System

Abstract

To provide a system capable of improving a diet success rate.SOLUTION: User interface means for inputting information relating to a target weight, a target body shape, a time that can be spent, and an environment of an individual, database means for storing user information, algorithm means for generating an individually optimal diet menu on the basis of the user information, communication means for transmitting the generated diet menu to a user terminal, evaluation means for receiving daily exercise and meal records and evaluating a progress of the user on the basis of the records, message generation means for generating a support message or an encouragement message on the basis of the evaluation means and transmitting the support message or the encouragement message to the user terminal, report generation means for periodically generating a progress report on the basis of the progress and transmitting the progress report to the user terminal, and alternative menu generation means for generating an alternative diet menu in a case where a target is not achieved and transmitting the alternative diet menu to the user terminal.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Many people face limitations when it comes to dieting, such as a lack of willpower, time, and the cost of going to the gym. Many users also find it difficult to plan and implement effective diet plans on their own. Furthermore, a lack of effective feedback and support makes it difficult to maintain motivation. This invention aims to increase the success rate of dieting for such target groups by proposing diet plans tailored to their individual lifestyles and providing ongoing support. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by the following means: The present invention provides a user interface means for a user to input information regarding his / her target weight, target body shape, available time, and environment. The present invention also has a database means for storing the provided user information and an algorithm means for generating an optimal diet menu for an individual based on the user information. The generated diet menu is provided to the user using a communication means for transmitting it to a user terminal.

[0006] The present invention further includes an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records. It also includes a message generation means for generating a supportive or encouraging message based on the evaluation means and sending it to the user terminal. It also includes a report generation means for periodically generating a progress report based on the progress and sending it to the user terminal. It also includes an alternative menu generation means for generating an alternative diet menu and sending it to the user terminal if the user does not reach their goal.

[0007] These measures make it easier for users to implement a diet menu that is best suited to them, and by providing continuous feedback and support, the success rate of dieting can be increased.

[0008] The "user interface means" is an interface for the user to input information regarding the target weight, the target body shape, the available time, and the environment.

[0009] The "database means" is a system for storing and managing the user information.

[0010] The "algorithm means" is a calculation means for generating an optimal diet menu for each individual based on the stored user information.

[0011] The "communication means" is a system for transmitting the generated diet menu to the user's terminal.

[0012] The "evaluation means" is a system for receiving daily exercise and diet records and evaluating the user's progress based on the records.

[0013] The "message generating means" is a system for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[0014] The "report generation means" is a system for periodically generating progress reports based on progress and transmitting them to the user terminal.

[0015] The "alternative menu generating means" is a system for generating an alternative diet menu and transmitting it to the user terminal when the user does not reach the goal. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] To practice the present invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, and an alternative menu generation means.

[0038] User Interface Means

[0039] A user uses a smartphone app to set goals for a diet plan. The app provides an interface for the user to input information about their goal weight, body shape, available time, and exercise environment (e.g., home, gym). This allows for personalized input of information.

[0040] Database Means

[0041] The entered user information is sent from the terminal to the server, and the server stores the received information in a database that contains information such as the user ID, target weight, target body shape, available time, and environmental information.

[0042] Algorithmic means

[0043] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This algorithm customizes exercise and meal plans based on the user's lifestyle and goals. For example, a plan combining 30 minutes of light aerobic exercise and strength training per day is generated. The generated diet menu is sent to the user's device in JSON format.

[0044] communication means

[0045] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu according to their daily progress.

[0046] Evaluation methods

[0047] The user records their daily exercise and dietary habits in the app. For example, they input the duration of their exercise and the calories they ingest, and the device sends this information to the server. The server stores the received records in a database and evaluates their progress. This evaluation quantifies the user's progress toward their goals and their persistence.

[0048] Message Generation Method

[0049] The server generates a message of encouragement or support based on the evaluation results. For example, it sends positive feedback such as "You did a great job today!" or an encouraging message such as "It may have been difficult today, but I'm sure you can do it tomorrow!" This helps to maintain the user's motivation.

[0050] Report Generation Method

[0051] The server periodically compiles the user's progress data and generates a report, which includes information such as the level of achievement, total exercise time, and calorie intake. This report is sent to the user's device, allowing the user to check their progress.

[0052] Alternative Menu Generation Methods

[0053] If the user does not reach their goal, the server analyzes the information and generates an alternative approach, such as changing their exercise routine or revising their meal plan, to create a new diet menu. This menu is also sent to the user's device, allowing the user to try a new approach.

[0054] Specific examples

[0055] For example, suppose user "C" sets his target weight at 60 kg, the amount of time he can devote to it per day at home, and his preferred exercise environment. C enters and sends this information through the app. The server receives C's information and stores it in a database. The server then generates the optimal diet menu for C. For example, it could generate a menu that combines 40 minutes of jogging and abdominal exercises per day. This is sent to C's device, and C follows the displayed menu.

[0056] C records his daily exercise and meals in the app, and his device sends that information to the server. The server evaluates C's progress and sends encouraging messages such as "You did a great job today!" This way, C can maintain his motivation and continue his diet.

[0057] If C does not reach his / her goal, the server will generate a new approach and suggest a new menu with a modified exercise program, for example, so that C can continue his / her diet in a new way.

[0058] In this way, the present invention functions as a system that supports users in succeeding in dieting.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[0062] Step 2:

[0063] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[0064] Step 3:

[0065] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[0066] Step 4:

[0067] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[0068] Step 5:

[0069] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[0070] Step 6:

[0071] Users record their daily exercise and dietary habits in the app. The device then sends the recorded data in JSON format to the server. This data includes exercise time, calories burned, calories ingested, etc.

[0072] Step 7:

[0073] The server stores the received daily record data in a database and runs an algorithm to evaluate progress, including the user's progress toward goals, achievement rate, and retention rate.

[0074] Step 8:

[0075] Based on the progress evaluation results, the server generates feedback messages to keep the user motivated. These messages include encouragement and encouragement and are sent to the terminal.

[0076] Step 9:

[0077] The server periodically compiles the progress data and generates a progress report, which includes the progress level, total exercise time, and calorie intake trend, and is sent to the device.

[0078] Step 10:

[0079] If the user does not reach their goal, the server analyzes the data and generates an alternative diet menu, which could include changing the exercise routine or revising the meal plan. The alternative menu is then sent to the device, allowing the user to try a new approach.

[0080] Through this series of steps, the system of the present invention can provide a diet plan that suits the user and provide continuous support, thereby increasing the success rate of dieting.

[0081] Example 1

[0082] 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."

[0083] Conventional diet plans often have a one-size-fits-all approach, failing to fully address individual users' lifestyles and goals. As a result, it's difficult for users to find the plan that's best for them and maintain their motivation. Furthermore, insufficient progress management, evaluation, and follow-up make it difficult to provide appropriate feedback or alternative plans if users don't reach their goals. In addition, there are technical challenges, such as secure data transmission and the efficiency of plan generation.

[0084] 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.

[0085] In this invention, the server includes a user interface for inputting information about an individual's goal weight, goal body shape, available time, and environment, a database for storing the user information, an algorithm for generating an optimal exercise and meal plan for each individual based on the user information, a communication means for transmitting the generated exercise and meal plan to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating supportive or encouraging messages based on the evaluation means and transmitting them to the user terminal, a report generation means for periodically generating progress reports based on the progress and transmitting them to the user terminal, an alternative plan generation means for generating an alternative exercise and meal plan if the goal is not achieved and transmitting them to the user terminal, a communication security means for securely communicating the information and progress status entered by the user, and a data formatting means for transmitting the generated plan, message, and report in JSON format. This enables the server to provide an optimal diet plan for each individual user, manage the progress, send supportive messages, generate periodic reports, and suggest alternative plans if the goal is not achieved.

[0086] "User interface means" refers to means that provides an interface for an individual to input information regarding the target weight, the target body shape, the amount of time available, and the exercise environment.

[0087] The "database means" is a database system for storing and managing information input by the user.

[0088] "Algorithmic means" refers to computational means for generating a personalized optimal exercise and diet plan based on stored user information.

[0089] "Communication means" refers to the communication protocols and infrastructure for transmitting the generated exercise and meal plan to the user terminal.

[0090] The "evaluation means" is a means for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[0091] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[0092] The "report generating means" is a means for periodically generating a progress report based on the progress and transmitting the report to the user terminal.

[0093] The "alternative plan generating means" is a means for generating an alternative exercise and meal plan when the goal is not achieved, and transmitting the plan to the user terminal.

[0094] "Communication security measures" are security protocols and techniques for securely communicating user-entered information and progress.

[0095] "Data Format Means" means the data format and means for sending and receiving generated plans, messages, and reports in JSON format.

[0096] In order to implement the present invention, the following means and processes must be utilized: The system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative plan generation means, a communication security means, and a data formatting means.

[0097] User Interface Means

[0098] Users use a smartphone app to input information about their personal goal weight, body shape, available time, and exercise environment (home, gym, etc.). The app was developed using Flutter, allowing users to input information intuitively.

[0099] Database Means

[0100] The entered user information is sent from the device to the server, which then stores it in a MySQL database, including the user ID, target weight, target body shape, available time, and exercise environment.

[0101] Algorithmic means

[0102] The server uses a Python-based algorithm to generate personalized exercise and diet plans based on the user's saved information, such as a plan that combines 30 minutes of aerobic exercise and strength training per day to suit the user's goals and lifestyle.

[0103] communication means

[0104] The generated exercise and meal plan is sent to the user's device in JSON format, and this communication is securely performed using the HTTPS protocol.

[0105] Evaluation methods

[0106] Users record their daily exercise and dietary habits in the app, such as the duration of exercise, calories burned, and the types and calories of food they ingest. This information is then sent from the device to the server, where it is stored in a database and progress is evaluated using an evaluation algorithm implemented in Python.

[0107] Message Generation Method

[0108] The server generates encouraging and supportive messages based on the progress assessment, using NLP techniques and generative AI models (e.g., GPT-3). Generated messages include "You did a great job today!" and "Today may have been difficult, but I'm sure you can do it tomorrow!"

[0109] Report Generation Method

[0110] The server periodically collects the user's progress data and generates a PDF report containing information such as progress, total exercise time, and calorie intake. The report is then sent to the user's device.

[0111] Alternative plan generation methods

[0112] If the user does not reach their goal, the server analyzes the progress data and offers a new approach, for example, generating a new plan with modified exercise content. This plan is also generated in JSON format and sent to the user's device.

[0113] Communications Security Measures

[0114] The HTTPS protocol is used to securely transmit user input information and progress, ensuring data safety and privacy.

[0115] Data Formatting Method

[0116] It is a means of sending and receiving generated exercise and meal plans, messages, and reports in JSON format. Using the JSON format structured data makes it easy to exchange various information.

[0117] Specific examples

[0118] For example, user "C" inputs a goal weight of 60 kg, 40 minutes of exercise per day, and training at home. The device sends the following data to the server: {"Goal weight": "60 kg", "Exercise time": "40 minutes per day", "Environment": "Home"}. The server saves this data and uses an algorithm to generate a plan of "40 minutes of jogging and sit-ups per day" and sends it to the device.

[0119] Example of an input prompt for a generative AI model:

[0120] Generate an optimal diet plan based on user-specified information. Use the following information:

[0121] Target weight: 60kg

[0122] Available time: 40 minutes per day

[0123] Exercise environment: Home

[0124] Please suggest a plan that combines jogging and abdominal exercises.

[0125] In this way, the present invention functions as a system that provides high-level support for users to succeed in dieting.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Program processing flow

[0128] Step 1:

[0129] The user opens the app and inputs their target weight, body shape, available time, and exercise environment. The input information is retrieved from the smartphone app's UI.

[0130] input:

[0131] Target weight

[0132] Target body shape

[0133] Time available

[0134] exercise environment

[0135] output:

[0136] User information in JSON format

[0137] Specific behavior:

[0138] User "A" inputs his / her goal weight of 60kg, his / her goal body shape, 40 minutes of exercise per day, and home workouts into the app. The app structures this information in JSON format and generates the following JSON data, for example:

[0139] json

[0140] {

[0141] "Goal Weight": "60kg",

[0142] "Target Body Type": "Slim",

[0143] "Time available": "40 minutes a day",

[0144] "Exercise environment": "Home"

[0145] }

[0146] Step 2:

[0147] The device sends the entered information to the server. This communication is carried out using the HTTPS protocol.

[0148] input:

[0149] User information in JSON format

[0150] output:

[0151] User information sent to the server

[0152] Specific behavior:

[0153] The terminal sends the aforementioned JSON data to the server using the HTTPS protocol. The data received on the server side is

[0154] json

[0155] {

[0156] "Goal Weight": "60kg",

[0157] "Target Body Type": "Slim",

[0158] "Time available": "40 minutes a day",

[0159] "Exercise environment": "Home"

[0160] }

[0161] Step 3:

[0162] The server stores the received information in a database.

[0163] input:

[0164] User information sent to the server

[0165] output:

[0166] User information stored in a database

[0167] Specific behavior:

[0168] The server parses the received JSON data and stores it in a MySQL database. For example, it executes the following SQL statement to store the data:

[0169] sql

[0170] INSERT INTO users (user_id, goal_weight, goal_shape, exercise_time, environment)

[0171] VALUES ("A's ID", "60kg", "Slim", "40 minutes a day", "Home");

[0172] Step 4:

[0173] The server uses an algorithm to generate an optimal diet menu based on the stored user information. This algorithm is implemented in Python.

[0174] input:

[0175] User information stored in a database

[0176] output:

[0177] Diet menu in JSON format

[0178] Specific behavior:

[0179] The server retrieves user information from the MySQL database and uses an algorithm to generate an optimal diet menu, such as "40 minutes of jogging and sit-ups a day." The generated menu is the following JSON data:

[0180] json

[0181] {

[0182] "exercise": "jogging and sit-ups",

[0183] "duration": "40 minutes a day",

[0184] "detailed_plan": ["20 minutes of jogging", "20 minutes of sit-ups"]

[0185] }

[0186] Step 5:

[0187] The server sends the generated diet menu to the terminal.

[0188] input:

[0189] Diet menu in JSON format

[0190] output:

[0191] Diet menu sent to the user's device

[0192] Specific behavior:

[0193] The server sends the JSON data to the user's device using the HTTPS protocol. The generated menu is displayed on the user's device.

[0194] Step 6:

[0195] The user uses the app to record their daily exercise and dietary habits, for example, by entering the duration of exercise, calories burned, and the types and calories of food consumed.

[0196] input:

[0197] Daily exercise and dietary habits

[0198] output:

[0199] Execution status data in JSON format

[0200] Specific behavior:

[0201] User "A" jogs for 20 minutes and does sit-ups for 20 minutes, and records this information in the app. The app generates the following JSON data:

[0202] json

[0203] {

[0204] "jogging": "20 minutes",

[0205] "Sit-ups": "20 minutes"

[0206] }

[0207] Step 7:

[0208] The terminal transmits the execution status data to the server.

[0209] input:

[0210] Execution status data in JSON format

[0211] output:

[0212] Execution status data sent to the server

[0213] Specific behavior:

[0214] The terminal sends the above JSON data to the server. The data received by the server is

[0215] json

[0216] {

[0217] "jogging": "20 minutes",

[0218] "Sit-ups": "20 minutes"

[0219] }

[0220] Step 8:

[0221] The server receives execution status data, stores it in a database, and evaluates the progress. This evaluation is implemented in Python.

[0222] input:

[0223] Execution status data sent to the server

[0224] output:

[0225] Progress evaluation results

[0226] Specific behavior:

[0227] The server stores the received data in a MySQL database and runs a Python script to evaluate progress, generating results such as "Today's achievement rate is 80%."

[0228] Step 9:

[0229] The server generates supportive and encouraging messages based on the evaluation results, using a generative AI model.

[0230] input:

[0231] Progress evaluation results

[0232] output:

[0233] Messages of support or encouragement

[0234] Specific behavior:

[0235] Based on the evaluation results, the server uses a generative AI model to generate messages such as "You worked hard today!" or "You can do better tomorrow!"

[0236] Step 10:

[0237] The server generates a message and sends it to the user's terminal.

[0238] input:

[0239] Messages of support or encouragement

[0240] output:

[0241] Message sent to user device

[0242] Specific behavior:

[0243] The server sends the generated message to the user's device using the HTTPS protocol, and user "A" receives the message in the app.

