, the server uses the generative AI model and emotion engine to generate an optimal meal plan and sends the final plan to User B's device. User B can then use food delivery services based on the plan and manage his or her health.

[0518] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0519] Step 1:

[0520] Input: The user inputs information such as food preferences, allergies, health goals, food log, exercise log, and emotional state into the device.

[0521] Specific operation: The user launches the application and enters information into the form. For example, the user might enter "My favorite foods are chicken, spinach, and tomatoes" as their preference information, "I'm allergic to wheat" as their allergy information, and "I want to gain muscle mass" as their health goal.

[0522] Output: The terminal formats the input data and converts it into a format that can be sent to the server.

[0523] Step 2:

[0524] Input: Data entered by the user.

[0525] Specific operation: The terminal encrypts the input data and sends it to the server using a secure protocol (e.g., HTTPS).

[0526] Output: The server stores the received data in a database.

[0527] Step 3:

[0528] Input: Encrypted data sent from the device.

[0529] What it does: The server decrypts the encrypted data and stores it in a database, ensuring your information is stored securely.

[0530] Output: A saved dataset.

[0531] Step 4:

[0532] Input: User preferences, allergies, health goals, and past food and exercise log data.

[0533] What it does: The server takes this data and provides input to the generative AI model as a prompt, like this:

[0534] "

[0535] Age: 28

[0536] Gender: Male

[0537] Health Goal: Muscle Gain

[0538] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[0539] Emotional state: Stress

[0540] Allergens: Wheat

[0541] Favorites: Chicken, spinach, tomatoes

[0542] Dislikes: Celery

[0543] "

[0544] The generative AI model uses this information to generate an optimal meal plan.

[0545] Output: The generated meal plan.

[0546] Step 5:

[0547] Input: A meal plan generated by a generative AI model.

[0548] What it does: The server passes the meal plan to the emotion engine, which fine-tunes it based on the user's emotional state. For example, if the user is rated as "stressed," the server adjusts the menu to include ingredients with a relaxing effect (e.g., herbal tea and bananas).

[0549] Output: Adjusted final meal plan.

[0550] Step 6:

[0551] Input: Your adjusted final meal plan.

[0552] Specific operation: The server sends the final plan to an external food delivery service. Based on the previously adjusted plan, it proposes specific meal menus and allows the user to select and order.

[0553] Output: The final meal plan sent to the user's device, along with a link to the food delivery service.

[0554] Step 7:

[0555] Input: Final meal plan and food delivery link sent by the server.

[0556] What it does: The device notifies the user and displays the menu within the app, allowing the user to view the menu and order delivery with a single click.

[0557] Output: The user has viewed and ordered from the health-conscious menu.

[0558] 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.

[0559] 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 (registered trademark) (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.

[0560] 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.

[0561] [Second embodiment]

[0562] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0563] 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.

[0564] 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).

[0565] 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.

[0566] 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.

[0567] 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).

[0568] 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. 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.

[0569] 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.

[0570] 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.

[0571] 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.

[0572] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0573] 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."

[0574] The present invention relates to a system for providing a meal plan for the purpose of maintaining and improving the health of a user. Specific embodiments of the system will be described below.

[0575] System Overview

[0576] This system consists of three main components: the user, the device, and the server. The user inputs their health data and preferences and sends them to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, which is then presented to the user via their device.

[0577] Program processing flow

[0578] 1. User enters basic information and goals

[0579] The user launches the application and creates an account.

[0580] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0581] 2. The user enters their daily diet and exercise log

[0582] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[0583] Users also record their exercise details (type of exercise, duration, and calories burned).

[0584] 3. The device sends the data to the server

[0585] The data entered by the user is sent from the device (smartphone or tablet) to the server.

[0586] 4. The server analyzes the data

[0587] The server stores the received user data in storage.

[0588] The server retrieves the user's past data from the database and evaluates and analyzes their current health condition.

[0589] 5. The server generates the meal plan

[0590] The server calls the generating AI and uses the user's dietary history, allergy information, and health goals as input parameters.

[0591] Generative AI generates optimal meal plans, taking into account nutritional balance and user preferences.

[0592] 6. Server notifies meal plan

[0593] The server sends the generated meal plan to the terminal.

[0594] 7. The device will display your plan.

[0595] The device (smartphone or tablet) displays the meal plan received from the server.

[0596] The user is provided with a specific meal menu and cooking instructions.

[0597] Specific examples

[0598] Enter user information

[0599] For example, User A creates an account and enters the following information:

[0600] Age: 30

[0601] Gender: Female

[0602] Height: 165 cm

[0603] Weight: 60 kg

[0604] Food preferences: Likes chicken and broccoli, dislikes eggplant

[0605] Allergies: Nut allergies

[0606] Health goal: weight loss

[0607] Daily Record

[0608] At the end of the day, User A opens the app and records the oatmeal and banana he ate for breakfast, the salad and grilled chicken for lunch, and the salmon steak and stir-fried vegetables for dinner. He also records a 30-minute run.

[0609] Server Analysis

[0610] The server analyzes User A's current nutritional intake and calorie consumption status based on their past data and newly entered data. Based on this, it identifies any nutrients that are lacking or elements that are being consumed in excess.

[0611] Generate a meal plan

[0612] The Generator AI takes User A's data as input parameters and generates the following meal plan:

[0613] Breakfast: Avocado toast and scrambled eggs

[0614] Lunch: Grilled chicken salad (broccoli, tomato, lettuce, creamy dressing)

[0615] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[0616] Notification and implementation of the plan

[0617] The meal plan generated by the server is sent to User A's device, and the app displays the plan. User A follows the suggested menu while looking at the app.

[0618] The above is a specific embodiment for carrying out the present invention. By using this system, a meal plan suited to each individual user can be provided, helping to maintain and improve health.

[0619] The processing flow will be explained below.

[0620] Step 1:

[0621] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0622] Step 2:

[0623] The user records their daily diet, specifically the names of ingredients, amounts, cooking methods, and calorie intake. At the same time, the user also records their exercise, including the type of exercise, duration, and calories burned.

[0624] Step 3:

[0625] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[0626] Step 4:

[0627] The server stores the received user data in a database. The server also stores the user's past data, and combines the new data with the past data for analysis.

[0628] Step 5:

[0629] The server retrieves the user's past data from the database and evaluates their current health status, comparing the data previously entered by the user with their current data to analyze their current nutritional intake and calorie consumption.

[0630] Step 6:

[0631] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The server evaluates the user's nutritional balance based on data supervised by nutritionists and general nutritional rules.

[0632] Step 7:

[0633] The server calls the AI ​​generator and passes the user's dietary history, allergy information, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[0634] Step 8:

[0635] The AI ​​generative system considers nutritional balance and proposes a different menu each day that matches the user's preferences. Specifically, it designs a meal plan that meets the user's needs for protein, vitamins, minerals, etc.

[0636] Step 9:

[0637] The server then formats the generated meal plan and sends it to the user's device as encrypted data, again using a secure protocol to keep the data safe.

[0638] Step 10:

[0639] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow.

[0640] Step 11:

[0641] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[0642] Step 12:

[0643] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[0644] In this way, this system works in cooperation between the server and the terminal based on the user's input data, and utilizes generative AI to provide the optimal meal plan for each individual user.

[0645] Example 1

[0646] 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."

[0647] Conventional meal plan providing systems have difficulty in fully considering the user's individual health condition, preferences, and allergy information. Furthermore, the quality and accuracy of the meal plans are low, making it difficult to provide optimal meal plans for users and achieving results. Furthermore, meal plans rarely change from day to day, making it difficult for users to maintain motivation to continue using the system.

[0648] 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.

[0649] In this invention, the server includes a means for analyzing the user's past data and newly acquired data, a means for generating a meal plan based on prompts using a generative AI model, and a means for assessing the user's health status using multiple data science techniques. This allows for the provision of highly accurate meal plans optimized for the user's health status. Furthermore, by proposing meal plans that change daily, the server can maintain the user's motivation and efficiently manage their health.

[0650] "Health information" refers to basic health data such as the user's age, gender, height, weight, allergies, and health goals.

[0651] "Dietary preferences" is information about the user's preferred ingredients, cooking methods, and ingredients to avoid.

[0652] "Allergy" is information indicating that the user has an allergic reaction to a specific food ingredient or component.

[0653] A "health goal" is a health-related goal that a user wants to achieve (e.g., weight loss, muscle gain, blood sugar management).

[0654] A "meal log" is data recorded by a user about the contents of their daily meals (food ingredients, portions, cooking methods, calorie intake).

[0655] An "exercise log" is data recorded by a user regarding the details of their daily exercise (type of exercise, duration, calories burned).

[0656] A "terminal" is a device (e.g., a smartphone or tablet) that a user uses to input data or receive data from a server.

[0657] A "server" is a computing device that analyzes data received from users and generates meal plans.

[0658] A "database" is an information management system that stores a user's past data and retrieves it as needed.

[0659] A "generative AI model" is an artificial intelligence technology that generates optimal meal plans based on user data.

[0660] A "prompt sentence" is an explanatory sentence that describes the user's health information, dietary history, etc. to be input into the generative AI model.

[0661] "Data science techniques" are statistical and machine learning methods used to assess and analyze a user's health status.

[0662] A "meal plan" is a specific meal menu and cooking instructions created taking into account the user's health condition and preferences.

[0663] This invention relates to a system that provides meal plans for users to maintain and improve their health. The system consists of three main components: a user, a terminal, and a server.

[0664] Users enter their health information, preferences, allergies, and health goals via their device. For example, a user uses a device (smartphone or tablet) to launch a health application and enter their age, gender, height, weight, food preferences, allergies, and health goals. Next, the user enters their daily food and exercise logs. For example, if they eat oatmeal for breakfast and go running, they record that information in the application. This data is sent from the device to the server. An HTTP POST request is used for transmission, and HTTPS communication is used to ensure data security.

[0665] The server stores the received data in a database and analyzes the user's past data and newly acquired data. Data analysis uses data science techniques such as Python and R. Based on the analysis results, the server uses a generative AI model to create prompts and generate meal plans. Generative AI models such as ChatGPT and OpenAI's GPT-4 are used.

[0666] Here is an example prompt:

[0667] User Basic Information:

[0668] Age: 30

[0669] Gender: Female

[0670] Height: 165 cm

[0671] Weight: 60 kg

[0672] Food preferences: Likes chicken and broccoli, dislikes eggplant

[0673] Allergies: Nut allergies

[0674] Health goal: weight loss

[0675] User's diet history:

[0676] Breakfast: oatmeal and banana

[0677] Lunch: Salad, grilled chicken

[0678] Dinner: Salmon steak, stir-fried vegetables

[0679] User's exercise history:

[0680] Exercise: Running for 30 minutes

[0681] Based on this prompt, the generative AI model generates the optimal meal plan for the user. For example, the following meal plan might be generated:

[0682] Breakfast: Avocado toast and scrambled eggs

[0683] Lunch: Grilled Chin Salad (broccoli, tomato, lettuce, creamy dressing)

[0684] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[0685] The generated meal plan is sent from the server to the device, which then displays it to the user, along with specific meal menus and cooking instructions, allowing the user to prepare the meal.

[0686] By using this system, users can easily obtain the optimal meal plan for themselves and efficiently manage their health. Because the server performs the analysis and generation, the processing load is not placed on the device, providing a comfortable environment for users.

[0687] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0688] Step 1:

[0689] The user enters health information and goals.

[0690] Users launch a health application on their smartphone or tablet and enter their age, gender, height, weight, food preferences, allergies, and health goals. This data is collected using an input form on the device. The entered data is temporarily stored in local storage.

[0691] Input: Age, gender, height, weight, food preferences, allergies, health goals

[0692] Output: Health information data, goal data

[0693] Step 2:

[0694] The user inputs a daily food log and exercise log.

[0695] Users log in to the application to record their daily diet and exercise. For example, if they had oatmeal and a banana for breakfast and then went for a run, they would enter that information. The food log includes the ingredients, portion sizes, cooking methods, and calorie intake. The exercise log includes the type of exercise, time, and calories burned.

[0696] Input: Ingredient name, amount, cooking method, calorie intake, type of exercise, time, calories burned

[0697] Output: Food log data, exercise log data

[0698] Step 3:

[0699] The device sends the data to the server.

[0700] The device sends the data entered by the user to the server using an HTTP POST request, using HTTPS for secure communication. This request includes health information data, goal data, meal log data, and exercise log data.

[0701] Input: Health information data, goal data, food log data, exercise log data

[0702] Output: Data sent to the server

[0703] Step 4:

[0704] The server analyzes the data.

[0705] The server stores the received data in a database. It then compares the user's past data with the newly acquired data to assess their current health status. This is done using data science techniques such as Python and R. The server calculates nutrient deficiencies and excesses, as well as calorie balance.

[0706] Input: Data sent to the server, historical data

[0707] Output: Analysis result data (nutrient surplus / deficiency, calorie balance)

[0708] Step 5:

[0709] The server generates the meal plan.

[0710] The server calls the generative AI model and creates a prompt based on the analysis results. This prompt is then input into the generative AI model to generate the optimal meal plan for the user. ChatGPT and OpenAI's GPT-4 are used as generative AI models.

[0711] Input: Analysis result data

[0712] Output: Meal plan prompt, generated meal plan

[0713] Step 6:

[0714] The server will notify you of the meal plan.

[0715] The server sends the generated meal plan to the device using an HTTP POST request, allowing the user to receive the updated meal plan.

[0716] Input: Generated meal plan

[0717] Output: Meal plan sent to device

[0718] Step 7:

[0719] The device will display the plan.

[0720] The device displays the meal plan received from the server to the user, and when the user opens the application, a specific menu and cooking instructions are displayed on the screen.

[0721] Input: Meal plan sent to device

[0722] Output: A specific meal plan and cooking instructions displayed to the user

[0723] The above are the specific processing steps of the system program, which allow users to efficiently obtain a meal plan that suits them and manage their health.

[0724] (Application example 1)

[0725] 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."

[0726] In modern society, the growing health consciousness has led to an increased importance of personalized dietary management. However, there is no easy way to obtain a meal plan that suits each individual's dietary preferences, allergies, and health goals, and then easily implement the meals based on that plan. Furthermore, there is a lack of sufficient coordination between the proposal of a meal plan and the actual delivery of the meal, which requires users to go through complicated procedures. Furthermore, there are insufficient means for users to track the progress of their meal or the delivery status.

[0727] 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.

[0728] In this invention, the server includes: a means for a user to input information such as dietary preferences, allergies, and health goals; a means for the user to input a meal log and exercise log; a means for transmitting the input data to a data center; a means for the data center to store the received user data; a means for the data center to generate a meal plan suitable for the user using a generative AI model; a means for transmitting the generated meal plan from the data center to a terminal and displaying it to the user; a means for a delivery service to suggest an optimal menu based on the generated meal plan; and a means for tracking delivery progress in real time and notifying the user. This allows users to quickly obtain an individually optimized meal plan and easily purchase meals based on it. Furthermore, knowing the delivery progress in real time improves convenience.

[0729] "User" refers to an individual who intends to use the system to manage their health.

[0730] "Dietary preferences" is information about ingredients and dishes that the user likes.

[0731] "Allergy" refers to a food ingredient or ingredient that is harmful to the user's health if ingested.

[0732] "Health goal" refers to a specific health or fitness goal that a user wishes to achieve.

[0733] A "meal log" is data that allows a user to record the contents of their daily meals.

