System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting personal information; means for setting a diet goal based on the personal information; means for generating daily behavioral instructions based on the diet goal; means for notifying a user of the behavioral instructions; means for monitoring the user's behavior; means for generating additional instructions if the user's behavior is not on schedule; and means for periodically checking the user's progress and providing feedback.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many people want to lose weight but put off dieting because they lack motivation, can't find a trigger, or need a push. Effective diet support methods for these inactive people are needed, but current support methods often fail to produce sufficient results. Furthermore, there is a lack of follow-up when users don't follow instructions, making it difficult to maintain a consistent diet. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for inputting personal information and a means for setting diet goals based on the personal information. It also includes a means for generating daily behavioral instructions based on the diet goals and a means for notifying the user of the behavioral instructions. It also includes a means for monitoring the user's behavior and a means for generating additional instructions if the user's behavior is not as planned. This allows the user to achieve their goal simply by following the instructions, even if they are inactive. Furthermore, by providing a means for periodically checking the user's progress and providing feedback, continuous diet support can be realized.

[0006] "Personal Information" refers to information including a user's age, weight, height, health information, etc.

[0007] "Diet goal" refers to the weight the user sets and the deadline for achieving that weight.

[0008] "Behavioral instructions" refers to information that specifically instructs the user on the meal menu, exercise content, and daily behavior plan that they should follow.

[0009] "Notification" refers to the action of informing the user of instructions to act via a device.

[0010] "Monitoring" refers to detecting a user's location and activity data and monitoring their behavior.

[0011] "Additional instructions" refers to supplementary instructions provided if the user does not follow the initial instruction.

[0012] "Feedback" refers to information that provides evaluation and advice based on the user's progress.

[0013] "System" refers to a comprehensive set of components that input personal information, set diet goals, generate behavioral instructions, notify, monitor, generate additional instructions, and provide feedback. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0036] System configuration

[0037] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[0038] Implementation details

[0039] 1. User Registration

[0040] User: Installs and launches the app. Enters personal information such as age, weight, height, and health information on the screen that appears when the app is launched.

[0041] Terminal: The personal information entered is immediately sent to the server.

[0042] Server: Validates the received personal information and stores it in a database.

[0043] 2. Goal Setting

[0044] User: Enter the target weight you want to lose and the time frame to achieve it. For example, you can set "lose 5 kg in 3 months."

[0045] Terminal: Sends target data to the server.

[0046] Server: Identifies your goals and generates an appropriate diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[0047] 3. Daily instruction generation

[0048] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0049] Server: Sends the generated action plan to the device.

[0050] Terminal: The terminal notifies the user of the received action plan in real time.

[0051] 4. Behavioral monitoring

[0052] Device: Detects the user's location and activity through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[0053] Device: Sends detected behavioral data to the server.

[0054] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[0055] 5. Providing follow-up instructions

[0056] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0057] Terminal: Inform the user of alternative instructions.

[0058] 6. Progress Check and Feedback

[0059] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0060] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[0061] Device: Notify the user of the feedback.

[0062] This means that even if the user is inactive, they can effectively diet by simply following the system's instructions.

[0063] The processing flow will be explained below.

[0064] Step 1:

[0065] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is first launched.

[0066] Step 2:

[0067] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[0068] Step 3:

[0069] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[0070] Step 4:

[0071] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[0072] Step 5:

[0073] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[0074] Step 6:

[0075] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[0076] Step 7:

[0077] Server: Stores the generated diet plan in a database and sends it to the device.

[0078] Step 8:

[0079] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0080] Step 9:

[0081] Server: Sends the generated action plan to the device in real time.

[0082] Step 10:

[0083] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[0084] Step 11:

[0085] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[0086] Step 12:

[0087] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[0088] Step 13:

[0089] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[0090] Step 14:

[0091] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0092] Step 15:

[0093] Terminal: Provide the user with alternative instructions that are specific and clearly understandable.

[0094] Step 16:

[0095] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0096] Step 17:

[0097] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[0098] Step 18:

[0099] Device: Notifies the user of feedback in a format that is easily understood by the user.

[0100] Example 1

[0101] 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."

[0102] Conventional diet systems require users to actively manage themselves, which makes it difficult to maintain motivation. Additionally, they lack the functionality to properly monitor user behavior and provide real-time feedback, making it difficult to promote an effective diet.

[0103] 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.

[0104] In this invention, the server includes means for a user to input personal information, means for setting a diet goal based on the personal information, means for using a generative AI model to generate daily action instructions based on the diet goal, means for notifying the user of the action instructions, means for monitoring the user's behavior, means for generating additional instructions if the user's behavior is not as planned, and means for periodically checking the user's progress and providing feedback. This allows the user to effectively progress with their diet by simply following the system's instructions, even if they are inactive.

[0105] "Personal information" refers to individual data such as a user's age, weight, height, and health information.

[0106] A "diet goal" is a goal set by a user, such as the weight they want to lose and the time period they want to achieve it.

[0107] A "generative AI model" is an artificial intelligence algorithm that creates appropriate action instructions and plans based on a user's personal information and goals.

[0108] "Action instructions" are instructions such as specific meal menus and exercises that the user should follow.

[0109] "Notification" is a system for informing users of action plans and instructions generated by the server in real time.

[0110] "Monitoring" refers to detecting and recording user behavior and location information using sensors and GPS.

[0111] "Additional instructions" are newly created action instructions when the user's action is not performed as planned.

[0112] "Feedback" is information that the server periodically analyzes the user's progress and communicates areas for improvement and achievements to the user.

[0113] "Location Information" means data that identifies a user's current geographic location.

[0114] "Activity data" refers to data that indicates a user's physical activity and behavioral history.

[0115] An "action plan" is a plan that shows detailed daily meal and exercise schedules based on the diet goals set by the user.

[0116] A "prompt" is an instruction sentence that is input to a generative AI model to generate a user's action plan.

[0117] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0118] System configuration

[0119] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[0120] Implementation details

[0121] User Registration

[0122] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[0123] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[0124] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[0125] goal setting

[0126] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[0127] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[0128] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[0129] Daily instruction generation

[0130] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[0131] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[0132] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[0133] Behavioral monitoring

[0134] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[0135] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[0136] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[0137] Providing follow-up instructions

[0138] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[0139] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[0140] Progress check and feedback

[0141] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[0142] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[0143] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[0144] Prompt Sentence Examples

[0145] An example of a prompt to input to a generative AI model is:

[0146] "A user is 30 years old, weighs 70kg, and is 170cm tall and wants to lose 5kg in 3 months. Please suggest an appropriate daily action plan for this user."

[0147] This allows users to effectively diet simply by following the system's instructions.

[0148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0149] Step 1: User Registration

[0150] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[0151] Input: Age, Weight, Height, Health Information.

[0152] Output: Personal information entered.

[0153] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[0154] Input: Personal information entered by the user.

[0155] Output: Personal information data sent to the server.

[0156] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[0157] Input: Personal information data sent to the server.

[0158] Output: Personal information stored in a database.

[0159] Step 2: Goal Setting

[0160] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[0161] Input: Diet goal weight, time period to achieve.

[0162] Output: The diet goal entered.

[0163] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[0164] Input: Diet goals entered on the dedicated goal setting screen.

[0165] Output: The target data sent to the server.

[0166] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[0167] Input: The target data sent to the server.

[0168] Output: The generated diet plan.

[0169] Step 3: Daily instruction generation

[0170] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[0171] Input: Personal information, diet goals.

[0172] Output: Daily action plan.

[0173] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[0174] Input: The generated action plan.

[0175] Output: Action plan data sent to the device.

[0176] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[0177] Input: Action plan data sent from the server.

[0178] Output: Informed action plan.

[0179] Step 4: Behavioral monitoring

[0180] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[0181] Input: User location and activity data.

[0182] Output: Detected behavior data.

[0183] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[0184] Input: Detected behavior data.

[0185] Output: Behavioral data sent to the server.

[0186] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[0187] Input: Behavioral data sent to the server.

[0188] Output: Behavioral analysis results.

[0189] Step 5: Provide follow-up instructions

[0190] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[0191] Input: Behavioral analysis results.

[0192] Output: New action instructions.

[0193] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[0194] Input: New command.

[0195] Output: The new instruction notified.

[0196] Step 6: Progress review and feedback

[0197] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[0198] Input: Data about progress.

[0199] Output: Analysis results.

[0200] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[0201] Input: Analysis results.

[0202] Output: Feedback content.

[0203] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[0204] Input: Feedback content.

[0205] Output: Notified feedback.

[0206] (Application example 1)

[0207] 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."

[0208] Conventional diet support systems have the problem that it is difficult for users to maintain motivation, as they have to take the time and effort to plan and come up with meal menus themselves. In particular, diet management requires users to determine nutritional balance and appropriate calorie intake themselves, which requires specialized knowledge. In addition, purchasing ingredients and cooking them is time-consuming, making it difficult to continue daily. We want to provide a system that solves these problems and allows users to manage their weight effectively and continuously.

[0209] 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.

[0210] In this invention, the server includes means for inputting personal data, means for setting weight management goals, means for generating a daily action plan, means for notifying, means for monitoring, means for generating additional instructions, means for periodically checking progress and providing feedback, means for generating a nutrition plan and supporting food selection, means for supporting food ordering, and means for notifying food selection and order processing, thereby enabling a user to continuously manage their weight by following appropriate nutrition management and the action plan even without specialized knowledge.

[0211] "Personal Data" means data that contains information about an individual, such as a user's age, weight, height, and health information.

[0212] A "weight management goal" is a specific goal set by a user, including a target weight and a time period for achieving the target weight.

[0213] An "action plan" is a plan for a user's daily activities and diet that is generated based on weight management goals.

[0214] "Notifications" are the means by which the system communicates information to the user in real time, such as action plans, progress, and additional instructions.

[0215] "Monitoring" is a means of detecting a user's location and activity data and monitoring their behavior and progress.

[0216] An "additional instruction" is a new, complementary instruction for an action that is generated when the user does not perform the action as planned.

[0217] "Feedback" is evaluation and advice provided based on a user's actions and progress.

[0218] A "nutritional plan" is a specific meal plan generated based on a user's weight management goals and health information.

[0219] "Food selection assistance" is a means to help users choose appropriate foods based on the generated nutrition plan.

[0220] "Food ordering support" means a means for enabling a user to easily order selected food items.

[0221] MODE FOR CARRYING OUT THE INVENTION

[0222] This invention is a "diet food delivery support system" that supports users to succeed in dieting by simply following instructions without any motivation. The embodiment of this system is mainly composed of three entities: a server, a terminal, and a user. Below, we will explain in detail how to realize the program of this system and specific examples of each step.

[0223] System configuration

[0224] The system works in tandem with the following processes: inputting personal data, setting weight management goals, generating an action plan, notification, monitoring, generating additional instructions, tracking progress, providing feedback, generating a nutrition plan, assisting with food selection, and supporting food ordering.

[0225] User Registration

[0226] User: First, the user installs the application on their device and launches it. At startup, they enter personal data such as age, weight, height, and health information on the screen that appears.

[0227] Terminal: Personal data entered is immediately sent to the server.

[0228] Server: Validates the received personal data and stores it in a database.

[0229] goal setting

[0230] User: The user inputs the weight loss goal and the time frame to achieve it. For example, they can set "lose 5 kg in 3 months."

[0231] Terminal: Sends target data to the server.

[0232] Server: Identifies your goals and generates an appropriate weight management plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[0233] Generate daily action plans

[0234] Server: Generates a daily action plan based on the user's goals and personal data, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0235] Server: Sends the generated action plan to the device.

[0236] Terminal: The terminal notifies the user of the received action plan in real time.

[0237] Behavioral monitoring

[0238] Device: Detects the user's location and activity data through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[0239] Device: Sends detected behavioral data to the server.

[0240] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[0241] Providing follow-up instructions

[0242] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0243] Terminal: Inform the user of alternative instructions.

[0244] Food selection and ordering assistance

[0245] Server: Generates a nutrition plan based on the user's weight management goals and health information, and assists in making appropriate food choices.

[0246] Terminal: Informs the user of suggested food selections and allows the user to easily order the selected food.

[0247] Server: Helps process the order for the selected food items and notifies the user about the order status.

[0248] Progress check and feedback

[0249] Server: Checks the user's progress periodically (for example, once a week), extracting and analyzing weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0250] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[0251] Device: Notify the user of the feedback.

[0252] Examples of specific examples and prompts

[0253] For example, if a user sets a goal of "lose 5 kg in 3 months," the server will generate a menu such as "Today's recommended meal plan: Chicken breast salad" and notify the device. The user can select the menu and easily complete the ordering process. After placing an order, a notification such as "Expected delivery: 30 minutes" will be displayed on the device.

[0254] An example of a prompt to input to a generative AI model is as follows:

[0255] Set your weight goal and time frame based on your age, weight, height and health information, then generate a meal plan based on that.

[0256] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0257] Step 1:

[0258] User Registration

[0259] Input: A user installs an application on their device and enters personal data such as age, weight, height, and health information.

[0260] Specific operation: The device immediately sends the entered personal data to the server, which then verifies the received personal data and stores it in a database.

[0261] Output: A user ID is generated and sent back from the server to the device.

[0262] Step 2:

[0263] goal setting

[0264] Input: The user inputs the weight they want to lose and the timeframe they want to achieve it.

[0265] How it works: The device sends goal data to the server, which then verifies the goal and generates an appropriate weight management plan based on historical and statistical data.

[0266] Output: The generated weight management plan is sent to the device.

[0267] Step 3:

[0268] Generate daily action plans

[0269] Input: User's goal weight and personal data.

[0270] Specific operation: The server generates a daily action plan based on the user's goals and personal data. Specifically, it determines the meal menu from breakfast to dinner, exercise content, etc. The generated action plan is sent to the device.

[0271] Output: The completed action plan is provided to the terminal.

[0272] Step 4:

[0273] Behavioral monitoring

[0274] Input: User location and activity data.

[0275] Specific operation: The device collects user behavior data through sensors and GPS. For example, it checks whether the user is walking during the walking time. The collected data is sent from the device to the server. The server analyzes the received data and checks whether the user is performing the activity as planned.

[0276] Output: Monitoring data is saved on the server and the analysis results are notified.

[0277] Step 5:

[0278] Providing follow-up instructions

[0279] Input: User behavior data and monitoring results.

[0280] Specific behavior: If the user does not follow the initial action instructions, the server generates new instructions. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock because your plans are delayed." The generated alternative instructions are sent to the device.

[0281] Output: Alternative instructions are sent to the user.

[0282] Step 6:

[0283] Food selection and ordering assistance

[0284] Input: User's weight management goals and health information.

[0285] Specific operations: The server generates a nutrition plan based on the user's weight management goals and health information to help them choose appropriate foods. The suggested food selections are notified to the device. The user selects the foods and the device sends an order to the server. The server processes the order and notifies the device of the order status.

[0286] Output: Suggested food selections, instructions for ordering, and order status are provided to the user.

[0287] Step 7:

[0288] Progress check and feedback

[0289] Input: Data such as user weight fluctuations, behavioral history, and calorie intake.

[0290] Specific operation: The server periodically checks the user's progress and analyzes weight fluctuations, behavioral history, calorie intake, etc. Based on the analysis results, it generates appropriate feedback. For example, it provides advice such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so reduce it next week."

[0291] Output: User is given feedback on progress.

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

[0293] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0294] System configuration

[0295] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[0296] Implementation details

[0297] 1. User Registration

[0298] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[0299] Terminal: The personal information entered is immediately sent to the server.

[0300] Server: Validates the received personal information and stores it in a database.

[0301] 2. Goal Setting

[0302] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[0303] Terminal: Sends target data to the server.

[0304] Server: Identify your goals and generate a suitable diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance.

[0305] 3. Daily instruction generation

[0306] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0307] Server: Sends the generated action plan to the device in real time.

[0308] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[0309] 4. Behavioral monitoring

[0310] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[0311] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[0312] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[0313] 5. Emotional Engine Adjustment

[0314] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[0315] Device: Sends detected emotion data to the server.

[0316] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[0317] 6. Providing follow-up instructions

[0318] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0319] Terminal: Inform the user of alternative instructions.

[0320] 7. Progress Check and Feedback

[0321] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0322] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[0323] Device: Notify the user of the feedback.

[0324] 8. Emotional feedback

[0325] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[0326] Device: Provide emotional feedback to users.

[0327] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[0328] The processing flow will be explained below.

[0329] Step 1:

[0330] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[0331] Step 2:

[0332] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[0333] Step 3:

[0334] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[0335] Step 4:

[0336] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[0337] Step 5:

[0338] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[0339] Step 6:

[0340] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[0341] Step 7:

[0342] Server: Stores the generated diet plan in a database and sends it to the device.

[0343] Step 8:

[0344] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and action instructions (e.g., walking at a specific time).

[0345] Step 9:

[0346] Server: Sends the generated action plan to the device in real time.