[0244] Step 11:

[0245] The server periodically aggregates user progress data and generates reports, which are generated using Python and ReportLab.

[0246] input:

[0247] User progress data

[0248] output:

[0249] Progress report in PDF format

[0250] Specific behavior:

[0251] The server will compile your progress data weekly and generate a PDF report containing the following:

[0252] Achievement level: 80%

[0253] Total exercise time: 280 minutes

[0254] Calorie intake trend: Stable

[0255] Step 12:

[0256] The server sends the generated report to the user's terminal.

[0257] input:

[0258] Progress report in PDF format

[0259] output:

[0260] Reports sent to user devices

[0261] Specific behavior:

[0262] The server sends the report in PDF format to the user's device, and user "A" checks the report in the app.

[0263] Step 13:

[0264] The server generates alternative plans as needed and sends them to the user's device, also in JSON format.

[0265] input:

[0266] User history and ratings

[0267] output:

[0268] New exercise and meal plans in JSON format

[0269] Specific behavior:

[0270] If user "A" does not reach his / her goal, the server analyzes past records, generates a new plan such as "20 minutes of brisk walking and plank exercises per day," and sends it to the user's terminal.

[0271] In this way, the system of the present invention uses various means to provide high support for the user's successful dieting.

[0272] (Application example 1)

[0273] 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."

[0274] Conventional diet support systems lack real-time feedback to help users train efficiently toward their set goals. Also, because it is difficult to maintain accurate training form, there is a high risk of injury due to improper form. Furthermore, users often lose motivation and have difficulty achieving their goals because they rely solely on self-evaluation to manage their progress.

[0275] 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.

[0276] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, an interface means for displaying the generated diet menu through smart glasses and providing real-time training assistance, and a motion sensor means for detecting movements during training and displaying instructions for maintaining correct form. This allows the user to receive real-time feedback, train safely with proper form, and effectively diet while maintaining motivation.

[0277] The "user interface means" is an interface for inputting information regarding an individual's target weight, target body shape, available time, and environment.

[0278] The "database means" is a storage system for storing the user information.

[0279] The "algorithm means" is a calculation method for generating an optimal diet menu for each individual based on the user information.

[0280] The "communication means" is a communication device for transmitting the generated diet menu to the user terminal.

[0281] The "evaluation means" is a method for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[0282] The "message generating means" is a device for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[0283] The "report generating means" is a device for generating a progress report periodically based on the progress and transmitting the report to the user terminal.

[0284] The "alternative menu generating means" is a device for generating an alternative diet menu when the goal is not achieved and transmitting it to the user terminal.

[0285] The "interface means" is an interface for displaying the generated diet menu through smart glasses and providing real-time training assistance.

[0286] The "motion sensor means" is a device that detects movements during training and displays instructions to help maintain correct form.

[0287] To practice this invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, an interface means, and a motion sensor means.

[0288] User Interface Means

[0289] Through the smart glasses, users input information about their target weight, target body shape, available time, and exercise environment (home, gym, etc.). This information is input via an interface displayed on the smart glasses' display.

[0290] Database Means

[0291] The entered user information is sent to the server and stored in a database, which includes information such as the user ID, target weight, target body shape, available time, and exercise environment.

[0292] Algorithmic means

[0293] The server is equipped with an algorithm that generates an optimal diet menu based on the user information stored in the database. This algorithm uses TensorFlow, for example, to generate an individually customized diet plan.

[0294] communication means

[0295] The generated diet menu is sent from the server to the smart glasses, where the user can review and follow it.

[0296] Evaluation methods

[0297] Users enter their daily exercise and diet records through the smart glasses. These records are then sent back to the server, where progress is assessed using an assessment tool. The assessment results are quantified to show the degree of achievement and continuity.

[0298] Message Generation Method

[0299] Based on the evaluation results, the server generates a message of encouragement or encouragement and sends it to the smart glasses, thereby maintaining the user's motivation.

[0300] Report Generation Method

[0301] The server periodically aggregates the user's progress data and generates progress reports that are sent to the user so that they can view their progress.

[0302] Alternative Menu Generation Methods

[0303] If the user does not reach their goal, the server will take into account past records and evaluations and generate a new diet menu, which will also be sent to the smart glasses.

[0304] Interface Means

[0305] The smart glasses visually display the generated diet menu and provide real-time assistance during training.

[0306] Motion Sensor Means

[0307] The smart glasses' built-in motion sensors detect movements during training and provide real-time guidance to help maintain proper form.

[0308] Specific examples

[0309] For example, user "A" sets a target weight of 70 kg, 30 minutes of training time per day, and a gym as the exercise environment. A uses smart glasses to input this information. The server receives A's information, generates an optimal diet plan, and sends it to the smart glasses. A trains according to the menu displayed on the smart glasses. During training, a motion sensor checks the form and displays correction instructions as needed. A also records their daily training and meals, which are sent to the server. The server evaluates the data and sends encouraging messages such as "You did a great job today!"

[0310] Using a generative AI model, the following prompt is generated:

[0311] "User name: A

[0312] Target weight: 70kg

[0313] Time available: 30 minutes a day

[0314] Exercise environment: Gym

[0315] This allows users to receive real-time feedback, train safely and effectively, and stay motivated to achieve their goals.

[0316] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0317] Step 1:

[0318] The user inputs information about their target weight, body shape, available time, and exercise environment through the smart glasses interface. The input information is temporarily stored inside the smart glasses and prepared for transmission to the server.

[0319] Input: Goal and environment information input by the user through smart glasses

[0320] Output: Temporarily saved user information

[0321] Step 2:

[0322] The smart glasses send the entered user information to the server, which receives the information and stores it in a database.

[0323] Input: User information sent from smart glasses

[0324] Output: User information stored in the database

[0325] Step 3:

[0326] The server passes the user information stored in the database to an algorithm that generates the optimal diet menu based on the user's lifestyle and goals. This is done using machine learning models such as TensorFlow.

[0327] Input: User information stored in the database

[0328] Output: Generated diet menu

[0329] Step 4:

[0330] The generated diet menu is sent from the server to the smart glasses, which then display it to the user, providing a visual of the training content.

[0331] Input: Diet menu sent from the server

[0332] Output: Diet menu displayed on smart glasses

[0333] Step 5:

[0334] The user performs training according to the display on the smart glasses. The smart glasses' built-in motion sensors detect training movements and provide guidance on maintaining correct form. Incorrect form is pointed out in real time and correction instructions are displayed.

[0335] Input: User training behavior

[0336] Output: Data detected by the motion sensor, correction instructions

[0337] Step 6:

[0338] Users enter their daily training and diet records and send them via smart glasses to a server, which then receives and evaluates their progress data.

[0339] Input: User-entered training and meal logs

[0340] Output: Progress data stored on the server

[0341] Step 7:

[0342] The server analyzes the progress data based on the evaluation method, quantifies the achievement level and continuity, and generates messages of encouragement and support, which are sent to the smart glasses.

[0343] Input: Progress data

[0344] Output: Evaluation results, generated cheering message

[0345] Step 8:

[0346] The server periodically generates and sends progress reports for the user to the smart glasses, allowing the user to view their progress.

[0347] Input: Past progress data

[0348] Output: Generated progress report

[0349] Step 9:

[0350] If the goal is not achieved, the server uses past records and evaluation data to generate an alternative diet menu and transmits it to the smart glasses, where the user can then implement the new menu.

[0351] Input: Historical records and evaluation data

[0352] Output: Alternative diet menu

[0353] The above is a specific process flow for implementing this invention. At each step, data is exchanged between the smart glasses and the server, and training and feedback are effectively carried out to help the user achieve their goals.

[0354] 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.

[0355] To implement the present invention, it is necessary to consider a configuration that combines a conventional system with an emotion engine means. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[0356] User Interface Means

[0357] Users use a smartphone app to input information about their target weight, body shape, available time, and exercise environment, which provides an intuitive interface to facilitate detailed input of user information.

[0358] Database Means

[0359] The input information is sent from the device to the server, which then stores it in a database, including the user ID, target weight, target body shape, available time, and exercise environment.

[0360] Algorithmic means

[0361] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database, which is customized to the user's lifestyle and goals.

[0362] communication means

[0363] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu to manage their exercise and diet.

[0364] Evaluation methods

[0365] Users record their daily exercise and dietary habits in the app, and the device sends the data to the server. The server stores the data in a database and evaluates the progress using an evaluation tool. The evaluation is a numerical representation of the user's progress toward their goals.

[0366] Message Generation Method

[0367] The server generates encouraging or supportive messages based on the evaluation results, providing the necessary feedback to keep the user motivated.

[0368] Report Generation Method

[0369] The server periodically generates a progress report and sends it to the user's device, which includes information such as progress, total exercise time, and calorie intake.

[0370] Alternative Menu Generation Methods

[0371] If the user does not reach the goal, the server runs an algorithm to generate a new approach and sends an alternative menu to the user's terminal.

[0372] Emotion Engine Means

[0373] The emotion engine recognizes the user's emotional state based on the user's input data. This emotion engine analyzes the user's recorded data and information acquired from the biometric information sensor to determine the user's emotional state. For example, it can analyze the level of stress or satisfaction.

[0374] Specific examples

[0375] User "D" starts the app and inputs information about his / her target weight, target body shape, available time, and exercise environment (home). The input information is sent from the device to the server and stored in a database. The server uses this information to generate an optimal diet menu for D and sends it to D's device. For example, it generates a plan that combines 30 minutes of jogging and abdominal exercises per day.

[0376] Person D records his / her daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates his / her progress and sends him / her messages of encouragement and support. Furthermore, the server recognizes Person D's emotional state using an emotion engine means and sends him / her messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax," further increasing his / her motivation.

[0377] If D does not reach his goal, the server calculates a new approach and generates an alternative diet menu to present to D. This allows D to continue his diet with a new approach.

[0378] Through this series of processes, the system of the present invention also takes into account the user's emotional state and provides individually tailored feedback and support, further increasing the success rate of dieting.

[0379] The processing flow will be explained below.

[0380] Step 1:

[0381] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[0382] Step 2:

[0383] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[0384] Step 3:

[0385] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[0386] Step 4:

[0387] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[0388] Step 5:

[0389] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[0390] Step 6:

[0391] Users record their daily exercise and dietary habits in the app, for example by entering the duration of exercise and the calories they consume. The device then sends this data in JSON format to the server.

[0392] Step 7:

[0393] The server stores the received daily record data in a database and evaluates the progress using an evaluation tool, including the progress, achievement rate, and continuation rate of the user toward their goal.

[0394] Step 8:

[0395] Based on the progress evaluation, the server generates messages of encouragement and support to keep the user motivated, such as "You did a great job today!" or "You'll do better tomorrow!"

[0396] Step 9:

[0397] The emotion engine means analyzes the user's input data and the data from the biometric sensor to recognize the user's emotional state, for example, to identify when the user is feeling stressed or has low motivation.

[0398] Step 10:

[0399] The server generates a customized message according to the user's emotional state obtained from the emotion engine means, for example, a message such as "You seem to be feeling a bit stressed today. Take a deep breath and relax."

[0400] Step 11:

[0401] The server generates periodic progress reports and sends them to the user's device. These reports include the level of achievement, the total exercise time, and the trend of calorie intake, allowing the user to check their own progress.

[0402] Step 12:

[0403] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu, which may include changing the exercise routine or revising the meal plan. The generated alternative menu is sent to the device, allowing the user to try a new approach.

[0404] Through this series of steps, the system of the present invention provides a diet plan tailored to the user and provides continuous and personalized support while taking into account their emotional state, thereby increasing the success rate of dieting.

[0405] Example 2

[0406] 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."

[0407] Conventional diet support systems only provide feedback based on the user's physical information and activity data. However, they lack support tailored to the user's motivation and psychological state, resulting in low rates of continuity and success in diet plans. In addition, because they do not take the user's emotional state into account, stress and frustration tend to accumulate, making it difficult to generate optimal diet menus. The objective of this invention is to solve this problem.

[0408] 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.

[0409] In this invention, the server includes input means for inputting information regarding an individual's target weight, target body shape, available time, and environment, storage means for storing the user information, generation means for generating an individually optimized menu based on the user information, transmission means for transmitting the generated menu to the user device, evaluation means for receiving a record of daily progress and evaluating progress based on the record, generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user device, reporting means for periodically generating a progress report based on the progress and transmitting it to the user device, alternative generation means for generating an alternative menu if the target is not achieved and transmitting it to the user device, and recognition means for recognizing the user's emotional state from the input data and biosensor information and providing feedback. This makes it possible to provide individually optimized feedback and support while taking the user's emotional state into consideration, thereby supporting the continuation and success of the diet plan.

[0410] The "input means" is an interface for the user to input information regarding the individual's target weight, target body shape, available time, and environment.

[0411] The "storage means" refers to a function for storing the user information in a database or the like.

[0412] The "generation means" is a function that includes algorithms and processes that create an optimal menu for each user based on the stored user information.

[0413] The "transmission means" refers to a function for transmitting the generated menu or message to the user device.

[0414] The "evaluation means" is a function for receiving records of daily implementation status and evaluating the user's progress based on those records.

[0415] The "generation means" refers to a function for creating cheering messages and the like based on the evaluation means and other data.

[0416] The "reporting means" is a function for periodically generating progress reports based on the progress and transmitting them to the user device.

[0417] The "alternative generation means" refers to a function for generating a new menu and transmitting it to the user device if the target is not achieved.

[0418] The "recognition means" is a function that analyzes the user's emotional state from input data and biosensor information and provides feedback.

[0419] The present invention provides a diet support system that meets the individual needs of users. Below, each element for implementing the present invention and its operation will be described in detail.

[0420] User Interface Means

[0421] Users use a smartphone app to enter information about their target weight, body shape, available time, and exercise environment. The app provides an intuitive interface and is designed to allow users to easily enter information using sliders and checkboxes, allowing users to register their information quickly and accurately.

[0422] Database Means

[0423] The entered information is sent from the terminal to a server, which stores the received information in a database and manages information such as the user's ID, target weight, target body shape, available time, and exercise environment. This database uses a modern database management system (DBMS) to provide fast and reliable data access.

[0424] Algorithmic means

[0425] The server generates an optimal diet menu based on the user's information stored in the database. The algorithm creates a customized menu based on the user's lifestyle and goals. For example, it takes into account the user's individual energy expenditure and preferred food types.

[0426] communication means

[0427] The generated diet menu is sent from the server to the user's device, which then displays the menu to the user as a push notification or in-app message. This allows the user to always check the latest menu information and manage their exercise and diet accordingly.

[0428] Evaluation methods

[0429] Users record their daily exercise and dietary habits in the app. This data is sent from the device to a server, which stores the information in a database. The server evaluates the progress and quantifies how close the user is to achieving their goals. The evaluation results are presented to the user in the form of graphs and statistics.

[0430] Message Generation Method

[0431] The server generates messages of encouragement or support based on the evaluation results. These messages are important as feedback to maintain the user's motivation. The generated messages are sent to the user's device via push notification.

[0432] Report Generation Method

[0433] The server periodically generates progress reports and sends them to the user's device. The reports contain detailed information such as the level of achievement, cumulative exercise time, and calorie intake, and are designed to allow the user to visually check their progress.

[0434] Alternative Menu Generation Methods

[0435] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu, allowing the user to continue with the new approach.

[0436] Emotion Engine Means

[0437] The emotion engine analyzes the user's input data and information from biometric sensors to determine the user's emotional state. Based on this, it provides feedback aimed at reducing stress and increasing motivation. For example, it sends a message such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[0438] Specific examples

[0439] The user launches the smartphone app and inputs their target weight and exercise environment. The input information is sent from the device to the server, which stores it in a database. For example, a plan combining 30 minutes of jogging and sit-ups per day is generated and sent to the user's device.

[0440] Users record their daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates the progress and generates and sends messages of encouragement and support. It also uses an emotion engine to recognize the user's emotional state and send appropriate messages.

[0441] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu to present to the user. Through this series of processes, the system of the present invention provides individually tailored feedback and support while also taking into account the user's emotional state, increasing the success rate of dieting.

[0442] Example of input prompt for generative AI model

[0443] Here are some examples of prompts to input to a generative AI model:

[0444] "Please provide a detailed explanation of each processing step of a diet support system, including the user interface, database, algorithm, communication, evaluation, message generation, report generation, alternative menu generation, and emotion engine means. The subject should be either the server, terminal, or user, and please also include specific operations in the explanation."