[0734] An "exercise log" is data that allows a user to record the details of their daily exercise.

[0735] "Data Center" refers to a computer system for storing user data and for performing analysis and plan generation.

[0736] "Generative AI model" refers to artificial intelligence technology that automatically generates optimal meal plans based on user information.

[0737] A "meal plan" is a plan that takes into consideration specific meal menus and nutritional balance proposed to the user.

[0738] "Terminal" refers to the device through which a user enters information and receives meal plans.

[0739] "Delivery Service" refers to the logistics and distribution system for delivering meals to users.

[0740] "Delivery progress" refers to the process and progress of the meal being delivered to the user.

[0741] The present invention is a system for generating an individually optimized meal plan based on a user's health condition and preferences, and then reliably providing meals based on that plan. This system is mainly composed of three elements: the user, a terminal, and a data center.

[0742] Hardware and Software

[0743] Hardware:

[0744] Device: refers to a smartphone or tablet, which is the device through which the user enters information and receives the meal plan.

[0745] Data center: A group of servers that processes and analyzes information, typically using cloud services (e.g., AWS or Google Cloud Platform).

[0746] software:

[0747] Generative AI models: Use artificial intelligence (e.g., generative AI models such as GPT-4) to generate personalized, optimized meal plans.

[0748] Database: Use a database such as SQL or NoSQL to manage and store user information.

[0749] Process Overview

[0750] 1. The user enters basic information, preferences, and allergies

[0751] Users enter basic information such as age, gender, height, weight, food preferences, allergies, and health goals through the terminal, which is then sent to a data center.

[0752] 2. Enter your daily food log

[0753] Users record their daily diet and exercise logs, and this data is also sent to a data center.

[0754] 3. Data storage and analysis

[0755] The data center stores and analyzes the received user data, including the user's past data, to assess the user's health status.

[0756] 4. Generative AI Meal Plan Generation

[0757] The data center generates an individually optimized meal plan by inputting user data into a generative AI model, specifically using prompts such as:

[0758] (Example of a prompt)

[0759] Generate a daily meal plan based on your health data.

[0760] Age: 30

[0761] Gender: Female

[0762] Height: 165 cm

[0763] Weight: 60 kg

[0764] Preferences: Likes chicken and broccoli, dislikes eggplant

[0765] Allergies: Nut allergies

[0766] Health goal: weight loss

[0767] 5. Send and view your meal plan

[0768] The generated meal plan is sent from the data center to the user's device, where the user can review it. The delivery service also suggests optimal menus based on the meal plan.

[0769] 6. Track delivery progress

[0770] Users can track delivery progress in real time and check the progress on their devices.

[0771] This system allows users to easily obtain individually optimized meal plans and efficiently manage their health based on those plans. In addition, delivery progress can be monitored in real time, improving user convenience.

[0772] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0773] Step 1:

[0774] The user enters basic information, preferences, and allergies.

[0775] Input: Age, Gender, Height, Weight, Food Preferences, Allergies, Health Goals.

[0776] How it works: The user enters this information into the application through a terminal.

[0777] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[0778] Step 2:

[0779] The user inputs a daily food log and exercise log.

[0780] Input: Daily dietary information (ingredients, amounts, cooking methods), calorie intake, exercise information (type of exercise, time, calories burned).

[0781] How it works: The user uses the device to record and enter their daily diet and exercise log.

[0782] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[0783] Step 3:

[0784] The device sends the data to the data center.

[0785] Input: User data entered in step 1 and step 2.

[0786] How it works: The device sends stored user data over the internet to a data center.

[0787] Output: The data center receives the user data and stores it in a database.

[0788] Step 4:

[0789] The server evaluates the current health status based on the data received.

[0790] Input: User's basic information, preferences, allergies, daily food log, and exercise log.

[0791] How it works: The server analyzes your current nutritional intake and calorie consumption status based on past data stored in a database. Specifically, it retrieves the data using SQL queries and applies analysis algorithms.

[0792] Output: An assessment of the user's current health status and nutrient and calorie needs.

[0793] Step 5:

[0794] Generate meal plans using generative AI models.

[0795] Input: Health assessment results, user demographics, preferences, allergies, and health goals.

[0796] How it works: The server sends prompts to a generative AI model (e.g., GPT-4) to generate an optimal meal plan.

[0797] Example prompt sentence:

[0798] Generate a daily meal plan based on your health data.

[0799] Age: 30

[0800] Gender: Female

[0801] Height: 165 cm

[0802] Weight: 60 kg

[0803] Preferences: Likes chicken and broccoli, dislikes eggplant

[0804] Allergies: Nut allergies

[0805] Health goal: weight loss

[0806] Output: A specific meal plan tailored to the user (e.g., breakfast, lunch, and dinner menus).

[0807] Step 6:

[0808] The generated meal plan is sent to the terminal and displayed to the user.

[0809] Input: A meal plan generated from a generative AI model.

[0810] Operation: The server sends the generated meal plan to the device.

[0811] Output: The meal plan is displayed on the user's device. The user confirms the suggested menu.

[0812] Step 7:

[0813] The delivery service will suggest the best menu based on the generated meal plan.

[0814] Input: Meal plan and delivery preferences set by the user.

[0815] How it works: Based on your meal plan, the server will select and suggest the best items from the menu offered by the delivery service.

[0816] Output: Delivery menu suggestions are displayed on the user's device.

[0817] Step 8:

[0818] Track delivery progress in real time and notify users.

[0819] Input: The progress of the delivery ordered by the user.

[0820] How it works: The server receives progress information from the delivery service and notifies the device.

[0821] Output: Delivery progress is displayed in real time on the user's device.

[0822] 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.

[0823] The present invention combines an emotion engine with a system that provides meal plans aimed at maintaining and improving the user's health. Specific embodiments of the system are described below.

[0824] System Overview

[0825] This system consists of three main components: the user, the device, and the server. The user inputs their health data, preferences, and emotional state, which are then sent to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, then adjusts the plan using an emotion engine. The plan is then finally presented to the user via their device.

[0826] Program processing flow

[0827] 1. Enter user information

[0828] The user launches the application and creates an account.

[0829] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0830] 2. Entering Emotion Data

[0831] Users input their emotional state in real time, based on their reactions to daily events and meals.

[0832] Emotions come in categories such as happy, sad, stressed, and relaxed.

[0833] 3. The user enters their daily diet and exercise log

[0834] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[0835] Users also record their exercise details (type of exercise, duration, and calories burned).

[0836] 4. Data Transmission

[0837] The terminal encrypts the data entered by the user and sends it to the server. All communication is carried out using a secure protocol to ensure data confidentiality.

[0838] 5. Server Analysis

[0839] The server stores the received user data in a database and analyzes it.

[0840] The server retrieves the user's past data from the database and uses it to evaluate their current health condition.

[0841] 6. Meal plan generation

[0842] The server calls the generation AI and passes the user's dietary history, allergy information, emotional state, and health goals as input parameters.

[0843] Generative AI uses this data to generate an optimal meal plan.

[0844] 7. Use of Emotion Engines

[0845] An emotion engine analyzes the user's emotional data and adjusts the generated meal plan.

[0846] For example, if a user is feeling stressed, a menu containing ingredients with a high relaxing effect is suggested.

[0847] The emotion engine assesses the user's motivation to achieve their health goals and stress level, and provides encouraging messages and advice accordingly.

[0848] 8. Transmission and Display

[0849] The server then sends the final adjusted meal plan to the device, again using a secure protocol.

[0850] The device displays the received meal plan and encouraging messages to the user.

[0851] Specific examples

[0852] Enter user information

[0853] For example, User B creates an account and enters the following information:

[0854] Age: 28

[0855] Gender: Male

[0856] Height: 175 cm

[0857] Weight: 70 kg

[0858] Favorite ingredients: chicken, spinach, tomatoes

[0859] Disliked food: Celery

[0860] Allergens: Wheat

[0861] Health Goal: Muscle Gain

[0862] Entering emotion data

[0863] User B enters their daily physical and emotional state in categories such as "stress," "relaxation," and "happiness."

[0864] Daily Record

[0865] User B records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner. He also trains at the gym and records his exercise schedule.

[0866] Server Analysis and Plan Generation

[0867] The server analyzes nutritional balance based on User B's data, and the AI ​​generates a meal plan. Based on this, the emotion engine suggests additional menu items with a relaxing effect on days when the user feels stressed.

[0868] Meal plan notification and implementation

[0869] The generated plan and advice based on emotions are sent to the device and displayed in User B's app. User B follows this advice and eats accordingly, then enters feedback.

[0870] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to provide an appropriate and effective meal plan that also takes into account the emotional state of each individual user.

[0871] The processing flow will be explained below.

[0872] Step 1:

[0873] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[0874] Step 2:

[0875] The user inputs their emotional state, specifically their reactions to daily events and meals, in categories such as "happy," "sad," "stressed," and "relaxed."

[0876] Step 3:

[0877] The user records the contents of their daily meals, specifically the names of ingredients, amounts, cooking methods, calorie intake, etc. They also record exercise, entering the type, duration, and calories burned.

[0878] Step 4:

[0879] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[0880] Step 5:

[0881] The server stores the received user data in a database, and then integrates the user's past data with new data for analysis.

[0882] Step 6:

[0883] The server retrieves the user's past data from the database and evaluates their current health condition, which is then used to analyze their current nutritional intake and calorie consumption.

[0884] Step 7:

[0885] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The analysis uses data supervised by nutritionists and general nutritional rules.

[0886] Step 8:

[0887] The server calls the AI ​​generator, which uses the user's dietary history, allergy information, emotional state, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[0888] Step 9:

[0889] The emotion engine analyzes the user's emotional data. Specifically, the emotion engine evaluates the user's emotional state and adjusts the generated meal plan as needed. For example, if the user is feeling stressed, the engine will suggest a menu containing ingredients that will reduce stress.

[0890] Step 10:

[0891] The server then formats the meal plan tailored by the emotion engine and sends it to the device as encrypted data, again using a secure protocol to keep the data safe.

[0892] Step 11:

[0893] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow. Encouraging messages and advice generated by the emotion engine are also displayed.

[0894] Step 12:

[0895] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[0896] Step 13:

[0897] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[0898] This process allows the system to provide appropriate and effective meal plans that take into account each user's emotional state.

[0899] Example 2

[0900] 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."

[0901] Many people today find it difficult to balance health management and diet. It is also difficult to independently determine the optimal meal plan that corresponds to one's health and emotional state. Even if a meal plan is appropriate, it can be difficult to adhere to due to the influence of emotions and stress. To solve these problems, a system is needed that takes into account each user's health data and daily emotional state and provides the optimal meal plan.

[0902] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0903] In this invention, the server includes: means for the user to input information such as food preferences, allergies, and health goals; means for the user to input daily emotional data and a meal log and exercise log; means for encrypting the input data and sending it to the server; means for the server to store the user data received; means for the server to generate a meal plan suitable for the user using an artificial intelligence model; means for the emotion engine to adjust the meal plan based on the user's emotional data; and means for sending the generated meal plan from the server to a terminal and displaying it to the user. This makes it possible to provide an optimal meal plan that takes into consideration the health and emotional state of each individual user.

[0904] A "user" is an individual who uses the system and inputs health data and emotion data.

[0905] "Dietary preferences" refers to the types of ingredients and dishes that a user likes to eat.

[0906] "Allergy" refers to a health problem that occurs when a user ingests a particular food ingredient.

[0907] A "health goal" refers to a specific health goal that a user wants to achieve, such as losing weight or gaining muscle.

[0908] "Emotion data" is data that indicates the user's daily emotional state, including states such as stress, relaxation, and happiness.

[0909] A "meal log" is data in which a user records the contents of their daily meals, and includes the names of ingredients, portions, calories, etc.

[0910] An "exercise log" is data in which a user records the details of their daily exercise, including the type of exercise, time, calories burned, and so on.

[0911] "Encryption" refers to a technique for converting transmitted data into a format that cannot be deciphered by third parties.

[0912] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates and sends meal plans.

[0913] An "artificial intelligence model" refers to a computational model that learns from large amounts of data and generates meal plans that are suitable for the user.

[0914] "Emotion engine" refers to a system that analyzes a user's emotional data and adjusts meal plans based on the results.

[0915] "Terminal" refers to a device through which a user can input data and display meal plans received from a server.

[0916] This invention is a system that provides meal plans for users to maintain and improve their health, and is combined with an emotion engine. In this embodiment, it operates through three main elements: the user, the terminal, and the server.

[0917] System Configuration

[0918] Enter user information

[0919] First, users install the dedicated application and create an account. The information they enter includes basic information (age, gender, height, weight), food preferences, allergies, and health goals. The application collects this information through a GUI.

[0920] Entering emotion data

[0921] Next, users input their daily emotional data into the application. Emotional states are presented in categories such as "stress," "relaxed," and "happy," and users can select their daily emotional state and add comments.

[0922] Enter your daily diet and exercise log

[0923] Users input their daily dietary information (ingredients, portions, calories, cooking methods) and exercise information (type of exercise, time, calories burned) into the application, which updates the user's health data daily.

[0924] Data transmission

[0925] The device encrypts the collected data using AES encryption and transmits it securely to the server via the HTTPS protocol, ensuring the confidentiality of the data.

[0926] Server Analysis

[0927] The server stores the received data in a database and analyzes the user's current health status based on their past data. The server also uses an artificial intelligence (AI) model to generate an optimal meal plan for the user. The generated plan is adjusted according to the user's stress level and relaxation state by analyzing the user's emotional data using an emotion engine.

[0928] View Meal Plans

[0929] Finally, the server sends the tailored meal plan to the device, where the application displays it to the user, including encouraging messages and advice tailored to the user's emotional state.

[0930] Specific examples

[0931] User B creates an account and enters the following information:

[0932] Age: 28

[0933] Gender: Male

[0934] Height: 175 cm

[0935] Weight: 70 kg

[0936] Favorite ingredients: chicken, spinach, tomatoes

[0937] Disliked food: Celery

[0938] Allergens: Wheat

[0939] Health Goal: Muscle Gain

[0940] When inputting daily emotional data, User B inputs his / her daily emotional state such as "stress," "relaxation," or "happiness."

[0941] I eat oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner, and I record each of them in the app. I also enter my gym workouts.

[0942] The server analyzes this data, and a generative AI model generates a meal plan. The emotion engine suggests additional ingredients with a relaxing effect (e.g., herbal tea) on stressful days.

[0943] Finally, the adjusted meal plan and emotion-based advice are sent to the device and displayed in User B's app, where User B follows the plan and provides feedback.

[0944] Prompt Sentence Examples

[0945] Generate a meal plan that suggests foods that will have a relaxing effect on the user's stressful days. The user's information is: age 28, male, 175cm, 70kg, favorite foods are chicken, spinach, and tomato, dislikes are celery, wheat allergy, and health goal is to gain muscle.

[0946] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0947] Step 1:

[0948] A user creates an account and enters basic information.

[0949] Input: Install the application and enter user information (age, gender, height, weight, favorite ingredients, disliked ingredients, allergies, health goals).

[0950] Output: The user information is saved on the device.

[0951] Specific operation: The user downloads and installs the application, then creates an account by entering an email address and password, and enters basic information.

[0952] Step 2:

[0953] The user inputs daily emotion data.

[0954] Input: Enter your emotional state (stressed, relaxed, happy, etc.) and any related comments.

[0955] Output: Emotion data is saved on the device.