[0347] Step 10:

[0348] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[0349] Step 11:

[0350] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[0351] Step 12:

[0352] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[0353] Step 13:

[0354] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[0355] Step 14:

[0356] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[0357] Step 15:

[0358] Device: Sends detected emotion data to the server, including the user's tone of voice and facial expression analysis results.

[0359] Step 16:

[0360] Server: Analyzes the emotional data and generates behavioral instructions based on the user's emotional state. For example, if the user is feeling stressed, it suggests relaxation exercises.

[0361] Step 17:

[0362] Server: Sends new action instructions to the device.

[0363] Step 18:

[0364] On the device: Notify the user of alternative or new instructions, such as "Do 5 minutes of deep breathing exercises."

[0365] Step 19:

[0366] Server: Checks the user's progress periodically (for example, once a week), extracts and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0367] Step 20:

[0368] Server: Based on the analysis results, the server generates appropriate feedback, taking into account the user's emotional state. For example, it generates feedback such as, "You've successfully lost 1 kg in a week. If you feel stressed, try the following exercise."

[0369] Step 21:

[0370] Device: Notify the user of the feedback in a format that is easily understood by the user and includes appropriate advice.

[0371] Example 2

[0372] 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."

[0373] Conventional diet support systems provide uniform behavioral instructions without considering the user's emotional state, which can lead to stress and reduced diet sustainability. In addition, follow-up and feedback when users do not follow the action plan is mechanical, making it difficult to maintain user motivation.

[0374] 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.

[0375] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for recognizing and adjusting the user's emotional state, a means for generating additional instructions if the user's actions are not being performed as planned, and a means for periodically checking the user's progress and providing feedback. This enables flexible and sustainable diet support while taking the user's emotional state into consideration in real time.

[0376] "Personal Information" refers to information relating to an individual, such as a user's age, weight, height, or health condition.

[0377] "Diet Goals" refers to specific weight loss or health improvement goals set by a user.

[0378] "Behavioral instructions" refer to specific actions that users should take in their daily lives, such as meal menus and exercise details.

[0379] "Means of notification" refers to the application or push notification function on the device that notifies the user of instructions to act or feedback.

[0380] "Means of monitoring" refers to GPS and activity sensors that track user behavior in real time and collect data.

[0381] "Means for recognizing and adjusting emotional state" refers to algorithms or engines that analyze the user's voice and facial expressions to determine their emotions and adjust their behavioral instructions accordingly.

[0382] "Means for generating additional instructions" refers to a function for generating supplementary instructions when the user does not perform the planned action.

[0383] "Means of providing feedback" refers to analytics and notification features that inform users of areas for improvement and achievements based on their progress.

[0384] "Location information" refers to data indicating a user's current location, and refers to information obtained by GPS.

[0385] "Activity data" refers to data that indicates a user's exercise volume and activity patterns, such as the number of steps taken and calories burned.

[0386] A "Daily Action Plan" is a plan that includes specific dietary and exercise instructions that a user should follow throughout the day.

[0387] "Diet Menu" refers to a list of specific foods and drinks that a user should consume.

[0388] "Exercise content" refers to the type, duration, and frequency of exercise that the user should do.

[0389] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0390] System configuration

[0391] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[0392] Implementation details

[0393] The server accepts the user's personal information and diet goals and generates a specific diet plan based on them. The generated plan includes calorie goals, exercise frequency, exercise type, and meal balance. The server also monitors the user's progress and generates additional instructions if the user's actions are not performed as planned. In addition, the server is equipped with an emotion engine that can recognize the user's emotional state and adjust action instructions accordingly.

[0394] The device sends the personal information and diet goals entered by the user to the server. The device also notifies the user of action instructions and feedback received from the server. The device also has the function of collecting the user's location information and activity data and sending it to the server. As part of the emotion engine, the device analyzes the user's voice and facial expressions and sends emotional data to the server.

[0395] Users install the app on their device and enter their personal information, health information, and diet goals. They then act according to the daily instructions and feedback they receive from the device. The user's behavior and emotional state are also sent to the server via the device and analyzed there.

[0396] Specific examples

[0397] For example, let's say a user who is 35 years old, weighs 75 kg, and is 170 cm tall sets a goal of "losing 5 kg in three months." The user enters this information through the app and submits it. The server generates an appropriate calorie restriction and exercise plan based on the received information. An action plan for the first day is generated and sent to the device. Specific action instructions, such as "eat oatmeal and fruit at 7 a.m.", are then notified.

[0398] If the user fails to follow the instructions for the day, for example, if they forget to eat breakfast, the server generates alternative instructions and sends them to the device, such as "Eat one banana by 9 o'clock." If the device detects that the user is feeling stressed, the server will suggest relaxation exercises.

[0399] Prompt Sentence Examples

[0400] Examples of prompts include:

[0401] Taking into account the diet goals set by the user and their current progress, the system generates an action plan for the next day and feedback based on their emotions.

[0402] Age: 35

[0403] Weight: 75kg

[0404] Height: 170cm

[0405] Health Information: None

[0406] Goal: Lose 5kg in 3 months

[0407] Today's progress: You forgot to eat breakfast, so we suggest you eat a banana before lunch. You're also feeling stressed, so we offer some relaxation exercises.

[0408] Generate action plans and feedback.

[0409] This system allows users to effectively diet even if they are inactive, simply by following instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

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

[0411] Step 1:

[0412] User Registration

[0413] The user installs and launches the app. On the registration screen that appears, the user enters their age, weight, height, and health information (allergies, medical history, etc.). An example of input data is "Age: 35 years old," "Weight: 75 kg," "Height: 170 cm," and "Health information: None."

[0414] The terminal immediately transmits the input personal information to the server. The personal information is transmitted from the terminal to the server as input data.

[0415] The server safely stores the received personal information in a database, updating the database and storing the personal information.

[0416] Step 2:

[0417] goal setting

[0418] The user sets a diet goal. For example, the user can set a goal of "losing 5 kg in 3 months."

[0419] The terminal transmits the goal data to the server. The diet goal is transmitted as input data from the terminal to the server.

[0420] The server receives the goal data and generates an appropriate diet plan based on the user's past data and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance. The data is calculated to create the plan, and the diet plan is generated.

[0421] Step 3:

[0422] Daily instruction generation

[0423] The server automatically generates a daily action plan based on the user's goals and personal information. For example, it generates a plan such as "Eat oatmeal and fruit at 7 a.m." and "Jogging for 30 minutes at 5 p.m." The generated action plan is then sent to the device.

[0424] The device notifies the user of the received action plan. For example, the notification might say, "Eat oatmeal and fruit at 7 a.m." The notification content is displayed to the user as output data.

[0425] Step 4:

[0426] Behavioral monitoring

[0427] The device acquires the user's location information using GPS and activity sensors. For example, it checks whether the user is walking during exercise time. Location information and activity data are collected as input data on the device.

[0428] The device sends the acquired data to a server, including the user's location, number of steps, and exercise time.

[0429] The server analyzes the received data and checks whether the user is following the plan. Specifically, it analyzes the data to see if the user is running the appropriate distance within the set jogging time. The behavior confirmation results are output as data.

[0430] Step 5:

[0431] Emotional engine regulation

[0432] The device activates an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. For example, it can detect when the user is feeling stressed. Audio and video data are analyzed as input data.

[0433] The device transmits the sensed emotion data to the server, and the transmitted input data includes the emotion recognition results.

[0434] The server analyzes the emotion data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises to a user who is feeling stressed. The output data is behavioral instructions according to the emotion.

[0435] Step 6:

[0436] Providing follow-up instructions

[0437] The server generates new instructions if the user does not follow the initial instruction. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock." The behavior monitoring results are sent to the server as input data, and follow-up instructions are generated based on them.

[0438] The device notifies the user of the generated alternative instruction. For example, the device notifies the user of the alternative instruction "Please eat one banana" at 9:00 AM. The alternative instruction is displayed to the user as output data.

[0439] Step 7:

[0440] Progress check and feedback

[0441] The server periodically (for example, once a week) checks the user's progress. It retrieves and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database. The progress data is read from the database as input data.

[0442] The server generates feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week." The feedback content is generated as output data.

[0443] The device notifies the user of the feedback. Specifically, the device notifies the user at the end of the week, saying, "This week's achievement: You successfully lost 1 kg. Great job!" The notification of the achievement is displayed to the user as output data.

[0444] Step 8:

[0445] Emotional feedback

[0446] The server adjusts the feedback content based on the user's emotional state. For example, if the user is frustrated, it will suggest something like, "Don't push yourself too hard, it's okay to take a short break." The feedback content is generated based on emotional data.

[0447] The device will then provide feedback based on the user's emotions. Specifically, if a user feels stressed, the device will notify them by saying, "Try to take some time to relax today." Feedback based on their emotions will be displayed to the user as output data.

[0448] (Application example 2)

[0449] 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."

[0450] Conventional diet support systems provide only uniform instructions without considering the user's emotional state, resulting in low long-term diet sustainability and low success rates. Furthermore, due to a lack of feedback tailored to the user's individual situation and emotions, dieters often abandon their diet midway due to a lack of motivation or stress. In response to these issues, there is a strong demand for a system that provides personalized guidance tailored to the user's specific situation and emotional state.

[0451] 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.

[0452] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for generating additional instructions if the user's actions are not being performed as planned, a means for detecting the user's emotional state, a means for adjusting the action instructions based on the emotional state, and a means for periodically checking the user's progress and providing feedback. This enables flexible guidance that takes the user's emotional state into consideration, allowing for effective dieting even when the user is inactive.

[0453] "Means for inputting personal information" refers to a system in which a user inputs personal information such as age, weight, height, and health information via a terminal and sends it to a server.

[0454] The "means for setting diet goals" is a mechanism by which users set their own weight loss goals and time period and send that information to the server.

[0455] The "means for generating daily action instructions" is a mechanism by which the server generates an action plan, including daily meal menus and exercise content, based on the user's personal information and diet goals.

[0456] The "means for notifying the user of action instructions" is a mechanism for notifying the user of the generated action plan in real time via the terminal.

[0457] "Means for monitoring user behavior" refers to a system that detects user location and activity data through sensors or GPS and sends that data to a server.

[0458] "Means for generating additional instructions when the user's actions are not performed as planned" refers to a mechanism for generating new instructions and notifying the user via the terminal when the user does not perform the planned actions.

[0459] "Means for detecting the user's emotional state" refers to a mechanism for obtaining emotional data through an emotion engine that analyzes the user's voice and facial expressions to recognize emotions.

[0460] The "means for adjusting behavioral instructions based on the emotional state" is a mechanism for adaptively changing behavioral instructions and feedback content based on the detected emotional state of the user.

[0461] "Means for regularly checking the user's progress and providing feedback" refers to a system that regularly reviews the user's weight fluctuations and behavioral history, and provides appropriate feedback based on the results.

[0462] The present invention relates to a diet AI system that supports users in succeeding in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Detailed embodiments of this system are described below.

[0463] System configuration

[0464] The system is mainly composed of three components: a server, a device, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[0465] Hardware and software used

[0466] Hardware: VR headset (e.g. Oculus Quest), sensors, GPS, smartphone.

[0467] Software: Emotion Engine, diet plan generation algorithm, virtual reality application.

[0468] Implementation details

[0469] 1. User Registration

[0470] User: Puts on a VR headset and creates an avatar in the virtual reality environment, entering basic information (age, weight, height, health information).

[0471] Terminal: The personal information entered is immediately sent to the server.

[0472] Server: Validates the received personal information and stores it in a database.

[0473] 2. Goal Setting

[0474] User: Set a weight loss goal in the VR environment. For example, enter "lose 5 kg in 3 months."

[0475] Terminal: Sends target data to the server.

[0476] Server: Identify your goals and generate an appropriate diet plan based on your historical and statistical data.

[0477] 3. Daily instruction generation

[0478] Server: Generates a daily action plan based on the user's goals and personal information. Creates action instructions such as meal menus and exercise routines.

[0479] Server: Sends the generated action plan to the device in real time.

[0480] Device: Notifies the user of the received action plan. For example, a virtual diet coach will display instructions such as "Eat oatmeal and fruit at 7 a.m."

[0481] 4. Behavioral monitoring

[0482] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[0483] Device: Sends detected behavioral data to the server.

[0484] 5. Emotional Engine Adjustment

[0485] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[0486] Device: Sends detected emotion data to the server.

[0487] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[0488] 6. Providing follow-up instructions

[0489] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0490] Terminal: Inform the user of alternative instructions.

[0491] 7. Progress Check and Feedback

[0492] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0493] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[0494] Device: Notify the user of the feedback.

[0495] 8. Emotional feedback

[0496] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[0497] Device: Provide emotional feedback to users.

[0498] Examples of specific examples and prompts

[0499] Examples:

[0500] The user puts on a VR headset and sees the progress of their diet plan through an avatar in a virtual reality environment. A virtual diet coach displays instructions such as, "This week's exercise plan is to jog three times a week. Let's do our best!" If the user feels stressed during the session, the emotion engine detects this and displays a message saying, "Take a deep breath to relax."

[0501] Example prompt sentence:

[0502] Generate a feedback message for when you detect a user is low motivated:

[0503] "Now that your motivation is low, don't push yourself too hard and take a break. Set a new goal and try again!"

[0504] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[0505] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0506] Step 1:

[0507] The user puts on a VR headset, creates an avatar in the virtual reality environment, and enters personal information (age, weight, height, health information).

[0508] Input: Age, weight, height, health information

[0509] Output: Personal information data sent to the server

[0510] Specific operation: The device sends personal information entered by the user to the server in real time, and the server receives it and stores it in a database.

[0511] Step 2:

[0512] The user sets a diet goal in the VR environment. For example, they can enter "lose 5 kg in 3 months."

[0513] Input: Diet goal

[0514] Output: Target data sent to the server

[0515] Specific operation: The device sends the diet goals set by the user to the server, which then verifies the goals and stores them in a database.

[0516] Step 3:

[0517] The server generates a daily action plan based on the user's personal information and diet goals.

[0518] Input: Personal information, diet goals

[0519] Output: Action plan data

[0520] Specific operation: The server refers to past data and statistical data and generates an individual action plan (meal menu, exercise content, etc.).

[0521] Step 4:

[0522] The generated action plan is sent to the terminal in real time and notified to the user.

[0523] Input: Action plan data

[0524] Output: Instructions to be sent to the user

[0525] Specific operation: The device notifies the user of the received action plan, and displays instructions such as "Eat oatmeal and fruit at 7 a.m." as a virtual diet coach.

[0526] Step 5:

[0527] The device detects the user's location and activity through sensors and GPS and sends it to the server.

[0528] Input: Location, activity data

[0529] Output: Behavioral data sent to the server

[0530] How it works: The device monitors the user's location and activity in real time and sends the detected data to the server, which then receives it and stores it in a database.

[0531] Step 6:

[0532] The emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends that data to the server.

[0533] Input: Voice data, facial expression data

[0534] Output: Emotional state data

[0535] How it works: The device's emotion engine analyzes the user's emotions from their voice and facial expressions, and sends the results to the server. The server then analyzes the user's emotional state and stores it in a database.

[0536] Step 7:

[0537] The server adjusts behavioral instructions and feedback content based on the emotional state.

[0538] Input: Emotional state data, action plan data

[0539] Output: Adjusted action instruction data

[0540] Specific operation: The server adjusts the behavioral instructions based on the emotional data, for example, suggesting relaxation exercises for a user who is feeling stressed.

[0541] Step 8:

[0542] If the user's actions are not performed as planned, the server generates new instructions and notifies the user through the terminal.

[0543] Input: Action data, action plan data

[0544] Output: Additional instruction data

[0545] Specific operation: If the behavioral data is not as planned, the server regenerates the plan and displays instructions such as "The plan is delayed, so please eat one banana by 9 o'clock" through the terminal.

[0546] Step 9:

[0547] The server periodically checks the user's progress, generates appropriate feedback, and notifies them via the device.

[0548] Input: weight fluctuation data, behavioral history data, calorie intake data

[0549] Output: Feedback content data

[0550] Specific operation: The server analyzes the user's progress periodically (for example, once a week) and generates feedback such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so please reduce it next week," and notifies the user via their device.

[0551] Step 10:

[0552] The server adjusts the feedback content based on the user's emotional state and notifies the user via the device.

[0553] Input: Emotional state data, feedback content data

[0554] Output: Adjusted feedback content data

[0555] Specific operation: The server adjusts the feedback content based on emotional data. For example, if the user is frustrated, the content will be changed to suggest a more flexible response, such as "Don't try too hard, it's okay to take a short break."

[0556] 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.

[0557] 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.

[0558] 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.

[0559] [Second embodiment]

[0560] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0561] 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.

[0562] 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).

[0563] 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.

[0564] 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.

[0565] 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).

[0566] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] 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.

[0571] 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."

[0572] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0573] System configuration

[0574] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[0575] Implementation details

[0576] 1. User Registration

[0577] User: Installs and launches the app. Enters personal information such as age, weight, height, and health information on the screen that appears when the app is launched.