[0445] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0446] Step 1: Enter your user information

[0447] Detailed description: The user launches the smartphone app and inputs information about their target weight, target body shape, available time, and exercise environment.

[0448] Input and Output: Input includes data about the user's goal weight, goal body shape, amount of time available to exercise, and exercise environment. The output is a dataset of this information.

[0449] What it does: The user enters information using sliders and checkboxes within the app. Each time the information is entered, a dataset is generated.

[0450] Step 2: Send and save information

[0451] Specific explanation: The terminal sends the input information to the server, and the server stores the received information in a database.

[0452] Input and Output: Input is the data entered by the user into the terminal, and output is the data stored in the server's database.

[0453] Specific operation: The device sends data to the server over the network, and the server executes an SQL query to store the received data in a database.

[0454] Step 3: Create a diet menu

[0455] Specific explanation: The server generates an optimal diet menu based on the user information stored in the database.

[0456] Input and Output: The input is the user information in the database, and the output is the generated diet menu.

[0457] Specific operation: The server pulls user information from a database, runs an algorithm based on that information, and generates a customized diet menu.

[0458] Step 4: Submit the menu

[0459] Specific explanation: The server sends the generated diet menu to the user's terminal.

[0460] Input and Output: The input is the generated diet menu, and the output is the menu sent to the user's terminal.

[0461] Specific operation: The server pushes the generated diet menu to the user's device, which receives the notification and displays it within the app.

[0462] Step 5: Record the implementation status

[0463] Specifically, users record their daily exercise and dietary habits in the app, and the device sends the data to the server.

[0464] Input and Output: The input is the exercise and diet data recorded by the user, and the output is the performance status data sent to the server.

[0465] Specific operation: Users record their daily exercise time and calorie intake within the app, and when they press the save button, the data is sent to the server.

[0466] Step 6: Evaluate your progress

[0467] Specifically, the server stores the received data in a database and evaluates the progress, which is a numerical representation of the user's progress toward their goal.

[0468] Inputs and Outputs: Inputs are implementation status data and outputs are progress assessment results.

[0469] Specific operation: The server analyzes the implementation status data in the database and calculates the progress using an algorithm.

[0470] Step 7: Generate a message

[0471] Specifically, the server generates messages of encouragement and support based on the progress and sends them to the user's device.

[0472] Input and Output: The input is the progress evaluation result and the output is the generated message.

[0473] Specific operation: The server generates an appropriate message based on the evaluation results and sends it to the user's device as a push notification or in-app message.

[0474] Step 8: Generate a progress report

[0475] Specifically, the server periodically generates progress reports and sends them to the user's terminal.

[0476] Inputs and Outputs: Inputs are implementation data and evaluation results, and outputs are progress reports.

[0477] Specific operation: The server compiles user data at regular intervals, generates a report visually represented as graphs and numbers, and sends it to the user's device.

[0478] Step 9: Generate Alternate Menus

[0479] Specific Description: If the user does not reach the goal, the server calculates a new approach, generates an alternative diet menu, and sends it to the user's terminal.

[0480] Input and Output: The input is the progress assessment results and past records, and the output is the newly generated substitution menu.

[0481] Specific operation: The server reanalyzes the evaluation results and past data, generates a new exercise and meal plan, and presents it to the user.

[0482] Step 10: Emotional state analysis and feedback

[0483] Specific Description: The server uses an emotion engine means to recognize the user's emotional state based on input data and biosensor information, and provides feedback.

[0484] Input and output: The input is the user's recorded data and biometric information, and the output is the emotion recognition results and feedback messages based on them.

[0485] Specific operation: The server analyzes the user's input data and sensor information, runs an algorithm to recognize the emotional state, and generates appropriate feedback messages and sends them to the user's device.

[0486] (Application example 2)

[0487] 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."

[0488] Conventional diet support systems provide optimal menus based on information such as the user's target weight and exercise time, but lack feedback that takes the user's emotional state into consideration. This can lead to problems such as a decrease in user motivation and difficulty in continuing the diet. Therefore, the present invention aims to provide a system that analyzes the user's emotional state and provides optimal meal menus and encouraging messages based on that state.

[0489] 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.

[0490] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, and a means for analyzing the user's emotional state using an emotion engine and providing a meal menu and feedback messages based on that state, thereby enabling optimal diet support that takes the user's emotional state into consideration.

[0491] A "personal weight goal" is a body weight goal that a user wishes to achieve.

[0492] The "target body shape" is the ideal body shape or physical condition that the user aims for.

[0493] "Available time" refers to the amount of time a user can devote to dieting and exercise.

[0494] The "environment" refers to the specific location or situation where the user diets or exercises.

[0495] A "user interface means" is a means by which a user inputs information into a system.

[0496] "Database Means" means means for storing and managing user information and records.

[0497] The "algorithm means" is a means for calculating the optimal diet menu based on user information.

[0498] "Communication means" refers to a means for transmitting the generated diet menu and feedback to the user terminal.

[0499] The "evaluation means" is a means for evaluating the progress of the user based on the user's daily exercise and diet records.

[0500] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation.

[0501] The "report generation means" is a means for creating periodic progress reports based on the user's progress data.

[0502] The "substitute menu generating means" is a means for generating a new diet menu when the user is unable to achieve their goal.

[0503] An "emotion engine" is a means for analyzing a user's emotional state and providing feedback based on that state.

[0504] A "meal menu" is a specific meal plan proposed to suit the user's diet goals.

[0505] "Feedback messages" are encouraging messages or advice provided based on the user's progress or emotional state.

[0506] 1. System Overview

[0507] The present invention is a system that provides an optimal diet menu based on information on an individual's target weight, target body shape, available time, and environment, and provides feedback while taking into account the user's emotional state. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[0508] 2. Hardware and Software Used

[0509] Hardware: Smartphones, servers (physical or cloud-based)

[0510] software:

[0511] Smartphone application (iOS, Android)

[0512] Application Server:Flask (Python)

[0513] Database: PostgreSQL

[0514] Emotion Engine: Google Cloud Natural Language API

[0515] Communication: HTTP / HTTPS (requests library)

[0516] 3. User Interface Methods

[0517] Users input information about their target weight, body shape, available time, and exercise environment through a smartphone application. This information is designed to be input intuitively. The data entered by the user is sent to a server and stored in a database.

[0518] 4. Algorithmic Means

[0519] The server generates an optimal diet menu based on the user information stored in the database. The algorithm customizes the diet and exercise menu based on the user's lifestyle and goals. The generated menu is then sent to the user's smartphone via communication means.

[0520] 5. Evaluation and Emotion Engine Methods

[0521] The user records daily exercise and diet data in the smartphone application. This data is sent to the server and stored in a database. The evaluation means analyzes the user's progress, and the emotion engine means analyzes the user's emotional state.

[0522] 6. Message Generation and Report Generation Methods

[0523] The server generates supportive and encouraging messages based on the evaluation results and the user's emotional state and sends them to the user's device. It also periodically generates progress reports and sends them to the user's device. For example, if the user is feeling stressed, the server generates a message saying, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[0524] 7. Alternative Menu Generation Methods

[0525] If the user does not achieve the goal, the server generates an alternative diet menu and sends it to the user's terminal. This alternative menu is generated taking into account the user's past records and evaluation results.

[0526] 8. Examples of concrete examples and prompts

[0527] For example, when user "A" uses the app to input his / her target weight and exercise environment, the system suggests an optimal meal menu and exercise plan. A records his / her daily progress and sends the data to the server. The emotion engine analyzes A's emotional state and sends messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[0528] Example prompt sentence:

[0529] "Emodish is a personalized food delivery service based on the user's diet goals and emotional state. It proposes optimal meal plans based on the user's input of target weight and exercise time, and uses an emotion engine to analyze the user's emotional state and provide appropriate feedback."

[0530] In this way, the system of the present invention can take into account the user's emotional state and provide individually tailored feedback and support, further increasing the success rate of dieting.

[0531] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0532] Step 1:

[0533] Users use a smartphone application to input information about their target weight, body shape, available time, and exercise environment.

[0534] Input: Target weight, target body shape, available time, exercise environment

[0535] Output: User information entered (JSON format)

[0536] Specific behavior: The user enters the required information into the input form and presses the "Submit" button.

[0537] Step 2:

[0538] The entered information is sent from the terminal to the server, and the server stores the received information in a database.

[0539] Input: User information in JSON format

[0540] Output: User information stored in the database

[0541] Specific behavior: The server receives the HTTP request and writes the information to the database.

[0542] Step 3:

[0543] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database.

[0544] Input: User information stored in the database

[0545] Output: Optimal diet menu

[0546] What it does: The server runs an algorithm to calculate a diet menu based on the user's lifestyle and goals.

[0547] Step 4:

[0548] The generated diet menu is sent from the server to the user's terminal.

[0549] Enter: Optimal Diet Menu

[0550] Output: Diet menu displayed on the user's device

[0551] Specific operation: The server sends a diet menu as an HTTP response, and the user's device receives and displays it.

[0552] Step 5:

[0553] Users record their daily exercise and dietary habits in the app, and the data is sent to a server.

[0554] Input: Daily exercise and dietary habits

[0555] Output: Recorded data stored on the server

[0556] Specific behavior: The user uses the app's recording function and the data they enter is sent to the server.

[0557] Step 6:

[0558] The server stores this in a database and evaluates the progress using an evaluation means.

[0559] Input: Saved recording data

[0560] Output: Evaluation results (progress)

[0561] What happens: The server analyzes the recorded data and calculates the progress towards the goal.

[0562] Step 7:

[0563] The server generates a message of encouragement or support based on the evaluation result and transmits it to the user's terminal.

[0564] Input: Evaluation result

[0565] Output: A message of encouragement or support

[0566] Specific operation: The server uses the generative AI model to create a message and send it to the user's device.

[0567] Step 8:

[0568] The server periodically generates progress reports and sends them to the user's terminal.

[0569] Input: Evaluation results and recorded data

[0570] Output: Progress report

[0571] Specific operation: The server creates a progress report and periodically sends it to the user's terminal.

[0572] Step 9:

[0573] An emotion engine is used to recognize the user's emotional state and provide feedback messages based on that state.

[0574] Input: User recorded data and information from biometric sensors

[0575] Output: Feedback message based on emotion

[0576] Specific operation: The server uses the emotion engine to analyze the emotional state and generates and sends a message accordingly.

[0577] Step 10:

[0578] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu to present to the user.

[0579] Input: Past records and evaluation results

[0580] Output: New diet menu

[0581] Specific operation: The server re-runs the algorithm and sends the alternative diet menu to the user's device.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] [Second embodiment]

[0586] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0587] 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.

[0588] 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).

[0589] 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.

[0590] 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.

[0591] 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).

[0592] 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.

[0593] 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.

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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."

[0598] To practice the present invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, and an alternative menu generation means.

[0599] User Interface Means

[0600] A user uses a smartphone app to set goals for a diet plan. The app provides an interface for the user to input information about their goal weight, body shape, available time, and exercise environment (e.g., home, gym). This allows for personalized input of information.

[0601] Database Means

[0602] The entered user information is sent from the terminal to the server, and the server stores the received information in a database that contains information such as the user ID, target weight, target body shape, available time, and environmental information.

[0603] Algorithmic means

[0604] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This algorithm customizes exercise and meal plans based on the user's lifestyle and goals. For example, a plan combining 30 minutes of light aerobic exercise and strength training per day is generated. The generated diet menu is sent to the user's device in JSON format.

[0605] communication means

[0606] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu according to their daily progress.

[0607] Evaluation methods

[0608] The user records their daily exercise and dietary habits in the app. For example, they input the duration of their exercise and the calories they ingest, and the device sends this information to the server. The server stores the received records in a database and evaluates their progress. This evaluation quantifies the user's progress toward their goals and their persistence.

[0609] Message Generation Method

[0610] The server generates a message of encouragement or support based on the evaluation results. For example, it sends positive feedback such as "You did a great job today!" or an encouraging message such as "It may have been difficult today, but I'm sure you can do it tomorrow!" This helps to maintain the user's motivation.

[0611] Report Generation Method

[0612] The server periodically compiles the user's progress data and generates a report, which includes information such as the level of achievement, total exercise time, and calorie intake. This report is sent to the user's device, allowing the user to check their progress.

[0613] Alternative Menu Generation Methods

[0614] If the user does not reach their goal, the server analyzes the information and generates an alternative approach, such as changing their exercise routine or revising their meal plan, to create a new diet menu. This menu is also sent to the user's device, allowing the user to try a new approach.

[0615] Specific examples

[0616] For example, suppose user "C" sets his target weight at 60 kg, the amount of time he can devote to it per day at home, and his preferred exercise environment. C enters and sends this information through the app. The server receives C's information and stores it in a database. The server then generates the optimal diet menu for C. For example, it could generate a menu that combines 40 minutes of jogging and abdominal exercises per day. This is sent to C's device, and C follows the displayed menu.

[0617] C records his daily exercise and meals in the app, and his device sends that information to the server. The server evaluates C's progress and sends encouraging messages such as "You did a great job today!" This way, C can maintain his motivation and continue his diet.

[0618] If C does not reach his / her goal, the server will generate a new approach and suggest a new menu with a modified exercise program, for example, so that C can continue his / her diet in a new way.

[0619] In this way, the present invention functions as a system that supports users in succeeding in dieting.

[0620] The processing flow will be explained below.

[0621] Step 1:

[0622] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[0623] Step 2:

[0624] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[0625] Step 3:

[0626] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[0627] Step 4:

[0628] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[0629] Step 5:

[0630] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[0631] Step 6:

[0632] Users record their daily exercise and dietary habits in the app. The device then sends the recorded data in JSON format to the server. This data includes exercise time, calories burned, calories ingested, etc.

[0633] Step 7:

[0634] The server stores the received daily record data in a database and runs an algorithm to evaluate progress, including the user's progress toward goals, achievement rate, and retention rate.

[0635] Step 8:

[0636] Based on the progress evaluation results, the server generates feedback messages to keep the user motivated. These messages include encouragement and encouragement and are sent to the terminal.

[0637] Step 9:

[0638] The server periodically compiles the progress data and generates a progress report, which includes the progress level, total exercise time, and calorie intake trend, and is sent to the device.

[0639] Step 10:

[0640] If the user does not reach their goal, the server analyzes the data and generates an alternative diet menu, which could include changing the exercise routine or revising the meal plan. The alternative menu is then sent to the device, allowing the user to try a new approach.

[0641] Through this series of steps, the system of the present invention can provide a diet plan that suits the user and provide continuous support, thereby increasing the success rate of dieting.

[0642] Example 1

[0643] 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."

[0644] Conventional diet plans often have a one-size-fits-all approach, failing to fully address individual users' lifestyles and goals. As a result, it's difficult for users to find the plan that's best for them and maintain their motivation. Furthermore, insufficient progress management, evaluation, and follow-up make it difficult to provide appropriate feedback or alternative plans if users don't reach their goals. In addition, there are technical challenges, such as secure data transmission and the efficiency of plan generation.

[0645] 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.

[0646] In this invention, the server includes a user interface for inputting information about an individual's goal weight, goal body shape, available time, and environment, a database for storing the user information, an algorithm for generating an optimal exercise and meal plan for each individual based on the user information, a communication means for transmitting the generated exercise and meal plan to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating supportive or encouraging messages based on the evaluation means and transmitting them to the user terminal, a report generation means for periodically generating progress reports based on the progress and transmitting them to the user terminal, an alternative plan generation means for generating an alternative exercise and meal plan if the goal is not achieved and transmitting them to the user terminal, a communication security means for securely communicating the information and progress status entered by the user, and a data formatting means for transmitting the generated plan, message, and report in JSON format. This enables the server to provide an optimal diet plan for each individual user, manage the progress, send supportive messages, generate periodic reports, and suggest alternative plans if the goal is not achieved.

[0647] "User interface means" refers to means that provides an interface for an individual to input information regarding the target weight, the target body shape, the amount of time available, and the exercise environment.

[0648] The "database means" is a database system for storing and managing information input by the user.

[0649] "Algorithmic means" refers to computational means for generating a personalized optimal exercise and diet plan based on stored user information.

[0650] "Communication means" refers to the communication protocols and infrastructure for transmitting the generated exercise and meal plan to the user terminal.