[0956] Specific operation: The user opens the application, selects their current emotional state on the emotion input screen, and optionally adds a comment.

[0957] Step 3:

[0958] The user inputs a daily food log and exercise log.

[0959] Input: Enter the meal details (ingredients, amount, cooking method, calories) and exercise details (type of exercise, time, calories burned).

[0960] Output: Food log and exercise log are saved on the device.

[0961] Specific operation: The user opens the application, enters the names of ingredients, amounts, cooking methods, and calories on the meal input screen, and enters the type of exercise, time, and calories burned on the exercise input screen.

[0962] Step 4:

[0963] The device encrypts the data and sends it to the server.

[0964] Input: Obtain user information, emotional data, food log, and exercise log.

[0965] Output: The encrypted data is sent to the server.

[0966] Specific operation: The terminal encrypts the data using the AES encryption algorithm and sends it to the server via the HTTPS protocol.

[0967] Step 5:

[0968] The server stores the received data in a database.

[0969] Input: Encrypted data is sent to the server.

[0970] Output: Encrypted data stored in the database.

[0971] Specific operation: The server decrypts the received data and stores it in a database, classifying it by user.

[0972] Step 6:

[0973] The server compares the current health status with past data and analyzes it.

[0974] Input: Retrieves past data in the database and newly received data.

[0975] Output: The analysis results are obtained.

[0976] How it works: The server compares past user data with new data and uses statistical algorithms to assess current health status.

[0977] Step 7:

[0978] The server calls the generation AI to generate a meal plan.

[0979] Input: Obtain user information, emotional data, food log, exercise log, and health status analysis results.

[0980] Output: An optimal meal plan is generated.

[0981] Specific operation: The server provides the necessary parameters to the generative AI model, allowing it to generate the optimal meal plan for the user.

[0982] Step 8:

[0983] An emotion engine adjusts meal plans based on the user's emotional data.

[0984] Input: Obtain the generated meal plan and the user's sentiment data.

[0985] Output: You get a tailored meal plan.

[0986] Specific operation: The emotion engine analyzes the user's emotional data and adds menus that have stress-reducing or relaxing effects as needed.

[0987] Step 9:

[0988] The server sends the final meal plan to the device.

[0989] Enter: Get your tailored meal plan.

[0990] Output: The encrypted meal plan is sent to the device.

[0991] How it works: The server encrypts the meal plan using AES encryption and sends it to the device via HTTPS protocol.

[0992] Step 10:

[0993] The device displays the meal plan to the user.

[0994] Enter: Get your encrypted meal plan.

[0995] Output: The meal plan is displayed to the user.

[0996] Specific operation: The device decodes the received data and displays the meal plan in an easy-to-understand format for the user in the application.

[0997] (Application example 2)

[0998] 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."

[0999] While conventional meal plan providing systems can take into account a user's health condition and preferences, they have the problem of not being able to incorporate the user's emotional state. As a result, it is difficult to provide an appropriate meal plan even when the user is feeling stressed or tired. Furthermore, there has been no system that seamlessly links to providing specific meal menus based on the generated meal plan. This makes it difficult for users to easily incorporate optimal meals and to continuously manage their health.

[1000] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1001] In this invention, the server includes means for generating a meal plan suitable for the user using a generative AI model, means for adjusting the meal plan using an emotion engine, and means for providing a menu based on the meal plan to the user in cooperation with an external service. This makes it possible to generate an optimal meal plan that takes the user's emotional state into consideration, and to seamlessly present and provide a specific menu based on the meal plan.

[1002] "User" means an individual who uses the System to receive a Meal Plan.

[1003] "Dietary preferences" refers to information about the ingredients and dishes that a user likes to eat.

[1004] "Allergy" refers to information that indicates a user has an allergic reaction to a particular food ingredient.

[1005] "Health Goal" means a health or fitness goal that a User wishes to achieve.

[1006] "Data" refers to information entered by the user, such as food preferences, allergies, health goals, food logs, and exercise logs.

[1007] "Food log" refers to data used by a user to record the meals they eat each day.

[1008] "Exercise log" refers to data that records the exercise a user has performed and the calories they have burned.

[1009] "Generative AI model" refers to an artificial intelligence model that generates optimal meal plans based on user data.

[1010] "Emotion Engine" refers to an algorithm that analyzes a user's emotional state and adjusts their meal plan.

[1011] "External Services" refers to service providers and stores that cooperate with us to provide specific menus based on the meal plan.

[1012] "Server" refers to the computing resources that store the data submitted by the user and generate meal plans using the generative AI model and emotion engine.

[1013] "Terminal" means the electronic device used by a User to enter data and view meal plans.

[1014] System Overview

[1015] The system of the present invention is composed of three main elements: a user, a terminal, and a server. The details of each element and their roles are explained below.

[1016] User

[1017] Users input information such as their food preferences, allergies, and health goals through the device, as well as daily food and exercise logs. Furthermore, their emotional state is recorded and sent to the system.

[1018] Terminal

[1019] The terminal functions as a user interface and is an electronic device such as a smartphone or tablet. A dedicated application is available on the terminal, allowing the user to input and send their own data. The input data is encrypted and sent to the server. The terminal also displays meal plans and related messages sent from the server.

[1020] server

[1021] The server is responsible for storing and analyzing data received from users. The server has the following main functions:

[1022] Generative AI model: Generates optimal meal plans based on a user's dietary history, allergy information, and health goals.

[1023] Emotion engine: Analyzes the user's emotional data and adjusts the generated meal plan. For example, if the user is feeling stressed, the generative AI model will add menu items containing ingredients with a relaxing effect to the plan it suggests.

[1024] External service integration: Collaborate with a food delivery service to provide specific menus based on the generated meal plan.

[1025] Program processing

[1026] The server analyzes the data using AI models and emotion engines. Specifically, it performs the following steps:

[1027] 1. Receiving and storing data: We receive and securely store data sent by users.

[1028] 2. Health status assessment: Retrieve historical data from the database and assess current health status.

[1029] 3. Meal plan generation: Have the generative AI model generate an optimal meal plan using a prompt, such as:

[1030] "

[1031] Age: 28

[1032] Gender: Male

[1033] Health Goal: Muscle Gain

[1034] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[1035] Emotional state: Stress

[1036] Allergens: Wheat

[1037] Favorites: Chicken, spinach, tomatoes

[1038] Dislikes: Celery

[1039] "

[1040] 4. Adjustment by the emotion engine: The emotion engine further adjusts the generated plan, for example, adding ingredients that have a relaxing effect if you are feeling stressed.

[1041] 5. Send Final Plan: The final, adjusted meal plan is sent to the device, again using secure protocols for all communications.

[1042] 6. Notification and Display: The device displays the received meal plan and encouraging messages to the user.

[1043] Specific examples

[1044] As a real-world example, User B creates an account and enters the following information:

[1045] Age: 28

[1046] Gender: Male

[1047] Height: 175 cm

[1048] Weight: 70 kg

[1049] Favorite ingredients: Chicken, spinach, tomatoes

[1050] Disliked food: Celery

[1051] Allergens: Wheat

[1052] Health Goal: Muscle Gain

[1053] User B enters "stress" as his emotional state and records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner in his food log. Based on this, the server uses the generative AI model and emotion engine to generate an optimal meal plan and sends the final plan to User B's device. User B can then use food delivery services based on the plan and manage his or her health.

[1054] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1055] Step 1:

[1056] Input: The user inputs information such as food preferences, allergies, health goals, food log, exercise log, and emotional state into the device.

[1057] Specific operation: The user launches the application and enters information into the form. For example, the user might enter "My favorite foods are chicken, spinach, and tomatoes" as their preference information, "I'm allergic to wheat" as their allergy information, and "I want to gain muscle mass" as their health goal.

[1058] Output: The terminal formats the input data and converts it into a format that can be sent to the server.

[1059] Step 2:

[1060] Input: Data entered by the user.

[1061] Specific operation: The terminal encrypts the input data and sends it to the server using a secure protocol (e.g., HTTPS).

[1062] Output: The server stores the received data in a database.

[1063] Step 3:

[1064] Input: Encrypted data sent from the device.

[1065] What it does: The server decrypts the encrypted data and stores it in a database, ensuring your information is stored securely.

[1066] Output: A saved dataset.

[1067] Step 4:

[1068] Input: User preferences, allergies, health goals, and past food and exercise log data.

[1069] What it does: The server takes this data and provides input to the generative AI model as a prompt, like this:

[1070] "

[1071] Age: 28

[1072] Gender: Male

[1073] Health Goal: Muscle Gain

[1074] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[1075] Emotional state: Stress

[1076] Allergens: Wheat

[1077] Favorites: Chicken, spinach, tomatoes

[1078] Dislikes: Celery

[1079] "

[1080] The generative AI model uses this information to generate an optimal meal plan.

[1081] Output: The generated meal plan.

[1082] Step 5:

[1083] Input: A meal plan generated by a generative AI model.

[1084] What it does: The server passes the meal plan to the emotion engine, which fine-tunes it based on the user's emotional state. For example, if the user is rated as "stressed," the server adjusts the menu to include ingredients with a relaxing effect (e.g., herbal tea and bananas).

[1085] Output: Adjusted final meal plan.

[1086] Step 6:

[1087] Input: Your adjusted final meal plan.

[1088] Specific operation: The server sends the final plan to an external food delivery service. Based on the previously adjusted plan, it proposes specific meal menus and allows the user to select and order.

[1089] Output: The final meal plan sent to the user's device, along with a link to the food delivery service.

[1090] Step 7:

[1091] Input: Final meal plan and food delivery link sent by the server.

[1092] What it does: The device notifies the user and displays the menu within the app, allowing the user to view the menu and order delivery with a single click.

[1093] Output: The user has viewed and ordered from the health-conscious menu.

[1094] 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.

[1095] 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.

[1096] 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.

[1097] [Third embodiment]

[1098] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1099] 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.

[1100] 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).

[1101] 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.

[1102] 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.

[1103] 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).

[1104] 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. 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.

[1105] 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.

[1106] 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.

[1107] 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.

[1108] 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.

[1109] 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."

[1110] The present invention relates to a system for providing a meal plan for the purpose of maintaining and improving the health of a user. Specific embodiments of the system will be described below.

[1111] System Overview

[1112] This system consists of three main components: the user, the device, and the server. The user inputs their health data and preferences and sends them to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, which is then presented to the user via their device.

[1113] Program processing flow

[1114] 1. User enters basic information and goals

[1115] The user launches the application and creates an account.

[1116] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1117] 2. The user enters their daily diet and exercise log

[1118] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[1119] Users also record their exercise details (type of exercise, duration, and calories burned).

[1120] 3. The device sends the data to the server

[1121] The data entered by the user is sent from the device (smartphone or tablet) to the server.

[1122] 4. The server analyzes the data

[1123] The server stores the received user data in storage.

[1124] The server retrieves the user's past data from the database and evaluates and analyzes their current health condition.

[1125] 5. The server generates the meal plan

[1126] The server calls the generating AI and uses the user's dietary history, allergy information, and health goals as input parameters.

[1127] Generative AI generates optimal meal plans, taking into account nutritional balance and user preferences.

[1128] 6. Server notifies meal plan

[1129] The server sends the generated meal plan to the terminal.

[1130] 7. The device will display your plan.

[1131] The device (smartphone or tablet) displays the meal plan received from the server.

[1132] The user is provided with a specific meal menu and cooking instructions.

[1133] Specific examples

[1134] Enter user information

[1135] For example, User A creates an account and enters the following information:

[1136] Age: 30

[1137] Gender: Female

[1138] Height: 165 cm

[1139] Weight: 60 kg

[1140] Food preferences: Likes chicken and broccoli, dislikes eggplant

[1141] Allergies: Nut allergies

[1142] Health goal: weight loss

[1143] Daily Record

[1144] At the end of the day, User A opens the app and records the oatmeal and banana he ate for breakfast, the salad and grilled chicken for lunch, and the salmon steak and stir-fried vegetables for dinner. He also records a 30-minute run.

[1145] Server Analysis

[1146] The server analyzes User A's current nutritional intake and calorie consumption status based on their past data and newly entered data. Based on this, it identifies any nutrients that are lacking or elements that are being consumed in excess.

[1147] Generate a meal plan

[1148] The Generator AI takes User A's data as input parameters and generates the following meal plan:

[1149] Breakfast: Avocado toast and scrambled eggs

[1150] Lunch: Grilled chicken salad (broccoli, tomato, lettuce, creamy dressing)

[1151] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[1152] Notification and implementation of the plan

[1153] The meal plan generated by the server is sent to User A's device, and the app displays the plan. User A follows the suggested menu while looking at the app.

[1154] The above is a specific embodiment for carrying out the present invention. By using this system, a meal plan suited to each individual user can be provided, helping to maintain and improve health.

[1155] The processing flow will be explained below.

[1156] Step 1:

[1157] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1158] Step 2:

[1159] The user records their daily diet, specifically the names of ingredients, amounts, cooking methods, and calorie intake. At the same time, the user also records their exercise, including the type of exercise, duration, and calories burned.

[1160] Step 3:

[1161] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[1162] Step 4:

[1163] The server stores the received user data in a database. The server also stores the user's past data, and combines the new data with the past data for analysis.

[1164] Step 5:

[1165] The server retrieves the user's past data from the database and evaluates their current health status, comparing the data previously entered by the user with their current data to analyze their current nutritional intake and calorie consumption.

[1166] Step 6:

[1167] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The server evaluates the user's nutritional balance based on data supervised by nutritionists and general nutritional rules.

[1168] Step 7:

[1169] The server calls the AI ​​generator and passes the user's dietary history, allergy information, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[1170] Step 8:

[1171] The AI ​​generative system considers nutritional balance and proposes a different menu each day that matches the user's preferences. Specifically, it designs a meal plan that meets the user's needs for protein, vitamins, minerals, etc.

[1172] Step 9:

[1173] The server then formats the generated meal plan and sends it to the user's device as encrypted data, again using a secure protocol to keep the data safe.

[1174] Step 10:

[1175] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow.

[1176] Step 11:

[1177] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[1178] Step 12:

[1179] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[1180] In this way, this system works in cooperation between the server and the terminal based on the user's input data, and utilizes generative AI to provide the optimal meal plan for each individual user.

[1181] Example 1

[1182] 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."

[1183] Conventional meal plan providing systems have difficulty in fully considering the user's individual health condition, preferences, and allergy information. Furthermore, the quality and accuracy of the meal plans are low, making it difficult to provide optimal meal plans for users and achieving results. Furthermore, meal plans rarely change from day to day, making it difficult for users to maintain motivation to continue using the system.

[1184] 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.

[1185] In this invention, the server includes a means for analyzing the user's past data and newly acquired data, a means for generating a meal plan based on prompts using a generative AI model, and a means for assessing the user's health status using multiple data science techniques. This allows for the provision of highly accurate meal plans optimized for the user's health status. Furthermore, by proposing meal plans that change daily, the server can maintain the user's motivation and efficiently manage their health.

[1186] "Health information" refers to basic health data such as the user's age, gender, height, weight, allergies, and health goals.

[1187] "Dietary preferences" is information about the user's preferred ingredients, cooking methods, and ingredients to avoid.

[1188] "Allergy" is information indicating that the user has an allergic reaction to a specific food ingredient or component.

[1189] A "health goal" is a health-related goal that a user wants to achieve (e.g., weight loss, muscle gain, blood sugar management).