[0578] Terminal: The personal information entered is immediately sent to the server.

[0579] Server: Validates the received personal information and stores it in a database.

[0580] 2. Goal Setting

[0581] User: Enter the target weight you want to lose and the time frame to achieve it. For example, you can set "lose 5 kg in 3 months."

[0582] Terminal: Sends target data to the server.

[0583] Server: Identifies your goals and generates an appropriate diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[0584] 3. Daily instruction generation

[0585] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0586] Server: Sends the generated action plan to the device.

[0587] Terminal: The terminal notifies the user of the received action plan in real time.

[0588] 4. Behavioral monitoring

[0589] Device: Detects the user's location and activity through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[0590] Device: Sends detected behavioral data to the server.

[0591] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[0592] 5. Providing follow-up instructions

[0593] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0594] Terminal: Inform the user of alternative instructions.

[0595] 6. Progress Check and Feedback

[0596] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0597] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[0598] Device: Notify the user of the feedback.

[0599] This means that even if the user is inactive, they can effectively diet by simply following the system's instructions.

[0600] The processing flow will be explained below.

[0601] Step 1:

[0602] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is first launched.

[0603] Step 2:

[0604] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[0605] Step 3:

[0606] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[0607] Step 4:

[0608] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[0609] Step 5:

[0610] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[0611] Step 6:

[0612] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[0613] Step 7:

[0614] Server: Stores the generated diet plan in a database and sends it to the device.

[0615] Step 8:

[0616] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0617] Step 9:

[0618] Server: Sends the generated action plan to the device in real time.

[0619] Step 10:

[0620] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[0621] Step 11:

[0622] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[0623] Step 12:

[0624] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[0625] Step 13:

[0626] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[0627] Step 14:

[0628] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0629] Step 15:

[0630] Terminal: Provide the user with alternative instructions that are specific and clearly understandable.

[0631] Step 16:

[0632] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0633] Step 17:

[0634] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[0635] Step 18:

[0636] Device: Notifies the user of feedback in a format that is easily understood by the user.

[0637] Example 1

[0638] 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."

[0639] Conventional diet systems require users to actively manage themselves, which makes it difficult to maintain motivation. Additionally, they lack the functionality to properly monitor user behavior and provide real-time feedback, making it difficult to promote an effective diet.

[0640] 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.

[0641] In this invention, the server includes means for a user to input personal information, means for setting a diet goal based on the personal information, means for using a generative AI model to generate daily action instructions based on the diet goal, means for notifying the user of the action instructions, means for monitoring the user's behavior, means for generating additional instructions if the user's behavior is not as planned, and means for periodically checking the user's progress and providing feedback. This allows the user to effectively progress with their diet by simply following the system's instructions, even if they are inactive.

[0642] "Personal information" refers to individual data such as a user's age, weight, height, and health information.

[0643] A "diet goal" is a goal set by a user, such as the weight they want to lose and the time period they want to achieve it.

[0644] A "generative AI model" is an artificial intelligence algorithm that creates appropriate action instructions and plans based on a user's personal information and goals.

[0645] "Action instructions" are instructions such as specific meal menus and exercises that the user should follow.

[0646] "Notification" is a system for informing users of action plans and instructions generated by the server in real time.

[0647] "Monitoring" refers to detecting and recording user behavior and location information using sensors and GPS.

[0648] "Additional instructions" are newly created action instructions when the user's action is not performed as planned.

[0649] "Feedback" is information that the server periodically analyzes the user's progress and communicates areas for improvement and achievements to the user.

[0650] "Location Information" means data that identifies a user's current geographic location.

[0651] "Activity data" refers to data that indicates a user's physical activity and behavioral history.

[0652] An "action plan" is a plan that shows detailed daily meal and exercise schedules based on the diet goals set by the user.

[0653] A "prompt" is an instruction sentence that is input to a generative AI model to generate a user's action plan.

[0654] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0655] System configuration

[0656] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[0657] Implementation details

[0658] User Registration

[0659] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[0660] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[0661] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[0662] goal setting

[0663] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[0664] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[0665] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[0666] Daily instruction generation

[0667] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[0668] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[0669] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[0670] Behavioral monitoring

[0671] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[0672] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[0673] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[0674] Providing follow-up instructions

[0675] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[0676] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[0677] Progress check and feedback

[0678] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[0679] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[0680] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[0681] Prompt Sentence Examples

[0682] An example of a prompt to input to a generative AI model is:

[0683] "A user is 30 years old, weighs 70kg, and is 170cm tall and wants to lose 5kg in 3 months. Please suggest an appropriate daily action plan for this user."

[0684] This allows users to effectively diet simply by following the system's instructions.

[0685] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0686] Step 1: User Registration

[0687] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[0688] Input: Age, Weight, Height, Health Information.

[0689] Output: Personal information entered.

[0690] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[0691] Input: Personal information entered by the user.

[0692] Output: Personal information data sent to the server.

[0693] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[0694] Input: Personal information data sent to the server.

[0695] Output: Personal information stored in a database.

[0696] Step 2: Goal Setting

[0697] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[0698] Input: Diet goal weight, time period to achieve.

[0699] Output: The diet goal entered.

[0700] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[0701] Input: Diet goals entered on the dedicated goal setting screen.

[0702] Output: The target data sent to the server.

[0703] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[0704] Input: The target data sent to the server.

[0705] Output: The generated diet plan.

[0706] Step 3: Daily instruction generation

[0707] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[0708] Input: Personal information, diet goals.

[0709] Output: Daily action plan.

[0710] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[0711] Input: The generated action plan.

[0712] Output: Action plan data sent to the device.

[0713] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[0714] Input: Action plan data sent from the server.

[0715] Output: Informed action plan.

[0716] Step 4: Behavioral monitoring

[0717] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[0718] Input: User location and activity data.

[0719] Output: Detected behavior data.

[0720] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[0721] Input: Detected behavior data.

[0722] Output: Behavioral data sent to the server.

[0723] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[0724] Input: Behavioral data sent to the server.

[0725] Output: Behavioral analysis results.

[0726] Step 5: Provide follow-up instructions

[0727] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[0728] Input: Behavioral analysis results.

[0729] Output: New action instructions.

[0730] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[0731] Input: New command.

[0732] Output: The new instruction notified.

[0733] Step 6: Progress review and feedback

[0734] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[0735] Input: Data about progress.

[0736] Output: Analysis results.

[0737] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[0738] Input: Analysis results.

[0739] Output: Feedback content.

[0740] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[0741] Input: Feedback content.

[0742] Output: Notified feedback.

[0743] (Application example 1)

[0744] 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."

[0745] Conventional diet support systems have the problem that it is difficult for users to maintain motivation, as they have to take the time and effort to plan and come up with meal menus themselves. In particular, diet management requires users to determine nutritional balance and appropriate calorie intake themselves, which requires specialized knowledge. In addition, purchasing ingredients and cooking them is time-consuming, making it difficult to continue daily. We want to provide a system that solves these problems and allows users to manage their weight effectively and continuously.

[0746] 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.

[0747] In this invention, the server includes means for inputting personal data, means for setting weight management goals, means for generating a daily action plan, means for notifying, means for monitoring, means for generating additional instructions, means for periodically checking progress and providing feedback, means for generating a nutrition plan and supporting food selection, means for supporting food ordering, and means for notifying food selection and order processing, thereby enabling a user to continuously manage their weight by following appropriate nutrition management and the action plan even without specialized knowledge.

[0748] "Personal Data" means data that contains information about an individual, such as a user's age, weight, height, and health information.

[0749] A "weight management goal" is a specific goal set by a user, including a target weight and a time period for achieving the target weight.

[0750] An "action plan" is a plan for a user's daily activities and diet that is generated based on weight management goals.

[0751] "Notifications" are the means by which the system communicates information to the user in real time, such as action plans, progress, and additional instructions.

[0752] "Monitoring" is a means of detecting a user's location and activity data and monitoring their behavior and progress.

[0753] An "additional instruction" is a new, complementary instruction for an action that is generated when the user does not perform the action as planned.

[0754] "Feedback" is evaluation and advice provided based on a user's actions and progress.

[0755] A "nutritional plan" is a specific meal plan generated based on a user's weight management goals and health information.

[0756] "Food selection assistance" is a means to help users choose appropriate foods based on the generated nutrition plan.

[0757] "Food ordering support" means a means for enabling a user to easily order selected food items.

[0758] MODE FOR CARRYING OUT THE INVENTION

[0759] This invention is a "diet food delivery support system" that supports users to succeed in dieting by simply following instructions without any motivation. The embodiment of this system is mainly composed of three entities: a server, a terminal, and a user. Below, we will explain in detail how to realize the program of this system and specific examples of each step.

[0760] System configuration

[0761] The system works in tandem with the following processes: inputting personal data, setting weight management goals, generating an action plan, notification, monitoring, generating additional instructions, tracking progress, providing feedback, generating a nutrition plan, assisting with food selection, and supporting food ordering.

[0762] User Registration

[0763] User: First, the user installs the application on their device and launches it. At startup, they enter personal data such as age, weight, height, and health information on the screen that appears.

[0764] Terminal: Personal data entered is immediately sent to the server.

[0765] Server: Validates the received personal data and stores it in a database.

[0766] goal setting

[0767] User: The user inputs the weight loss goal and the time frame to achieve it. For example, they can set "lose 5 kg in 3 months."

[0768] Terminal: Sends target data to the server.

[0769] Server: Identifies your goals and generates an appropriate weight management plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[0770] Generate daily action plans

[0771] Server: Generates a daily action plan based on the user's goals and personal data, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0772] Server: Sends the generated action plan to the device.

[0773] Terminal: The terminal notifies the user of the received action plan in real time.

[0774] Behavioral monitoring

[0775] Device: Detects the user's location and activity data through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[0776] Device: Sends detected behavioral data to the server.

[0777] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[0778] Providing follow-up instructions

[0779] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0780] Terminal: Inform the user of alternative instructions.

[0781] Food selection and ordering assistance

[0782] Server: Generates a nutrition plan based on the user's weight management goals and health information, and assists in making appropriate food choices.

[0783] Terminal: Informs the user of suggested food selections and allows the user to easily order the selected food.

[0784] Server: Helps process the order for the selected food items and notifies the user about the order status.

[0785] Progress check and feedback

[0786] Server: Checks the user's progress periodically (for example, once a week), extracting and analyzing weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0787] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[0788] Device: Notify the user of the feedback.

[0789] Examples of specific examples and prompts

[0790] For example, if a user sets a goal of "lose 5 kg in 3 months," the server will generate a menu such as "Today's recommended meal plan: Chicken breast salad" and notify the device. The user can select the menu and easily complete the ordering process. After placing an order, a notification such as "Expected delivery: 30 minutes" will be displayed on the device.

[0791] An example of a prompt to input to a generative AI model is as follows:

[0792] Set your weight goal and time frame based on your age, weight, height and health information, then generate a meal plan based on that.

[0793] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0794] Step 1:

[0795] User Registration

[0796] Input: A user installs an application on their device and enters personal data such as age, weight, height, and health information.

[0797] Specific operation: The device immediately sends the entered personal data to the server, which then verifies the received personal data and stores it in a database.

[0798] Output: A user ID is generated and sent back from the server to the device.

[0799] Step 2:

[0800] goal setting

[0801] Input: The user inputs the weight they want to lose and the timeframe they want to achieve it.

[0802] How it works: The device sends goal data to the server, which then verifies the goal and generates an appropriate weight management plan based on historical and statistical data.

[0803] Output: The generated weight management plan is sent to the device.

[0804] Step 3:

[0805] Generate daily action plans

[0806] Input: User's goal weight and personal data.

[0807] Specific operation: The server generates a daily action plan based on the user's goals and personal data. Specifically, it determines the meal menu from breakfast to dinner, exercise content, etc. The generated action plan is sent to the device.

[0808] Output: The completed action plan is provided to the terminal.

[0809] Step 4:

[0810] Behavioral monitoring

[0811] Input: User location and activity data.

[0812] Specific operation: The device collects user behavior data through sensors and GPS. For example, it checks whether the user is walking during the walking time. The collected data is sent from the device to the server. The server analyzes the received data and checks whether the user is performing the activity as planned.

[0813] Output: Monitoring data is saved on the server and the analysis results are notified.

[0814] Step 5:

[0815] Providing follow-up instructions

[0816] Input: User behavior data and monitoring results.

[0817] Specific behavior: If the user does not follow the initial action instructions, the server generates new instructions. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock because your plans are delayed." The generated alternative instructions are sent to the device.

[0818] Output: Alternative instructions are sent to the user.

[0819] Step 6:

[0820] Food selection and ordering assistance

[0821] Input: User's weight management goals and health information.

[0822] Specific operations: The server generates a nutrition plan based on the user's weight management goals and health information to help them choose appropriate foods. The suggested food selections are notified to the device. The user selects the foods and the device sends an order to the server. The server processes the order and notifies the device of the order status.

[0823] Output: Suggested food selections, instructions for ordering, and order status are provided to the user.

[0824] Step 7:

[0825] Progress check and feedback

[0826] Input: Data such as user weight fluctuations, behavioral history, and calorie intake.

[0827] Specific operation: The server periodically checks the user's progress and analyzes weight fluctuations, behavioral history, calorie intake, etc. Based on the analysis results, it generates appropriate feedback. For example, it provides advice such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so reduce it next week."

[0828] Output: User is given feedback on progress.

[0829] 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.

[0830] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0831] System configuration

[0832] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[0833] Implementation details

[0834] 1. User Registration

[0835] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[0836] Terminal: The personal information entered is immediately sent to the server.

[0837] Server: Validates the received personal information and stores it in a database.

[0838] 2. Goal Setting

[0839] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[0840] Terminal: Sends target data to the server.

[0841] Server: Identify your goals and generate a suitable diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance.

[0842] 3. Daily instruction generation

[0843] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[0844] Server: Sends the generated action plan to the device in real time.

[0845] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[0846] 4. Behavioral monitoring

[0847] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[0848] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[0849] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[0850] 5. Emotional Engine Adjustment

[0851] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[0852] Device: Sends detected emotion data to the server.

[0853] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[0854] 6. Providing follow-up instructions

[0855] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[0856] Terminal: Inform the user of alternative instructions.

[0857] 7. Progress Check and Feedback

[0858] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0859] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[0860] Device: Notify the user of the feedback.

[0861] 8. Emotional feedback

[0862] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[0863] Device: Provide emotional feedback to users.

[0864] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[0865] The processing flow will be explained below.

[0866] Step 1:

[0867] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[0868] Step 2:

[0869] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[0870] Step 3:

[0871] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[0872] Step 4:

[0873] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[0874] Step 5:

[0875] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[0876] Step 6:

[0877] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[0878] Step 7:

[0879] Server: Stores the generated diet plan in a database and sends it to the device.

[0880] Step 8:

[0881] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and action instructions (e.g., walking at a specific time).

[0882] Step 9:

[0883] Server: Sends the generated action plan to the device in real time.

[0884] Step 10:

[0885] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[0886] Step 11:

[0887] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[0888] Step 12:

[0889] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[0890] Step 13:

[0891] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[0892] Step 14:

[0893] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[0894] Step 15:

[0895] Device: Sends detected emotion data to the server, including the user's tone of voice and facial expression analysis results.

[0896] Step 16:

[0897] Server: Analyzes the emotional data and generates behavioral instructions based on the user's emotional state. For example, if the user is feeling stressed, it suggests relaxation exercises.

[0898] Step 17:

[0899] Server: Sends new action instructions to the device.

[0900] Step 18:

[0901] On the device: Notify the user of alternative or new instructions, such as "Do 5 minutes of deep breathing exercises."

[0902] Step 19:

[0903] Server: Checks the user's progress periodically (for example, once a week), extracts and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[0904] Step 20:

[0905] Server: Based on the analysis results, the server generates appropriate feedback, taking into account the user's emotional state. For example, it generates feedback such as, "You've successfully lost 1 kg in a week. If you feel stressed, try the following exercise."

[0906] Step 21:

[0907] Device: Notify the user of the feedback in a format that is easily understood by the user and includes appropriate advice.

[0908] Example 2

[0909] 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."

[0910] Conventional diet support systems provide uniform behavioral instructions without considering the user's emotional state, which can lead to stress and reduced diet sustainability. In addition, follow-up and feedback when users do not follow the action plan is mechanical, making it difficult to maintain user motivation.

[0911] 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.

[0912] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for recognizing and adjusting the user's emotional state, a means for generating additional instructions if the user's actions are not being performed as planned, and a means for periodically checking the user's progress and providing feedback. This enables flexible and sustainable diet support while taking the user's emotional state into consideration in real time.

[0913] "Personal Information" refers to information relating to an individual, such as a user's age, weight, height, or health condition.

[0914] "Diet Goals" refers to specific weight loss or health improvement goals set by a user.

[0915] "Behavioral instructions" refer to specific actions that users should take in their daily lives, such as meal menus and exercise details.

[0916] "Means of notification" refers to the application or push notification function on the device that notifies the user of instructions to act or feedback.