[0651] The "evaluation means" is a means for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[0652] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[0653] The "report generating means" is a means for periodically generating a progress report based on the progress and transmitting the report to the user terminal.

[0654] The "alternative plan generating means" is a means for generating an alternative exercise and meal plan when the goal is not achieved, and transmitting the plan to the user terminal.

[0655] "Communication security measures" are security protocols and techniques for securely communicating user-entered information and progress.

[0656] "Data Format Means" means the data format and means for sending and receiving generated plans, messages, and reports in JSON format.

[0657] In order to implement the present invention, the following means and processes must be utilized: The system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative plan generation means, a communication security means, and a data formatting means.

[0658] User Interface Means

[0659] Users use a smartphone app to input information about their personal goal weight, body shape, available time, and exercise environment (home, gym, etc.). The app was developed using Flutter, allowing users to input information intuitively.

[0660] Database Means

[0661] The entered user information is sent from the device to the server, which then stores it in a MySQL database, including the user ID, target weight, target body shape, available time, and exercise environment.

[0662] Algorithmic means

[0663] The server uses a Python-based algorithm to generate personalized exercise and diet plans based on the user's saved information, such as a plan that combines 30 minutes of aerobic exercise and strength training per day to suit the user's goals and lifestyle.

[0664] communication means

[0665] The generated exercise and meal plan is sent to the user's device in JSON format, and this communication is securely performed using the HTTPS protocol.

[0666] Evaluation methods

[0667] Users record their daily exercise and dietary habits in the app, such as the duration of exercise, calories burned, and the types and calories of food they ingest. This information is then sent from the device to the server, where it is stored in a database and progress is evaluated using an evaluation algorithm implemented in Python.

[0668] Message Generation Method

[0669] The server generates encouraging and supportive messages based on the progress assessment, using NLP techniques and generative AI models (e.g., GPT-3). Generated messages include "You did a great job today!" and "Today may have been difficult, but I'm sure you can do it tomorrow!"

[0670] Report Generation Method

[0671] The server periodically collects the user's progress data and generates a PDF report containing information such as progress, total exercise time, and calorie intake. The report is then sent to the user's device.

[0672] Alternative plan generation methods

[0673] If the user does not reach their goal, the server analyzes the progress data and offers a new approach, for example, generating a new plan with modified exercise content. This plan is also generated in JSON format and sent to the user's device.

[0674] Communications Security Measures

[0675] The HTTPS protocol is used to securely transmit user input information and progress, ensuring data safety and privacy.

[0676] Data Formatting Method

[0677] It is a means of sending and receiving generated exercise and meal plans, messages, and reports in JSON format. Using the JSON format structured data makes it easy to exchange various information.

[0678] Specific examples

[0679] For example, user "C" inputs a goal weight of 60 kg, 40 minutes of exercise per day, and training at home. The device sends the following data to the server: {"Goal weight": "60 kg", "Exercise time": "40 minutes per day", "Environment": "Home"}. The server saves this data and uses an algorithm to generate a plan of "40 minutes of jogging and sit-ups per day" and sends it to the device.

[0680] Example of an input prompt for a generative AI model:

[0681] Generate an optimal diet plan based on user-specified information. Use the following information:

[0682] Target weight: 60kg

[0683] Available time: 40 minutes per day

[0684] Exercise environment: Home

[0685] Please suggest a plan that combines jogging and abdominal exercises.

[0686] In this way, the present invention functions as a system that provides high-level support for users to succeed in dieting.

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

[0688] Program processing flow

[0689] Step 1:

[0690] The user opens the app and inputs their target weight, body shape, available time, and exercise environment. The input information is retrieved from the smartphone app's UI.

[0691] input:

[0692] Target weight

[0693] Target body shape

[0694] Time available

[0695] exercise environment

[0696] output:

[0697] User information in JSON format

[0698] Specific behavior:

[0699] User "A" inputs his / her goal weight of 60kg, his / her goal body shape, 40 minutes of exercise per day, and home workouts into the app. The app structures this information in JSON format and generates the following JSON data, for example:

[0700] json

[0701] {

[0702] "Goal Weight": "60kg",

[0703] "Target Body Type": "Slim",

[0704] "Time available": "40 minutes a day",

[0705] "Exercise environment": "Home"

[0706] }

[0707] Step 2:

[0708] The device sends the entered information to the server. This communication is carried out using the HTTPS protocol.

[0709] input:

[0710] User information in JSON format

[0711] output:

[0712] User information sent to the server

[0713] Specific behavior:

[0714] The terminal sends the aforementioned JSON data to the server using the HTTPS protocol. The data received on the server side is

[0715] json

[0716] {

[0717] "Goal Weight": "60kg",

[0718] "Target Body Type": "Slim",

[0719] "Time available": "40 minutes a day",

[0720] "Exercise environment": "Home"

[0721] }

[0722] Step 3:

[0723] The server stores the received information in a database.

[0724] input:

[0725] User information sent to the server

[0726] output:

[0727] User information stored in a database

[0728] Specific behavior:

[0729] The server parses the received JSON data and stores it in a MySQL database. For example, it executes the following SQL statement to store the data:

[0730] sql

[0731] INSERT INTO users (user_id, goal_weight, goal_shape, exercise_time, environment)

[0732] VALUES ("A's ID", "60kg", "Slim", "40 minutes a day", "Home");

[0733] Step 4:

[0734] The server uses an algorithm to generate an optimal diet menu based on the stored user information. This algorithm is implemented in Python.

[0735] input:

[0736] User information stored in a database

[0737] output:

[0738] Diet menu in JSON format

[0739] Specific behavior:

[0740] The server retrieves user information from the MySQL database and uses an algorithm to generate an optimal diet menu, such as "40 minutes of jogging and sit-ups a day." The generated menu is the following JSON data:

[0741] json

[0742] {

[0743] "exercise": "jogging and sit-ups",

[0744] "duration": "40 minutes a day",

[0745] "detailed_plan": ["20 minutes of jogging", "20 minutes of sit-ups"]

[0746] }

[0747] Step 5:

[0748] The server sends the generated diet menu to the terminal.

[0749] input:

[0750] Diet menu in JSON format

[0751] output:

[0752] Diet menu sent to the user's device

[0753] Specific behavior:

[0754] The server sends the JSON data to the user's device using the HTTPS protocol. The generated menu is displayed on the user's device.

[0755] Step 6:

[0756] The user uses the app to record their daily exercise and dietary habits, for example, by entering the duration of exercise, calories burned, and the types and calories of food consumed.

[0757] input:

[0758] Daily exercise and dietary habits

[0759] output:

[0760] Execution status data in JSON format

[0761] Specific behavior:

[0762] User "A" jogs for 20 minutes and does sit-ups for 20 minutes, and records this information in the app. The app generates the following JSON data:

[0763] json

[0764] {

[0765] "jogging": "20 minutes",

[0766] "Sit-ups": "20 minutes"

[0767] }

[0768] Step 7:

[0769] The terminal transmits the execution status data to the server.

[0770] input:

[0771] Execution status data in JSON format

[0772] output:

[0773] Execution status data sent to the server

[0774] Specific behavior:

[0775] The terminal sends the above JSON data to the server. The data received by the server is

[0776] json

[0777] {

[0778] "jogging": "20 minutes",

[0779] "Sit-ups": "20 minutes"

[0780] }

[0781] Step 8:

[0782] The server receives execution status data, stores it in a database, and evaluates the progress. This evaluation is implemented in Python.

[0783] input:

[0784] Execution status data sent to the server

[0785] output:

[0786] Progress evaluation results

[0787] Specific behavior:

[0788] The server stores the received data in a MySQL database and runs a Python script to evaluate progress, generating results such as "Today's achievement rate is 80%."

[0789] Step 9:

[0790] The server generates supportive and encouraging messages based on the evaluation results, using a generative AI model.

[0791] input:

[0792] Progress evaluation results

[0793] output:

[0794] Messages of support or encouragement

[0795] Specific behavior:

[0796] Based on the evaluation results, the server uses a generative AI model to generate messages such as "You worked hard today!" or "You can do better tomorrow!"

[0797] Step 10:

[0798] The server generates a message and sends it to the user's terminal.

[0799] input:

[0800] Messages of support or encouragement

[0801] output:

[0802] Message sent to user device

[0803] Specific behavior:

[0804] The server sends the generated message to the user's device using the HTTPS protocol, and user "A" receives the message in the app.

[0805] Step 11:

[0806] The server periodically aggregates user progress data and generates reports, which are generated using Python and ReportLab.

[0807] input:

[0808] User progress data

[0809] output:

[0810] Progress report in PDF format

[0811] Specific behavior:

[0812] The server will compile your progress data weekly and generate a PDF report containing the following:

[0813] Achievement level: 80%

[0814] Total exercise time: 280 minutes

[0815] Calorie intake trend: Stable

[0816] Step 12:

[0817] The server sends the generated report to the user's terminal.

[0818] input:

[0819] Progress report in PDF format

[0820] output:

[0821] Reports sent to user devices

[0822] Specific behavior:

[0823] The server sends the report in PDF format to the user's device, and user "A" checks the report in the app.

[0824] Step 13:

[0825] The server generates alternative plans as needed and sends them to the user's device, also in JSON format.

[0826] input:

[0827] User history and ratings

[0828] output:

[0829] New exercise and meal plans in JSON format

[0830] Specific behavior:

[0831] If user "A" does not reach his / her goal, the server analyzes past records, generates a new plan such as "20 minutes of brisk walking and plank exercises per day," and sends it to the user's terminal.

[0832] In this way, the system of the present invention uses various means to provide high support for the user's successful dieting.

[0833] (Application example 1)

[0834] 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."

[0835] Conventional diet support systems lack real-time feedback to help users train efficiently toward their set goals. Also, because it is difficult to maintain accurate training form, there is a high risk of injury due to improper form. Furthermore, users often lose motivation and have difficulty achieving their goals because they rely solely on self-evaluation to manage their progress.

[0836] 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.

[0837] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, an interface means for displaying the generated diet menu through smart glasses and providing real-time training assistance, and a motion sensor means for detecting movements during training and displaying instructions for maintaining correct form. This allows the user to receive real-time feedback, train safely with proper form, and effectively diet while maintaining motivation.

[0838] The "user interface means" is an interface for inputting information regarding an individual's target weight, target body shape, available time, and environment.

[0839] The "database means" is a storage system for storing the user information.

[0840] The "algorithm means" is a calculation method for generating an optimal diet menu for each individual based on the user information.

[0841] The "communication means" is a communication device for transmitting the generated diet menu to the user terminal.

[0842] The "evaluation means" is a method for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[0843] The "message generating means" is a device for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[0844] The "report generating means" is a device for generating a progress report periodically based on the progress and transmitting the report to the user terminal.

[0845] The "alternative menu generating means" is a device for generating an alternative diet menu when the goal is not achieved and transmitting it to the user terminal.

[0846] The "interface means" is an interface for displaying the generated diet menu through smart glasses and providing real-time training assistance.

[0847] The "motion sensor means" is a device that detects movements during training and displays instructions to help maintain correct form.

[0848] To practice this invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, an interface means, and a motion sensor means.

[0849] User Interface Means

[0850] Through the smart glasses, users input information about their target weight, target body shape, available time, and exercise environment (home, gym, etc.). This information is input via an interface displayed on the smart glasses' display.

[0851] Database Means

[0852] The entered user information is sent to the server and stored in a database, which includes information such as the user ID, target weight, target body shape, available time, and exercise environment.

[0853] Algorithmic means

[0854] The server is equipped with an algorithm that generates an optimal diet menu based on the user information stored in the database. This algorithm uses TensorFlow, for example, to generate an individually customized diet plan.

[0855] communication means

[0856] The generated diet menu is sent from the server to the smart glasses, where the user can review and follow it.

[0857] Evaluation methods

[0858] Users enter their daily exercise and diet records through the smart glasses. These records are then sent back to the server, where progress is assessed using an assessment tool. The assessment results are quantified to show the degree of achievement and continuity.

[0859] Message Generation Method

[0860] Based on the evaluation results, the server generates a message of encouragement or encouragement and sends it to the smart glasses, thereby maintaining the user's motivation.

[0861] Report Generation Method

[0862] The server periodically aggregates the user's progress data and generates progress reports that are sent to the user so that they can view their progress.

[0863] Alternative Menu Generation Methods

[0864] If the user does not reach their goal, the server will take into account past records and evaluations and generate a new diet menu, which will also be sent to the smart glasses.

[0865] Interface Means

[0866] The smart glasses visually display the generated diet menu and provide real-time assistance during training.

[0867] Motion Sensor Means

[0868] The smart glasses' built-in motion sensors detect movements during training and provide real-time guidance to help maintain proper form.

[0869] Specific examples

[0870] For example, user "A" sets a target weight of 70 kg, 30 minutes of training time per day, and a gym as the exercise environment. A uses smart glasses to input this information. The server receives A's information, generates an optimal diet plan, and sends it to the smart glasses. A trains according to the menu displayed on the smart glasses. During training, a motion sensor checks the form and displays correction instructions as needed. A also records their daily training and meals, which are sent to the server. The server evaluates the data and sends encouraging messages such as "You did a great job today!"

[0871] Using a generative AI model, the following prompt is generated:

[0872] "User name: A

[0873] Target weight: 70kg

[0874] Time available: 30 minutes a day

[0875] Exercise environment: Gym

[0876] This allows users to receive real-time feedback, train safely and effectively, and stay motivated to achieve their goals.

[0877] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0878] Step 1:

[0879] The user inputs information about their target weight, body shape, available time, and exercise environment through the smart glasses interface. The input information is temporarily stored inside the smart glasses and prepared for transmission to the server.

[0880] Input: Goal and environment information input by the user through smart glasses

[0881] Output: Temporarily saved user information

[0882] Step 2:

[0883] The smart glasses send the entered user information to the server, which receives the information and stores it in a database.

[0884] Input: User information sent from smart glasses

[0885] Output: User information stored in the database

[0886] Step 3:

[0887] The server passes the user information stored in the database to an algorithm that generates the optimal diet menu based on the user's lifestyle and goals. This is done using machine learning models such as TensorFlow.

[0888] Input: User information stored in the database

[0889] Output: Generated diet menu

[0890] Step 4:

[0891] The generated diet menu is sent from the server to the smart glasses, which then display it to the user, providing a visual of the training content.

[0892] Input: Diet menu sent from the server

[0893] Output: Diet menu displayed on smart glasses

[0894] Step 5:

[0895] The user performs training according to the display on the smart glasses. The smart glasses' built-in motion sensors detect training movements and provide guidance on maintaining correct form. Incorrect form is pointed out in real time and correction instructions are displayed.

[0896] Input: User training behavior

[0897] Output: Data detected by the motion sensor, correction instructions

[0898] Step 6:

[0899] Users enter their daily training and diet records and send them via smart glasses to a server, which then receives and evaluates their progress data.

[0900] Input: User-entered training and meal logs

[0901] Output: Progress data stored on the server

[0902] Step 7:

[0903] The server analyzes the progress data based on the evaluation method, quantifies the achievement level and continuity, and generates messages of encouragement and support, which are sent to the smart glasses.

[0904] Input: Progress data

[0905] Output: Evaluation results, generated cheering message

[0906] Step 8:

[0907] The server periodically generates and sends progress reports for the user to the smart glasses, allowing the user to view their progress.

[0908] Input: Past progress data

[0909] Output: Generated progress report

[0910] Step 9:

[0911] If the goal is not achieved, the server uses past records and evaluation data to generate an alternative diet menu and transmits it to the smart glasses, where the user can then implement the new menu.

[0912] Input: Historical records and evaluation data

[0913] Output: Alternative diet menu

[0914] The above is a specific process flow for implementing this invention. At each step, data is exchanged between the smart glasses and the server, and training and feedback are effectively carried out to help the user achieve their goals.

[0915] 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.

[0916] To implement the present invention, it is necessary to consider a configuration that combines a conventional system with an emotion engine means. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[0917] User Interface Means

[0918] Users use a smartphone app to input information about their target weight, body shape, available time, and exercise environment, which provides an intuitive interface to facilitate detailed input of user information.

[0919] Database Means

[0920] The input information is sent from the device to the server, which then stores it in a database, including the user ID, target weight, target body shape, available time, and exercise environment.