[1190] A "meal log" is data recorded by a user about the contents of their daily meals (food ingredients, portions, cooking methods, calorie intake).

[1191] An "exercise log" is data recorded by a user regarding the details of their daily exercise (type of exercise, duration, calories burned).

[1192] A "terminal" is a device (e.g., a smartphone or tablet) that a user uses to input data or receive data from a server.

[1193] A "server" is a computing device that analyzes data received from users and generates meal plans.

[1194] A "database" is an information management system that stores a user's past data and retrieves it as needed.

[1195] A "generative AI model" is an artificial intelligence technology that generates optimal meal plans based on user data.

[1196] A "prompt sentence" is an explanatory sentence that describes the user's health information, dietary history, etc. to be input into the generative AI model.

[1197] "Data science techniques" are statistical and machine learning methods used to assess and analyze a user's health status.

[1198] A "meal plan" is a specific meal menu and cooking instructions created taking into account the user's health condition and preferences.

[1199] This invention relates to a system that provides meal plans for users to maintain and improve their health. The system consists of three main components: a user, a terminal, and a server.

[1200] Users enter their health information, preferences, allergies, and health goals via their device. For example, a user uses a device (smartphone or tablet) to launch a health application and enter their age, gender, height, weight, food preferences, allergies, and health goals. Next, the user enters their daily food and exercise logs. For example, if they eat oatmeal for breakfast and go running, they record that information in the application. This data is sent from the device to the server. An HTTP POST request is used for transmission, and HTTPS communication is used to ensure data security.

[1201] The server stores the received data in a database and analyzes the user's past data and newly acquired data. Data analysis uses data science techniques such as Python and R. Based on the analysis results, the server uses a generative AI model to create prompts and generate meal plans. Generative AI models such as ChatGPT and OpenAI's GPT-4 are used.

[1202] Here is an example prompt:

[1203] User Basic Information:

[1204] Age: 30

[1205] Gender: Female

[1206] Height: 165 cm

[1207] Weight: 60 kg

[1208] Food preferences: Likes chicken and broccoli, dislikes eggplant

[1209] Allergies: Nut allergies

[1210] Health goal: weight loss

[1211] User's diet history:

[1212] Breakfast: oatmeal and banana

[1213] Lunch: Salad, grilled chicken

[1214] Dinner: Salmon steak, stir-fried vegetables

[1215] User's exercise history:

[1216] Exercise: Running for 30 minutes

[1217] Based on this prompt, the generative AI model generates the optimal meal plan for the user. For example, the following meal plan might be generated:

[1218] Breakfast: Avocado toast and scrambled eggs

[1219] Lunch: Grilled Chin Salad (broccoli, tomato, lettuce, creamy dressing)

[1220] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[1221] The generated meal plan is sent from the server to the device, which then displays it to the user, along with specific meal menus and cooking instructions, allowing the user to prepare the meal.

[1222] By using this system, users can easily obtain the optimal meal plan for themselves and efficiently manage their health. Because the server performs the analysis and generation, the processing load is not placed on the device, providing a comfortable environment for users.

[1223] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1224] Step 1:

[1225] The user enters health information and goals.

[1226] Users launch a health application on their smartphone or tablet and enter their age, gender, height, weight, food preferences, allergies, and health goals. This data is collected using an input form on the device. The entered data is temporarily stored in local storage.

[1227] Input: Age, gender, height, weight, food preferences, allergies, health goals

[1228] Output: Health information data, goal data

[1229] Step 2:

[1230] The user inputs a daily food log and exercise log.

[1231] Users log in to the application to record their daily diet and exercise. For example, if they had oatmeal and a banana for breakfast and then went for a run, they would enter that information. The food log includes the ingredients, portion sizes, cooking methods, and calorie intake. The exercise log includes the type of exercise, time, and calories burned.

[1232] Input: Ingredient name, amount, cooking method, calorie intake, type of exercise, time, calories burned

[1233] Output: Food log data, exercise log data

[1234] Step 3:

[1235] The device sends the data to the server.

[1236] The device sends the data entered by the user to the server using an HTTP POST request, using HTTPS for secure communication. This request includes health information data, goal data, meal log data, and exercise log data.

[1237] Input: Health information data, goal data, food log data, exercise log data

[1238] Output: Data sent to the server

[1239] Step 4:

[1240] The server analyzes the data.

[1241] The server stores the received data in a database. It then compares the user's past data with the newly acquired data to assess their current health status. This is done using data science techniques such as Python and R. The server calculates nutrient deficiencies and excesses, as well as calorie balance.

[1242] Input: Data sent to the server, historical data

[1243] Output: Analysis result data (nutrient surplus / deficiency, calorie balance)

[1244] Step 5:

[1245] The server generates the meal plan.

[1246] The server calls the generative AI model and creates a prompt based on the analysis results. This prompt is then input into the generative AI model to generate the optimal meal plan for the user. ChatGPT and OpenAI's GPT-4 are used as generative AI models.

[1247] Input: Analysis result data

[1248] Output: Meal plan prompt, generated meal plan

[1249] Step 6:

[1250] The server will notify you of the meal plan.

[1251] The server sends the generated meal plan to the device using an HTTP POST request, allowing the user to receive the updated meal plan.

[1252] Input: Generated meal plan

[1253] Output: Meal plan sent to device

[1254] Step 7:

[1255] The device will display the plan.

[1256] The device displays the meal plan received from the server to the user, and when the user opens the application, a specific menu and cooking instructions are displayed on the screen.

[1257] Input: Meal plan sent to device

[1258] Output: A specific meal plan and cooking instructions displayed to the user

[1259] The above are the specific processing steps of the system program, which allow users to efficiently obtain a meal plan that suits them and manage their health.

[1260] (Application example 1)

[1261] 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."

[1262] In modern society, the growing health consciousness has led to an increased importance of personalized dietary management. However, there is no easy way to obtain a meal plan that suits each individual's dietary preferences, allergies, and health goals, and then easily implement the meals based on that plan. Furthermore, there is a lack of sufficient coordination between the proposal of a meal plan and the actual delivery of the meal, which requires users to go through complicated procedures. Furthermore, there are insufficient means for users to track the progress of their meal or the delivery status.

[1263] 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.

[1264] In this invention, the server includes: a means for a user to input information such as dietary preferences, allergies, and health goals; a means for the user to input a meal log and exercise log; a means for transmitting the input data to a data center; a means for the data center to store the received user data; a means for the data center to generate a meal plan suitable for the user using a generative AI model; a means for transmitting the generated meal plan from the data center to a terminal and displaying it to the user; a means for a delivery service to suggest an optimal menu based on the generated meal plan; and a means for tracking delivery progress in real time and notifying the user. This allows users to quickly obtain an individually optimized meal plan and easily purchase meals based on it. Furthermore, knowing the delivery progress in real time improves convenience.

[1265] "User" refers to an individual who intends to use the system to manage their health.

[1266] "Dietary preferences" is information about ingredients and dishes that the user likes.

[1267] "Allergy" refers to a food ingredient or ingredient that is harmful to the user's health if ingested.

[1268] "Health goal" refers to a specific health or fitness goal that a user wishes to achieve.

[1269] A "meal log" is data that allows a user to record the contents of their daily meals.

[1270] An "exercise log" is data that allows a user to record the details of their daily exercise.

[1271] "Data Center" refers to a computer system for storing user data and for performing analysis and plan generation.

[1272] "Generative AI model" refers to artificial intelligence technology that automatically generates optimal meal plans based on user information.

[1273] A "meal plan" is a plan that takes into consideration specific meal menus and nutritional balance proposed to the user.

[1274] "Terminal" refers to the device through which a user enters information and receives meal plans.

[1275] "Delivery Service" refers to the logistics and distribution system for delivering meals to users.

[1276] "Delivery progress" refers to the process and progress of the meal being delivered to the user.

[1277] The present invention is a system for generating an individually optimized meal plan based on a user's health condition and preferences, and then reliably providing meals based on that plan. This system is mainly composed of three elements: the user, a terminal, and a data center.

[1278] Hardware and Software

[1279] Hardware:

[1280] Device: refers to a smartphone or tablet, which is the device through which the user enters information and receives the meal plan.

[1281] Data center: A group of servers that processes and analyzes information, typically using cloud services (e.g., AWS or Google Cloud Platform).

[1282] software:

[1283] Generative AI models: Use artificial intelligence (e.g., generative AI models such as GPT-4) to generate personalized, optimized meal plans.

[1284] Database: Use a database such as SQL or NoSQL to manage and store user information.

[1285] Process Overview

[1286] 1. The user enters basic information, preferences, and allergies

[1287] Users enter basic information such as age, gender, height, weight, food preferences, allergies, and health goals through the terminal, which is then sent to a data center.

[1288] 2. Enter your daily food log

[1289] Users record their daily diet and exercise logs, and this data is also sent to a data center.

[1290] 3. Data storage and analysis

[1291] The data center stores and analyzes the received user data, including the user's past data, to assess the user's health status.

[1292] 4. Generative AI Meal Plan Generation

[1293] The data center generates an individually optimized meal plan by inputting user data into a generative AI model, specifically using prompts such as:

[1294] (Example of a prompt)

[1295] Generate a daily meal plan based on your health data.

[1296] Age: 30

[1297] Gender: Female

[1298] Height: 165 cm

[1299] Weight: 60 kg

[1300] Preferences: Likes chicken and broccoli, dislikes eggplant

[1301] Allergies: Nut allergies

[1302] Health goal: weight loss

[1303] 5. Send and view your meal plan

[1304] The generated meal plan is sent from the data center to the user's device, where the user can review it. The delivery service also suggests optimal menus based on the meal plan.

[1305] 6. Track delivery progress

[1306] Users can track delivery progress in real time and check the progress on their devices.

[1307] This system allows users to easily obtain individually optimized meal plans and efficiently manage their health based on those plans. In addition, delivery progress can be monitored in real time, improving user convenience.

[1308] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1309] Step 1:

[1310] The user enters basic information, preferences, and allergies.

[1311] Input: Age, Gender, Height, Weight, Food Preferences, Allergies, Health Goals.

[1312] How it works: The user enters this information into the application through a terminal.

[1313] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[1314] Step 2:

[1315] The user inputs a daily food log and exercise log.

[1316] Input: Daily dietary information (ingredients, amounts, cooking methods), calorie intake, exercise information (type of exercise, time, calories burned).

[1317] How it works: The user uses the device to record and enter their daily diet and exercise log.

[1318] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[1319] Step 3:

[1320] The device sends the data to the data center.

[1321] Input: User data entered in step 1 and step 2.

[1322] How it works: The device sends stored user data over the internet to a data center.

[1323] Output: The data center receives the user data and stores it in a database.

[1324] Step 4:

[1325] The server evaluates the current health status based on the data received.

[1326] Input: User's basic information, preferences, allergies, daily food log, and exercise log.

[1327] How it works: The server analyzes your current nutritional intake and calorie consumption status based on past data stored in a database. Specifically, it retrieves the data using SQL queries and applies analysis algorithms.

[1328] Output: An assessment of the user's current health status and nutrient and calorie needs.

[1329] Step 5:

[1330] Generate meal plans using generative AI models.

[1331] Input: Health assessment results, user demographics, preferences, allergies, and health goals.

[1332] How it works: The server sends prompts to a generative AI model (e.g., GPT-4) to generate an optimal meal plan.

[1333] Example prompt sentence:

[1334] Generate a daily meal plan based on your health data.

[1335] Age: 30

[1336] Gender: Female

[1337] Height: 165 cm

[1338] Weight: 60 kg

[1339] Preferences: Likes chicken and broccoli, dislikes eggplant

[1340] Allergies: Nut allergies

[1341] Health goal: weight loss

[1342] Output: A specific meal plan tailored to the user (e.g., breakfast, lunch, and dinner menus).

[1343] Step 6:

[1344] The generated meal plan is sent to the terminal and displayed to the user.

[1345] Input: A meal plan generated from a generative AI model.

[1346] Operation: The server sends the generated meal plan to the device.

[1347] Output: The meal plan is displayed on the user's device. The user confirms the suggested menu.

[1348] Step 7:

[1349] The delivery service will suggest the best menu based on the generated meal plan.

[1350] Input: Meal plan and delivery preferences set by the user.

[1351] How it works: Based on your meal plan, the server will select and suggest the best items from the menu offered by the delivery service.

[1352] Output: Delivery menu suggestions are displayed on the user's device.

[1353] Step 8:

[1354] Track delivery progress in real time and notify users.

[1355] Input: The progress of the delivery ordered by the user.

[1356] How it works: The server receives progress information from the delivery service and notifies the device.

[1357] Output: Delivery progress is displayed in real time on the user's device.

[1358] 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.

[1359] The present invention combines an emotion engine with a system that provides meal plans aimed at maintaining and improving the user's health. Specific embodiments of the system are described below.

[1360] System Overview

[1361] This system consists of three main components: the user, the device, and the server. The user inputs their health data, preferences, and emotional state, which are then sent to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, then adjusts the plan using an emotion engine. The plan is then finally presented to the user via their device.

[1362] Program processing flow

[1363] 1. Enter user information

[1364] The user launches the application and creates an account.

[1365] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1366] 2. Entering Emotion Data

[1367] Users input their emotional state in real time, based on their reactions to daily events and meals.

[1368] Emotions come in categories such as happy, sad, stressed, and relaxed.

[1369] 3. The user enters their daily diet and exercise log

[1370] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[1371] Users also record their exercise details (type of exercise, duration, and calories burned).

[1372] 4. Data Transmission

[1373] The terminal encrypts the data entered by the user and sends it to the server. All communication is carried out using a secure protocol to ensure data confidentiality.

[1374] 5. Server Analysis

[1375] The server stores the received user data in a database and analyzes it.

[1376] The server retrieves the user's past data from the database and uses it to evaluate their current health condition.

[1377] 6. Meal plan generation

[1378] The server calls the generation AI and passes the user's dietary history, allergy information, emotional state, and health goals as input parameters.

[1379] Generative AI uses this data to generate an optimal meal plan.

[1380] 7. Use of Emotion Engines

[1381] An emotion engine analyzes the user's emotional data and adjusts the generated meal plan.

[1382] For example, if a user is feeling stressed, a menu containing ingredients with a high relaxing effect is suggested.

[1383] The emotion engine assesses the user's motivation to achieve their health goals and stress level, and provides encouraging messages and advice accordingly.

[1384] 8. Transmission and Display

[1385] The server then sends the final adjusted meal plan to the device, again using a secure protocol.

[1386] The device displays the received meal plan and encouraging messages to the user.

[1387] Specific examples

[1388] Enter user information

[1389] For example, User B creates an account and enters the following information:

[1390] Age: 28

[1391] Gender: Male

[1392] Height: 175 cm

[1393] Weight: 70 kg

[1394] Favorite ingredients: chicken, spinach, tomatoes

[1395] Disliked food: Celery

[1396] Allergens: Wheat

[1397] Health Goal: Muscle Gain

[1398] Entering emotion data

[1399] User B enters their daily physical and emotional state in categories such as "stress," "relaxation," and "happiness."

[1400] Daily Record

[1401] User B records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner. He also trains at the gym and records his exercise schedule.

[1402] Server Analysis and Plan Generation

[1403] The server analyzes nutritional balance based on User B's data, and the AI ​​generates a meal plan. Based on this, the emotion engine suggests additional menu items with a relaxing effect on days when the user feels stressed.