[0917] "Means of monitoring" refers to GPS and activity sensors that track user behavior in real time and collect data.

[0918] "Means for recognizing and adjusting emotional state" refers to algorithms or engines that analyze the user's voice and facial expressions to determine their emotions and adjust their behavioral instructions accordingly.

[0919] "Means for generating additional instructions" refers to a function for generating supplementary instructions when the user does not perform the planned action.

[0920] "Means of providing feedback" refers to analytics and notification features that inform users of areas for improvement and achievements based on their progress.

[0921] "Location information" refers to data indicating a user's current location, and refers to information obtained by GPS.

[0922] "Activity data" refers to data that indicates a user's exercise volume and activity patterns, such as the number of steps taken and calories burned.

[0923] A "Daily Action Plan" is a plan that includes specific dietary and exercise instructions that a user should follow throughout the day.

[0924] "Diet Menu" refers to a list of specific foods and drinks that a user should consume.

[0925] "Exercise content" refers to the type, duration, and frequency of exercise that the user should do.

[0926] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[0927] System configuration

[0928] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[0929] Implementation details

[0930] The server accepts the user's personal information and diet goals and generates a specific diet plan based on them. The generated plan includes calorie goals, exercise frequency, exercise type, and meal balance. The server also monitors the user's progress and generates additional instructions if the user's actions are not performed as planned. In addition, the server is equipped with an emotion engine that can recognize the user's emotional state and adjust action instructions accordingly.

[0931] The device sends the personal information and diet goals entered by the user to the server. The device also notifies the user of action instructions and feedback received from the server. The device also has the function of collecting the user's location information and activity data and sending it to the server. As part of the emotion engine, the device analyzes the user's voice and facial expressions and sends emotional data to the server.

[0932] Users install the app on their device and enter their personal information, health information, and diet goals. They then act according to the daily instructions and feedback they receive from the device. The user's behavior and emotional state are also sent to the server via the device and analyzed there.

[0933] Specific examples

[0934] For example, let's say a user who is 35 years old, weighs 75 kg, and is 170 cm tall sets a goal of "losing 5 kg in three months." The user enters this information through the app and submits it. The server generates an appropriate calorie restriction and exercise plan based on the received information. An action plan for the first day is generated and sent to the device. Specific action instructions, such as "eat oatmeal and fruit at 7 a.m.", are then notified.

[0935] If the user fails to follow the instructions for the day, for example, if they forget to eat breakfast, the server generates alternative instructions and sends them to the device, such as "Eat one banana by 9 o'clock." If the device detects that the user is feeling stressed, the server will suggest relaxation exercises.

[0936] Prompt Sentence Examples

[0937] Examples of prompts include:

[0938] Taking into account the diet goals set by the user and their current progress, the system generates an action plan for the next day and feedback based on their emotions.

[0939] Age: 35

[0940] Weight: 75kg

[0941] Height: 170cm

[0942] Health Information: None

[0943] Goal: Lose 5kg in 3 months

[0944] Today's progress: You forgot to eat breakfast, so we suggest you eat a banana before lunch. You're also feeling stressed, so we offer some relaxation exercises.

[0945] Generate action plans and feedback.

[0946] This system allows users to effectively diet even if they are inactive, simply by following instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[0947] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0948] Step 1:

[0949] User Registration

[0950] The user installs and launches the app. On the registration screen that appears, the user enters their age, weight, height, and health information (allergies, medical history, etc.). An example of input data is "Age: 35 years old," "Weight: 75 kg," "Height: 170 cm," and "Health information: None."

[0951] The terminal immediately transmits the input personal information to the server. The personal information is transmitted from the terminal to the server as input data.

[0952] The server safely stores the received personal information in a database, updating the database and storing the personal information.

[0953] Step 2:

[0954] goal setting

[0955] The user sets a diet goal. For example, the user can set a goal of "losing 5 kg in 3 months."

[0956] The terminal transmits the goal data to the server. The diet goal is transmitted as input data from the terminal to the server.

[0957] The server receives the goal data and generates an appropriate diet plan based on the user's past data and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance. The data is calculated to create the plan, and the diet plan is generated.

[0958] Step 3:

[0959] Daily instruction generation

[0960] The server automatically generates a daily action plan based on the user's goals and personal information. For example, it generates a plan such as "Eat oatmeal and fruit at 7 a.m." and "Jogging for 30 minutes at 5 p.m." The generated action plan is then sent to the device.

[0961] The device notifies the user of the received action plan. For example, the notification might say, "Eat oatmeal and fruit at 7 a.m." The notification content is displayed to the user as output data.

[0962] Step 4:

[0963] Behavioral monitoring

[0964] The device acquires the user's location information using GPS and activity sensors. For example, it checks whether the user is walking during exercise time. Location information and activity data are collected as input data on the device.

[0965] The device sends the acquired data to a server, including the user's location, number of steps, and exercise time.

[0966] The server analyzes the received data and checks whether the user is following the plan. Specifically, it analyzes the data to see if the user is running the appropriate distance within the set jogging time. The behavior confirmation results are output as data.

[0967] Step 5:

[0968] Emotional engine regulation

[0969] The device activates an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. For example, it can detect when the user is feeling stressed. Audio and video data are analyzed as input data.

[0970] The device transmits the sensed emotion data to the server, and the transmitted input data includes the emotion recognition results.

[0971] The server analyzes the emotion data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises to a user who is feeling stressed. The output data is behavioral instructions according to the emotion.

[0972] Step 6:

[0973] Providing follow-up instructions

[0974] The server generates new instructions if the user does not follow the initial instruction. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock." The behavior monitoring results are sent to the server as input data, and follow-up instructions are generated based on them.

[0975] The device notifies the user of the generated alternative instruction. For example, the device notifies the user of the alternative instruction "Please eat one banana" at 9:00 AM. The alternative instruction is displayed to the user as output data.

[0976] Step 7:

[0977] Progress check and feedback

[0978] The server periodically (for example, once a week) checks the user's progress. It retrieves and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database. The progress data is read from the database as input data.

[0979] The server generates feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week." The feedback content is generated as output data.

[0980] The device notifies the user of the feedback. Specifically, the device notifies the user at the end of the week, saying, "This week's achievement: You successfully lost 1 kg. Great job!" The notification of the achievement is displayed to the user as output data.

[0981] Step 8:

[0982] Emotional feedback

[0983] The server adjusts the feedback content based on the user's emotional state. For example, if the user is frustrated, it will suggest something like, "Don't push yourself too hard, it's okay to take a short break." The feedback content is generated based on emotional data.

[0984] The device will then provide feedback based on the user's emotions. Specifically, if a user feels stressed, the device will notify them by saying, "Try to take some time to relax today." Feedback based on their emotions will be displayed to the user as output data.

[0985] (Application example 2)

[0986] 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."

[0987] Conventional diet support systems provide only uniform instructions without considering the user's emotional state, resulting in low long-term diet sustainability and low success rates. Furthermore, due to a lack of feedback tailored to the user's individual situation and emotions, dieters often abandon their diet midway due to a lack of motivation or stress. In response to these issues, there is a strong demand for a system that provides personalized guidance tailored to the user's specific situation and emotional state.

[0988] 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.

[0989] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for generating additional instructions if the user's actions are not being performed as planned, a means for detecting the user's emotional state, a means for adjusting the action instructions based on the emotional state, and a means for periodically checking the user's progress and providing feedback. This enables flexible guidance that takes the user's emotional state into consideration, allowing for effective dieting even when the user is inactive.

[0990] "Means for inputting personal information" refers to a system in which a user inputs personal information such as age, weight, height, and health information via a terminal and sends it to a server.

[0991] The "means for setting diet goals" is a mechanism by which users set their own weight loss goals and time period and send that information to the server.

[0992] The "means for generating daily action instructions" is a mechanism by which the server generates an action plan, including daily meal menus and exercise content, based on the user's personal information and diet goals.

[0993] The "means for notifying the user of action instructions" is a mechanism for notifying the user of the generated action plan in real time via the terminal.

[0994] "Means for monitoring user behavior" refers to a system that detects user location and activity data through sensors or GPS and sends that data to a server.

[0995] "Means for generating additional instructions when the user's actions are not performed as planned" refers to a mechanism for generating new instructions and notifying the user via the terminal when the user does not perform the planned actions.

[0996] "Means for detecting the user's emotional state" refers to a mechanism for obtaining emotional data through an emotion engine that analyzes the user's voice and facial expressions to recognize emotions.

[0997] The "means for adjusting behavioral instructions based on the emotional state" is a mechanism for adaptively changing behavioral instructions and feedback content based on the detected emotional state of the user.

[0998] "Means for regularly checking the user's progress and providing feedback" refers to a system that regularly reviews the user's weight fluctuations and behavioral history, and provides appropriate feedback based on the results.

[0999] The present invention relates to a diet AI system that supports users in succeeding in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Detailed embodiments of this system are described below.

[1000] System configuration

[1001] The system is mainly composed of three components: a server, a device, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[1002] Hardware and software used

[1003] Hardware: VR headset (e.g. Oculus Quest), sensors, GPS, smartphone.

[1004] Software: Emotion Engine, diet plan generation algorithm, virtual reality application.

[1005] Implementation details

[1006] 1. User Registration

[1007] User: Puts on a VR headset and creates an avatar in the virtual reality environment, entering basic information (age, weight, height, health information).

[1008] Terminal: The personal information entered is immediately sent to the server.

[1009] Server: Validates the received personal information and stores it in a database.

[1010] 2. Goal Setting

[1011] User: Set a weight loss goal in the VR environment. For example, enter "lose 5 kg in 3 months."

[1012] Terminal: Sends target data to the server.

[1013] Server: Identify your goals and generate an appropriate diet plan based on your historical and statistical data.

[1014] 3. Daily instruction generation

[1015] Server: Generates a daily action plan based on the user's goals and personal information. Creates action instructions such as meal menus and exercise routines.

[1016] Server: Sends the generated action plan to the device in real time.

[1017] Device: Notifies the user of the received action plan. For example, a virtual diet coach will display instructions such as "Eat oatmeal and fruit at 7 a.m."

[1018] 4. Behavioral monitoring

[1019] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1020] Device: Sends detected behavioral data to the server.

[1021] 5. Emotional Engine Adjustment

[1022] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[1023] Device: Sends detected emotion data to the server.

[1024] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[1025] 6. Providing follow-up instructions

[1026] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1027] Terminal: Inform the user of alternative instructions.

[1028] 7. Progress Check and Feedback

[1029] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1030] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[1031] Device: Notify the user of the feedback.

[1032] 8. Emotional feedback

[1033] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[1034] Device: Provide emotional feedback to users.

[1035] Examples of specific examples and prompts

[1036] Examples:

[1037] The user puts on a VR headset and sees the progress of their diet plan through an avatar in a virtual reality environment. A virtual diet coach displays instructions such as, "This week's exercise plan is to jog three times a week. Let's do our best!" If the user feels stressed during the session, the emotion engine detects this and displays a message saying, "Take a deep breath to relax."

[1038] Example prompt sentence:

[1039] Generate a feedback message for when you detect a user is low motivated:

[1040] "Now that your motivation is low, don't push yourself too hard and take a break. Set a new goal and try again!"

[1041] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[1042] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1043] Step 1:

[1044] The user puts on a VR headset, creates an avatar in the virtual reality environment, and enters personal information (age, weight, height, health information).

[1045] Input: Age, weight, height, health information

[1046] Output: Personal information data sent to the server

[1047] Specific operation: The device sends personal information entered by the user to the server in real time, and the server receives it and stores it in a database.

[1048] Step 2:

[1049] The user sets a diet goal in the VR environment. For example, they can enter "lose 5 kg in 3 months."

[1050] Input: Diet goal

[1051] Output: Target data sent to the server

[1052] Specific operation: The device sends the diet goals set by the user to the server, which then verifies the goals and stores them in a database.

[1053] Step 3:

[1054] The server generates a daily action plan based on the user's personal information and diet goals.

[1055] Input: Personal information, diet goals

[1056] Output: Action plan data

[1057] Specific operation: The server refers to past data and statistical data and generates an individual action plan (meal menu, exercise content, etc.).

[1058] Step 4:

[1059] The generated action plan is sent to the terminal in real time and notified to the user.

[1060] Input: Action plan data

[1061] Output: Instructions to be sent to the user

[1062] Specific operation: The device notifies the user of the received action plan, and displays instructions such as "Eat oatmeal and fruit at 7 a.m." as a virtual diet coach.

[1063] Step 5:

[1064] The device detects the user's location and activity through sensors and GPS and sends it to the server.

[1065] Input: Location, activity data

[1066] Output: Behavioral data sent to the server

[1067] How it works: The device monitors the user's location and activity in real time and sends the detected data to the server, which then receives it and stores it in a database.

[1068] Step 6:

[1069] The emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends that data to the server.

[1070] Input: Voice data, facial expression data

[1071] Output: Emotional state data

[1072] How it works: The device's emotion engine analyzes the user's emotions from their voice and facial expressions, and sends the results to the server. The server then analyzes the user's emotional state and stores it in a database.

[1073] Step 7:

[1074] The server adjusts behavioral instructions and feedback content based on the emotional state.

[1075] Input: Emotional state data, action plan data

[1076] Output: Adjusted action instruction data

[1077] Specific operation: The server adjusts the behavioral instructions based on the emotional data, for example, suggesting relaxation exercises for a user who is feeling stressed.

[1078] Step 8:

[1079] If the user's actions are not performed as planned, the server generates new instructions and notifies the user through the terminal.

[1080] Input: Action data, action plan data

[1081] Output: Additional instruction data

[1082] Specific operation: If the behavioral data is not as planned, the server regenerates the plan and displays instructions such as "The plan is delayed, so please eat one banana by 9 o'clock" through the terminal.

[1083] Step 9:

[1084] The server periodically checks the user's progress, generates appropriate feedback, and notifies them via the device.

[1085] Input: weight fluctuation data, behavioral history data, calorie intake data

[1086] Output: Feedback content data

[1087] Specific operation: The server analyzes the user's progress periodically (for example, once a week) and generates feedback such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so please reduce it next week," and notifies the user via their device.

[1088] Step 10:

[1089] The server adjusts the feedback content based on the user's emotional state and notifies the user via the device.

[1090] Input: Emotional state data, feedback content data

[1091] Output: Adjusted feedback content data

[1092] Specific operation: The server adjusts the feedback content based on emotional data. For example, if the user is frustrated, the content will be changed to suggest a more flexible response, such as "Don't try too hard, it's okay to take a short break."

[1093] 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.

[1094] 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.

[1095] 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.

[1096] [Third embodiment]

[1097] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1098] 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.

[1099] 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).

[1100] 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.

[1101] 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.

[1102] 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).

[1103] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1104] 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.

[1105] 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.

[1106] 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.

[1107] 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.

[1108] 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."

[1109] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[1110] System configuration

[1111] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[1112] Implementation details

[1113] 1. User Registration

[1114] User: Installs and launches the app. Enters personal information such as age, weight, height, and health information on the screen that appears when the app is launched.

[1115] Terminal: The personal information entered is immediately sent to the server.

[1116] Server: Validates the received personal information and stores it in a database.

[1117] 2. Goal Setting

[1118] User: Enter the target weight you want to lose and the time frame to achieve it. For example, you can set "lose 5 kg in 3 months."

[1119] Terminal: Sends target data to the server.

[1120] Server: Identifies your goals and generates an appropriate diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[1121] 3. Daily instruction generation

[1122] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1123] Server: Sends the generated action plan to the device.

[1124] Terminal: The terminal notifies the user of the received action plan in real time.

[1125] 4. Behavioral monitoring

[1126] Device: Detects the user's location and activity through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[1127] Device: Sends detected behavioral data to the server.

[1128] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[1129] 5. Providing follow-up instructions

[1130] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1131] Terminal: Inform the user of alternative instructions.

[1132] 6. Progress Check and Feedback

[1133] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1134] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[1135] Device: Notify the user of the feedback.

[1136] This means that even if the user is inactive, they can effectively diet by simply following the system's instructions.

[1137] The processing flow will be explained below.

[1138] Step 1:

[1139] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is first launched.

[1140] Step 2:

[1141] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[1142] Step 3:

[1143] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[1144] Step 4:

[1145] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[1146] Step 5:

[1147] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[1148] Step 6:

[1149] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[1150] Step 7:

[1151] Server: Stores the generated diet plan in a database and sends it to the device.

[1152] Step 8:

[1153] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1154] Step 9:

[1155] Server: Sends the generated action plan to the device in real time.

[1156] Step 10:

[1157] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[1158] Step 11:

[1159] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1160] Step 12:

[1161] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[1162] Step 13:

[1163] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[1164] Step 14:

[1165] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1166] Step 15:

[1167] Terminal: Provide the user with alternative instructions that are specific and clearly understandable.

[1168] Step 16:

[1169] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1170] Step 17:

[1171] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[1172] Step 18:

[1173] Device: Notifies the user of feedback in a format that is easily understood by the user.