[0921] Algorithmic means

[0922] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database, which is customized to the user's lifestyle and goals.

[0923] communication means

[0924] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu to manage their exercise and diet.

[0925] Evaluation methods

[0926] Users record their daily exercise and dietary habits in the app, and the device sends the data to the server. The server stores the data in a database and evaluates the progress using an evaluation tool. The evaluation is a numerical representation of the user's progress toward their goals.

[0927] Message Generation Method

[0928] The server generates encouraging or supportive messages based on the evaluation results, providing the necessary feedback to keep the user motivated.

[0929] Report Generation Method

[0930] The server periodically generates a progress report and sends it to the user's device, which includes information such as progress, total exercise time, and calorie intake.

[0931] Alternative Menu Generation Methods

[0932] If the user does not reach the goal, the server runs an algorithm to generate a new approach and sends an alternative menu to the user's terminal.

[0933] Emotion Engine Means

[0934] The emotion engine recognizes the user's emotional state based on the user's input data. This emotion engine analyzes the user's recorded data and information acquired from the biometric information sensor to determine the user's emotional state. For example, it can analyze the level of stress or satisfaction.

[0935] Specific examples

[0936] User "D" starts the app and inputs information about his / her target weight, target body shape, available time, and exercise environment (home). The input information is sent from the device to the server and stored in a database. The server uses this information to generate an optimal diet menu for D and sends it to D's device. For example, it generates a plan that combines 30 minutes of jogging and abdominal exercises per day.

[0937] Person D records his / her daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates his / her progress and sends him / her messages of encouragement and support. Furthermore, the server recognizes Person D's emotional state using an emotion engine means and sends him / her messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax," further increasing his / her motivation.

[0938] If D does not reach his goal, the server calculates a new approach and generates an alternative diet menu to present to D. This allows D to continue his diet with a new approach.

[0939] Through this series of processes, the system of the present invention also takes into account the user's emotional state and provides individually tailored feedback and support, further increasing the success rate of dieting.

[0940] The processing flow will be explained below.

[0941] Step 1:

[0942] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[0943] Step 2:

[0944] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[0945] Step 3:

[0946] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[0947] Step 4:

[0948] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[0949] Step 5:

[0950] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[0951] Step 6:

[0952] Users record their daily exercise and dietary habits in the app, for example by entering the duration of exercise and the calories they consume. The device then sends this data in JSON format to the server.

[0953] Step 7:

[0954] The server stores the received daily record data in a database and evaluates the progress using an evaluation tool, including the progress, achievement rate, and continuation rate of the user toward their goal.

[0955] Step 8:

[0956] Based on the progress evaluation, the server generates messages of encouragement and support to keep the user motivated, such as "You did a great job today!" or "You'll do better tomorrow!"

[0957] Step 9:

[0958] The emotion engine means analyzes the user's input data and the data from the biometric sensor to recognize the user's emotional state, for example, to identify when the user is feeling stressed or has low motivation.

[0959] Step 10:

[0960] The server generates a customized message according to the user's emotional state obtained from the emotion engine means, for example, a message such as "You seem to be feeling a bit stressed today. Take a deep breath and relax."

[0961] Step 11:

[0962] The server generates periodic progress reports and sends them to the user's device. These reports include the level of achievement, the total exercise time, and the trend of calorie intake, allowing the user to check their own progress.

[0963] Step 12:

[0964] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu, which may include changing the exercise routine or revising the meal plan. The generated alternative menu is sent to the device, allowing the user to try a new approach.

[0965] Through this series of steps, the system of the present invention provides a diet plan tailored to the user and provides continuous and personalized support while taking into account their emotional state, thereby increasing the success rate of dieting.

[0966] Example 2

[0967] 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."

[0968] Conventional diet support systems only provide feedback based on the user's physical information and activity data. However, they lack support tailored to the user's motivation and psychological state, resulting in low rates of continuity and success in diet plans. In addition, because they do not take the user's emotional state into account, stress and frustration tend to accumulate, making it difficult to generate optimal diet menus. The objective of this invention is to solve this problem.

[0969] 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.

[0970] In this invention, the server includes input means for inputting information regarding an individual's target weight, target body shape, available time, and environment, storage means for storing the user information, generation means for generating an individually optimized menu based on the user information, transmission means for transmitting the generated menu to the user device, evaluation means for receiving a record of daily progress and evaluating progress based on the record, generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user device, reporting means for periodically generating a progress report based on the progress and transmitting it to the user device, alternative generation means for generating an alternative menu if the target is not achieved and transmitting it to the user device, and recognition means for recognizing the user's emotional state from the input data and biosensor information and providing feedback. This makes it possible to provide individually optimized feedback and support while taking the user's emotional state into consideration, thereby supporting the continuation and success of the diet plan.

[0971] The "input means" is an interface for the user to input information regarding the individual's target weight, target body shape, available time, and environment.

[0972] The "storage means" refers to a function for storing the user information in a database or the like.

[0973] The "generation means" is a function that includes algorithms and processes that create an optimal menu for each user based on the stored user information.

[0974] The "transmission means" refers to a function for transmitting the generated menu or message to the user device.

[0975] The "evaluation means" is a function for receiving records of daily implementation status and evaluating the user's progress based on those records.

[0976] The "generation means" refers to a function for creating cheering messages and the like based on the evaluation means and other data.

[0977] The "reporting means" is a function for periodically generating progress reports based on the progress and transmitting them to the user device.

[0978] The "alternative generation means" refers to a function for generating a new menu and transmitting it to the user device if the target is not achieved.

[0979] The "recognition means" is a function that analyzes the user's emotional state from input data and biosensor information and provides feedback.

[0980] The present invention provides a diet support system that meets the individual needs of users. Below, each element for implementing the present invention and its operation will be described in detail.

[0981] User Interface Means

[0982] Users use a smartphone app to enter information about their target weight, body shape, available time, and exercise environment. The app provides an intuitive interface and is designed to allow users to easily enter information using sliders and checkboxes, allowing users to register their information quickly and accurately.

[0983] Database Means

[0984] The entered information is sent from the terminal to a server, which stores the received information in a database and manages information such as the user's ID, target weight, target body shape, available time, and exercise environment. This database uses a modern database management system (DBMS) to provide fast and reliable data access.

[0985] Algorithmic means

[0986] The server generates an optimal diet menu based on the user's information stored in the database. The algorithm creates a customized menu based on the user's lifestyle and goals. For example, it takes into account the user's individual energy expenditure and preferred food types.

[0987] communication means

[0988] The generated diet menu is sent from the server to the user's device, which then displays the menu to the user as a push notification or in-app message. This allows the user to always check the latest menu information and manage their exercise and diet accordingly.

[0989] Evaluation methods

[0990] Users record their daily exercise and dietary habits in the app. This data is sent from the device to a server, which stores the information in a database. The server evaluates the progress and quantifies how close the user is to achieving their goals. The evaluation results are presented to the user in the form of graphs and statistics.

[0991] Message Generation Method

[0992] The server generates messages of encouragement or support based on the evaluation results. These messages are important as feedback to maintain the user's motivation. The generated messages are sent to the user's device via push notification.

[0993] Report Generation Method

[0994] The server periodically generates progress reports and sends them to the user's device. The reports contain detailed information such as the level of achievement, cumulative exercise time, and calorie intake, and are designed to allow the user to visually check their progress.

[0995] Alternative Menu Generation Methods

[0996] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu, allowing the user to continue with the new approach.

[0997] Emotion Engine Means

[0998] The emotion engine analyzes the user's input data and information from biometric sensors to determine the user's emotional state. Based on this, it provides feedback aimed at reducing stress and increasing motivation. For example, it sends a message such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[0999] Specific examples

[1000] The user launches the smartphone app and inputs their target weight and exercise environment. The input information is sent from the device to the server, which stores it in a database. For example, a plan combining 30 minutes of jogging and sit-ups per day is generated and sent to the user's device.

[1001] Users record their daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates the progress and generates and sends messages of encouragement and support. It also uses an emotion engine to recognize the user's emotional state and send appropriate messages.

[1002] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu to present to the user. Through this series of processes, the system of the present invention provides individually tailored feedback and support while also taking into account the user's emotional state, increasing the success rate of dieting.

[1003] Example of input prompt for generative AI model

[1004] Here are some examples of prompts to input to a generative AI model:

[1005] "Please provide a detailed explanation of each processing step of a diet support system, including the user interface, database, algorithm, communication, evaluation, message generation, report generation, alternative menu generation, and emotion engine means. The subject should be either the server, terminal, or user, and please also include specific operations in the explanation."

[1006] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1007] Step 1: Enter your user information

[1008] Detailed description: The user launches the smartphone app and inputs information about their target weight, target body shape, available time, and exercise environment.

[1009] Input and Output: Input includes data about the user's goal weight, goal body shape, amount of time available to exercise, and exercise environment. The output is a dataset of this information.

[1010] What it does: The user enters information using sliders and checkboxes within the app. Each time the information is entered, a dataset is generated.

[1011] Step 2: Send and save information

[1012] Specific explanation: The terminal sends the input information to the server, and the server stores the received information in a database.

[1013] Input and Output: Input is the data entered by the user into the terminal, and output is the data stored in the server's database.

[1014] Specific operation: The device sends data to the server over the network, and the server executes an SQL query to store the received data in a database.

[1015] Step 3: Create a diet menu

[1016] Specific explanation: The server generates an optimal diet menu based on the user information stored in the database.

[1017] Input and Output: The input is the user information in the database, and the output is the generated diet menu.

[1018] Specific operation: The server pulls user information from a database, runs an algorithm based on that information, and generates a customized diet menu.

[1019] Step 4: Submit the menu

[1020] Specific explanation: The server sends the generated diet menu to the user's terminal.

[1021] Input and Output: The input is the generated diet menu, and the output is the menu sent to the user's terminal.

[1022] Specific operation: The server pushes the generated diet menu to the user's device, which receives the notification and displays it within the app.

[1023] Step 5: Record the implementation status

[1024] Specifically, users record their daily exercise and dietary habits in the app, and the device sends the data to the server.

[1025] Input and Output: The input is the exercise and diet data recorded by the user, and the output is the performance status data sent to the server.

[1026] Specific operation: Users record their daily exercise time and calorie intake within the app, and when they press the save button, the data is sent to the server.

[1027] Step 6: Evaluate your progress

[1028] Specifically, the server stores the received data in a database and evaluates the progress, which is a numerical representation of the user's progress toward their goal.

[1029] Inputs and Outputs: Inputs are implementation status data and outputs are progress assessment results.

[1030] Specific operation: The server analyzes the implementation status data in the database and calculates the progress using an algorithm.

[1031] Step 7: Generate a message

[1032] Specifically, the server generates messages of encouragement and support based on the progress and sends them to the user's device.

[1033] Input and Output: The input is the progress evaluation result and the output is the generated message.

[1034] Specific operation: The server generates an appropriate message based on the evaluation results and sends it to the user's device as a push notification or in-app message.

[1035] Step 8: Generate a progress report

[1036] Specifically, the server periodically generates progress reports and sends them to the user's terminal.

[1037] Inputs and Outputs: Inputs are implementation data and evaluation results, and outputs are progress reports.

[1038] Specific operation: The server compiles user data at regular intervals, generates a report visually represented as graphs and numbers, and sends it to the user's device.

[1039] Step 9: Generate Alternate Menus

[1040] Specific Description: If the user does not reach the goal, the server calculates a new approach, generates an alternative diet menu, and sends it to the user's terminal.

[1041] Input and Output: The input is the progress assessment results and past records, and the output is the newly generated substitution menu.

[1042] Specific operation: The server reanalyzes the evaluation results and past data, generates a new exercise and meal plan, and presents it to the user.

[1043] Step 10: Emotional state analysis and feedback

[1044] Specific Description: The server uses an emotion engine means to recognize the user's emotional state based on input data and biosensor information, and provides feedback.

[1045] Input and output: The input is the user's recorded data and biometric information, and the output is the emotion recognition results and feedback messages based on them.

[1046] Specific operation: The server analyzes the user's input data and sensor information, runs an algorithm to recognize the emotional state, and generates appropriate feedback messages and sends them to the user's device.

[1047] (Application example 2)

[1048] 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."

[1049] Conventional diet support systems provide optimal menus based on information such as the user's target weight and exercise time, but lack feedback that takes the user's emotional state into consideration. This can lead to problems such as a decrease in user motivation and difficulty in continuing the diet. Therefore, the present invention aims to provide a system that analyzes the user's emotional state and provides optimal meal menus and encouraging messages based on that state.

[1050] 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.

[1051] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, and a means for analyzing the user's emotional state using an emotion engine and providing a meal menu and feedback messages based on that state, thereby enabling optimal diet support that takes the user's emotional state into consideration.

[1052] A "personal weight goal" is a body weight goal that a user wishes to achieve.

[1053] The "target body shape" is the ideal body shape or physical condition that the user aims for.

[1054] "Available time" refers to the amount of time a user can devote to dieting and exercise.

[1055] The "environment" refers to the specific location or situation where the user diets or exercises.

[1056] A "user interface means" is a means by which a user inputs information into a system.

[1057] "Database Means" means means for storing and managing user information and records.

[1058] The "algorithm means" is a means for calculating the optimal diet menu based on user information.

[1059] "Communication means" refers to a means for transmitting the generated diet menu and feedback to the user terminal.

[1060] The "evaluation means" is a means for evaluating the progress of the user based on the user's daily exercise and diet records.

[1061] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation.

[1062] The "report generation means" is a means for creating periodic progress reports based on the user's progress data.

[1063] The "substitute menu generating means" is a means for generating a new diet menu when the user is unable to achieve their goal.

[1064] An "emotion engine" is a means for analyzing a user's emotional state and providing feedback based on that state.

[1065] A "meal menu" is a specific meal plan proposed to suit the user's diet goals.

[1066] "Feedback messages" are encouraging messages or advice provided based on the user's progress or emotional state.

[1067] 1. System Overview

[1068] The present invention is a system that provides an optimal diet menu based on information on an individual's target weight, target body shape, available time, and environment, and provides feedback while taking into account the user's emotional state. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[1069] 2. Hardware and Software Used

[1070] Hardware: Smartphones, servers (physical or cloud-based)

[1071] software:

[1072] Smartphone application (iOS, Android)

[1073] Application Server:Flask (Python)

[1074] Database: PostgreSQL

[1075] Emotion Engine: Google Cloud Natural Language API

[1076] Communication: HTTP / HTTPS (requests library)

[1077] 3. User Interface Methods

[1078] Users input information about their target weight, body shape, available time, and exercise environment through a smartphone application. This information is designed to be input intuitively. The data entered by the user is sent to a server and stored in a database.

[1079] 4. Algorithmic Means

[1080] The server generates an optimal diet menu based on the user information stored in the database. The algorithm customizes the diet and exercise menu based on the user's lifestyle and goals. The generated menu is then sent to the user's smartphone via communication means.

[1081] 5. Evaluation and Emotion Engine Methods

[1082] The user records daily exercise and diet data in the smartphone application. This data is sent to the server and stored in a database. The evaluation means analyzes the user's progress, and the emotion engine means analyzes the user's emotional state.

[1083] 6. Message Generation and Report Generation Methods

[1084] The server generates supportive and encouraging messages based on the evaluation results and the user's emotional state and sends them to the user's device. It also periodically generates progress reports and sends them to the user's device. For example, if the user is feeling stressed, the server generates a message saying, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[1085] 7. Alternative Menu Generation Methods

[1086] If the user does not achieve the goal, the server generates an alternative diet menu and sends it to the user's terminal. This alternative menu is generated taking into account the user's past records and evaluation results.

[1087] 8. Examples of concrete examples and prompts

[1088] For example, when user "A" uses the app to input his / her target weight and exercise environment, the system suggests an optimal meal menu and exercise plan. A records his / her daily progress and sends the data to the server. The emotion engine analyzes A's emotional state and sends messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[1089] Example prompt sentence:

[1090] "Emodish is a personalized food delivery service based on the user's diet goals and emotional state. It proposes optimal meal plans based on the user's input of target weight and exercise time, and uses an emotion engine to analyze the user's emotional state and provide appropriate feedback."

[1091] In this way, the system of the present invention can take into account the user's emotional state and provide individually tailored feedback and support, further increasing the success rate of dieting.