[1404] Meal plan notification and implementation

[1405] The generated plan and advice based on emotions are sent to the device and displayed in User B's app. User B follows this advice and eats accordingly, then enters feedback.

[1406] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to provide an appropriate and effective meal plan that also takes into account the emotional state of each individual user.

[1407] The processing flow will be explained below.

[1408] Step 1:

[1409] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1410] Step 2:

[1411] The user inputs their emotional state, specifically their reactions to daily events and meals, in categories such as "happy," "sad," "stressed," and "relaxed."

[1412] Step 3:

[1413] The user records the contents of their daily meals, specifically the names of ingredients, amounts, cooking methods, calorie intake, etc. They also record exercise, entering the type, duration, and calories burned.

[1414] Step 4:

[1415] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[1416] Step 5:

[1417] The server stores the received user data in a database, and then integrates the user's past data with new data for analysis.

[1418] Step 6:

[1419] The server retrieves the user's past data from the database and evaluates their current health condition, which is then used to analyze their current nutritional intake and calorie consumption.

[1420] Step 7:

[1421] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The analysis uses data supervised by nutritionists and general nutritional rules.

[1422] Step 8:

[1423] The server calls the AI ​​generator, which uses the user's dietary history, allergy information, emotional state, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[1424] Step 9:

[1425] The emotion engine analyzes the user's emotional data. Specifically, the emotion engine evaluates the user's emotional state and adjusts the generated meal plan as needed. For example, if the user is feeling stressed, the engine will suggest a menu containing ingredients that will reduce stress.

[1426] Step 10:

[1427] The server then formats the meal plan tailored by the emotion engine and sends it to the device as encrypted data, again using a secure protocol to keep the data safe.

[1428] Step 11:

[1429] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow. Encouraging messages and advice generated by the emotion engine are also displayed.

[1430] Step 12:

[1431] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[1432] Step 13:

[1433] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[1434] This process allows the system to provide appropriate and effective meal plans that take into account each user's emotional state.

[1435] Example 2

[1436] 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."

[1437] Many people today find it difficult to balance health management and diet. It is also difficult to independently determine the optimal meal plan that corresponds to one's health and emotional state. Even if a meal plan is appropriate, it can be difficult to adhere to due to the influence of emotions and stress. To solve these problems, a system is needed that takes into account each user's health data and daily emotional state and provides the optimal meal plan.

[1438] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1439] In this invention, the server includes: means for the user to input information such as food preferences, allergies, and health goals; means for the user to input daily emotional data and a meal log and exercise log; means for encrypting the input data and sending it to the server; means for the server to store the user data received; means for the server to generate a meal plan suitable for the user using an artificial intelligence model; means for the emotion engine to adjust the meal plan based on the user's emotional data; and means for sending the generated meal plan from the server to a terminal and displaying it to the user. This makes it possible to provide an optimal meal plan that takes into consideration the health and emotional state of each individual user.

[1440] A "user" is an individual who uses the system and inputs health data and emotion data.

[1441] "Dietary preferences" refers to the types of ingredients and dishes that a user likes to eat.

[1442] "Allergy" refers to a health problem that occurs when a user ingests a particular food ingredient.

[1443] A "health goal" refers to a specific health goal that a user wants to achieve, such as losing weight or gaining muscle.

[1444] "Emotion data" is data that indicates the user's daily emotional state, including states such as stress, relaxation, and happiness.

[1445] A "meal log" is data in which a user records the contents of their daily meals, and includes the names of ingredients, portions, calories, etc.

[1446] An "exercise log" is data in which a user records the details of their daily exercise, including the type of exercise, time, calories burned, and so on.

[1447] "Encryption" refers to a technique for converting transmitted data into a format that cannot be deciphered by third parties.

[1448] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates and sends meal plans.

[1449] An "artificial intelligence model" refers to a computational model that learns from large amounts of data and generates meal plans that are suitable for the user.

[1450] "Emotion engine" refers to a system that analyzes a user's emotional data and adjusts meal plans based on the results.

[1451] "Terminal" refers to a device through which a user can input data and display meal plans received from a server.

[1452] This invention is a system that provides meal plans for users to maintain and improve their health, and is combined with an emotion engine. In this embodiment, it operates through three main elements: the user, the terminal, and the server.

[1453] System Configuration

[1454] Enter user information

[1455] First, users install the dedicated application and create an account. The information they enter includes basic information (age, gender, height, weight), food preferences, allergies, and health goals. The application collects this information through a GUI.

[1456] Entering emotion data

[1457] Next, users input their daily emotional data into the application. Emotional states are presented in categories such as "stress," "relaxed," and "happy," and users can select their daily emotional state and add comments.

[1458] Enter your daily diet and exercise log

[1459] Users input their daily dietary information (ingredients, portions, calories, cooking methods) and exercise information (type of exercise, time, calories burned) into the application, which updates the user's health data daily.

[1460] Data transmission

[1461] The device encrypts the collected data using AES encryption and transmits it securely to the server via the HTTPS protocol, ensuring the confidentiality of the data.

[1462] Server Analysis

[1463] The server stores the received data in a database and analyzes the user's current health status based on their past data. The server also uses an artificial intelligence (AI) model to generate an optimal meal plan for the user. The generated plan is adjusted according to the user's stress level and relaxation state by analyzing the user's emotional data using an emotion engine.

[1464] View Meal Plans

[1465] Finally, the server sends the tailored meal plan to the device, where the application displays it to the user, including encouraging messages and advice tailored to the user's emotional state.

[1466] Specific examples

[1467] User B creates an account and enters the following information:

[1468] Age: 28

[1469] Gender: Male

[1470] Height: 175 cm

[1471] Weight: 70 kg

[1472] Favorite ingredients: chicken, spinach, tomatoes

[1473] Disliked food: Celery

[1474] Allergens: Wheat

[1475] Health Goal: Muscle Gain

[1476] When inputting daily emotional data, User B inputs his / her daily emotional state such as "stress," "relaxation," or "happiness."

[1477] I eat oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner, and I record each of them in the app. I also enter my gym workouts.

[1478] The server analyzes this data, and a generative AI model generates a meal plan. The emotion engine suggests additional ingredients with a relaxing effect (e.g., herbal tea) on stressful days.

[1479] Finally, the adjusted meal plan and emotion-based advice are sent to the device and displayed in User B's app, where User B follows the plan and provides feedback.

[1480] Prompt Sentence Examples

[1481] Generate a meal plan that suggests foods that will have a relaxing effect on the user's stressful days. The user's information is: age 28, male, 175cm, 70kg, favorite foods are chicken, spinach, and tomato, dislikes are celery, wheat allergy, and health goal is to gain muscle.

[1482] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1483] Step 1:

[1484] A user creates an account and enters basic information.

[1485] Input: Install the application and enter user information (age, gender, height, weight, favorite ingredients, disliked ingredients, allergies, health goals).

[1486] Output: The user information is saved on the device.

[1487] Specific operation: The user downloads and installs the application, then creates an account by entering an email address and password, and enters basic information.

[1488] Step 2:

[1489] The user inputs daily emotion data.

[1490] Input: Enter your emotional state (stressed, relaxed, happy, etc.) and any related comments.

[1491] Output: Emotion data is saved on the device.

[1492] Specific operation: The user opens the application, selects their current emotional state on the emotion input screen, and optionally adds a comment.

[1493] Step 3:

[1494] The user inputs a daily food log and exercise log.

[1495] Input: Enter the meal details (ingredients, amount, cooking method, calories) and exercise details (type of exercise, time, calories burned).

[1496] Output: Food log and exercise log are saved on the device.

[1497] Specific operation: The user opens the application, enters the names of ingredients, amounts, cooking methods, and calories on the meal input screen, and enters the type of exercise, time, and calories burned on the exercise input screen.

[1498] Step 4:

[1499] The device encrypts the data and sends it to the server.

[1500] Input: Obtain user information, emotional data, food log, and exercise log.

[1501] Output: The encrypted data is sent to the server.

[1502] Specific operation: The terminal encrypts the data using the AES encryption algorithm and sends it to the server via the HTTPS protocol.

[1503] Step 5:

[1504] The server stores the received data in a database.

[1505] Input: Encrypted data is sent to the server.

[1506] Output: Encrypted data stored in the database.

[1507] Specific operation: The server decrypts the received data and stores it in a database, classifying it by user.

[1508] Step 6:

[1509] The server compares the current health status with past data and analyzes it.

[1510] Input: Retrieves past data in the database and newly received data.

[1511] Output: The analysis results are obtained.

[1512] How it works: The server compares past user data with new data and uses statistical algorithms to assess current health status.

[1513] Step 7:

[1514] The server calls the generation AI to generate a meal plan.

[1515] Input: Obtain user information, emotional data, food log, exercise log, and health status analysis results.

[1516] Output: An optimal meal plan is generated.

[1517] Specific operation: The server provides the necessary parameters to the generative AI model, allowing it to generate the optimal meal plan for the user.

[1518] Step 8:

[1519] An emotion engine adjusts meal plans based on the user's emotional data.

[1520] Input: Obtain the generated meal plan and the user's sentiment data.

[1521] Output: You get a tailored meal plan.

[1522] Specific operation: The emotion engine analyzes the user's emotional data and adds menus that have stress-reducing or relaxing effects as needed.

[1523] Step 9:

[1524] The server sends the final meal plan to the device.

[1525] Enter: Get your tailored meal plan.

[1526] Output: The encrypted meal plan is sent to the device.

[1527] How it works: The server encrypts the meal plan using AES encryption and sends it to the device via HTTPS protocol.

[1528] Step 10:

[1529] The device displays the meal plan to the user.

[1530] Enter: Get your encrypted meal plan.

[1531] Output: The meal plan is displayed to the user.

[1532] Specific operation: The device decodes the received data and displays the meal plan in an easy-to-understand format for the user in the application.

[1533] (Application example 2)

[1534] 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."

[1535] While conventional meal plan providing systems can take into account a user's health condition and preferences, they have the problem of not being able to incorporate the user's emotional state. As a result, it is difficult to provide an appropriate meal plan even when the user is feeling stressed or tired. Furthermore, there has been no system that seamlessly links to providing specific meal menus based on the generated meal plan. This makes it difficult for users to easily incorporate optimal meals and to continuously manage their health.

[1536] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1537] In this invention, the server includes means for generating a meal plan suitable for the user using a generative AI model, means for adjusting the meal plan using an emotion engine, and means for providing a menu based on the meal plan to the user in cooperation with an external service. This makes it possible to generate an optimal meal plan that takes the user's emotional state into consideration, and to seamlessly present and provide a specific menu based on the meal plan.

[1538] "User" means an individual who uses the System to receive a Meal Plan.

[1539] "Dietary preferences" refers to information about the ingredients and dishes that a user likes to eat.

[1540] "Allergy" refers to information that indicates a user has an allergic reaction to a particular food ingredient.

[1541] "Health Goal" means a health or fitness goal that a User wishes to achieve.

[1542] "Data" refers to information entered by the user, such as food preferences, allergies, health goals, food logs, and exercise logs.

[1543] "Food log" refers to data used by a user to record the meals they eat each day.

[1544] "Exercise log" refers to data that records the exercise a user has performed and the calories they have burned.

[1545] "Generative AI model" refers to an artificial intelligence model that generates optimal meal plans based on user data.

[1546] "Emotion Engine" refers to an algorithm that analyzes a user's emotional state and adjusts their meal plan.

[1547] "External Services" refers to service providers and stores that cooperate with us to provide specific menus based on the meal plan.

[1548] "Server" refers to the computing resources that store the data submitted by the user and generate meal plans using the generative AI model and emotion engine.

[1549] "Terminal" means the electronic device used by a User to enter data and view meal plans.

[1550] System Overview

[1551] The system of the present invention is composed of three main elements: a user, a terminal, and a server. The details of each element and their roles are explained below.

[1552] User

[1553] Users input information such as their food preferences, allergies, and health goals through the device, as well as daily food and exercise logs. Furthermore, their emotional state is recorded and sent to the system.

[1554] Terminal

[1555] The terminal functions as a user interface and is an electronic device such as a smartphone or tablet. A dedicated application is available on the terminal, allowing the user to input and send their own data. The input data is encrypted and sent to the server. The terminal also displays meal plans and related messages sent from the server.

[1556] server

[1557] The server is responsible for storing and analyzing data received from users. The server has the following main functions:

[1558] Generative AI model: Generates optimal meal plans based on a user's dietary history, allergy information, and health goals.

[1559] Emotion engine: Analyzes the user's emotional data and adjusts the generated meal plan. For example, if the user is feeling stressed, the generative AI model will add menu items containing ingredients with a relaxing effect to the plan it suggests.

[1560] External service integration: Collaborate with a food delivery service to provide specific menus based on the generated meal plan.

[1561] Program processing

[1562] The server analyzes the data using AI models and emotion engines. Specifically, it performs the following steps:

[1563] 1. Receiving and storing data: We receive and securely store data sent by users.

[1564] 2. Health status assessment: Retrieve historical data from the database and assess current health status.

[1565] 3. Meal plan generation: Have the generative AI model generate an optimal meal plan using a prompt, such as:

[1566] "

[1567] Age: 28

[1568] Gender: Male

[1569] Health Goal: Muscle Gain

[1570] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[1571] Emotional state: Stress

[1572] Allergens: Wheat

[1573] Favorites: Chicken, spinach, tomatoes

[1574] Dislikes: Celery

[1575] "

[1576] 4. Adjustment by the emotion engine: The emotion engine further adjusts the generated plan, for example, adding ingredients that have a relaxing effect if you are feeling stressed.

[1577] 5. Send Final Plan: The final, adjusted meal plan is sent to the device, again using secure protocols for all communications.

[1578] 6. Notification and Display: The device displays the received meal plan and encouraging messages to the user.

[1579] Specific examples

[1580] As a real-world example, User B creates an account and enters the following information:

[1581] Age: 28

[1582] Gender: Male

[1583] Height: 175 cm

[1584] Weight: 70 kg

[1585] Favorite ingredients: Chicken, spinach, tomatoes

[1586] Disliked food: Celery

[1587] Allergens: Wheat

[1588] Health Goal: Muscle Gain

[1589] User B enters "stress" as his emotional state and records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner in his food log. Based on this, the server uses the generative AI model and emotion engine to generate an optimal meal plan and sends the final plan to User B's device. User B can then use food delivery services based on the plan and manage his or her health.

[1590] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1591] Step 1:

[1592] Input: The user inputs information such as food preferences, allergies, health goals, food log, exercise log, and emotional state into the device.

[1593] Specific operation: The user launches the application and enters information into the form. For example, the user might enter "My favorite foods are chicken, spinach, and tomatoes" as their preference information, "I'm allergic to wheat" as their allergy information, and "I want to gain muscle mass" as their health goal.

[1594] Output: The terminal formats the input data and converts it into a format that can be sent to the server.

[1595] Step 2:

[1596] Input: Data entered by the user.

[1597] Specific operation: The terminal encrypts the input data and sends it to the server using a secure protocol (e.g., HTTPS).

[1598] Output: The server stores the received data in a database.

[1599] Step 3:

[1600] Input: Encrypted data sent from the device.

[1601] What it does: The server decrypts the encrypted data and stores it in a database, ensuring your information is stored securely.

[1602] Output: A saved dataset.

[1603] Step 4:

[1604] Input: User preferences, allergies, health goals, and past food and exercise log data.