[1174] Example 1

[1175] 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."

[1176] Conventional diet systems require users to actively manage themselves, which makes it difficult to maintain motivation. Additionally, they lack the functionality to properly monitor user behavior and provide real-time feedback, making it difficult to promote an effective diet.

[1177] 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.

[1178] In this invention, the server includes means for a user to input personal information, means for setting a diet goal based on the personal information, means for using a generative AI model to generate daily action instructions based on the diet goal, means for notifying the user of the action instructions, means for monitoring the user's behavior, means for generating additional instructions if the user's behavior is not as planned, and means for periodically checking the user's progress and providing feedback. This allows the user to effectively progress with their diet by simply following the system's instructions, even if they are inactive.

[1179] "Personal information" refers to individual data such as a user's age, weight, height, and health information.

[1180] A "diet goal" is a goal set by a user, such as the weight they want to lose and the time period they want to achieve it.

[1181] A "generative AI model" is an artificial intelligence algorithm that creates appropriate action instructions and plans based on a user's personal information and goals.

[1182] "Action instructions" are instructions such as specific meal menus and exercises that the user should follow.

[1183] "Notification" is a system for informing users of action plans and instructions generated by the server in real time.

[1184] "Monitoring" refers to detecting and recording user behavior and location information using sensors and GPS.

[1185] "Additional instructions" are newly created action instructions when the user's action is not performed as planned.

[1186] "Feedback" is information that the server periodically analyzes the user's progress and communicates areas for improvement and achievements to the user.

[1187] "Location Information" means data that identifies a user's current geographic location.

[1188] "Activity data" refers to data that indicates a user's physical activity and behavioral history.

[1189] An "action plan" is a plan that shows detailed daily meal and exercise schedules based on the diet goals set by the user.

[1190] A "prompt" is an instruction sentence that is input to a generative AI model to generate a user's action plan.

[1191] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[1192] System configuration

[1193] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[1194] Implementation details

[1195] User Registration

[1196] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[1197] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[1198] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[1199] goal setting

[1200] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[1201] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[1202] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[1203] Daily instruction generation

[1204] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[1205] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[1206] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[1207] Behavioral monitoring

[1208] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[1209] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[1210] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[1211] Providing follow-up instructions

[1212] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[1213] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[1214] Progress check and feedback

[1215] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[1216] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[1217] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[1218] Prompt Sentence Examples

[1219] An example of a prompt to input to a generative AI model is:

[1220] "A user is 30 years old, weighs 70kg, and is 170cm tall and wants to lose 5kg in 3 months. Please suggest an appropriate daily action plan for this user."

[1221] This allows users to effectively diet simply by following the system's instructions.

[1222] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1223] Step 1: User Registration

[1224] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[1225] Input: Age, Weight, Height, Health Information.

[1226] Output: Personal information entered.

[1227] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[1228] Input: Personal information entered by the user.

[1229] Output: Personal information data sent to the server.

[1230] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[1231] Input: Personal information data sent to the server.

[1232] Output: Personal information stored in a database.

[1233] Step 2: Goal Setting

[1234] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[1235] Input: Diet goal weight, time period to achieve.

[1236] Output: The diet goal entered.

[1237] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[1238] Input: Diet goals entered on the dedicated goal setting screen.

[1239] Output: The target data sent to the server.

[1240] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[1241] Input: The target data sent to the server.

[1242] Output: The generated diet plan.

[1243] Step 3: Daily instruction generation

[1244] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[1245] Input: Personal information, diet goals.

[1246] Output: Daily action plan.

[1247] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[1248] Input: The generated action plan.

[1249] Output: Action plan data sent to the device.

[1250] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[1251] Input: Action plan data sent from the server.

[1252] Output: Informed action plan.

[1253] Step 4: Behavioral monitoring

[1254] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[1255] Input: User location and activity data.

[1256] Output: Detected behavior data.

[1257] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[1258] Input: Detected behavior data.

[1259] Output: Behavioral data sent to the server.

[1260] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[1261] Input: Behavioral data sent to the server.

[1262] Output: Behavioral analysis results.

[1263] Step 5: Provide follow-up instructions

[1264] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[1265] Input: Behavioral analysis results.

[1266] Output: New action instructions.

[1267] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[1268] Input: New command.

[1269] Output: The new instruction notified.

[1270] Step 6: Progress review and feedback

[1271] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[1272] Input: Data about progress.

[1273] Output: Analysis results.

[1274] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[1275] Input: Analysis results.

[1276] Output: Feedback content.

[1277] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[1278] Input: Feedback content.

[1279] Output: Notified feedback.

[1280] (Application example 1)

[1281] 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."

[1282] Conventional diet support systems have the problem that it is difficult for users to maintain motivation, as they have to take the time and effort to plan and come up with meal menus themselves. In particular, diet management requires users to determine nutritional balance and appropriate calorie intake themselves, which requires specialized knowledge. In addition, purchasing ingredients and cooking them is time-consuming, making it difficult to continue daily. We want to provide a system that solves these problems and allows users to manage their weight effectively and continuously.

[1283] 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.

[1284] In this invention, the server includes means for inputting personal data, means for setting weight management goals, means for generating a daily action plan, means for notifying, means for monitoring, means for generating additional instructions, means for periodically checking progress and providing feedback, means for generating a nutrition plan and supporting food selection, means for supporting food ordering, and means for notifying food selection and order processing, thereby enabling a user to continuously manage their weight by following appropriate nutrition management and the action plan even without specialized knowledge.

[1285] "Personal Data" means data that contains information about an individual, such as a user's age, weight, height, and health information.

[1286] A "weight management goal" is a specific goal set by a user, including a target weight and a time period for achieving the target weight.

[1287] An "action plan" is a plan for a user's daily activities and diet that is generated based on weight management goals.

[1288] "Notifications" are the means by which the system communicates information to the user in real time, such as action plans, progress, and additional instructions.

[1289] "Monitoring" is a means of detecting a user's location and activity data and monitoring their behavior and progress.

[1290] An "additional instruction" is a new, complementary instruction for an action that is generated when the user does not perform the action as planned.

[1291] "Feedback" is evaluation and advice provided based on a user's actions and progress.

[1292] A "nutritional plan" is a specific meal plan generated based on a user's weight management goals and health information.

[1293] "Food selection assistance" is a means to help users choose appropriate foods based on the generated nutrition plan.

[1294] "Food ordering support" means a means for enabling a user to easily order selected food items.

[1295] MODE FOR CARRYING OUT THE INVENTION

[1296] This invention is a "diet food delivery support system" that supports users to succeed in dieting by simply following instructions without any motivation. The embodiment of this system is mainly composed of three entities: a server, a terminal, and a user. Below, we will explain in detail how to realize the program of this system and specific examples of each step.

[1297] System configuration

[1298] The system works in tandem with the following processes: inputting personal data, setting weight management goals, generating an action plan, notification, monitoring, generating additional instructions, tracking progress, providing feedback, generating a nutrition plan, assisting with food selection, and supporting food ordering.

[1299] User Registration

[1300] User: First, the user installs the application on their device and launches it. At startup, they enter personal data such as age, weight, height, and health information on the screen that appears.

[1301] Terminal: Personal data entered is immediately sent to the server.

[1302] Server: Validates the received personal data and stores it in a database.

[1303] goal setting

[1304] User: The user inputs the weight loss goal and the time frame to achieve it. For example, they can set "lose 5 kg in 3 months."

[1305] Terminal: Sends target data to the server.

[1306] Server: Identifies your goals and generates an appropriate weight management plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[1307] Generate daily action plans

[1308] Server: Generates a daily action plan based on the user's goals and personal data, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1309] Server: Sends the generated action plan to the device.

[1310] Terminal: The terminal notifies the user of the received action plan in real time.

[1311] Behavioral monitoring

[1312] Device: Detects the user's location and activity data through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[1313] Device: Sends detected behavioral data to the server.

[1314] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[1315] Providing follow-up instructions

[1316] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1317] Terminal: Inform the user of alternative instructions.

[1318] Food selection and ordering assistance

[1319] Server: Generates a nutrition plan based on the user's weight management goals and health information, and assists in making appropriate food choices.

[1320] Terminal: Informs the user of suggested food selections and allows the user to easily order the selected food.

[1321] Server: Helps process the order for the selected food items and notifies the user about the order status.

[1322] Progress check and feedback

[1323] Server: Checks the user's progress periodically (for example, once a week), extracting and analyzing weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1324] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[1325] Device: Notify the user of the feedback.

[1326] Examples of specific examples and prompts

[1327] For example, if a user sets a goal of "lose 5 kg in 3 months," the server will generate a menu such as "Today's recommended meal plan: Chicken breast salad" and notify the device. The user can select the menu and easily complete the ordering process. After placing an order, a notification such as "Expected delivery: 30 minutes" will be displayed on the device.

[1328] An example of a prompt to input to a generative AI model is as follows:

[1329] Set your weight goal and time frame based on your age, weight, height and health information, then generate a meal plan based on that.

[1330] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1331] Step 1:

[1332] User Registration

[1333] Input: A user installs an application on their device and enters personal data such as age, weight, height, and health information.

[1334] Specific operation: The device immediately sends the entered personal data to the server, which then verifies the received personal data and stores it in a database.

[1335] Output: A user ID is generated and sent back from the server to the device.

[1336] Step 2:

[1337] goal setting

[1338] Input: The user inputs the weight they want to lose and the timeframe they want to achieve it.

[1339] How it works: The device sends goal data to the server, which then verifies the goal and generates an appropriate weight management plan based on historical and statistical data.

[1340] Output: The generated weight management plan is sent to the device.

[1341] Step 3:

[1342] Generate daily action plans

[1343] Input: User's goal weight and personal data.

[1344] Specific operation: The server generates a daily action plan based on the user's goals and personal data. Specifically, it determines the meal menu from breakfast to dinner, exercise content, etc. The generated action plan is sent to the device.

[1345] Output: The completed action plan is provided to the terminal.

[1346] Step 4:

[1347] Behavioral monitoring

[1348] Input: User location and activity data.

[1349] Specific operation: The device collects user behavior data through sensors and GPS. For example, it checks whether the user is walking during the walking time. The collected data is sent from the device to the server. The server analyzes the received data and checks whether the user is performing the activity as planned.

[1350] Output: Monitoring data is saved on the server and the analysis results are notified.

[1351] Step 5:

[1352] Providing follow-up instructions

[1353] Input: User behavior data and monitoring results.

[1354] Specific behavior: If the user does not follow the initial action instructions, the server generates new instructions. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock because your plans are delayed." The generated alternative instructions are sent to the device.

[1355] Output: Alternative instructions are sent to the user.

[1356] Step 6:

[1357] Food selection and ordering assistance

[1358] Input: User's weight management goals and health information.

[1359] Specific operations: The server generates a nutrition plan based on the user's weight management goals and health information to help them choose appropriate foods. The suggested food selections are notified to the device. The user selects the foods and the device sends an order to the server. The server processes the order and notifies the device of the order status.

[1360] Output: Suggested food selections, instructions for ordering, and order status are provided to the user.

[1361] Step 7:

[1362] Progress check and feedback

[1363] Input: Data such as user weight fluctuations, behavioral history, and calorie intake.

[1364] Specific operation: The server periodically checks the user's progress and analyzes weight fluctuations, behavioral history, calorie intake, etc. Based on the analysis results, it generates appropriate feedback. For example, it provides advice such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so reduce it next week."

[1365] Output: User is given feedback on progress.

[1366] 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.

[1367] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[1368] System configuration

[1369] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[1370] Implementation details

[1371] 1. User Registration

[1372] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[1373] Terminal: The personal information entered is immediately sent to the server.

[1374] Server: Validates the received personal information and stores it in a database.

[1375] 2. Goal Setting

[1376] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[1377] Terminal: Sends target data to the server.

[1378] Server: Identify your goals and generate a suitable diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance.

[1379] 3. Daily instruction generation

[1380] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1381] Server: Sends the generated action plan to the device in real time.

[1382] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[1383] 4. Behavioral monitoring

[1384] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1385] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[1386] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[1387] 5. Emotional Engine Adjustment

[1388] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[1389] Device: Sends detected emotion data to the server.

[1390] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[1391] 6. Providing follow-up instructions

[1392] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1393] Terminal: Inform the user of alternative instructions.

[1394] 7. Progress Check and Feedback

[1395] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1396] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[1397] Device: Notify the user of the feedback.

[1398] 8. Emotional feedback

[1399] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[1400] Device: Provide emotional feedback to users.

[1401] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[1402] The processing flow will be explained below.

[1403] Step 1:

[1404] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[1405] Step 2:

[1406] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[1407] Step 3:

[1408] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[1409] Step 4:

[1410] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[1411] Step 5:

[1412] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[1413] Step 6:

[1414] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[1415] Step 7:

[1416] Server: Stores the generated diet plan in a database and sends it to the device.

[1417] Step 8:

[1418] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and action instructions (e.g., walking at a specific time).

[1419] Step 9:

[1420] Server: Sends the generated action plan to the device in real time.

[1421] Step 10:

[1422] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[1423] Step 11:

[1424] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1425] Step 12:

[1426] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[1427] Step 13:

[1428] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[1429] Step 14:

[1430] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[1431] Step 15:

[1432] Device: Sends detected emotion data to the server, including the user's tone of voice and facial expression analysis results.

[1433] Step 16:

[1434] Server: Analyzes the emotional data and generates behavioral instructions based on the user's emotional state. For example, if the user is feeling stressed, it suggests relaxation exercises.

[1435] Step 17:

[1436] Server: Sends new action instructions to the device.

[1437] Step 18:

[1438] On the device: Notify the user of alternative or new instructions, such as "Do 5 minutes of deep breathing exercises."

[1439] Step 19:

[1440] Server: Checks the user's progress periodically (for example, once a week), extracts and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1441] Step 20:

[1442] Server: Based on the analysis results, the server generates appropriate feedback, taking into account the user's emotional state. For example, it generates feedback such as, "You've successfully lost 1 kg in a week. If you feel stressed, try the following exercise."

[1443] Step 21:

[1444] Device: Notify the user of the feedback in a format that is easily understood by the user and includes appropriate advice.

[1445] Example 2

[1446] 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."

[1447] Conventional diet support systems provide uniform behavioral instructions without considering the user's emotional state, which can lead to stress and reduced diet sustainability. In addition, follow-up and feedback when users do not follow the action plan is mechanical, making it difficult to maintain user motivation.

[1448] 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.

[1449] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for recognizing and adjusting the user's emotional state, a means for generating additional instructions if the user's actions are not being performed as planned, and a means for periodically checking the user's progress and providing feedback. This enables flexible and sustainable diet support while taking the user's emotional state into consideration in real time.

[1450] "Personal Information" refers to information relating to an individual, such as a user's age, weight, height, or health condition.

[1451] "Diet Goals" refers to specific weight loss or health improvement goals set by a user.

[1452] "Behavioral instructions" refer to specific actions that users should take in their daily lives, such as meal menus and exercise details.

[1453] "Means of notification" refers to the application or push notification function on the device that notifies the user of instructions to act or feedback.

[1454] "Means of monitoring" refers to GPS and activity sensors that track user behavior in real time and collect data.

[1455] "Means for recognizing and adjusting emotional state" refers to algorithms or engines that analyze the user's voice and facial expressions to determine their emotions and adjust their behavioral instructions accordingly.

[1456] "Means for generating additional instructions" refers to a function for generating supplementary instructions when the user does not perform the planned action.

[1457] "Means of providing feedback" refers to analytics and notification features that inform users of areas for improvement and achievements based on their progress.

[1458] "Location information" refers to data indicating a user's current location, and refers to information obtained by GPS.

[1459] "Activity data" refers to data that indicates a user's exercise volume and activity patterns, such as the number of steps taken and calories burned.

[1460] A "Daily Action Plan" is a plan that includes specific dietary and exercise instructions that a user should follow throughout the day.

[1461] "Diet Menu" refers to a list of specific foods and drinks that a user should consume.

[1462] "Exercise content" refers to the type, duration, and frequency of exercise that the user should do.

[1463] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[1464] System configuration

[1465] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[1466] Implementation details

[1467] The server accepts the user's personal information and diet goals and generates a specific diet plan based on them. The generated plan includes calorie goals, exercise frequency, exercise type, and meal balance. The server also monitors the user's progress and generates additional instructions if the user's actions are not performed as planned. In addition, the server is equipped with an emotion engine that can recognize the user's emotional state and adjust action instructions accordingly.

[1468] The device sends the personal information and diet goals entered by the user to the server. The device also notifies the user of action instructions and feedback received from the server. The device also has the function of collecting the user's location information and activity data and sending it to the server. As part of the emotion engine, the device analyzes the user's voice and facial expressions and sends emotional data to the server.

[1469] Users install the app on their device and enter their personal information, health information, and diet goals. They then act according to the daily instructions and feedback they receive from the device. The user's behavior and emotional state are also sent to the server via the device and analyzed there.