[1092] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1093] Step 1:

[1094] Users use a smartphone application to input information about their target weight, body shape, available time, and exercise environment.

[1095] Input: Target weight, target body shape, available time, exercise environment

[1096] Output: User information entered (JSON format)

[1097] Specific behavior: The user enters the required information into the input form and presses the "Submit" button.

[1098] Step 2:

[1099] The entered information is sent from the terminal to the server, and the server stores the received information in a database.

[1100] Input: User information in JSON format

[1101] Output: User information stored in the database

[1102] Specific behavior: The server receives the HTTP request and writes the information to the database.

[1103] Step 3:

[1104] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database.

[1105] Input: User information stored in the database

[1106] Output: Optimal diet menu

[1107] What it does: The server runs an algorithm to calculate a diet menu based on the user's lifestyle and goals.

[1108] Step 4:

[1109] The generated diet menu is sent from the server to the user's terminal.

[1110] Enter: Optimal Diet Menu

[1111] Output: Diet menu displayed on the user's device

[1112] Specific operation: The server sends a diet menu as an HTTP response, and the user's device receives and displays it.

[1113] Step 5:

[1114] Users record their daily exercise and dietary habits in the app, and the data is sent to a server.

[1115] Input: Daily exercise and dietary habits

[1116] Output: Recorded data stored on the server

[1117] Specific behavior: The user uses the app's recording function and the data they enter is sent to the server.

[1118] Step 6:

[1119] The server stores this in a database and evaluates the progress using an evaluation means.

[1120] Input: Saved recording data

[1121] Output: Evaluation results (progress)

[1122] What happens: The server analyzes the recorded data and calculates the progress towards the goal.

[1123] Step 7:

[1124] The server generates a message of encouragement or support based on the evaluation result and transmits it to the user's terminal.

[1125] Input: Evaluation result

[1126] Output: A message of encouragement or support

[1127] Specific operation: The server uses the generative AI model to create a message and send it to the user's device.

[1128] Step 8:

[1129] The server periodically generates progress reports and sends them to the user's terminal.

[1130] Input: Evaluation results and recorded data

[1131] Output: Progress report

[1132] Specific operation: The server creates a progress report and periodically sends it to the user's terminal.

[1133] Step 9:

[1134] An emotion engine is used to recognize the user's emotional state and provide feedback messages based on that state.

[1135] Input: User recorded data and information from biometric sensors

[1136] Output: Feedback message based on emotion

[1137] Specific operation: The server uses the emotion engine to analyze the emotional state and generates and sends a message accordingly.

[1138] Step 10:

[1139] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu to present to the user.

[1140] Input: Past records and evaluation results

[1141] Output: New diet menu

[1142] Specific operation: The server re-runs the algorithm and sends the alternative diet menu to the user's device.

[1143] 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.

[1144] 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.

[1145] 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.

[1146] [Third embodiment]

[1147] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1148] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1149] 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).

[1150] 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.

[1151] 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.

[1152] 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).

[1153] 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.

[1154] 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.

[1155] 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.

[1156] 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.

[1157] 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.

[1158] 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."

[1159] To practice the present invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, and an alternative menu generation means.

[1160] User Interface Means

[1161] A user uses a smartphone app to set goals for a diet plan. The app provides an interface for the user to input information about their goal weight, body shape, available time, and exercise environment (e.g., home, gym). This allows for personalized input of information.

[1162] Database Means

[1163] The entered user information is sent from the terminal to the server, and the server stores the received information in a database that contains information such as the user ID, target weight, target body shape, available time, and environmental information.

[1164] Algorithmic means

[1165] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This algorithm customizes exercise and meal plans based on the user's lifestyle and goals. For example, a plan combining 30 minutes of light aerobic exercise and strength training per day is generated. The generated diet menu is sent to the user's device in JSON format.

[1166] communication means

[1167] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu according to their daily progress.

[1168] Evaluation methods

[1169] The user records their daily exercise and dietary habits in the app. For example, they input the duration of their exercise and the calories they ingest, and the device sends this information to the server. The server stores the received records in a database and evaluates their progress. This evaluation quantifies the user's progress toward their goals and their persistence.

[1170] Message Generation Method

[1171] The server generates a message of encouragement or support based on the evaluation results. For example, it sends positive feedback such as "You did a great job today!" or an encouraging message such as "It may have been difficult today, but I'm sure you can do it tomorrow!" This helps to maintain the user's motivation.

[1172] Report Generation Method

[1173] The server periodically compiles the user's progress data and generates a report, which includes information such as the level of achievement, total exercise time, and calorie intake. This report is sent to the user's device, allowing the user to check their progress.

[1174] Alternative Menu Generation Methods

[1175] If the user does not reach their goal, the server analyzes the information and generates an alternative approach, such as changing their exercise routine or revising their meal plan, to create a new diet menu. This menu is also sent to the user's device, allowing the user to try a new approach.

[1176] Specific examples

[1177] For example, suppose user "C" sets his target weight at 60 kg, the amount of time he can devote to it per day at home, and his preferred exercise environment. C enters and sends this information through the app. The server receives C's information and stores it in a database. The server then generates the optimal diet menu for C. For example, it could generate a menu that combines 40 minutes of jogging and abdominal exercises per day. This is sent to C's device, and C follows the displayed menu.

[1178] C records his daily exercise and meals in the app, and his device sends that information to the server. The server evaluates C's progress and sends encouraging messages such as "You did a great job today!" This way, C can maintain his motivation and continue his diet.

[1179] If C does not reach his / her goal, the server will generate a new approach and suggest a new menu with a modified exercise program, for example, so that C can continue his / her diet in a new way.

[1180] In this way, the present invention functions as a system that supports users in succeeding in dieting.

[1181] The processing flow will be explained below.

[1182] Step 1:

[1183] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[1184] Step 2:

[1185] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[1186] Step 3:

[1187] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[1188] Step 4:

[1189] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[1190] Step 5:

[1191] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[1192] Step 6:

[1193] Users record their daily exercise and dietary habits in the app. The device then sends the recorded data in JSON format to the server. This data includes exercise time, calories burned, calories ingested, etc.

[1194] Step 7:

[1195] The server stores the received daily record data in a database and runs an algorithm to evaluate progress, including the user's progress toward goals, achievement rate, and retention rate.

[1196] Step 8:

[1197] Based on the progress evaluation results, the server generates feedback messages to keep the user motivated. These messages include encouragement and encouragement and are sent to the terminal.

[1198] Step 9:

[1199] The server periodically compiles the progress data and generates a progress report, which includes the progress level, total exercise time, and calorie intake trend, and is sent to the device.

[1200] Step 10:

[1201] If the user does not reach their goal, the server analyzes the data and generates an alternative diet menu, which could include changing the exercise routine or revising the meal plan. The alternative menu is then sent to the device, allowing the user to try a new approach.

[1202] Through this series of steps, the system of the present invention can provide a diet plan that suits the user and provide continuous support, thereby increasing the success rate of dieting.

[1203] Example 1

[1204] 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."

[1205] Conventional diet plans often have a one-size-fits-all approach, failing to fully address individual users' lifestyles and goals. As a result, it's difficult for users to find the plan that's best for them and maintain their motivation. Furthermore, insufficient progress management, evaluation, and follow-up make it difficult to provide appropriate feedback or alternative plans if users don't reach their goals. In addition, there are technical challenges, such as secure data transmission and the efficiency of plan generation.

[1206] 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.

[1207] In this invention, the server includes a user interface for inputting information about an individual's goal weight, goal body shape, available time, and environment, a database for storing the user information, an algorithm for generating an optimal exercise and meal plan for each individual based on the user information, a communication means for transmitting the generated exercise and meal plan to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating supportive or encouraging messages based on the evaluation means and transmitting them to the user terminal, a report generation means for periodically generating progress reports based on the progress and transmitting them to the user terminal, an alternative plan generation means for generating an alternative exercise and meal plan if the goal is not achieved and transmitting them to the user terminal, a communication security means for securely communicating the information and progress status entered by the user, and a data formatting means for transmitting the generated plan, message, and report in JSON format. This enables the server to provide an optimal diet plan for each individual user, manage the progress, send supportive messages, generate periodic reports, and suggest alternative plans if the goal is not achieved.

[1208] "User interface means" refers to means that provides an interface for an individual to input information regarding the target weight, the target body shape, the amount of time available, and the exercise environment.

[1209] The "database means" is a database system for storing and managing information input by the user.

[1210] "Algorithmic means" refers to computational means for generating a personalized optimal exercise and diet plan based on stored user information.

[1211] "Communication means" refers to the communication protocols and infrastructure for transmitting the generated exercise and meal plan to the user terminal.

[1212] The "evaluation means" is a means for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[1213] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[1214] The "report generating means" is a means for periodically generating a progress report based on the progress and transmitting the report to the user terminal.

[1215] The "alternative plan generating means" is a means for generating an alternative exercise and meal plan when the goal is not achieved, and transmitting the plan to the user terminal.

[1216] "Communication security measures" are security protocols and techniques for securely communicating user-entered information and progress.

[1217] "Data Format Means" means the data format and means for sending and receiving generated plans, messages, and reports in JSON format.

[1218] In order to implement the present invention, the following means and processes must be utilized: The system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative plan generation means, a communication security means, and a data formatting means.

[1219] User Interface Means

[1220] Users use a smartphone app to input information about their personal goal weight, body shape, available time, and exercise environment (home, gym, etc.). The app was developed using Flutter, allowing users to input information intuitively.

[1221] Database Means

[1222] The entered user information is sent from the device to the server, which then stores it in a MySQL database, including the user ID, target weight, target body shape, available time, and exercise environment.

[1223] Algorithmic means

[1224] The server uses a Python-based algorithm to generate personalized exercise and diet plans based on the user's saved information, such as a plan that combines 30 minutes of aerobic exercise and strength training per day to suit the user's goals and lifestyle.

[1225] communication means

[1226] The generated exercise and meal plan is sent to the user's device in JSON format, and this communication is securely performed using the HTTPS protocol.

[1227] Evaluation methods

[1228] Users record their daily exercise and dietary habits in the app, such as the duration of exercise, calories burned, and the types and calories of food they ingest. This information is then sent from the device to the server, where it is stored in a database and progress is evaluated using an evaluation algorithm implemented in Python.

[1229] Message Generation Method

[1230] The server generates encouraging and supportive messages based on the progress assessment, using NLP techniques and generative AI models (e.g., GPT-3). Generated messages include "You did a great job today!" and "Today may have been difficult, but I'm sure you can do it tomorrow!"

[1231] Report Generation Method

[1232] The server periodically collects the user's progress data and generates a PDF report containing information such as progress, total exercise time, and calorie intake. The report is then sent to the user's device.

[1233] Alternative plan generation methods

[1234] If the user does not reach their goal, the server analyzes the progress data and offers a new approach, for example, generating a new plan with modified exercise content. This plan is also generated in JSON format and sent to the user's device.

[1235] Communications Security Measures

[1236] The HTTPS protocol is used to securely transmit user input information and progress, ensuring data safety and privacy.

[1237] Data Formatting Method

[1238] It is a means of sending and receiving generated exercise and meal plans, messages, and reports in JSON format. Using the JSON format structured data makes it easy to exchange various information.

[1239] Specific examples

[1240] For example, user "C" inputs a goal weight of 60 kg, 40 minutes of exercise per day, and training at home. The device sends the following data to the server: {"Goal weight": "60 kg", "Exercise time": "40 minutes per day", "Environment": "Home"}. The server saves this data and uses an algorithm to generate a plan of "40 minutes of jogging and sit-ups per day" and sends it to the device.

[1241] Example of an input prompt for a generative AI model:

[1242] Generate an optimal diet plan based on user-specified information. Use the following information:

[1243] Target weight: 60kg

[1244] Available time: 40 minutes per day

[1245] Exercise environment: Home

[1246] Please suggest a plan that combines jogging and abdominal exercises.

[1247] In this way, the present invention functions as a system that provides high-level support for users to succeed in dieting.

[1248] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1249] Program processing flow

[1250] Step 1:

[1251] The user opens the app and inputs their target weight, body shape, available time, and exercise environment. The input information is retrieved from the smartphone app's UI.

[1252] input:

[1253] Target weight

[1254] Target body shape

[1255] Time available

[1256] exercise environment

[1257] output:

[1258] User information in JSON format

[1259] Specific behavior:

[1260] User "A" inputs his / her goal weight of 60kg, his / her goal body shape, 40 minutes of exercise per day, and home workouts into the app. The app structures this information in JSON format and generates the following JSON data, for example:

[1261] json

[1262] {

[1263] "Goal Weight": "60kg",

[1264] "Target Body Type": "Slim",

[1265] "Time available": "40 minutes a day",

[1266] "Exercise environment": "Home"

[1267] }

[1268] Step 2:

[1269] The device sends the entered information to the server. This communication is carried out using the HTTPS protocol.

[1270] input:

[1271] User information in JSON format

[1272] output:

[1273] User information sent to the server

[1274] Specific behavior:

[1275] The terminal sends the aforementioned JSON data to the server using the HTTPS protocol. The data received on the server side is

[1276] json

[1277] {

[1278] "Goal Weight": "60kg",

[1279] "Target Body Type": "Slim",

[1280] "Time available": "40 minutes a day",

[1281] "Exercise environment": "Home"

[1282] }

[1283] Step 3:

[1284] The server stores the received information in a database.

[1285] input:

[1286] User information sent to the server

[1287] output:

[1288] User information stored in a database

[1289] Specific behavior:

[1290] The server parses the received JSON data and stores it in a MySQL database. For example, it executes the following SQL statement to store the data:

[1291] sql

[1292] INSERT INTO users (user_id, goal_weight, goal_shape, exercise_time, environment)

[1293] VALUES ("A's ID", "60kg", "Slim", "40 minutes a day", "Home");

[1294] Step 4:

[1295] The server uses an algorithm to generate an optimal diet menu based on the stored user information. This algorithm is implemented in Python.

[1296] input:

[1297] User information stored in a database

[1298] output:

[1299] Diet menu in JSON format

[1300] Specific behavior:

[1301] The server retrieves user information from the MySQL database and uses an algorithm to generate an optimal diet menu, such as "40 minutes of jogging and sit-ups a day." The generated menu is the following JSON data:

[1302] json

[1303] {

[1304] "exercise": "jogging and sit-ups",

[1305] "duration": "40 minutes a day",

[1306] "detailed_plan": ["20 minutes of jogging", "20 minutes of sit-ups"]

[1307] }

[1308] Step 5:

[1309] The server sends the generated diet menu to the terminal.

[1310] input:

[1311] Diet menu in JSON format

[1312] output:

[1313] Diet menu sent to the user's device

[1314] Specific behavior:

[1315] The server sends the JSON data to the user's device using the HTTPS protocol. The generated menu is displayed on the user's device.

[1316] Step 6:

[1317] The user uses the app to record their daily exercise and dietary habits, for example, by entering the duration of exercise, calories burned, and the types and calories of food consumed.

[1318] input:

[1319] Daily exercise and dietary habits

[1320] output:

[1321] Execution status data in JSON format

[1322] Specific behavior:

[1323] User "A" jogs for 20 minutes and does sit-ups for 20 minutes, and records this information in the app. The app generates the following JSON data:

[1324] json

[1325] {

[1326] "jogging": "20 minutes",

[1327] "Sit-ups": "20 minutes"

[1328] }

[1329] Step 7:

[1330] The terminal transmits the execution status data to the server.

[1331] input:

[1332] Execution status data in JSON format

[1333] output:

[1334] Execution status data sent to the server

[1335] Specific behavior:

[1336] The terminal sends the above JSON data to the server. The data received by the server is

[1337] json

[1338] {

[1339] "jogging": "20 minutes",

[1340] "Sit-ups": "20 minutes"

[1341] }

[1342] Step 8:

[1343] The server receives execution status data, stores it in a database, and evaluates the progress. This evaluation is implemented in Python.

[1344] input:

[1345] Execution status data sent to the server

[1346] output:

[1347] Progress evaluation results

[1348] Specific behavior:

[1349] The server stores the received data in a MySQL database and runs a Python script to evaluate progress, generating results such as "Today's achievement rate is 80%."

[1350] Step 9:

[1351] The server generates supportive and encouraging messages based on the evaluation results, using a generative AI model.