[1605] What it does: The server takes this data and provides input to the generative AI model as a prompt, like this:

[1606] "

[1607] Age: 28

[1608] Gender: Male

[1609] Health Goal: Muscle Gain

[1610] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[1611] Emotional state: Stress

[1612] Allergens: Wheat

[1613] Favorites: Chicken, spinach, tomatoes

[1614] Dislikes: Celery

[1615] "

[1616] The generative AI model uses this information to generate an optimal meal plan.

[1617] Output: The generated meal plan.

[1618] Step 5:

[1619] Input: A meal plan generated by a generative AI model.

[1620] What it does: The server passes the meal plan to the emotion engine, which fine-tunes it based on the user's emotional state. For example, if the user is rated as "stressed," the server adjusts the menu to include ingredients with a relaxing effect (e.g., herbal tea and bananas).

[1621] Output: Adjusted final meal plan.

[1622] Step 6:

[1623] Input: Your adjusted final meal plan.

[1624] Specific operation: The server sends the final plan to an external food delivery service. Based on the previously adjusted plan, it proposes specific meal menus and allows the user to select and order.

[1625] Output: The final meal plan sent to the user's device, along with a link to the food delivery service.

[1626] Step 7:

[1627] Input: Final meal plan and food delivery link sent by the server.

[1628] What it does: The device notifies the user and displays the menu within the app, allowing the user to view the menu and order delivery with a single click.

[1629] Output: The user has viewed and ordered from the health-conscious menu.

[1630] 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.

[1631] 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.

[1632] 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.

[1633] [Fourth embodiment]

[1634] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1635] 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.

[1636] 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).

[1637] 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.

[1638] 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.

[1639] 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).

[1640] 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. 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.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] 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."

[1647] The present invention relates to a system for providing a meal plan for the purpose of maintaining and improving the health of a user. Specific embodiments of the system will be described below.

[1648] System Overview

[1649] This system consists of three main components: the user, the device, and the server. The user inputs their health data and preferences and sends them to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, which is then presented to the user via their device.

[1650] Program processing flow

[1651] 1. User enters basic information and goals

[1652] The user launches the application and creates an account.

[1653] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1654] 2. The user enters their daily diet and exercise log

[1655] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[1656] Users also record their exercise details (type of exercise, duration, and calories burned).

[1657] 3. The device sends the data to the server

[1658] The data entered by the user is sent from the device (smartphone or tablet) to the server.

[1659] 4. The server analyzes the data

[1660] The server stores the received user data in storage.

[1661] The server retrieves the user's past data from the database and evaluates and analyzes their current health condition.

[1662] 5. The server generates the meal plan

[1663] The server calls the generating AI and uses the user's dietary history, allergy information, and health goals as input parameters.

[1664] Generative AI generates optimal meal plans, taking into account nutritional balance and user preferences.

[1665] 6. Server notifies meal plan

[1666] The server sends the generated meal plan to the terminal.

[1667] 7. The device will display your plan.

[1668] The device (smartphone or tablet) displays the meal plan received from the server.

[1669] The user is provided with a specific meal menu and cooking instructions.

[1670] Specific examples

[1671] Enter user information

[1672] For example, User A creates an account and enters the following information:

[1673] Age: 30

[1674] Gender: Female

[1675] Height: 165 cm

[1676] Weight: 60 kg

[1677] Food preferences: Likes chicken and broccoli, dislikes eggplant

[1678] Allergies: Nut allergies

[1679] Health goal: weight loss

[1680] Daily Record

[1681] At the end of the day, User A opens the app and records the oatmeal and banana he ate for breakfast, the salad and grilled chicken for lunch, and the salmon steak and stir-fried vegetables for dinner. He also records a 30-minute run.

[1682] Server Analysis

[1683] The server analyzes User A's current nutritional intake and calorie consumption status based on their past data and newly entered data. Based on this, it identifies any nutrients that are lacking or elements that are being consumed in excess.

[1684] Generate a meal plan

[1685] The Generator AI takes User A's data as input parameters and generates the following meal plan:

[1686] Breakfast: Avocado toast and scrambled eggs

[1687] Lunch: Grilled chicken salad (broccoli, tomato, lettuce, creamy dressing)

[1688] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[1689] Notification and implementation of the plan

[1690] The meal plan generated by the server is sent to User A's device, and the app displays the plan. User A follows the suggested menu while looking at the app.

[1691] The above is a specific embodiment for carrying out the present invention. By using this system, a meal plan suited to each individual user can be provided, helping to maintain and improve health.

[1692] The processing flow will be explained below.

[1693] Step 1:

[1694] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1695] Step 2:

[1696] The user records their daily diet, specifically the names of ingredients, amounts, cooking methods, and calorie intake. At the same time, the user also records their exercise, including the type of exercise, duration, and calories burned.

[1697] Step 3:

[1698] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[1699] Step 4:

[1700] The server stores the received user data in a database. The server also stores the user's past data, and combines the new data with the past data for analysis.

[1701] Step 5:

[1702] The server retrieves the user's past data from the database and evaluates their current health status, comparing the data previously entered by the user with their current data to analyze their current nutritional intake and calorie consumption.

[1703] Step 6:

[1704] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The server evaluates the user's nutritional balance based on data supervised by nutritionists and general nutritional rules.

[1705] Step 7:

[1706] The server calls the AI ​​generator and passes the user's dietary history, allergy information, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[1707] Step 8:

[1708] The AI ​​generative system considers nutritional balance and proposes a different menu each day that matches the user's preferences. Specifically, it designs a meal plan that meets the user's needs for protein, vitamins, minerals, etc.

[1709] Step 9:

[1710] The server then formats the generated meal plan and sends it to the user's device as encrypted data, again using a secure protocol to keep the data safe.

[1711] Step 10:

[1712] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow.

[1713] Step 11:

[1714] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[1715] Step 12:

[1716] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[1717] In this way, this system works in cooperation between the server and the terminal based on the user's input data, and utilizes generative AI to provide the optimal meal plan for each individual user.

[1718] Example 1

[1719] 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."

[1720] Conventional meal plan providing systems have difficulty in fully considering the user's individual health condition, preferences, and allergy information. Furthermore, the quality and accuracy of the meal plans are low, making it difficult to provide optimal meal plans for users and achieving results. Furthermore, meal plans rarely change from day to day, making it difficult for users to maintain motivation to continue using the system.

[1721] 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.

[1722] In this invention, the server includes a means for analyzing the user's past data and newly acquired data, a means for generating a meal plan based on prompts using a generative AI model, and a means for assessing the user's health status using multiple data science techniques. This allows for the provision of highly accurate meal plans optimized for the user's health status. Furthermore, by proposing meal plans that change daily, the server can maintain the user's motivation and efficiently manage their health.

[1723] "Health information" refers to basic health data such as the user's age, gender, height, weight, allergies, and health goals.

[1724] "Dietary preferences" is information about the user's preferred ingredients, cooking methods, and ingredients to avoid.

[1725] "Allergy" is information indicating that the user has an allergic reaction to a specific food ingredient or component.

[1726] A "health goal" is a health-related goal that a user wants to achieve (e.g., weight loss, muscle gain, blood sugar management).

[1727] A "meal log" is data recorded by a user about the contents of their daily meals (food ingredients, portions, cooking methods, calorie intake).

[1728] An "exercise log" is data recorded by a user regarding the details of their daily exercise (type of exercise, duration, calories burned).

[1729] A "terminal" is a device (e.g., a smartphone or tablet) that a user uses to input data or receive data from a server.

[1730] A "server" is a computing device that analyzes data received from users and generates meal plans.

[1731] A "database" is an information management system that stores a user's past data and retrieves it as needed.

[1732] A "generative AI model" is an artificial intelligence technology that generates optimal meal plans based on user data.

[1733] A "prompt sentence" is an explanatory sentence that describes the user's health information, dietary history, etc. to be input into the generative AI model.

[1734] "Data science techniques" are statistical and machine learning methods used to assess and analyze a user's health status.

[1735] A "meal plan" is a specific meal menu and cooking instructions created taking into account the user's health condition and preferences.

[1736] This invention relates to a system that provides meal plans for users to maintain and improve their health. The system consists of three main components: a user, a terminal, and a server.

[1737] Users enter their health information, preferences, allergies, and health goals via their device. For example, a user uses a device (smartphone or tablet) to launch a health application and enter their age, gender, height, weight, food preferences, allergies, and health goals. Next, the user enters their daily food and exercise logs. For example, if they eat oatmeal for breakfast and go running, they record that information in the application. This data is sent from the device to the server. An HTTP POST request is used for transmission, and HTTPS communication is used to ensure data security.

[1738] The server stores the received data in a database and analyzes the user's past data and newly acquired data. Data analysis uses data science techniques such as Python and R. Based on the analysis results, the server uses a generative AI model to create prompts and generate meal plans. Generative AI models such as ChatGPT and OpenAI's GPT-4 are used.

[1739] Here is an example prompt:

[1740] User Basic Information:

[1741] Age: 30

[1742] Gender: Female

[1743] Height: 165 cm

[1744] Weight: 60 kg

[1745] Food preferences: Likes chicken and broccoli, dislikes eggplant

[1746] Allergies: Nut allergies

[1747] Health goal: weight loss

[1748] User's diet history:

[1749] Breakfast: oatmeal and banana

[1750] Lunch: Salad, grilled chicken

[1751] Dinner: Salmon steak, stir-fried vegetables

[1752] User's exercise history:

[1753] Exercise: Running for 30 minutes

[1754] Based on this prompt, the generative AI model generates the optimal meal plan for the user. For example, the following meal plan might be generated:

[1755] Breakfast: Avocado toast and scrambled eggs

[1756] Lunch: Grilled Chin Salad (broccoli, tomato, lettuce, creamy dressing)

[1757] Dinner: Pasta with tomato sauce (whole wheat pasta, tomatoes, basil, mozzarella cheese)

[1758] The generated meal plan is sent from the server to the device, which then displays it to the user, along with specific meal menus and cooking instructions, allowing the user to prepare the meal.

[1759] By using this system, users can easily obtain the optimal meal plan for themselves and efficiently manage their health. Because the server performs the analysis and generation, the processing load is not placed on the device, providing a comfortable environment for users.

[1760] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1761] Step 1:

[1762] The user enters health information and goals.

[1763] Users launch a health application on their smartphone or tablet and enter their age, gender, height, weight, food preferences, allergies, and health goals. This data is collected using an input form on the device. The entered data is temporarily stored in local storage.

[1764] Input: Age, gender, height, weight, food preferences, allergies, health goals

[1765] Output: Health information data, goal data

[1766] Step 2:

[1767] The user inputs a daily food log and exercise log.

[1768] Users log in to the application to record their daily diet and exercise. For example, if they had oatmeal and a banana for breakfast and then went for a run, they would enter that information. The food log includes the ingredients, portion sizes, cooking methods, and calorie intake. The exercise log includes the type of exercise, time, and calories burned.

[1769] Input: Ingredient name, amount, cooking method, calorie intake, type of exercise, time, calories burned

[1770] Output: Food log data, exercise log data

[1771] Step 3:

[1772] The device sends the data to the server.

[1773] The device sends the data entered by the user to the server using an HTTP POST request, using HTTPS for secure communication. This request includes health information data, goal data, meal log data, and exercise log data.

[1774] Input: Health information data, goal data, food log data, exercise log data

[1775] Output: Data sent to the server

[1776] Step 4:

[1777] The server analyzes the data.

[1778] The server stores the received data in a database. It then compares the user's past data with the newly acquired data to assess their current health status. This is done using data science techniques such as Python and R. The server calculates nutrient deficiencies and excesses, as well as calorie balance.

[1779] Input: Data sent to the server, historical data

[1780] Output: Analysis result data (nutrient surplus / deficiency, calorie balance)

[1781] Step 5:

[1782] The server generates the meal plan.

[1783] The server calls the generative AI model and creates a prompt based on the analysis results. This prompt is then input into the generative AI model to generate the optimal meal plan for the user. ChatGPT and OpenAI's GPT-4 are used as generative AI models.

[1784] Input: Analysis result data

[1785] Output: Meal plan prompt, generated meal plan

[1786] Step 6:

[1787] The server will notify you of the meal plan.

[1788] The server sends the generated meal plan to the device using an HTTP POST request, allowing the user to receive the updated meal plan.

[1789] Input: Generated meal plan

[1790] Output: Meal plan sent to device

[1791] Step 7:

[1792] The device will display the plan.

[1793] The device displays the meal plan received from the server to the user, and when the user opens the application, a specific menu and cooking instructions are displayed on the screen.

[1794] Input: Meal plan sent to device

[1795] Output: A specific meal plan and cooking instructions displayed to the user

[1796] The above are the specific processing steps of the system program, which allow users to efficiently obtain a meal plan that suits them and manage their health.

[1797] (Application example 1)

[1798] 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."

[1799] In modern society, the growing health consciousness has led to an increased importance of personalized dietary management. However, there is no easy way to obtain a meal plan that suits each individual's dietary preferences, allergies, and health goals, and then easily implement the meals based on that plan. Furthermore, there is a lack of sufficient coordination between the proposal of a meal plan and the actual delivery of the meal, which requires users to go through complicated procedures. Furthermore, there are insufficient means for users to track the progress of their meal or the delivery status.

[1800] 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.

[1801] In this invention, the server includes: a means for a user to input information such as dietary preferences, allergies, and health goals; a means for the user to input a meal log and exercise log; a means for transmitting the input data to a data center; a means for the data center to store the received user data; a means for the data center to generate a meal plan suitable for the user using a generative AI model; a means for transmitting the generated meal plan from the data center to a terminal and displaying it to the user; a means for a delivery service to suggest an optimal menu based on the generated meal plan; and a means for tracking delivery progress in real time and notifying the user. This allows users to quickly obtain an individually optimized meal plan and easily purchase meals based on it. Furthermore, knowing the delivery progress in real time improves convenience.

[1802] "User" refers to an individual who intends to use the system to manage their health.

[1803] "Dietary preferences" is information about ingredients and dishes that the user likes.

[1804] "Allergy" refers to a food ingredient or ingredient that is harmful to the user's health if ingested.

[1805] "Health goal" refers to a specific health or fitness goal that a user wishes to achieve.

[1806] A "meal log" is data that allows a user to record the contents of their daily meals.

[1807] An "exercise log" is data that allows a user to record the details of their daily exercise.

[1808] "Data Center" refers to a computer system for storing user data and for performing analysis and plan generation.

[1809] "Generative AI model" refers to artificial intelligence technology that automatically generates optimal meal plans based on user information.

[1810] A "meal plan" is a plan that takes into consideration specific meal menus and nutritional balance proposed to the user.

[1811] "Terminal" refers to the device through which a user enters information and receives meal plans.

[1812] "Delivery Service" refers to the logistics and distribution system for delivering meals to users.

[1813] "Delivery progress" refers to the process and progress of the meal being delivered to the user.

[1814] The present invention is a system for generating an individually optimized meal plan based on a user's health condition and preferences, and then reliably providing meals based on that plan. This system is mainly composed of three elements: the user, a terminal, and a data center.

[1815] Hardware and Software

[1816] Hardware:

[1817] Device: refers to a smartphone or tablet, which is the device through which the user enters information and receives the meal plan.

[1818] Data center: A group of servers that processes and analyzes information, typically using cloud services (e.g., AWS or Google Cloud Platform).

[1819] software:

[1820] Generative AI models: Use artificial intelligence (e.g., generative AI models such as GPT-4) to generate personalized, optimized meal plans.