[1470] Specific examples

[1471] For example, let's say a user who is 35 years old, weighs 75 kg, and is 170 cm tall sets a goal of "losing 5 kg in three months." The user enters this information through the app and submits it. The server generates an appropriate calorie restriction and exercise plan based on the received information. An action plan for the first day is generated and sent to the device. Specific action instructions, such as "eat oatmeal and fruit at 7 a.m.", are then notified.

[1472] If the user fails to follow the instructions for the day, for example, if they forget to eat breakfast, the server generates alternative instructions and sends them to the device, such as "Eat one banana by 9 o'clock." If the device detects that the user is feeling stressed, the server will suggest relaxation exercises.

[1473] Prompt Sentence Examples

[1474] Examples of prompts include:

[1475] Taking into account the diet goals set by the user and their current progress, the system generates an action plan for the next day and feedback based on their emotions.

[1476] Age: 35

[1477] Weight: 75kg

[1478] Height: 170cm

[1479] Health Information: None

[1480] Goal: Lose 5kg in 3 months

[1481] Today's progress: You forgot to eat breakfast, so we suggest you eat a banana before lunch. You're also feeling stressed, so we offer some relaxation exercises.

[1482] Generate action plans and feedback.

[1483] This system allows users to effectively diet even if they are inactive, simply by following instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[1484] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1485] Step 1:

[1486] User Registration

[1487] The user installs and launches the app. On the registration screen that appears, the user enters their age, weight, height, and health information (allergies, medical history, etc.). An example of input data is "Age: 35 years old," "Weight: 75 kg," "Height: 170 cm," and "Health information: None."

[1488] The terminal immediately transmits the input personal information to the server. The personal information is transmitted from the terminal to the server as input data.

[1489] The server safely stores the received personal information in a database, updating the database and storing the personal information.

[1490] Step 2:

[1491] goal setting

[1492] The user sets a diet goal. For example, the user can set a goal of "losing 5 kg in 3 months."

[1493] The terminal transmits the goal data to the server. The diet goal is transmitted as input data from the terminal to the server.

[1494] The server receives the goal data and generates an appropriate diet plan based on the user's past data and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance. The data is calculated to create the plan, and the diet plan is generated.

[1495] Step 3:

[1496] Daily instruction generation

[1497] The server automatically generates a daily action plan based on the user's goals and personal information. For example, it generates a plan such as "Eat oatmeal and fruit at 7 a.m." and "Jogging for 30 minutes at 5 p.m." The generated action plan is then sent to the device.

[1498] The device notifies the user of the received action plan. For example, the notification might say, "Eat oatmeal and fruit at 7 a.m." The notification content is displayed to the user as output data.

[1499] Step 4:

[1500] Behavioral monitoring

[1501] The device acquires the user's location information using GPS and activity sensors. For example, it checks whether the user is walking during exercise time. Location information and activity data are collected as input data on the device.

[1502] The device sends the acquired data to a server, including the user's location, number of steps, and exercise time.

[1503] The server analyzes the received data and checks whether the user is following the plan. Specifically, it analyzes the data to see if the user is running the appropriate distance within the set jogging time. The behavior confirmation results are output as data.

[1504] Step 5:

[1505] Emotional engine regulation

[1506] The device activates an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. For example, it can detect when the user is feeling stressed. Audio and video data are analyzed as input data.

[1507] The device transmits the sensed emotion data to the server, and the transmitted input data includes the emotion recognition results.

[1508] The server analyzes the emotion data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises to a user who is feeling stressed. The output data is behavioral instructions according to the emotion.

[1509] Step 6:

[1510] Providing follow-up instructions

[1511] The server generates new instructions if the user does not follow the initial instruction. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock." The behavior monitoring results are sent to the server as input data, and follow-up instructions are generated based on them.

[1512] The device notifies the user of the generated alternative instruction. For example, the device notifies the user of the alternative instruction "Please eat one banana" at 9:00 AM. The alternative instruction is displayed to the user as output data.

[1513] Step 7:

[1514] Progress check and feedback

[1515] The server periodically (for example, once a week) checks the user's progress. It retrieves and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database. The progress data is read from the database as input data.

[1516] The server generates feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week." The feedback content is generated as output data.

[1517] The device notifies the user of the feedback. Specifically, the device notifies the user at the end of the week, saying, "This week's achievement: You successfully lost 1 kg. Great job!" The notification of the achievement is displayed to the user as output data.

[1518] Step 8:

[1519] Emotional feedback

[1520] The server adjusts the feedback content based on the user's emotional state. For example, if the user is frustrated, it will suggest something like, "Don't push yourself too hard, it's okay to take a short break." The feedback content is generated based on emotional data.

[1521] The device will then provide feedback based on the user's emotions. Specifically, if a user feels stressed, the device will notify them by saying, "Try to take some time to relax today." Feedback based on their emotions will be displayed to the user as output data.

[1522] (Application example 2)

[1523] 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."

[1524] Conventional diet support systems provide only uniform instructions without considering the user's emotional state, resulting in low long-term diet sustainability and low success rates. Furthermore, due to a lack of feedback tailored to the user's individual situation and emotions, dieters often abandon their diet midway due to a lack of motivation or stress. In response to these issues, there is a strong demand for a system that provides personalized guidance tailored to the user's specific situation and emotional state.

[1525] 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.

[1526] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for generating additional instructions if the user's actions are not being performed as planned, a means for detecting the user's emotional state, a means for adjusting the action instructions based on the emotional state, and a means for periodically checking the user's progress and providing feedback. This enables flexible guidance that takes the user's emotional state into consideration, allowing for effective dieting even when the user is inactive.

[1527] "Means for inputting personal information" refers to a system in which a user inputs personal information such as age, weight, height, and health information via a terminal and sends it to a server.

[1528] The "means for setting diet goals" is a mechanism by which users set their own weight loss goals and time period and send that information to the server.

[1529] The "means for generating daily action instructions" is a mechanism by which the server generates an action plan, including daily meal menus and exercise content, based on the user's personal information and diet goals.

[1530] The "means for notifying the user of action instructions" is a mechanism for notifying the user of the generated action plan in real time via the terminal.

[1531] "Means for monitoring user behavior" refers to a system that detects user location and activity data through sensors or GPS and sends that data to a server.

[1532] "Means for generating additional instructions when the user's actions are not performed as planned" refers to a mechanism for generating new instructions and notifying the user via the terminal when the user does not perform the planned actions.

[1533] "Means for detecting the user's emotional state" refers to a mechanism for obtaining emotional data through an emotion engine that analyzes the user's voice and facial expressions to recognize emotions.

[1534] The "means for adjusting behavioral instructions based on the emotional state" is a mechanism for adaptively changing behavioral instructions and feedback content based on the detected emotional state of the user.

[1535] "Means for regularly checking the user's progress and providing feedback" refers to a system that regularly reviews the user's weight fluctuations and behavioral history, and provides appropriate feedback based on the results.

[1536] The present invention relates to a diet AI system that supports users in succeeding in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Detailed embodiments of this system are described below.

[1537] System configuration

[1538] The system is mainly composed of three components: a server, a device, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[1539] Hardware and software used

[1540] Hardware: VR headset (e.g. Oculus Quest), sensors, GPS, smartphone.

[1541] Software: Emotion Engine, diet plan generation algorithm, virtual reality application.

[1542] Implementation details

[1543] 1. User Registration

[1544] User: Puts on a VR headset and creates an avatar in the virtual reality environment, entering basic information (age, weight, height, health information).

[1545] Terminal: The personal information entered is immediately sent to the server.

[1546] Server: Validates the received personal information and stores it in a database.

[1547] 2. Goal Setting

[1548] User: Set a weight loss goal in the VR environment. For example, enter "lose 5 kg in 3 months."

[1549] Terminal: Sends target data to the server.

[1550] Server: Identify your goals and generate an appropriate diet plan based on your historical and statistical data.

[1551] 3. Daily instruction generation

[1552] Server: Generates a daily action plan based on the user's goals and personal information. Creates action instructions such as meal menus and exercise routines.

[1553] Server: Sends the generated action plan to the device in real time.

[1554] Device: Notifies the user of the received action plan. For example, a virtual diet coach will display instructions such as "Eat oatmeal and fruit at 7 a.m."

[1555] 4. Behavioral monitoring

[1556] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1557] Device: Sends detected behavioral data to the server.

[1558] 5. Emotional Engine Adjustment

[1559] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[1560] Device: Sends detected emotion data to the server.

[1561] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[1562] 6. Providing follow-up instructions

[1563] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1564] Terminal: Inform the user of alternative instructions.

[1565] 7. Progress Check and Feedback

[1566] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1567] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[1568] Device: Notify the user of the feedback.

[1569] 8. Emotional feedback

[1570] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[1571] Device: Provide emotional feedback to users.

[1572] Examples of specific examples and prompts

[1573] Examples:

[1574] The user puts on a VR headset and sees the progress of their diet plan through an avatar in a virtual reality environment. A virtual diet coach displays instructions such as, "This week's exercise plan is to jog three times a week. Let's do our best!" If the user feels stressed during the session, the emotion engine detects this and displays a message saying, "Take a deep breath to relax."

[1575] Example prompt sentence:

[1576] Generate a feedback message for when you detect a user is low motivated:

[1577] "Now that your motivation is low, don't push yourself too hard and take a break. Set a new goal and try again!"

[1578] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[1579] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1580] Step 1:

[1581] The user puts on a VR headset, creates an avatar in the virtual reality environment, and enters personal information (age, weight, height, health information).

[1582] Input: Age, weight, height, health information

[1583] Output: Personal information data sent to the server

[1584] Specific operation: The device sends personal information entered by the user to the server in real time, and the server receives it and stores it in a database.

[1585] Step 2:

[1586] The user sets a diet goal in the VR environment. For example, they can enter "lose 5 kg in 3 months."

[1587] Input: Diet goal

[1588] Output: Target data sent to the server

[1589] Specific operation: The device sends the diet goals set by the user to the server, which then verifies the goals and stores them in a database.

[1590] Step 3:

[1591] The server generates a daily action plan based on the user's personal information and diet goals.

[1592] Input: Personal information, diet goals

[1593] Output: Action plan data

[1594] Specific operation: The server refers to past data and statistical data and generates an individual action plan (meal menu, exercise content, etc.).

[1595] Step 4:

[1596] The generated action plan is sent to the terminal in real time and notified to the user.

[1597] Input: Action plan data

[1598] Output: Instructions to be sent to the user

[1599] Specific operation: The device notifies the user of the received action plan, and displays instructions such as "Eat oatmeal and fruit at 7 a.m." as a virtual diet coach.

[1600] Step 5:

[1601] The device detects the user's location and activity through sensors and GPS and sends it to the server.

[1602] Input: Location, activity data

[1603] Output: Behavioral data sent to the server

[1604] How it works: The device monitors the user's location and activity in real time and sends the detected data to the server, which then receives it and stores it in a database.

[1605] Step 6:

[1606] The emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends that data to the server.

[1607] Input: Voice data, facial expression data

[1608] Output: Emotional state data

[1609] How it works: The device's emotion engine analyzes the user's emotions from their voice and facial expressions, and sends the results to the server. The server then analyzes the user's emotional state and stores it in a database.

[1610] Step 7:

[1611] The server adjusts behavioral instructions and feedback content based on the emotional state.

[1612] Input: Emotional state data, action plan data

[1613] Output: Adjusted action instruction data

[1614] Specific operation: The server adjusts the behavioral instructions based on the emotional data, for example, suggesting relaxation exercises for a user who is feeling stressed.

[1615] Step 8:

[1616] If the user's actions are not performed as planned, the server generates new instructions and notifies the user through the terminal.

[1617] Input: Action data, action plan data

[1618] Output: Additional instruction data

[1619] Specific operation: If the behavioral data is not as planned, the server regenerates the plan and displays instructions such as "The plan is delayed, so please eat one banana by 9 o'clock" through the terminal.

[1620] Step 9:

[1621] The server periodically checks the user's progress, generates appropriate feedback, and notifies them via the device.

[1622] Input: weight fluctuation data, behavioral history data, calorie intake data

[1623] Output: Feedback content data

[1624] Specific operation: The server analyzes the user's progress periodically (for example, once a week) and generates feedback such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so please reduce it next week," and notifies the user via their device.

[1625] Step 10:

[1626] The server adjusts the feedback content based on the user's emotional state and notifies the user via the device.

[1627] Input: Emotional state data, feedback content data

[1628] Output: Adjusted feedback content data

[1629] Specific operation: The server adjusts the feedback content based on emotional data. For example, if the user is frustrated, the content will be changed to suggest a more flexible response, such as "Don't try too hard, it's okay to take a short break."

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

[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] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[1648] System configuration

[1649] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[1650] Implementation details

[1651] 1. User Registration

[1652] User: Installs and launches the app. Enters personal information such as age, weight, height, and health information on the screen that appears when the app is launched.

[1653] Terminal: The personal information entered is immediately sent to the server.

[1654] Server: Validates the received personal information and stores it in a database.

[1655] 2. Goal Setting

[1656] User: Enter the target weight you want to lose and the time frame to achieve it. For example, you can set "lose 5 kg in 3 months."

[1657] Terminal: Sends target data to the server.

[1658] Server: Identifies your goals and generates an appropriate diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[1659] 3. Daily instruction generation

[1660] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1661] Server: Sends the generated action plan to the device.

[1662] Terminal: The terminal notifies the user of the received action plan in real time.

[1663] 4. Behavioral monitoring

[1664] Device: Detects the user's location and activity through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[1665] Device: Sends detected behavioral data to the server.

[1666] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[1667] 5. Providing follow-up instructions

[1668] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1669] Terminal: Inform the user of alternative instructions.

[1670] 6. Progress Check and Feedback

[1671] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1672] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[1673] Device: Notify the user of the feedback.

[1674] This means that even if the user is inactive, they can effectively diet by simply following the system's instructions.

[1675] The processing flow will be explained below.

[1676] Step 1:

[1677] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is first launched.

[1678] Step 2:

[1679] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[1680] Step 3:

[1681] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[1682] Step 4:

[1683] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[1684] Step 5:

[1685] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[1686] Step 6:

[1687] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[1688] Step 7:

[1689] Server: Stores the generated diet plan in a database and sends it to the device.

[1690] Step 8:

[1691] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1692] Step 9:

[1693] Server: Sends the generated action plan to the device in real time.

[1694] Step 10:

[1695] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[1696] Step 11:

[1697] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1698] Step 12:

[1699] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[1700] Step 13:

[1701] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[1702] Step 14:

[1703] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1704] Step 15:

[1705] Terminal: Provide the user with alternative instructions that are specific and clearly understandable.

[1706] Step 16:

[1707] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1708] Step 17:

[1709] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[1710] Step 18:

[1711] Device: Notifies the user of feedback in a format that is easily understood by the user.

[1712] Example 1

[1713] 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."

[1714] Conventional diet systems require users to actively manage themselves, which makes it difficult to maintain motivation. Additionally, they lack the functionality to properly monitor user behavior and provide real-time feedback, making it difficult to promote an effective diet.

[1715] 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.

[1716] In this invention, the server includes means for a user to input personal information, means for setting a diet goal based on the personal information, means for using a generative AI model to generate daily action instructions based on the diet goal, means for notifying the user of the action instructions, means for monitoring the user's behavior, means for generating additional instructions if the user's behavior is not as planned, and means for periodically checking the user's progress and providing feedback. This allows the user to effectively progress with their diet by simply following the system's instructions, even if they are inactive.

[1717] "Personal information" refers to individual data such as a user's age, weight, height, and health information.

[1718] A "diet goal" is a goal set by a user, such as the weight they want to lose and the time period they want to achieve it.

[1719] A "generative AI model" is an artificial intelligence algorithm that creates appropriate action instructions and plans based on a user's personal information and goals.

[1720] "Action instructions" are instructions such as specific meal menus and exercises that the user should follow.

[1721] "Notification" is a system for informing users of action plans and instructions generated by the server in real time.

[1722] "Monitoring" refers to detecting and recording user behavior and location information using sensors and GPS.

[1723] "Additional instructions" are newly created action instructions when the user's action is not performed as planned.

[1724] "Feedback" is information that the server periodically analyzes the user's progress and communicates areas for improvement and achievements to the user.

[1725] "Location Information" means data that identifies a user's current geographic location.

[1726] "Activity data" refers to data that indicates a user's physical activity and behavioral history.

[1727] An "action plan" is a plan that shows detailed daily meal and exercise schedules based on the diet goals set by the user.

[1728] A "prompt" is an instruction sentence that is input to a generative AI model to generate a user's action plan.

[1729] This invention relates to a diet AI system that supports users to succeed in dieting by simply following instructions without the need for motivation. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[1730] System configuration

[1731] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: inputting personal information, setting diet goals, generating action instructions, notification, monitoring, generating additional instructions, and providing feedback.