[1352] input:

[1353] Progress evaluation results

[1354] output:

[1355] Messages of support or encouragement

[1356] Specific behavior:

[1357] Based on the evaluation results, the server uses a generative AI model to generate messages such as "You worked hard today!" or "You can do better tomorrow!"

[1358] Step 10:

[1359] The server generates a message and sends it to the user's terminal.

[1360] input:

[1361] Messages of support or encouragement

[1362] output:

[1363] Message sent to user device

[1364] Specific behavior:

[1365] The server sends the generated message to the user's device using the HTTPS protocol, and user "A" receives the message in the app.

[1366] Step 11:

[1367] The server periodically aggregates user progress data and generates reports, which are generated using Python and ReportLab.

[1368] input:

[1369] User progress data

[1370] output:

[1371] Progress report in PDF format

[1372] Specific behavior:

[1373] The server will compile your progress data weekly and generate a PDF report containing the following:

[1374] Achievement level: 80%

[1375] Total exercise time: 280 minutes

[1376] Calorie intake trend: Stable

[1377] Step 12:

[1378] The server sends the generated report to the user's terminal.

[1379] input:

[1380] Progress report in PDF format

[1381] output:

[1382] Reports sent to user devices

[1383] Specific behavior:

[1384] The server sends the report in PDF format to the user's device, and user "A" checks the report in the app.

[1385] Step 13:

[1386] The server generates alternative plans as needed and sends them to the user's device, also in JSON format.

[1387] input:

[1388] User history and ratings

[1389] output:

[1390] New exercise and meal plans in JSON format

[1391] Specific behavior:

[1392] If user "A" does not reach his / her goal, the server analyzes past records, generates a new plan such as "20 minutes of brisk walking and plank exercises per day," and sends it to the user's terminal.

[1393] In this way, the system of the present invention uses various means to provide high support for the user's successful dieting.

[1394] (Application example 1)

[1395] 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."

[1396] Conventional diet support systems lack real-time feedback to help users train efficiently toward their set goals. Also, because it is difficult to maintain accurate training form, there is a high risk of injury due to improper form. Furthermore, users often lose motivation and have difficulty achieving their goals because they rely solely on self-evaluation to manage their progress.

[1397] 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.

[1398] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, an interface means for displaying the generated diet menu through smart glasses and providing real-time training assistance, and a motion sensor means for detecting movements during training and displaying instructions for maintaining correct form. This allows the user to receive real-time feedback, train safely with proper form, and effectively diet while maintaining motivation.

[1399] The "user interface means" is an interface for inputting information regarding an individual's target weight, target body shape, available time, and environment.

[1400] The "database means" is a storage system for storing the user information.

[1401] The "algorithm means" is a calculation method for generating an optimal diet menu for each individual based on the user information.

[1402] The "communication means" is a communication device for transmitting the generated diet menu to the user terminal.

[1403] The "evaluation means" is a method for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[1404] The "message generating means" is a device for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[1405] The "report generating means" is a device for generating a progress report periodically based on the progress and transmitting the report to the user terminal.

[1406] The "alternative menu generating means" is a device for generating an alternative diet menu when the goal is not achieved and transmitting it to the user terminal.

[1407] The "interface means" is an interface for displaying the generated diet menu through smart glasses and providing real-time training assistance.

[1408] The "motion sensor means" is a device that detects movements during training and displays instructions to help maintain correct form.

[1409] To practice this invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, an interface means, and a motion sensor means.

[1410] User Interface Means

[1411] Through the smart glasses, users input information about their target weight, target body shape, available time, and exercise environment (home, gym, etc.). This information is input via an interface displayed on the smart glasses' display.

[1412] Database Means

[1413] The entered user information is sent to the server and stored in a database, which includes information such as the user ID, target weight, target body shape, available time, and exercise environment.

[1414] Algorithmic means

[1415] The server is equipped with an algorithm that generates an optimal diet menu based on the user information stored in the database. This algorithm uses TensorFlow, for example, to generate an individually customized diet plan.

[1416] communication means

[1417] The generated diet menu is sent from the server to the smart glasses, where the user can review and follow it.

[1418] Evaluation methods

[1419] Users enter their daily exercise and diet records through the smart glasses. These records are then sent back to the server, where progress is assessed using an assessment tool. The assessment results are quantified to show the degree of achievement and continuity.

[1420] Message Generation Method

[1421] Based on the evaluation results, the server generates a message of encouragement or encouragement and sends it to the smart glasses, thereby maintaining the user's motivation.

[1422] Report Generation Method

[1423] The server periodically aggregates the user's progress data and generates progress reports that are sent to the user so that they can view their progress.

[1424] Alternative Menu Generation Methods

[1425] If the user does not reach their goal, the server will take into account past records and evaluations and generate a new diet menu, which will also be sent to the smart glasses.

[1426] Interface Means

[1427] The smart glasses visually display the generated diet menu and provide real-time assistance during training.

[1428] Motion Sensor Means

[1429] The smart glasses' built-in motion sensors detect movements during training and provide real-time guidance to help maintain proper form.

[1430] Specific examples

[1431] For example, user "A" sets a target weight of 70 kg, 30 minutes of training time per day, and a gym as the exercise environment. A uses smart glasses to input this information. The server receives A's information, generates an optimal diet plan, and sends it to the smart glasses. A trains according to the menu displayed on the smart glasses. During training, a motion sensor checks the form and displays correction instructions as needed. A also records their daily training and meals, which are sent to the server. The server evaluates the data and sends encouraging messages such as "You did a great job today!"

[1432] Using a generative AI model, the following prompt is generated:

[1433] "User name: A

[1434] Target weight: 70kg

[1435] Time available: 30 minutes a day

[1436] Exercise environment: Gym

[1437] This allows users to receive real-time feedback, train safely and effectively, and stay motivated to achieve their goals.

[1438] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1439] Step 1:

[1440] The user inputs information about their target weight, body shape, available time, and exercise environment through the smart glasses interface. The input information is temporarily stored inside the smart glasses and prepared for transmission to the server.

[1441] Input: Goal and environment information input by the user through smart glasses

[1442] Output: Temporarily saved user information

[1443] Step 2:

[1444] The smart glasses send the entered user information to the server, which receives the information and stores it in a database.

[1445] Input: User information sent from smart glasses

[1446] Output: User information stored in the database

[1447] Step 3:

[1448] The server passes the user information stored in the database to an algorithm that generates the optimal diet menu based on the user's lifestyle and goals. This is done using machine learning models such as TensorFlow.

[1449] Input: User information stored in the database

[1450] Output: Generated diet menu

[1451] Step 4:

[1452] The generated diet menu is sent from the server to the smart glasses, which then display it to the user, providing a visual of the training content.

[1453] Input: Diet menu sent from the server

[1454] Output: Diet menu displayed on smart glasses

[1455] Step 5:

[1456] The user performs training according to the display on the smart glasses. The smart glasses' built-in motion sensors detect training movements and provide guidance on maintaining correct form. Incorrect form is pointed out in real time and correction instructions are displayed.

[1457] Input: User training behavior

[1458] Output: Data detected by the motion sensor, correction instructions

[1459] Step 6:

[1460] Users enter their daily training and diet records and send them via smart glasses to a server, which then receives and evaluates their progress data.

[1461] Input: User-entered training and meal logs

[1462] Output: Progress data stored on the server

[1463] Step 7:

[1464] The server analyzes the progress data based on the evaluation method, quantifies the achievement level and continuity, and generates messages of encouragement and support, which are sent to the smart glasses.

[1465] Input: Progress data

[1466] Output: Evaluation results, generated cheering message

[1467] Step 8:

[1468] The server periodically generates and sends progress reports for the user to the smart glasses, allowing the user to view their progress.

[1469] Input: Past progress data

[1470] Output: Generated progress report

[1471] Step 9:

[1472] If the goal is not achieved, the server uses past records and evaluation data to generate an alternative diet menu and transmits it to the smart glasses, where the user can then implement the new menu.

[1473] Input: Historical records and evaluation data

[1474] Output: Alternative diet menu

[1475] The above is a specific process flow for implementing this invention. At each step, data is exchanged between the smart glasses and the server, and training and feedback are effectively carried out to help the user achieve their goals.

[1476] 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.

[1477] To implement the present invention, it is necessary to consider a configuration that combines a conventional system with an emotion engine means. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[1478] User Interface Means

[1479] Users use a smartphone app to input information about their target weight, body shape, available time, and exercise environment, which provides an intuitive interface to facilitate detailed input of user information.

[1480] Database Means

[1481] The input information is sent from the device to the server, which then stores it in a database, including the user ID, target weight, target body shape, available time, and exercise environment.

[1482] Algorithmic means

[1483] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database, which is customized to the user's lifestyle and goals.

[1484] communication means

[1485] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu to manage their exercise and diet.

[1486] Evaluation methods

[1487] Users record their daily exercise and dietary habits in the app, and the device sends the data to the server. The server stores the data in a database and evaluates the progress using an evaluation tool. The evaluation is a numerical representation of the user's progress toward their goals.

[1488] Message Generation Method

[1489] The server generates encouraging or supportive messages based on the evaluation results, providing the necessary feedback to keep the user motivated.

[1490] Report Generation Method

[1491] The server periodically generates a progress report and sends it to the user's device, which includes information such as progress, total exercise time, and calorie intake.

[1492] Alternative Menu Generation Methods

[1493] If the user does not reach the goal, the server runs an algorithm to generate a new approach and sends an alternative menu to the user's terminal.

[1494] Emotion Engine Means

[1495] The emotion engine recognizes the user's emotional state based on the user's input data. This emotion engine analyzes the user's recorded data and information acquired from the biometric information sensor to determine the user's emotional state. For example, it can analyze the level of stress or satisfaction.

[1496] Specific examples

[1497] User "D" starts the app and inputs information about his / her target weight, target body shape, available time, and exercise environment (home). The input information is sent from the device to the server and stored in a database. The server uses this information to generate an optimal diet menu for D and sends it to D's device. For example, it generates a plan that combines 30 minutes of jogging and abdominal exercises per day.

[1498] Person D records his / her daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates his / her progress and sends him / her messages of encouragement and support. Furthermore, the server recognizes Person D's emotional state using an emotion engine means and sends him / her messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax," further increasing his / her motivation.

[1499] If D does not reach his goal, the server calculates a new approach and generates an alternative diet menu to present to D. This allows D to continue his diet with a new approach.

[1500] Through this series of processes, the system of the present invention also takes into account the user's emotional state and provides individually tailored feedback and support, further increasing the success rate of dieting.

[1501] The processing flow will be explained below.

[1502] Step 1:

[1503] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[1504] Step 2:

[1505] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[1506] Step 3:

[1507] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[1508] Step 4:

[1509] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[1510] Step 5:

[1511] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[1512] Step 6:

[1513] Users record their daily exercise and dietary habits in the app, for example by entering the duration of exercise and the calories they consume. The device then sends this data in JSON format to the server.

[1514] Step 7:

[1515] The server stores the received daily record data in a database and evaluates the progress using an evaluation tool, including the progress, achievement rate, and continuation rate of the user toward their goal.

[1516] Step 8:

[1517] Based on the progress evaluation, the server generates messages of encouragement and support to keep the user motivated, such as "You did a great job today!" or "You'll do better tomorrow!"

[1518] Step 9:

[1519] The emotion engine means analyzes the user's input data and the data from the biometric sensor to recognize the user's emotional state, for example, to identify when the user is feeling stressed or has low motivation.

[1520] Step 10:

[1521] The server generates a customized message according to the user's emotional state obtained from the emotion engine means, for example, a message such as "You seem to be feeling a bit stressed today. Take a deep breath and relax."

[1522] Step 11:

[1523] The server generates periodic progress reports and sends them to the user's device. These reports include the level of achievement, the total exercise time, and the trend of calorie intake, allowing the user to check their own progress.

[1524] Step 12:

[1525] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu, which may include changing the exercise routine or revising the meal plan. The generated alternative menu is sent to the device, allowing the user to try a new approach.

[1526] Through this series of steps, the system of the present invention provides a diet plan tailored to the user and provides continuous and personalized support while taking into account their emotional state, thereby increasing the success rate of dieting.

[1527] Example 2

[1528] 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."

[1529] Conventional diet support systems only provide feedback based on the user's physical information and activity data. However, they lack support tailored to the user's motivation and psychological state, resulting in low rates of continuity and success in diet plans. In addition, because they do not take the user's emotional state into account, stress and frustration tend to accumulate, making it difficult to generate optimal diet menus. The objective of this invention is to solve this problem.

[1530] 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.

[1531] In this invention, the server includes input means for inputting information regarding an individual's target weight, target body shape, available time, and environment, storage means for storing the user information, generation means for generating an individually optimized menu based on the user information, transmission means for transmitting the generated menu to the user device, evaluation means for receiving a record of daily progress and evaluating progress based on the record, generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user device, reporting means for periodically generating a progress report based on the progress and transmitting it to the user device, alternative generation means for generating an alternative menu if the target is not achieved and transmitting it to the user device, and recognition means for recognizing the user's emotional state from the input data and biosensor information and providing feedback. This makes it possible to provide individually optimized feedback and support while taking the user's emotional state into consideration, thereby supporting the continuation and success of the diet plan.

[1532] The "input means" is an interface for the user to input information regarding the individual's target weight, target body shape, available time, and environment.

[1533] The "storage means" refers to a function for storing the user information in a database or the like.

[1534] The "generation means" is a function that includes algorithms and processes that create an optimal menu for each user based on the stored user information.

[1535] The "transmission means" refers to a function for transmitting the generated menu or message to the user device.

[1536] The "evaluation means" is a function for receiving records of daily implementation status and evaluating the user's progress based on those records.

[1537] The "generation means" refers to a function for creating cheering messages and the like based on the evaluation means and other data.

[1538] The "reporting means" is a function for periodically generating progress reports based on the progress and transmitting them to the user device.

[1539] The "alternative generation means" refers to a function for generating a new menu and transmitting it to the user device if the target is not achieved.

[1540] The "recognition means" is a function that analyzes the user's emotional state from input data and biosensor information and provides feedback.

[1541] The present invention provides a diet support system that meets the individual needs of users. Below, each element for implementing the present invention and its operation will be described in detail.

[1542] User Interface Means

[1543] Users use a smartphone app to enter information about their target weight, body shape, available time, and exercise environment. The app provides an intuitive interface and is designed to allow users to easily enter information using sliders and checkboxes, allowing users to register their information quickly and accurately.

[1544] Database Means

[1545] The entered information is sent from the terminal to a server, which stores the received information in a database and manages information such as the user's ID, target weight, target body shape, available time, and exercise environment. This database uses a modern database management system (DBMS) to provide fast and reliable data access.

[1546] Algorithmic means

[1547] The server generates an optimal diet menu based on the user's information stored in the database. The algorithm creates a customized menu based on the user's lifestyle and goals. For example, it takes into account the user's individual energy expenditure and preferred food types.

[1548] communication means

[1549] The generated diet menu is sent from the server to the user's device, which then displays the menu to the user as a push notification or in-app message. This allows the user to always check the latest menu information and manage their exercise and diet accordingly.

[1550] Evaluation methods

[1551] Users record their daily exercise and dietary habits in the app. This data is sent from the device to a server, which stores the information in a database. The server evaluates the progress and quantifies how close the user is to achieving their goals. The evaluation results are presented to the user in the form of graphs and statistics.

[1552] Message Generation Method

[1553] The server generates messages of encouragement or support based on the evaluation results. These messages are important as feedback to maintain the user's motivation. The generated messages are sent to the user's device via push notification.

[1554] Report Generation Method

[1555] The server periodically generates progress reports and sends them to the user's device. The reports contain detailed information such as the level of achievement, cumulative exercise time, and calorie intake, and are designed to allow the user to visually check their progress.

[1556] Alternative Menu Generation Methods

[1557] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu, allowing the user to continue with the new approach.

[1558] Emotion Engine Means

[1559] The emotion engine analyzes the user's input data and information from biometric sensors to determine the user's emotional state. Based on this, it provides feedback aimed at reducing stress and increasing motivation. For example, it sends a message such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[1560] Specific examples

[1561] The user launches the smartphone app and inputs their target weight and exercise environment. The input information is sent from the device to the server, which stores it in a database. For example, a plan combining 30 minutes of jogging and sit-ups per day is generated and sent to the user's device.

[1562] Users record their daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates the progress and generates and sends messages of encouragement and support. It also uses an emotion engine to recognize the user's emotional state and send appropriate messages.