[1821] Database: Use a database such as SQL or NoSQL to manage and store user information.

[1822] Process Overview

[1823] 1. The user enters basic information, preferences, and allergies

[1824] Users enter basic information such as age, gender, height, weight, food preferences, allergies, and health goals through the terminal, which is then sent to a data center.

[1825] 2. Enter your daily food log

[1826] Users record their daily diet and exercise logs, and this data is also sent to a data center.

[1827] 3. Data storage and analysis

[1828] The data center stores and analyzes the received user data, including the user's past data, to assess the user's health status.

[1829] 4. Generative AI Meal Plan Generation

[1830] The data center generates an individually optimized meal plan by inputting user data into a generative AI model, specifically using prompts such as:

[1831] (Example of a prompt)

[1832] Generate a daily meal plan based on your health data.

[1833] Age: 30

[1834] Gender: Female

[1835] Height: 165 cm

[1836] Weight: 60 kg

[1837] Preferences: Likes chicken and broccoli, dislikes eggplant

[1838] Allergies: Nut allergies

[1839] Health goal: weight loss

[1840] 5. Send and view your meal plan

[1841] The generated meal plan is sent from the data center to the user's device, where the user can review it. The delivery service also suggests optimal menus based on the meal plan.

[1842] 6. Track delivery progress

[1843] Users can track delivery progress in real time and check the progress on their devices.

[1844] This system allows users to easily obtain individually optimized meal plans and efficiently manage their health based on those plans. In addition, delivery progress can be monitored in real time, improving user convenience.

[1845] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1846] Step 1:

[1847] The user enters basic information, preferences, and allergies.

[1848] Input: Age, Gender, Height, Weight, Food Preferences, Allergies, Health Goals.

[1849] How it works: The user enters this information into the application through a terminal.

[1850] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[1851] Step 2:

[1852] The user inputs a daily food log and exercise log.

[1853] Input: Daily dietary information (ingredients, amounts, cooking methods), calorie intake, exercise information (type of exercise, time, calories burned).

[1854] How it works: The user uses the device to record and enter their daily diet and exercise log.

[1855] Output: The entered data is temporarily stored on the device and is then ready to be sent to the server.

[1856] Step 3:

[1857] The device sends the data to the data center.

[1858] Input: User data entered in step 1 and step 2.

[1859] How it works: The device sends stored user data over the internet to a data center.

[1860] Output: The data center receives the user data and stores it in a database.

[1861] Step 4:

[1862] The server evaluates the current health status based on the data received.

[1863] Input: User's basic information, preferences, allergies, daily food log, and exercise log.

[1864] How it works: The server analyzes your current nutritional intake and calorie consumption status based on past data stored in a database. Specifically, it retrieves the data using SQL queries and applies analysis algorithms.

[1865] Output: An assessment of the user's current health status and nutrient and calorie needs.

[1866] Step 5:

[1867] Generate meal plans using generative AI models.

[1868] Input: Health assessment results, user demographics, preferences, allergies, and health goals.

[1869] How it works: The server sends prompts to a generative AI model (e.g., GPT-4) to generate an optimal meal plan.

[1870] Example prompt sentence:

[1871] Generate a daily meal plan based on your health data.

[1872] Age: 30

[1873] Gender: Female

[1874] Height: 165 cm

[1875] Weight: 60 kg

[1876] Preferences: Likes chicken and broccoli, dislikes eggplant

[1877] Allergies: Nut allergies

[1878] Health goal: weight loss

[1879] Output: A specific meal plan tailored to the user (e.g., breakfast, lunch, and dinner menus).

[1880] Step 6:

[1881] The generated meal plan is sent to the terminal and displayed to the user.

[1882] Input: A meal plan generated from a generative AI model.

[1883] Operation: The server sends the generated meal plan to the device.

[1884] Output: The meal plan is displayed on the user's device. The user confirms the suggested menu.

[1885] Step 7:

[1886] The delivery service will suggest the best menu based on the generated meal plan.

[1887] Input: Meal plan and delivery preferences set by the user.

[1888] How it works: Based on your meal plan, the server will select and suggest the best items from the menu offered by the delivery service.

[1889] Output: Delivery menu suggestions are displayed on the user's device.

[1890] Step 8:

[1891] Track delivery progress in real time and notify users.

[1892] Input: The progress of the delivery ordered by the user.

[1893] How it works: The server receives progress information from the delivery service and notifies the device.

[1894] Output: Delivery progress is displayed in real time on the user's device.

[1895] 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.

[1896] The present invention combines an emotion engine with a system that provides meal plans aimed at maintaining and improving the user's health. Specific embodiments of the system are described below.

[1897] System Overview

[1898] This system consists of three main components: the user, the device, and the server. The user inputs their health data, preferences, and emotional state, which are then sent to the server via their device. The server then analyzes the data and uses generative AI to generate an optimal meal plan for the user, then adjusts the plan using an emotion engine. The plan is then finally presented to the user via their device.

[1899] Program processing flow

[1900] 1. Enter user information

[1901] The user launches the application and creates an account.

[1902] Users enter basic information (age, gender, height, weight), food preferences, allergies, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1903] 2. Entering Emotion Data

[1904] Users input their emotional state in real time, based on their reactions to daily events and meals.

[1905] Emotions come in categories such as happy, sad, stressed, and relaxed.

[1906] 3. The user enters their daily diet and exercise log

[1907] Users record their daily meal details (ingredients, portions, cooking methods, and calorie intake).

[1908] Users also record their exercise details (type of exercise, duration, and calories burned).

[1909] 4. Data Transmission

[1910] The terminal encrypts the data entered by the user and sends it to the server. All communication is carried out using a secure protocol to ensure data confidentiality.

[1911] 5. Server Analysis

[1912] The server stores the received user data in a database and analyzes it.

[1913] The server retrieves the user's past data from the database and uses it to evaluate their current health condition.

[1914] 6. Meal plan generation

[1915] The server calls the generation AI and passes the user's dietary history, allergy information, emotional state, and health goals as input parameters.

[1916] Generative AI uses this data to generate an optimal meal plan.

[1917] 7. Use of Emotion Engines

[1918] An emotion engine analyzes the user's emotional data and adjusts the generated meal plan.

[1919] For example, if a user is feeling stressed, a menu containing ingredients with a high relaxing effect is suggested.

[1920] The emotion engine assesses the user's motivation to achieve their health goals and stress level, and provides encouraging messages and advice accordingly.

[1921] 8. Transmission and Display

[1922] The server then sends the final adjusted meal plan to the device, again using a secure protocol.

[1923] The device displays the received meal plan and encouraging messages to the user.

[1924] Specific examples

[1925] Enter user information

[1926] For example, User B creates an account and enters the following information:

[1927] Age: 28

[1928] Gender: Male

[1929] Height: 175 cm

[1930] Weight: 70 kg

[1931] Favorite ingredients: chicken, spinach, tomatoes

[1932] Disliked food: Celery

[1933] Allergens: Wheat

[1934] Health Goal: Muscle Gain

[1935] Entering emotion data

[1936] User B enters their daily physical and emotional state in categories such as "stress," "relaxation," and "happiness."

[1937] Daily Record

[1938] User B records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner. He also trains at the gym and records his exercise schedule.

[1939] Server Analysis and Plan Generation

[1940] The server analyzes nutritional balance based on User B's data, and the AI ​​generates a meal plan. Based on this, the emotion engine suggests additional menu items with a relaxing effect on days when the user feels stressed.

[1941] Meal plan notification and implementation

[1942] The generated plan and advice based on emotions are sent to the device and displayed in User B's app. User B follows this advice and eats accordingly, then enters feedback.

[1943] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to provide an appropriate and effective meal plan that also takes into account the emotional state of each individual user.

[1944] The processing flow will be explained below.

[1945] Step 1:

[1946] The user launches the application and creates an account. Following the instructions, the user enters basic information (age, gender, height, weight), food preferences (favorite foods, least favorite foods), allergy information, and health goals (e.g., weight loss, muscle gain, blood sugar management).

[1947] Step 2:

[1948] The user inputs their emotional state, specifically their reactions to daily events and meals, in categories such as "happy," "sad," "stressed," and "relaxed."

[1949] Step 3:

[1950] The user records the contents of their daily meals, specifically the names of ingredients, amounts, cooking methods, calorie intake, etc. They also record exercise, entering the type, duration, and calories burned.

[1951] Step 4:

[1952] The device encrypts the data entered by the user and sends it to the server. All communications are carried out using secure protocols to ensure data confidentiality and security.

[1953] Step 5:

[1954] The server stores the received user data in a database, and then integrates the user's past data with new data for analysis.

[1955] Step 6:

[1956] The server retrieves the user's past data from the database and evaluates their current health condition, which is then used to analyze their current nutritional intake and calorie consumption.

[1957] Step 7:

[1958] The server outputs the analysis results to identify necessary nutrients and areas for improvement. The analysis uses data supervised by nutritionists and general nutritional rules.

[1959] Step 8:

[1960] The server calls the AI ​​generator, which uses the user's dietary history, allergy information, emotional state, and health goals as input parameters. The AI ​​generator generates an optimal meal plan based on this data.

[1961] Step 9:

[1962] The emotion engine analyzes the user's emotional data. Specifically, the emotion engine evaluates the user's emotional state and adjusts the generated meal plan as needed. For example, if the user is feeling stressed, the engine will suggest a menu containing ingredients that will reduce stress.

[1963] Step 10:

[1964] The server then formats the meal plan tailored by the emotion engine and sends it to the device as encrypted data, again using a secure protocol to keep the data safe.

[1965] Step 11:

[1966] The device deserializes the meal plan received from the server and displays it to the user within the application. Specific meal menus and cooking instructions are displayed, making it easy for the user to follow. Encouraging messages and advice generated by the emotion engine are also displayed.

[1967] Step 12:

[1968] The user actually follows the meal plan and enters their results and impressions into the app, which records feedback on how well the user followed the plan and any changes in their physical condition.

[1969] Step 13:

[1970] The device then sends the feedback data back to the server, which uses it for future analysis and plan generation. The server then uses the user's feedback to further optimize future meal plans.

[1971] This process allows the system to provide appropriate and effective meal plans that take into account each user's emotional state.

[1972] Example 2

[1973] 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."

[1974] Many people today find it difficult to balance health management and diet. It is also difficult to independently determine the optimal meal plan that corresponds to one's health and emotional state. Even if a meal plan is appropriate, it can be difficult to adhere to due to the influence of emotions and stress. To solve these problems, a system is needed that takes into account each user's health data and daily emotional state and provides the optimal meal plan.

[1975] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1976] In this invention, the server includes: means for the user to input information such as food preferences, allergies, and health goals; means for the user to input daily emotional data and a meal log and exercise log; means for encrypting the input data and sending it to the server; means for the server to store the user data received; means for the server to generate a meal plan suitable for the user using an artificial intelligence model; means for the emotion engine to adjust the meal plan based on the user's emotional data; and means for sending the generated meal plan from the server to a terminal and displaying it to the user. This makes it possible to provide an optimal meal plan that takes into consideration the health and emotional state of each individual user.

[1977] A "user" is an individual who uses the system and inputs health data and emotion data.

[1978] "Dietary preferences" refers to the types of ingredients and dishes that a user likes to eat.

[1979] "Allergy" refers to a health problem that occurs when a user ingests a particular food ingredient.

[1980] A "health goal" refers to a specific health goal that a user wants to achieve, such as losing weight or gaining muscle.

[1981] "Emotion data" is data that indicates the user's daily emotional state, including states such as stress, relaxation, and happiness.

[1982] A "meal log" is data in which a user records the contents of their daily meals, and includes the names of ingredients, portions, calories, etc.

[1983] An "exercise log" is data in which a user records the details of their daily exercise, including the type of exercise, time, calories burned, and so on.

[1984] "Encryption" refers to a technique for converting transmitted data into a format that cannot be deciphered by third parties.

[1985] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates and sends meal plans.

[1986] An "artificial intelligence model" refers to a computational model that learns from large amounts of data and generates meal plans that are suitable for the user.

[1987] "Emotion engine" refers to a system that analyzes a user's emotional data and adjusts meal plans based on the results.

[1988] "Terminal" refers to a device through which a user can input data and display meal plans received from a server.

[1989] This invention is a system that provides meal plans for users to maintain and improve their health, and is combined with an emotion engine. In this embodiment, it operates through three main elements: the user, the terminal, and the server.

[1990] System Configuration

[1991] Enter user information

[1992] First, users install the dedicated application and create an account. The information they enter includes basic information (age, gender, height, weight), food preferences, allergies, and health goals. The application collects this information through a GUI.

[1993] Entering emotion data

[1994] Next, users input their daily emotional data into the application. Emotional states are presented in categories such as "stress," "relaxed," and "happy," and users can select their daily emotional state and add comments.

[1995] Enter your daily diet and exercise log

[1996] Users input their daily dietary information (ingredients, portions, calories, cooking methods) and exercise information (type of exercise, time, calories burned) into the application, which updates the user's health data daily.

[1997] Data transmission

[1998] The device encrypts the collected data using AES encryption and transmits it securely to the server via the HTTPS protocol, ensuring the confidentiality of the data.

[1999] Server Analysis

[2000] The server stores the received data in a database and analyzes the user's current health status based on their past data. The server also uses an artificial intelligence (AI) model to generate an optimal meal plan for the user. The generated plan is adjusted according to the user's stress level and relaxation state by analyzing the user's emotional data using an emotion engine.

[2001] View Meal Plans

[2002] Finally, the server sends the tailored meal plan to the device, where the application displays it to the user, including encouraging messages and advice tailored to the user's emotional state.

[2003] Specific examples

[2004] User B creates an account and enters the following information:

[2005] Age: 28

[2006] Gender: Male

[2007] Height: 175 cm

[2008] Weight: 70 kg

[2009] Favorite ingredients: chicken, spinach, tomatoes

[2010] Disliked food: Celery

[2011] Allergens: Wheat

[2012] Health Goal: Muscle Gain

[2013] When inputting daily emotional data, User B inputs his / her daily emotional state such as "stress," "relaxation," or "happiness."

[2014] I eat oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner, and I record each of them in the app. I also enter my gym workouts.

[2015] The server analyzes this data, and a generative AI model generates a meal plan. The emotion engine suggests additional ingredients with a relaxing effect (e.g., herbal tea) on stressful days.

[2016] Finally, the adjusted meal plan and emotion-based advice are sent to the device and displayed in User B's app, where User B follows the plan and provides feedback.

[2017] Prompt Sentence Examples

[2018] Generate a meal plan that suggests foods that will have a relaxing effect on the user's stressful days. The user's information is: age 28, male, 175cm, 70kg, favorite foods are chicken, spinach, and tomato, dislikes are celery, wheat allergy, and health goal is to gain muscle.

[2019] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2020] Step 1:

[2021] A user creates an account and enters basic information.

[2022] Input: Install the application and enter user information (age, gender, height, weight, favorite ingredients, disliked ingredients, allergies, health goals).

[2023] Output: The user information is saved on the device.

[2024] Specific operation: The user downloads and installs the application, then creates an account by entering an email address and password, and enters basic information.

[2025] Step 2:

[2026] The user inputs daily emotion data.

[2027] Input: Enter your emotional state (stressed, relaxed, happy, etc.) and any related comments.

[2028] Output: Emotion data is saved on the device.

[2029] Specific operation: The user opens the application, selects their current emotional state on the emotion input screen, and optionally adds a comment.