[1732] Implementation details

[1733] User Registration

[1734] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[1735] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[1736] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[1737] goal setting

[1738] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[1739] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[1740] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[1741] Daily instruction generation

[1742] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[1743] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[1744] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[1745] Behavioral monitoring

[1746] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[1747] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[1748] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[1749] Providing follow-up instructions

[1750] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[1751] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[1752] Progress check and feedback

[1753] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[1754] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[1755] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[1756] Prompt Sentence Examples

[1757] An example of a prompt to input to a generative AI model is:

[1758] "A user is 30 years old, weighs 70kg, and is 170cm tall and wants to lose 5kg in 3 months. Please suggest an appropriate daily action plan for this user."

[1759] This allows users to effectively diet simply by following the system's instructions.

[1760] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1761] Step 1: User Registration

[1762] User: Installs and launches the diet AI app. On the screen that appears upon startup, the user enters personal information such as age, weight, height, and health information. For example, the user's age is 30, weight is 70 kg, and height is 170 cm.

[1763] Input: Age, Weight, Height, Health Information.

[1764] Output: Personal information entered.

[1765] On the device: The personal information entered is immediately sent to the server. A module in the device captures the input data and sends it to the server using the HTTPS protocol.

[1766] Input: Personal information entered by the user.

[1767] Output: Personal information data sent to the server.

[1768] Server: Validates the received personal information and stores it in a database. MySQL is used as the database management system.

[1769] Input: Personal information data sent to the server.

[1770] Output: Personal information stored in a database.

[1771] Step 2: Goal Setting

[1772] User: Enter the target weight and the time period to achieve it. For example, set it to "lose 5 kg in 3 months."

[1773] Input: Diet goal weight, time period to achieve.

[1774] Output: The diet goal entered.

[1775] Terminal: Sends target data to the server. The communication module in the terminal captures the target data and sends it to the server.

[1776] Input: Diet goals entered on the dedicated goal setting screen.

[1777] Output: The target data sent to the server.

[1778] Server: Checks the goal and generates an appropriate diet plan. Using a generative AI model, an example plan is generated: "daily calorie goal of 1500 kcal, aerobic exercise three times a week."

[1779] Input: The target data sent to the server.

[1780] Output: The generated diet plan.

[1781] Step 3: Daily instruction generation

[1782] Server: Generates an action plan based on the user's goals and personal information. The generative AI model suggests meal menus, exercises, and behavioral instructions. For example, it generates "30 minutes of walking at 7am, oatmeal for breakfast."

[1783] Input: Personal information, diet goals.

[1784] Output: Daily action plan.

[1785] Server: Sends the generated action plan to the terminal. The server sends the action plan data to the terminal.

[1786] Input: The generated action plan.

[1787] Output: Action plan data sent to the device.

[1788] On the device: Notify the user of the received action plan. The device's notification system displays the action plan as a pop-up notification.

[1789] Input: Action plan data sent from the server.

[1790] Output: Informed action plan.

[1791] Step 4: Behavioral monitoring

[1792] Device: Detects the user's location and activity using sensors and GPS. The device's sensor module and GPS function record the user's behavior in real time. For example, it checks whether the user is walking within the walking time.

[1793] Input: User location and activity data.

[1794] Output: Detected behavior data.

[1795] Device: Sends detected behavioral data to the server. The device automatically sends collected data to the server.

[1796] Input: Detected behavior data.

[1797] Output: Behavioral data sent to the server.

[1798] Server: Analyzes the received data and checks whether the user is behaving as expected. The analytics engine analyzes the data and evaluates whether the user is behaving as expected.

[1799] Input: Behavioral data sent to the server.

[1800] Output: Behavioral analysis results.

[1801] Step 5: Provide follow-up instructions

[1802] Server: If the user does not follow the instructions, a new instruction is generated. The generative AI model creates alternative instructions. For example, it might say, "If you forget to eat breakfast, eat a banana by 9 o'clock."

[1803] Input: Behavioral analysis results.

[1804] Output: New action instructions.

[1805] Terminal: Notifies the user of new instructions. The terminal notifies the user of new instructions.

[1806] Input: New command.

[1807] Output: The new instruction notified.

[1808] Step 6: Progress review and feedback

[1809] Server: Periodically checks the user's progress, extracts data such as weight fluctuations, behavioral history, and calorie intake from the database, and analyzes it.

[1810] Input: Data about progress.

[1811] Output: Analysis results.

[1812] Server: Generates appropriate feedback based on the analysis results. The generative AI model generates the feedback content. For example, it might advise, "You've successfully lost 1 kg in one week," or "You're consuming too many calories, so try reducing your intake next week."

[1813] Input: Analysis results.

[1814] Output: Feedback content.

[1815] Device: Notify the user of the feedback. The device will communicate the feedback to the user via a pop-up notification or in-app message.

[1816] Input: Feedback content.

[1817] Output: Notified feedback.

[1818] (Application example 1)

[1819] 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."

[1820] Conventional diet support systems have the problem that it is difficult for users to maintain motivation, as they have to take the time and effort to plan and come up with meal menus themselves. In particular, diet management requires users to determine nutritional balance and appropriate calorie intake themselves, which requires specialized knowledge. In addition, purchasing ingredients and cooking them is time-consuming, making it difficult to continue daily. We want to provide a system that solves these problems and allows users to manage their weight effectively and continuously.

[1821] 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.

[1822] In this invention, the server includes means for inputting personal data, means for setting weight management goals, means for generating a daily action plan, means for notifying, means for monitoring, means for generating additional instructions, means for periodically checking progress and providing feedback, means for generating a nutrition plan and supporting food selection, means for supporting food ordering, and means for notifying food selection and order processing, thereby enabling a user to continuously manage their weight by following appropriate nutrition management and the action plan even without specialized knowledge.

[1823] "Personal Data" means data that contains information about an individual, such as a user's age, weight, height, and health information.

[1824] A "weight management goal" is a specific goal set by a user, including a target weight and a time period for achieving the target weight.

[1825] An "action plan" is a plan for a user's daily activities and diet that is generated based on weight management goals.

[1826] "Notifications" are the means by which the system communicates information to the user in real time, such as action plans, progress, and additional instructions.

[1827] "Monitoring" is a means of detecting a user's location and activity data and monitoring their behavior and progress.

[1828] An "additional instruction" is a new, complementary instruction for an action that is generated when the user does not perform the action as planned.

[1829] "Feedback" is evaluation and advice provided based on a user's actions and progress.

[1830] A "nutritional plan" is a specific meal plan generated based on a user's weight management goals and health information.

[1831] "Food selection assistance" is a means to help users choose appropriate foods based on the generated nutrition plan.

[1832] "Food ordering support" means a means for enabling a user to easily order selected food items.

[1833] MODE FOR CARRYING OUT THE INVENTION

[1834] This invention is a "diet food delivery support system" that supports users to succeed in dieting by simply following instructions without any motivation. The embodiment of this system is mainly composed of three entities: a server, a terminal, and a user. Below, we will explain in detail how to realize the program of this system and specific examples of each step.

[1835] System configuration

[1836] The system works in tandem with the following processes: inputting personal data, setting weight management goals, generating an action plan, notification, monitoring, generating additional instructions, tracking progress, providing feedback, generating a nutrition plan, assisting with food selection, and supporting food ordering.

[1837] User Registration

[1838] User: First, the user installs the application on their device and launches it. At startup, they enter personal data such as age, weight, height, and health information on the screen that appears.

[1839] Terminal: Personal data entered is immediately sent to the server.

[1840] Server: Validates the received personal data and stores it in a database.

[1841] goal setting

[1842] User: The user inputs the weight loss goal and the time frame to achieve it. For example, they can set "lose 5 kg in 3 months."

[1843] Terminal: Sends target data to the server.

[1844] Server: Identifies your goals and generates an appropriate weight management plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency and type, and dietary balance.

[1845] Generate daily action plans

[1846] Server: Generates a daily action plan based on the user's goals and personal data, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1847] Server: Sends the generated action plan to the device.

[1848] Terminal: The terminal notifies the user of the received action plan in real time.

[1849] Behavioral monitoring

[1850] Device: Detects the user's location and activity data through sensors and GPS, for example, to ensure the user is walking within the set walking time.

[1851] Device: Sends detected behavioral data to the server.

[1852] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[1853] Providing follow-up instructions

[1854] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1855] Terminal: Inform the user of alternative instructions.

[1856] Food selection and ordering assistance

[1857] Server: Generates a nutrition plan based on the user's weight management goals and health information, and assists in making appropriate food choices.

[1858] Terminal: Informs the user of suggested food selections and allows the user to easily order the selected food.

[1859] Server: Helps process the order for the selected food items and notifies the user about the order status.

[1860] Progress check and feedback

[1861] Server: Checks the user's progress periodically (for example, once a week), extracting and analyzing weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1862] Server: Generates appropriate feedback based on the analysis results. For example, it provides advice such as "You've successfully lost 1 kg in a week" or "Your calorie intake is too high, so try to reduce it next week."

[1863] Device: Notify the user of the feedback.

[1864] Examples of specific examples and prompts

[1865] For example, if a user sets a goal of "lose 5 kg in 3 months," the server will generate a menu such as "Today's recommended meal plan: Chicken breast salad" and notify the device. The user can select the menu and easily complete the ordering process. After placing an order, a notification such as "Expected delivery: 30 minutes" will be displayed on the device.

[1866] An example of a prompt to input to a generative AI model is as follows:

[1867] Set your weight goal and time frame based on your age, weight, height and health information, then generate a meal plan based on that.

[1868] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1869] Step 1:

[1870] User Registration

[1871] Input: A user installs an application on their device and enters personal data such as age, weight, height, and health information.

[1872] Specific operation: The device immediately sends the entered personal data to the server, which then verifies the received personal data and stores it in a database.

[1873] Output: A user ID is generated and sent back from the server to the device.

[1874] Step 2:

[1875] goal setting

[1876] Input: The user inputs the weight they want to lose and the timeframe they want to achieve it.

[1877] How it works: The device sends goal data to the server, which then verifies the goal and generates an appropriate weight management plan based on historical and statistical data.

[1878] Output: The generated weight management plan is sent to the device.

[1879] Step 3:

[1880] Generate daily action plans

[1881] Input: User's goal weight and personal data.

[1882] Specific operation: The server generates a daily action plan based on the user's goals and personal data. Specifically, it determines the meal menu from breakfast to dinner, exercise content, etc. The generated action plan is sent to the device.

[1883] Output: The completed action plan is provided to the terminal.

[1884] Step 4:

[1885] Behavioral monitoring

[1886] Input: User location and activity data.

[1887] Specific operation: The device collects user behavior data through sensors and GPS. For example, it checks whether the user is walking during the walking time. The collected data is sent from the device to the server. The server analyzes the received data and checks whether the user is performing the activity as planned.

[1888] Output: Monitoring data is saved on the server and the analysis results are notified.

[1889] Step 5:

[1890] Providing follow-up instructions

[1891] Input: User behavior data and monitoring results.

[1892] Specific behavior: If the user does not follow the initial action instructions, the server generates new instructions. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock because your plans are delayed." The generated alternative instructions are sent to the device.

[1893] Output: Alternative instructions are sent to the user.

[1894] Step 6:

[1895] Food selection and ordering assistance

[1896] Input: User's weight management goals and health information.

[1897] Specific operations: The server generates a nutrition plan based on the user's weight management goals and health information to help them choose appropriate foods. The suggested food selections are notified to the device. The user selects the foods and the device sends an order to the server. The server processes the order and notifies the device of the order status.

[1898] Output: Suggested food selections, instructions for ordering, and order status are provided to the user.

[1899] Step 7:

[1900] Progress check and feedback

[1901] Input: Data such as user weight fluctuations, behavioral history, and calorie intake.

[1902] Specific operation: The server periodically checks the user's progress and analyzes weight fluctuations, behavioral history, calorie intake, etc. Based on the analysis results, it generates appropriate feedback. For example, it provides advice such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so reduce it next week."

[1903] Output: User is given feedback on progress.

[1904] 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.

[1905] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[1906] System configuration

[1907] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[1908] Implementation details

[1909] 1. User Registration

[1910] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[1911] Terminal: The personal information entered is immediately sent to the server.

[1912] Server: Validates the received personal information and stores it in a database.

[1913] 2. Goal Setting

[1914] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[1915] Terminal: Sends target data to the server.

[1916] Server: Identify your goals and generate a suitable diet plan based on your historical and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance.

[1917] 3. Daily instruction generation

[1918] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and behavioral instructions (e.g., walking at a specific time).

[1919] Server: Sends the generated action plan to the device in real time.

[1920] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[1921] 4. Behavioral monitoring

[1922] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1923] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[1924] Server: Analyzes the received data and verifies whether the user is performing the expected actions.

[1925] 5. Emotional Engine Adjustment

[1926] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[1927] Device: Sends detected emotion data to the server.

[1928] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[1929] 6. Providing follow-up instructions

[1930] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[1931] Terminal: Inform the user of alternative instructions.

[1932] 7. Progress Check and Feedback

[1933] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1934] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[1935] Device: Notify the user of the feedback.

[1936] 8. Emotional feedback

[1937] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[1938] Device: Provide emotional feedback to users.

[1939] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[1940] The processing flow will be explained below.

[1941] Step 1:

[1942] User: Installs and launches the app. Enters age, weight, height, and health information (allergies, medical history, etc.) on the screen that appears when the app is launched.

[1943] Step 2:

[1944] Device: Sends the entered personal information to a server. The data sent includes the user's age, weight, height, and health information.

[1945] Step 3:

[1946] Server: Validates the received personal information and stores it in a database. Checks the data format and value range as necessary to ensure the validity of the personal information.

[1947] Step 4:

[1948] User: Set a weight loss goal. For example, enter "lose 5 kg in 3 months."

[1949] Step 5:

[1950] Device: Sends goal data to the server. The data includes the goal weight and the time period to achieve it.

[1951] Step 6:

[1952] Server: Confirm your goals and generate an appropriate diet plan based on your past and statistical data. The plan will include calorie goals, exercise frequency, exercise type, and diet balance.

[1953] Step 7:

[1954] Server: Stores the generated diet plan in a database and sends it to the device.

[1955] Step 8:

[1956] Server: Generates a daily action plan based on the user's goals and personal information, including meal plans from breakfast to dinner, exercise routines, and action instructions (e.g., walking at a specific time).

[1957] Step 9:

[1958] Server: Sends the generated action plan to the device in real time.

[1959] Step 10:

[1960] Device: Notifies the user of the received action plan, for example, by displaying instructions such as "Eat oatmeal and fruit at 7 AM."

[1961] Step 11:

[1962] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[1963] Step 12:

[1964] Device: Sends detected behavioral data to the server, including the user's location, number of steps, and exercise time.

[1965] Step 13:

[1966] Server: Analyzes the received data and checks whether the user is performing the expected actions. If necessary, stores the action history in a database.

[1967] Step 14:

[1968] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[1969] Step 15:

[1970] Device: Sends detected emotion data to the server, including the user's tone of voice and facial expression analysis results.

[1971] Step 16:

[1972] Server: Analyzes the emotional data and generates behavioral instructions based on the user's emotional state. For example, if the user is feeling stressed, it suggests relaxation exercises.

[1973] Step 17:

[1974] Server: Sends new action instructions to the device.

[1975] Step 18:

[1976] On the device: Notify the user of alternative or new instructions, such as "Do 5 minutes of deep breathing exercises."

[1977] Step 19:

[1978] Server: Checks the user's progress periodically (for example, once a week), extracts and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[1979] Step 20:

[1980] Server: Based on the analysis results, the server generates appropriate feedback, taking into account the user's emotional state. For example, it generates feedback such as, "You've successfully lost 1 kg in a week. If you feel stressed, try the following exercise."

[1981] Step 21:

[1982] Device: Notify the user of the feedback in a format that is easily understood by the user and includes appropriate advice.

[1983] Example 2

[1984] 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."

[1985] Conventional diet support systems provide uniform behavioral instructions without considering the user's emotional state, which can lead to stress and reduced diet sustainability. In addition, follow-up and feedback when users do not follow the action plan is mechanical, making it difficult to maintain user motivation.

[1986] 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.

[1987] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for recognizing and adjusting the user's emotional state, a means for generating additional instructions if the user's actions are not being performed as planned, and a means for periodically checking the user's progress and providing feedback. This enables flexible and sustainable diet support while taking the user's emotional state into consideration in real time.

[1988] "Personal Information" refers to information relating to an individual, such as a user's age, weight, height, or health condition.

[1989] "Diet Goals" refers to specific weight loss or health improvement goals set by a user.

[1990] "Behavioral instructions" refer to specific actions that users should take in their daily lives, such as meal menus and exercise details.

[1991] "Means of notification" refers to the application or push notification function on the device that notifies the user of instructions to act or feedback.

[1992] "Means of monitoring" refers to GPS and activity sensors that track user behavior in real time and collect data.

[1993] "Means for recognizing and adjusting emotional state" refers to algorithms or engines that analyze the user's voice and facial expressions to determine their emotions and adjust their behavioral instructions accordingly.