[2030] Step 3:

[2031] The user inputs a daily food log and exercise log.

[2032] Input: Enter the meal details (ingredients, amount, cooking method, calories) and exercise details (type of exercise, time, calories burned).

[2033] Output: Food log and exercise log are saved on the device.

[2034] Specific operation: The user opens the application, enters the names of ingredients, amounts, cooking methods, and calories on the meal input screen, and enters the type of exercise, time, and calories burned on the exercise input screen.

[2035] Step 4:

[2036] The device encrypts the data and sends it to the server.

[2037] Input: Obtain user information, emotional data, food log, and exercise log.

[2038] Output: The encrypted data is sent to the server.

[2039] Specific operation: The terminal encrypts the data using the AES encryption algorithm and sends it to the server via the HTTPS protocol.

[2040] Step 5:

[2041] The server stores the received data in a database.

[2042] Input: Encrypted data is sent to the server.

[2043] Output: Encrypted data stored in the database.

[2044] Specific operation: The server decrypts the received data and stores it in a database, classifying it by user.

[2045] Step 6:

[2046] The server compares the current health status with past data and analyzes it.

[2047] Input: Retrieves past data in the database and newly received data.

[2048] Output: The analysis results are obtained.

[2049] How it works: The server compares past user data with new data and uses statistical algorithms to assess current health status.

[2050] Step 7:

[2051] The server calls the generation AI to generate a meal plan.

[2052] Input: Obtain user information, emotional data, food log, exercise log, and health status analysis results.

[2053] Output: An optimal meal plan is generated.

[2054] Specific operation: The server provides the necessary parameters to the generative AI model, allowing it to generate the optimal meal plan for the user.

[2055] Step 8:

[2056] An emotion engine adjusts meal plans based on the user's emotional data.

[2057] Input: Obtain the generated meal plan and the user's sentiment data.

[2058] Output: You get a tailored meal plan.

[2059] Specific operation: The emotion engine analyzes the user's emotional data and adds menus that have stress-reducing or relaxing effects as needed.

[2060] Step 9:

[2061] The server sends the final meal plan to the device.

[2062] Enter: Get your tailored meal plan.

[2063] Output: The encrypted meal plan is sent to the device.

[2064] How it works: The server encrypts the meal plan using AES encryption and sends it to the device via HTTPS protocol.

[2065] Step 10:

[2066] The device displays the meal plan to the user.

[2067] Enter: Get your encrypted meal plan.

[2068] Output: The meal plan is displayed to the user.

[2069] Specific operation: The device decodes the received data and displays the meal plan in an easy-to-understand format for the user in the application.

[2070] (Application example 2)

[2071] 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."

[2072] While conventional meal plan providing systems can take into account a user's health condition and preferences, they have the problem of not being able to incorporate the user's emotional state. As a result, it is difficult to provide an appropriate meal plan even when the user is feeling stressed or tired. Furthermore, there has been no system that seamlessly links to providing specific meal menus based on the generated meal plan. This makes it difficult for users to easily incorporate optimal meals and to continuously manage their health.

[2073] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2074] In this invention, the server includes means for generating a meal plan suitable for the user using a generative AI model, means for adjusting the meal plan using an emotion engine, and means for providing a menu based on the meal plan to the user in cooperation with an external service. This makes it possible to generate an optimal meal plan that takes the user's emotional state into consideration, and to seamlessly present and provide a specific menu based on the meal plan.

[2075] "User" means an individual who uses the System to receive a Meal Plan.

[2076] "Dietary preferences" refers to information about the ingredients and dishes that a user likes to eat.

[2077] "Allergy" refers to information that indicates a user has an allergic reaction to a particular food ingredient.

[2078] "Health Goal" means a health or fitness goal that a User wishes to achieve.

[2079] "Data" refers to information entered by the user, such as food preferences, allergies, health goals, food logs, and exercise logs.

[2080] "Food log" refers to data used by a user to record the meals they eat each day.

[2081] "Exercise log" refers to data that records the exercise a user has performed and the calories they have burned.

[2082] "Generative AI model" refers to an artificial intelligence model that generates optimal meal plans based on user data.

[2083] "Emotion Engine" refers to an algorithm that analyzes a user's emotional state and adjusts their meal plan.

[2084] "External Services" refers to service providers and stores that cooperate with us to provide specific menus based on the meal plan.

[2085] "Server" refers to the computing resources that store the data submitted by the user and generate meal plans using the generative AI model and emotion engine.

[2086] "Terminal" means the electronic device used by a User to enter data and view meal plans.

[2087] System Overview

[2088] The system of the present invention is composed of three main elements: a user, a terminal, and a server. The details of each element and their roles are explained below.

[2089] User

[2090] Users input information such as their food preferences, allergies, and health goals through the device, as well as daily food and exercise logs. Furthermore, their emotional state is recorded and sent to the system.

[2091] Terminal

[2092] The terminal functions as a user interface and is an electronic device such as a smartphone or tablet. A dedicated application is available on the terminal, allowing the user to input and send their own data. The input data is encrypted and sent to the server. The terminal also displays meal plans and related messages sent from the server.

[2093] server

[2094] The server is responsible for storing and analyzing data received from users. The server has the following main functions:

[2095] Generative AI model: Generates optimal meal plans based on a user's dietary history, allergy information, and health goals.

[2096] Emotion engine: Analyzes the user's emotional data and adjusts the generated meal plan. For example, if the user is feeling stressed, the generative AI model will add menu items containing ingredients with a relaxing effect to the plan it suggests.

[2097] External service integration: Collaborate with a food delivery service to provide specific menus based on the generated meal plan.

[2098] Program processing

[2099] The server analyzes the data using AI models and emotion engines. Specifically, it performs the following steps:

[2100] 1. Receiving and storing data: We receive and securely store data sent by users.

[2101] 2. Health status assessment: Retrieve historical data from the database and assess current health status.

[2102] 3. Meal plan generation: Have the generative AI model generate an optimal meal plan using a prompt, such as:

[2103] "

[2104] Age: 28

[2105] Gender: Male

[2106] Health Goal: Muscle Gain

[2107] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[2108] Emotional state: Stress

[2109] Allergens: Wheat

[2110] Favorites: Chicken, spinach, tomatoes

[2111] Dislikes: Celery

[2112] "

[2113] 4. Adjustment by the emotion engine: The emotion engine further adjusts the generated plan, for example, adding ingredients that have a relaxing effect if you are feeling stressed.

[2114] 5. Send Final Plan: The final, adjusted meal plan is sent to the device, again using secure protocols for all communications.

[2115] 6. Notification and Display: The device displays the received meal plan and encouraging messages to the user.

[2116] Specific examples

[2117] As a real-world example, User B creates an account and enters the following information:

[2118] Age: 28

[2119] Gender: Male

[2120] Height: 175 cm

[2121] Weight: 70 kg

[2122] Favorite ingredients: Chicken, spinach, tomatoes

[2123] Disliked food: Celery

[2124] Allergens: Wheat

[2125] Health Goal: Muscle Gain

[2126] User B enters "stress" as his emotional state and records oatmeal for breakfast, grilled chicken and salad for lunch, and salmon and stir-fried vegetables for dinner in his food log. Based on this, the server uses the generative AI model and emotion engine to generate an optimal meal plan and sends the final plan to User B's device. User B can then use food delivery services based on the plan and manage his or her health.

[2127] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2128] Step 1:

[2129] Input: The user inputs information such as food preferences, allergies, health goals, food log, exercise log, and emotional state into the device.

[2130] Specific operation: The user launches the application and enters information into the form. For example, the user might enter "My favorite foods are chicken, spinach, and tomatoes" as their preference information, "I'm allergic to wheat" as their allergy information, and "I want to gain muscle mass" as their health goal.

[2131] Output: The terminal formats the input data and converts it into a format that can be sent to the server.

[2132] Step 2:

[2133] Input: Data entered by the user.

[2134] Specific operation: The terminal encrypts the input data and sends it to the server using a secure protocol (e.g., HTTPS).

[2135] Output: The server stores the received data in a database.

[2136] Step 3:

[2137] Input: Encrypted data sent from the device.

[2138] What it does: The server decrypts the encrypted data and stores it in a database, ensuring your information is stored securely.

[2139] Output: A saved dataset.

[2140] Step 4:

[2141] Input: User preferences, allergies, health goals, and past food and exercise log data.

[2142] What it does: The server takes this data and provides input to the generative AI model as a prompt, like this:

[2143] "

[2144] Age: 28

[2145] Gender: Male

[2146] Health Goal: Muscle Gain

[2147] Food history: Oatmeal for breakfast, grilled chicken and salad for lunch, salmon and stir-fried vegetables for dinner

[2148] Emotional state: Stress

[2149] Allergens: Wheat

[2150] Favorites: Chicken, spinach, tomatoes

[2151] Dislikes: Celery

[2152] "

[2153] The generative AI model uses this information to generate an optimal meal plan.

[2154] Output: The generated meal plan.

[2155] Step 5:

[2156] Input: A meal plan generated by a generative AI model.

[2157] What it does: The server passes the meal plan to the emotion engine, which fine-tunes it based on the user's emotional state. For example, if the user is rated as "stressed," the server adjusts the menu to include ingredients with a relaxing effect (e.g., herbal tea and bananas).

[2158] Output: Adjusted final meal plan.

[2159] Step 6:

[2160] Input: Your adjusted final meal plan.

[2161] Specific operation: The server sends the final plan to an external food delivery service. Based on the previously adjusted plan, it proposes specific meal menus and allows the user to select and order.

[2162] Output: The final meal plan sent to the user's device, along with a link to the food delivery service.

[2163] Step 7:

[2164] Input: Final meal plan and food delivery link sent by the server.

[2165] What it does: The device notifies the user and displays the menu within the app, allowing the user to view the menu and order delivery with a single click.

[2166] Output: The user has viewed and ordered from the health-conscious menu.

[2167] 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.

[2168] 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.

[2169] 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.

[2170] 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.

[2171] 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.

[2172] 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.

[2173] 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).

[2174] 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.

[2175] 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."

[2176] 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.

[2177] 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).

[2178] 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.

[2179] 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.

[2180] 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.

[2181] 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.

[2182] 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.

[2183] 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.

[2184] 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.

[2185] 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.

[2186] 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.

[2187] 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.

[2188] The following is further disclosed regarding the above embodiment.

[2189] (Claim 1)

[2190] a means for the user to input information such as dietary preferences, allergies, and health goals;

[2191] A means for users to input food logs and exercise logs;

[2192] means for transmitting the input data to a server;

[2193] a means for storing the user data received by the server;

[2194] A means for the server to use AI to generate a meal plan suitable for the user;

[2195] means for transmitting the generated meal plan from the server to the terminal and displaying it to the user;

[2196] A system including:

[2197] (Claim 2)

[2198] 2. The system of claim 1, wherein the server comprises means for using the user's past data as a basis for analyzing the user's health condition.

[2199] (Claim 3)

[2200] 2. The system according to claim 1, further comprising a means for generating meal plans that take into consideration nutritional balance and suggesting daily menus that suit the user's preferences.

[2201] "Example 1"

[2202] (Claim 1)

[2203] a means for the user to input information such as health information, dietary preferences, allergies, and health goals;

[2204] A means for users to input their daily food and exercise logs;

[2205] means for transmitting input data from the terminal to a server;

[2206] a means for storing the received user data in a database by the server;

[2207] A means for the server to analyze the user's past data and newly acquired data;

[2208] A means for the server to generate a meal plan based on the prompt using the generative AI model;

[2209] means for transmitting the generated meal plan from the server to the terminal and displaying it to the user;

[2210] A system including:

[2211] (Claim 2)

[2212] 10. The system of claim 1, wherein the server comprises means for assessing and analyzing the health status of the user using a plurality of data science techniques.

[2213] (Claim 3)

[2214] 2. The system according to claim 1, further comprising a means for generating a meal plan that takes into consideration the user's nutritional balance, reflects preferences and allergy information, and proposes daily menus for multiple days.

[2215] "Application Example 1"

[2216] (Claim 1)

[2217] a means for the user to input information such as dietary preferences, allergies, and health goals;

[2218] A means for users to input food logs and exercise logs;

[2219] means for transmitting the input data to a data center;

[2220] A means for storing the user data received by the data center;

[2221] A means for the data center to utilize the generative AI model to generate a meal plan suitable for the user;

[2222] a means for transmitting the generated meal plan from the data center to a terminal and displaying the plan to the user;

[2223] A means for suggesting optimal menu items from a delivery service based on the generated meal plan;

[2224] a means for tracking delivery progress in real time and notifying the user;

[2225] A system including:

[2226] (Claim 2)

[2227] 2. The system of claim 1, wherein the data center comprises means for using the user's past data as a criterion to evaluate the user's health status.

[2228] (Claim 3)

[2229] 2. The system according to claim 1, further comprising a means for generating a meal plan that takes into consideration nutritional balance and proposes a menu that changes daily according to the user's preferences.

[2230] "Example 2: Combining Emotion Engines"

[2231] (Claim 1)

[2232] a means for the user to input information such as dietary preferences, allergies, and health goals;

[2233] A means for users to input daily emotional data, food logs, and exercise logs;

[2234] means for encrypting input data and transmitting the data to a server;

[2235] a means for storing the user data received by the server;

[2236] a means for the server to utilize an artificial intelligence model to generate a meal plan suited to the user;

[2237] a means for the emotion engine to adjust the meal plan based on the user's emotion data;

[2238] means for transmitting the generated meal plan from the server to the terminal and displaying it to the user;

[2239] A system including:

[2240] (Claim 2)

[2241] 2. The system of claim 1, wherein the server comprises means for using the user's past data as a basis for analyzing the user's health condition.

[2242] (Claim 3)

[2243] 2. The system of claim 1, further comprising means for generating meal plans that take into account nutritional balance, suggest daily menus tailored to the user's preferences, and adjust the plans based on the user's emotional state.

[2244] "Application example 2 when combining emotion engines"

[2245] (Claim 1)

[2246] a means for the user to input information such as dietary preferences, allergies, and health goals;

[2247] A means for users to input food logs and exercise logs;

[2248] means for transmitting the input data to a server;

[2249] a means for storing the user data received by the server;

[2250] A means for the server to utilize the generative AI model to generate a meal plan suitable for the user;

[2251] A means of adjusting meal plans using an emotion engine;

[2252] A means for linking with external services to provide users with menus based on meal plans;

[2253] means for transmitting the generated meal plan from the server to the terminal and displaying it to the user;

[2254] A system including:

[2255] (Claim 2)

[2256] 2. The system of claim 1, wherein the server comprises means for using the user's past data as a basis for analyzing the user's health condition.

[2257] (Claim 3)

[2258] The system according to claim 1, further comprising: a means for generating meal plans that take into account nutritional balance and suggesting daily menus that suit the user's preferences; and a means for linking menus based on the meal plans with external services. [Explanation of symbols]

[2259] 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 the user to input information such as dietary preferences, allergies, and health goals; A means for users to input food logs and exercise logs; means for transmitting the input data to a server; a means for storing the user data received by the server; A means for the server to use AI to generate a meal plan suitable for the user; means for transmitting the generated meal plan from the server to the terminal and displaying it to the user; A system including:

2. 2. The system of claim 1, wherein the server comprises means for using the user's past data as a reference for analyzing the user's health condition.

3. 2. The system according to claim 1, further comprising means for generating meal plans that take into consideration nutritional balance and suggesting daily menus that suit the user's preferences.

Images