[1994] "Means for generating additional instructions" refers to a function for generating supplementary instructions when the user does not perform the planned action.

[1995] "Means of providing feedback" refers to analytics and notification features that inform users of areas for improvement and achievements based on their progress.

[1996] "Location information" refers to data indicating a user's current location, and refers to information obtained by GPS.

[1997] "Activity data" refers to data that indicates a user's exercise volume and activity patterns, such as the number of steps taken and calories burned.

[1998] A "Daily Action Plan" is a plan that includes specific dietary and exercise instructions that a user should follow throughout the day.

[1999] "Diet Menu" refers to a list of specific foods and drinks that a user should consume.

[2000] "Exercise content" refers to the type, duration, and frequency of exercise that the user should do.

[2001] This invention relates to a diet AI system that supports users to succeed in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Below, we will explain the program of this system in natural language and provide detailed explanations with concrete examples.

[2002] System configuration

[2003] This system is mainly composed of three components: a server, a terminal, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[2004] Implementation details

[2005] The server accepts the user's personal information and diet goals and generates a specific diet plan based on them. The generated plan includes calorie goals, exercise frequency, exercise type, and meal balance. The server also monitors the user's progress and generates additional instructions if the user's actions are not performed as planned. In addition, the server is equipped with an emotion engine that can recognize the user's emotional state and adjust action instructions accordingly.

[2006] The device sends the personal information and diet goals entered by the user to the server. The device also notifies the user of action instructions and feedback received from the server. The device also has the function of collecting the user's location information and activity data and sending it to the server. As part of the emotion engine, the device analyzes the user's voice and facial expressions and sends emotional data to the server.

[2007] Users install the app on their device and enter their personal information, health information, and diet goals. They then act according to the daily instructions and feedback they receive from the device. The user's behavior and emotional state are also sent to the server via the device and analyzed there.

[2008] Specific examples

[2009] For example, let's say a user who is 35 years old, weighs 75 kg, and is 170 cm tall sets a goal of "losing 5 kg in three months." The user enters this information through the app and submits it. The server generates an appropriate calorie restriction and exercise plan based on the received information. An action plan for the first day is generated and sent to the device. Specific action instructions, such as "eat oatmeal and fruit at 7 a.m.", are then notified.

[2010] If the user fails to follow the instructions for the day, for example, if they forget to eat breakfast, the server generates alternative instructions and sends them to the device, such as "Eat one banana by 9 o'clock." If the device detects that the user is feeling stressed, the server will suggest relaxation exercises.

[2011] Prompt Sentence Examples

[2012] Examples of prompts include:

[2013] Taking into account the diet goals set by the user and their current progress, the system generates an action plan for the next day and feedback based on their emotions.

[2014] Age: 35

[2015] Weight: 75kg

[2016] Height: 170cm

[2017] Health Information: None

[2018] Goal: Lose 5kg in 3 months

[2019] Today's progress: You forgot to eat breakfast, so we suggest you eat a banana before lunch. You're also feeling stressed, so we offer some relaxation exercises.

[2020] Generate action plans and feedback.

[2021] This system allows users to effectively diet even if they are inactive, simply by following instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[2022] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2023] Step 1:

[2024] User Registration

[2025] The user installs and launches the app. On the registration screen that appears, the user enters their age, weight, height, and health information (allergies, medical history, etc.). An example of input data is "Age: 35 years old," "Weight: 75 kg," "Height: 170 cm," and "Health information: None."

[2026] The terminal immediately transmits the input personal information to the server. The personal information is transmitted from the terminal to the server as input data.

[2027] The server safely stores the received personal information in a database, updating the database and storing the personal information.

[2028] Step 2:

[2029] goal setting

[2030] The user sets a diet goal. For example, the user can set a goal of "losing 5 kg in 3 months."

[2031] The terminal transmits the goal data to the server. The diet goal is transmitted as input data from the terminal to the server.

[2032] The server receives the goal data and generates an appropriate diet plan based on the user's past data and statistical data. The plan includes calorie goals, exercise frequency, exercise type, and diet balance. The data is calculated to create the plan, and the diet plan is generated.

[2033] Step 3:

[2034] Daily instruction generation

[2035] The server automatically generates a daily action plan based on the user's goals and personal information. For example, it generates a plan such as "Eat oatmeal and fruit at 7 a.m." and "Jogging for 30 minutes at 5 p.m." The generated action plan is then sent to the device.

[2036] The device notifies the user of the received action plan. For example, the notification might say, "Eat oatmeal and fruit at 7 a.m." The notification content is displayed to the user as output data.

[2037] Step 4:

[2038] Behavioral monitoring

[2039] The device acquires the user's location information using GPS and activity sensors. For example, it checks whether the user is walking during exercise time. Location information and activity data are collected as input data on the device.

[2040] The device sends the acquired data to a server, including the user's location, number of steps, and exercise time.

[2041] The server analyzes the received data and checks whether the user is following the plan. Specifically, it analyzes the data to see if the user is running the appropriate distance within the set jogging time. The behavior confirmation results are output as data.

[2042] Step 5:

[2043] Emotional engine regulation

[2044] The device activates an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. For example, it can detect when the user is feeling stressed. Audio and video data are analyzed as input data.

[2045] The device transmits the sensed emotion data to the server, and the transmitted input data includes the emotion recognition results.

[2046] The server analyzes the emotion data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises to a user who is feeling stressed. The output data is behavioral instructions according to the emotion.

[2047] Step 6:

[2048] Providing follow-up instructions

[2049] The server generates new instructions if the user does not follow the initial instruction. For example, if the user forgets to eat breakfast, the server generates the instruction "Please eat one banana by 9 o'clock." The behavior monitoring results are sent to the server as input data, and follow-up instructions are generated based on them.

[2050] The device notifies the user of the generated alternative instruction. For example, the device notifies the user of the alternative instruction "Please eat one banana" at 9:00 AM. The alternative instruction is displayed to the user as output data.

[2051] Step 7:

[2052] Progress check and feedback

[2053] The server periodically (for example, once a week) checks the user's progress. It retrieves and analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database. The progress data is read from the database as input data.

[2054] The server generates feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week." The feedback content is generated as output data.

[2055] The device notifies the user of the feedback. Specifically, the device notifies the user at the end of the week, saying, "This week's achievement: You successfully lost 1 kg. Great job!" The notification of the achievement is displayed to the user as output data.

[2056] Step 8:

[2057] Emotional feedback

[2058] The server adjusts the feedback content based on the user's emotional state. For example, if the user is frustrated, it will suggest something like, "Don't push yourself too hard, it's okay to take a short break." The feedback content is generated based on emotional data.

[2059] The device will then provide feedback based on the user's emotions. Specifically, if a user feels stressed, the device will notify them by saying, "Try to take some time to relax today." Feedback based on their emotions will be displayed to the user as output data.

[2060] (Application example 2)

[2061] 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."

[2062] Conventional diet support systems provide only uniform instructions without considering the user's emotional state, resulting in low long-term diet sustainability and low success rates. Furthermore, due to a lack of feedback tailored to the user's individual situation and emotions, dieters often abandon their diet midway due to a lack of motivation or stress. In response to these issues, there is a strong demand for a system that provides personalized guidance tailored to the user's specific situation and emotional state.

[2063] 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.

[2064] In this invention, the server includes a means for inputting personal information, a means for setting diet goals, a means for generating daily action instructions, a means for notifying the user of the action instructions, a means for monitoring the user's actions, a means for generating additional instructions if the user's actions are not being performed as planned, a means for detecting the user's emotional state, a means for adjusting the action instructions based on the emotional state, and a means for periodically checking the user's progress and providing feedback. This enables flexible guidance that takes the user's emotional state into consideration, allowing for effective dieting even when the user is inactive.

[2065] "Means for inputting personal information" refers to a system in which a user inputs personal information such as age, weight, height, and health information via a terminal and sends it to a server.

[2066] The "means for setting diet goals" is a mechanism by which users set their own weight loss goals and time period and send that information to the server.

[2067] The "means for generating daily action instructions" is a mechanism by which the server generates an action plan, including daily meal menus and exercise content, based on the user's personal information and diet goals.

[2068] The "means for notifying the user of action instructions" is a mechanism for notifying the user of the generated action plan in real time via the terminal.

[2069] "Means for monitoring user behavior" refers to a system that detects user location and activity data through sensors or GPS and sends that data to a server.

[2070] "Means for generating additional instructions when the user's actions are not performed as planned" refers to a mechanism for generating new instructions and notifying the user via the terminal when the user does not perform the planned actions.

[2071] "Means for detecting the user's emotional state" refers to a mechanism for obtaining emotional data through an emotion engine that analyzes the user's voice and facial expressions to recognize emotions.

[2072] The "means for adjusting behavioral instructions based on the emotional state" is a mechanism for adaptively changing behavioral instructions and feedback content based on the detected emotional state of the user.

[2073] "Means for regularly checking the user's progress and providing feedback" refers to a system that regularly reviews the user's weight fluctuations and behavioral history, and provides appropriate feedback based on the results.

[2074] The present invention relates to a diet AI system that supports users in succeeding in dieting even when they are not motivated, and in particular, by combining an emotion engine, it provides diet guidance that takes into account the user's emotional state. Detailed embodiments of this system are described below.

[2075] System configuration

[2076] The system is mainly composed of three components: a server, a device, and a user. Specifically, the following processes work together: input of personal information, setting of diet goals, generation of action instructions, notification, monitoring, generation of additional instructions, emotion recognition and adjustment by an emotion engine, and provision of feedback.

[2077] Hardware and software used

[2078] Hardware: VR headset (e.g. Oculus Quest), sensors, GPS, smartphone.

[2079] Software: Emotion Engine, diet plan generation algorithm, virtual reality application.

[2080] Implementation details

[2081] 1. User Registration

[2082] User: Puts on a VR headset and creates an avatar in the virtual reality environment, entering basic information (age, weight, height, health information).

[2083] Terminal: The personal information entered is immediately sent to the server.

[2084] Server: Validates the received personal information and stores it in a database.

[2085] 2. Goal Setting

[2086] User: Set a weight loss goal in the VR environment. For example, enter "lose 5 kg in 3 months."

[2087] Terminal: Sends target data to the server.

[2088] Server: Identify your goals and generate an appropriate diet plan based on your historical and statistical data.

[2089] 3. Daily instruction generation

[2090] Server: Generates a daily action plan based on the user's goals and personal information. Creates action instructions such as meal menus and exercise routines.

[2091] Server: Sends the generated action plan to the device in real time.

[2092] Device: Notifies the user of the received action plan. For example, a virtual diet coach will display instructions such as "Eat oatmeal and fruit at 7 a.m."

[2093] 4. Behavioral monitoring

[2094] Device: Detects the user's location and activity through sensors and GPS. Checks whether the user is moving within the set walking time.

[2095] Device: Sends detected behavioral data to the server.

[2096] 5. Emotional Engine Adjustment

[2097] On the device: Activates an emotion engine that analyzes the user's voice and facial expressions to recognize emotions, for example, detecting when the user is feeling stressed.

[2098] Device: Sends detected emotion data to the server.

[2099] Server: Analyzes emotional data and adjusts behavioral instructions according to the user's emotional state. For example, it suggests relaxation exercises for a user who is feeling stressed.

[2100] 6. Providing follow-up instructions

[2101] Server: If the user does not follow the initial action instructions, generate new instructions. For example, if the user forgets to eat breakfast, generate the instruction "Please eat one banana by 9 o'clock because your plans are behind schedule."

[2102] Terminal: Inform the user of alternative instructions.

[2103] 7. Progress Check and Feedback

[2104] Server: Checks the user's progress periodically (for example, once a week). Analyzes the user's weight fluctuations, behavioral history, calorie intake, etc. from the database.

[2105] Server: Generates appropriate feedback based on the analysis results. For example, it creates content such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so try to reduce it next week."

[2106] Device: Notify the user of the feedback.

[2107] 8. Emotional feedback

[2108] Server: Adjust the feedback based on the user's emotional state. For example, if the user is frustrated, suggest a more flexible response such as "Don't push yourself too hard, it's okay to take a break."

[2109] Device: Provide emotional feedback to users.

[2110] Examples of specific examples and prompts

[2111] Examples:

[2112] The user puts on a VR headset and sees the progress of their diet plan through an avatar in a virtual reality environment. A virtual diet coach displays instructions such as, "This week's exercise plan is to jog three times a week. Let's do our best!" If the user feels stressed during the session, the emotion engine detects this and displays a message saying, "Take a deep breath to relax."

[2113] Example prompt sentence:

[2114] Generate a feedback message for when you detect a user is low motivated:

[2115] "Now that your motivation is low, don't push yourself too hard and take a break. Set a new goal and try again!"

[2116] This allows users to effectively diet even if they are inactive, simply by following the system's instructions. In addition, flexible guidance that takes into account the user's emotional state improves the sustainability and success rate of the diet program.

[2117] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2118] Step 1:

[2119] The user puts on a VR headset, creates an avatar in the virtual reality environment, and enters personal information (age, weight, height, health information).

[2120] Input: Age, weight, height, health information

[2121] Output: Personal information data sent to the server

[2122] Specific operation: The device sends personal information entered by the user to the server in real time, and the server receives it and stores it in a database.

[2123] Step 2:

[2124] The user sets a diet goal in the VR environment. For example, they can enter "lose 5 kg in 3 months."

[2125] Input: Diet goal

[2126] Output: Target data sent to the server

[2127] Specific operation: The device sends the diet goals set by the user to the server, which then verifies the goals and stores them in a database.

[2128] Step 3:

[2129] The server generates a daily action plan based on the user's personal information and diet goals.

[2130] Input: Personal information, diet goals

[2131] Output: Action plan data

[2132] Specific operation: The server refers to past data and statistical data and generates an individual action plan (meal menu, exercise content, etc.).

[2133] Step 4:

[2134] The generated action plan is sent to the terminal in real time and notified to the user.

[2135] Input: Action plan data

[2136] Output: Instructions to be sent to the user

[2137] Specific operation: The device notifies the user of the received action plan, and displays instructions such as "Eat oatmeal and fruit at 7 a.m." as a virtual diet coach.

[2138] Step 5:

[2139] The device detects the user's location and activity through sensors and GPS and sends it to the server.

[2140] Input: Location, activity data

[2141] Output: Behavioral data sent to the server

[2142] How it works: The device monitors the user's location and activity in real time and sends the detected data to the server, which then receives it and stores it in a database.

[2143] Step 6:

[2144] The emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends that data to the server.

[2145] Input: Voice data, facial expression data

[2146] Output: Emotional state data

[2147] How it works: The device's emotion engine analyzes the user's emotions from their voice and facial expressions, and sends the results to the server. The server then analyzes the user's emotional state and stores it in a database.

[2148] Step 7:

[2149] The server adjusts behavioral instructions and feedback content based on the emotional state.

[2150] Input: Emotional state data, action plan data

[2151] Output: Adjusted action instruction data

[2152] Specific operation: The server adjusts the behavioral instructions based on the emotional data, for example, suggesting relaxation exercises for a user who is feeling stressed.

[2153] Step 8:

[2154] If the user's actions are not performed as planned, the server generates new instructions and notifies the user through the terminal.

[2155] Input: Action data, action plan data

[2156] Output: Additional instruction data

[2157] Specific operation: If the behavioral data is not as planned, the server regenerates the plan and displays instructions such as "The plan is delayed, so please eat one banana by 9 o'clock" through the terminal.

[2158] Step 9:

[2159] The server periodically checks the user's progress, generates appropriate feedback, and notifies them via the device.

[2160] Input: weight fluctuation data, behavioral history data, calorie intake data

[2161] Output: Feedback content data

[2162] Specific operation: The server analyzes the user's progress periodically (for example, once a week) and generates feedback such as "You have successfully lost 1 kg in one week" or "Your calorie intake is too high, so please reduce it next week," and notifies the user via their device.

[2163] Step 10:

[2164] The server adjusts the feedback content based on the user's emotional state and notifies the user via the device.

[2165] Input: Emotional state data, feedback content data

[2166] Output: Adjusted feedback content data

[2167] Specific operation: The server adjusts the feedback content based on emotional data. For example, if the user is frustrated, the content will be changed to suggest a more flexible response, such as "Don't try too hard, it's okay to take a short break."

[2168] 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.

[2169] 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.

[2170] 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.

[2171] 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.

[2172] 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.

[2173] 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.

[2174] The inside of emotion map 400 represents what is going on in the mind, and the outsid...

Claims

1. A means for entering personal information; A means for setting a diet goal based on the personal information; means for generating daily behavioral instructions based on said diet goal; means for notifying a user of the instruction to act; A means of monitoring user behavior; means for generating additional instructions if the user's action is not as expected; A system that includes a means to periodically check the user's progress and provide feedback.

2. 10. The system of claim 1, further comprising means for detecting location and activity data for monitoring user behavior.

3. Generate a daily action plan based on the user's personal information and diet goals, The system according to claim 1, further comprising means for instructing specific meal menus and exercise content based on said action plan.

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