[1563] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu to present to the user. Through this series of processes, the system of the present invention provides individually tailored feedback and support while also taking into account the user's emotional state, increasing the success rate of dieting.

[1564] Example of input prompt for generative AI model

[1565] Here are some examples of prompts to input to a generative AI model:

[1566] "Please provide a detailed explanation of each processing step of a diet support system, including the user interface, database, algorithm, communication, evaluation, message generation, report generation, alternative menu generation, and emotion engine means. The subject should be either the server, terminal, or user, and please also include specific operations in the explanation."

[1567] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1568] Step 1: Enter your user information

[1569] Detailed description: The user launches the smartphone app and inputs information about their target weight, target body shape, available time, and exercise environment.

[1570] Input and Output: Input includes data about the user's goal weight, goal body shape, amount of time available to exercise, and exercise environment. The output is a dataset of this information.

[1571] What it does: The user enters information using sliders and checkboxes within the app. Each time the information is entered, a dataset is generated.

[1572] Step 2: Send and save information

[1573] Specific explanation: The terminal sends the input information to the server, and the server stores the received information in a database.

[1574] Input and Output: Input is the data entered by the user into the terminal, and output is the data stored in the server's database.

[1575] Specific operation: The device sends data to the server over the network, and the server executes an SQL query to store the received data in a database.

[1576] Step 3: Create a diet menu

[1577] Specific explanation: The server generates an optimal diet menu based on the user information stored in the database.

[1578] Input and Output: The input is the user information in the database, and the output is the generated diet menu.

[1579] Specific operation: The server pulls user information from a database, runs an algorithm based on that information, and generates a customized diet menu.

[1580] Step 4: Submit the menu

[1581] Specific explanation: The server sends the generated diet menu to the user's terminal.

[1582] Input and Output: The input is the generated diet menu, and the output is the menu sent to the user's terminal.

[1583] Specific operation: The server pushes the generated diet menu to the user's device, which receives the notification and displays it within the app.

[1584] Step 5: Record the implementation status

[1585] Specifically, users record their daily exercise and dietary habits in the app, and the device sends the data to the server.

[1586] Input and Output: The input is the exercise and diet data recorded by the user, and the output is the performance status data sent to the server.

[1587] Specific operation: Users record their daily exercise time and calorie intake within the app, and when they press the save button, the data is sent to the server.

[1588] Step 6: Evaluate your progress

[1589] Specifically, the server stores the received data in a database and evaluates the progress, which is a numerical representation of the user's progress toward their goal.

[1590] Inputs and Outputs: Inputs are implementation status data and outputs are progress assessment results.

[1591] Specific operation: The server analyzes the implementation status data in the database and calculates the progress using an algorithm.

[1592] Step 7: Generate a message

[1593] Specifically, the server generates messages of encouragement and support based on the progress and sends them to the user's device.

[1594] Input and Output: The input is the progress evaluation result and the output is the generated message.

[1595] Specific operation: The server generates an appropriate message based on the evaluation results and sends it to the user's device as a push notification or in-app message.

[1596] Step 8: Generate a progress report

[1597] Specifically, the server periodically generates progress reports and sends them to the user's terminal.

[1598] Inputs and Outputs: Inputs are implementation data and evaluation results, and outputs are progress reports.

[1599] Specific operation: The server compiles user data at regular intervals, generates a report visually represented as graphs and numbers, and sends it to the user's device.

[1600] Step 9: Generate Alternate Menus

[1601] Specific Description: If the user does not reach the goal, the server calculates a new approach, generates an alternative diet menu, and sends it to the user's terminal.

[1602] Input and Output: The input is the progress assessment results and past records, and the output is the newly generated substitution menu.

[1603] Specific operation: The server reanalyzes the evaluation results and past data, generates a new exercise and meal plan, and presents it to the user.

[1604] Step 10: Emotional state analysis and feedback

[1605] Specific Description: The server uses an emotion engine means to recognize the user's emotional state based on input data and biosensor information, and provides feedback.

[1606] Input and output: The input is the user's recorded data and biometric information, and the output is the emotion recognition results and feedback messages based on them.

[1607] Specific operation: The server analyzes the user's input data and sensor information, runs an algorithm to recognize the emotional state, and generates appropriate feedback messages and sends them to the user's device.

[1608] (Application example 2)

[1609] 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."

[1610] Conventional diet support systems provide optimal menus based on information such as the user's target weight and exercise time, but lack feedback that takes the user's emotional state into consideration. This can lead to problems such as a decrease in user motivation and difficulty in continuing the diet. Therefore, the present invention aims to provide a system that analyzes the user's emotional state and provides optimal meal menus and encouraging messages based on that state.

[1611] 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.

[1612] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, and a means for analyzing the user's emotional state using an emotion engine and providing a meal menu and feedback messages based on that state, thereby enabling optimal diet support that takes the user's emotional state into consideration.

[1613] A "personal weight goal" is a body weight goal that a user wishes to achieve.

[1614] The "target body shape" is the ideal body shape or physical condition that the user aims for.

[1615] "Available time" refers to the amount of time a user can devote to dieting and exercise.

[1616] The "environment" refers to the specific location or situation where the user diets or exercises.

[1617] A "user interface means" is a means by which a user inputs information into a system.

[1618] "Database Means" means means for storing and managing user information and records.

[1619] The "algorithm means" is a means for calculating the optimal diet menu based on user information.

[1620] "Communication means" refers to a means for transmitting the generated diet menu and feedback to the user terminal.

[1621] The "evaluation means" is a means for evaluating the progress of the user based on the user's daily exercise and diet records.

[1622] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation.

[1623] The "report generation means" is a means for creating periodic progress reports based on the user's progress data.

[1624] The "substitute menu generating means" is a means for generating a new diet menu when the user is unable to achieve their goal.

[1625] An "emotion engine" is a means for analyzing a user's emotional state and providing feedback based on that state.

[1626] A "meal menu" is a specific meal plan proposed to suit the user's diet goals.

[1627] "Feedback messages" are encouraging messages or advice provided based on the user's progress or emotional state.

[1628] 1. System Overview

[1629] The present invention is a system that provides an optimal diet menu based on information on an individual's target weight, target body shape, available time, and environment, and provides feedback while taking into account the user's emotional state. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[1630] 2. Hardware and Software Used

[1631] Hardware: Smartphones, servers (physical or cloud-based)

[1632] software:

[1633] Smartphone application (iOS, Android)

[1634] Application Server:Flask (Python)

[1635] Database: PostgreSQL

[1636] Emotion Engine: Google Cloud Natural Language API

[1637] Communication: HTTP / HTTPS (requests library)

[1638] 3. User Interface Methods

[1639] Users input information about their target weight, body shape, available time, and exercise environment through a smartphone application. This information is designed to be input intuitively. The data entered by the user is sent to a server and stored in a database.

[1640] 4. Algorithmic Means

[1641] The server generates an optimal diet menu based on the user information stored in the database. The algorithm customizes the diet and exercise menu based on the user's lifestyle and goals. The generated menu is then sent to the user's smartphone via communication means.

[1642] 5. Evaluation and Emotion Engine Methods

[1643] The user records daily exercise and diet data in the smartphone application. This data is sent to the server and stored in a database. The evaluation means analyzes the user's progress, and the emotion engine means analyzes the user's emotional state.

[1644] 6. Message Generation and Report Generation Methods

[1645] The server generates supportive and encouraging messages based on the evaluation results and the user's emotional state and sends them to the user's device. It also periodically generates progress reports and sends them to the user's device. For example, if the user is feeling stressed, the server generates a message saying, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[1646] 7. Alternative Menu Generation Methods

[1647] If the user does not achieve the goal, the server generates an alternative diet menu and sends it to the user's terminal. This alternative menu is generated taking into account the user's past records and evaluation results.

[1648] 8. Examples of concrete examples and prompts

[1649] For example, when user "A" uses the app to input his / her target weight and exercise environment, the system suggests an optimal meal menu and exercise plan. A records his / her daily progress and sends the data to the server. The emotion engine analyzes A's emotional state and sends messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[1650] Example prompt sentence:

[1651] "Emodish is a personalized food delivery service based on the user's diet goals and emotional state. It proposes optimal meal plans based on the user's input of target weight and exercise time, and uses an emotion engine to analyze the user's emotional state and provide appropriate feedback."

[1652] In this way, the system of the present invention can take into account the user's emotional state and provide individually tailored feedback and support, further increasing the success rate of dieting.

[1653] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1654] Step 1:

[1655] Users use a smartphone application to input information about their target weight, body shape, available time, and exercise environment.

[1656] Input: Target weight, target body shape, available time, exercise environment

[1657] Output: User information entered (JSON format)

[1658] Specific behavior: The user enters the required information into the input form and presses the "Submit" button.

[1659] Step 2:

[1660] The entered information is sent from the terminal to the server, and the server stores the received information in a database.

[1661] Input: User information in JSON format

[1662] Output: User information stored in the database

[1663] Specific behavior: The server receives the HTTP request and writes the information to the database.

[1664] Step 3:

[1665] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database.

[1666] Input: User information stored in the database

[1667] Output: Optimal diet menu

[1668] What it does: The server runs an algorithm to calculate a diet menu based on the user's lifestyle and goals.

[1669] Step 4:

[1670] The generated diet menu is sent from the server to the user's terminal.

[1671] Enter: Optimal Diet Menu

[1672] Output: Diet menu displayed on the user's device

[1673] Specific operation: The server sends a diet menu as an HTTP response, and the user's device receives and displays it.

[1674] Step 5:

[1675] Users record their daily exercise and dietary habits in the app, and the data is sent to a server.

[1676] Input: Daily exercise and dietary habits

[1677] Output: Recorded data stored on the server

[1678] Specific behavior: The user uses the app's recording function and the data they enter is sent to the server.

[1679] Step 6:

[1680] The server stores this in a database and evaluates the progress using an evaluation means.

[1681] Input: Saved recording data

[1682] Output: Evaluation results (progress)

[1683] What happens: The server analyzes the recorded data and calculates the progress towards the goal.

[1684] Step 7:

[1685] The server generates a message of encouragement or support based on the evaluation result and transmits it to the user's terminal.

[1686] Input: Evaluation result

[1687] Output: A message of encouragement or support

[1688] Specific operation: The server uses the generative AI model to create a message and send it to the user's device.

[1689] Step 8:

[1690] The server periodically generates progress reports and sends them to the user's terminal.

[1691] Input: Evaluation results and recorded data

[1692] Output: Progress report

[1693] Specific operation: The server creates a progress report and periodically sends it to the user's terminal.

[1694] Step 9:

[1695] An emotion engine is used to recognize the user's emotional state and provide feedback messages based on that state.

[1696] Input: User recorded data and information from biometric sensors

[1697] Output: Feedback message based on emotion

[1698] Specific operation: The server uses the emotion engine to analyze the emotional state and generates and sends a message accordingly.

[1699] Step 10:

[1700] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu to present to the user.

[1701] Input: Past records and evaluation results

[1702] Output: New diet menu

[1703] Specific operation: The server re-runs the algorithm and sends the alternative diet menu to the user's device.

[1704] 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.

[1705] 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.

[1706] 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.

[1707] [Fourth embodiment]

[1708] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1709] 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.

[1710] 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).

[1711] 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.

[1712] 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.

[1713] 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).

[1714] 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.

[1715] 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.

[1716] 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.

[1717] 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.

[1718] 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.

[1719] 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.

[1720] 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."

[1721] To practice the present invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, and an alternative menu generation means.

[1722] User Interface Means

[1723] A user uses a smartphone app to set goals for a diet plan. The app provides an interface for the user to input information about their goal weight, body shape, available time, and exercise environment (e.g., home, gym). This allows for personalized input of information.

[1724] Database Means

[1725] The entered user information is sent from the terminal to the server, and the server stores the received information in a database that contains information such as the user ID, target weight, target body shape, available time, and environmental information.

[1726] Algorithmic means

[1727] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This algorithm customizes exercise and meal plans based on the user's lifestyle and goals. For example, a plan combining 30 minutes of light aerobic exercise and strength training per day is generated. The generated diet menu is sent to the user's device in JSON format.

[1728] communication means

[1729] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu according to their daily progress.

[1730] Evaluation methods

[1731] The user records their daily exercise and dietary habits in the app. For example, they input the duration of their exercise and the calories they ingest, and the device sends this information to the server. The server stores the received records in a database and evaluates their progress. This evaluation quantifies the user's progress toward their goals and their persistence.

[1732] Message Generation Method

[1733] The server generates a message of encouragement or support based on the evaluation results. For example, it sends positive feedback such as "You did a great job today!" or an encouraging message such as "It may have been difficult today, but I'm sure you can do it tomorrow!" This helps to maintain the user's motivation.

[1734] Report Generation Method

[1735] The server periodically compiles the user's progress data and generates a report, which includes information such as the level of achievement, total exercise time, and calorie intake. This report is sent to the user's device, allowing the user to check their progress.

[1736] Alternative Menu Generation Methods

[1737] If the user does not reach their goal, the server analyzes the information and generates an alternative approach, such as changing their exercise routine or revising their meal plan, to create a new diet menu. This menu is also sent to the user's device, allowing the user to try a new approach.

[1738] Specific examples

[1739] For example, suppose user "C" sets his target weight at 60 kg, the amount of time he can devote to it per day at home, and his preferred exercise environment. C enters and sends this information through the app. The server receives C's information and stores it in a database. The server then generates the optimal diet menu for C. For example, it could generate a menu that combines 40 minutes of jogging and abdominal exercises per day. This is sent to C's device, and C follows the displayed menu.

[1740] C records his daily exercise and meals in the app, and his device sends that information to the server. The server evaluates C's progress and sends encouraging messages such as "You did a great job today!" This way, C can maintain his motivation and continue his diet.

[1741] If C does not reach his / her goal, the server will generate a new approach and suggest a new menu with a modified exercise program, for example, so that C can continue his / her diet in a new way.

[1742] In this way, the present invention functions as a system that supports users in succeeding in dieting.

[1743] The processing flow will be explained below.

[1744] Step 1:

[1745] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[1746] Step 2:

[1747] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[1748] Step 3:

[1749] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[1750] Step 4:

[1751] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[1752] Step 5:

[1753] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[1754] Step 6:

[1755] Users record their daily exercise and dietary habits in the app. The device then sends the recorded data in JSON format to the server. This data includes exercise time, calories burned, calories ingested, etc.

[1756] Step 7:

[1757] The server stores the received daily record data in a database and runs an algorithm to evaluate progress, including the user's progress toward goals, achievement rate, and retention rate.

[1758] Step 8:

[1759] Based on the progress evaluation results, the server generates feedback messages to keep the user motivated. These messages include encouragement and encouragement and are sent to the terminal.

[1760] Step 9:

[1761] The server periodically compiles the progress data and generates a progress report, which includes the progress level, total exercise time, and calorie intake trend, and is sent to the device.

[1762] Step 10:

[1763] If the user does not reach their goal, the server analyzes the data and generates an alternative diet menu, which could include changing the exercise routine or revising the meal plan. The alternative menu is then sent to the device, allowing the user to try a new approach.

[1764] Through this series of steps, the system of the present invention can provide a diet plan that suits the user and provide continuous support, thereby increasing the success rate of dieting.

[1765] Example 1

[1766] 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."

[1767] Conventional diet plans often have a one-size-fits-all approach, failing to fully address individual users' lifestyles and goals. As a result, it's difficult for users to find the plan that's best for them and maintain their motivation. Furthermore, insufficient progress management, evaluation, and follow-up make it difficult to provide appropriate feedback or alternative plans if users don't reach their goals. In addition, there are technical challenges, such as secure data transmission and the efficiency of plan generation.

[1768] 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.

[1769] In this invention, the server includes a user interface for inputting information about an individual's goal weight, goal body shape, available time, and environment, a database for storing the user information, an algorithm for generating an optimal exercise and meal plan for each individual based on the user information, a communication means for transmitting the generated exercise and meal plan to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating supportive or encouraging messages based on the evaluation means and transmitting them to the user terminal, a report generation means for periodically generating progress reports based on the progress and transmitting them to the user terminal, an alternative plan generation means for generating an alternative exercise and meal plan if the goal is not achieved and transmitting them to the user terminal, a communication security means for securely communicating the information and progress status entered by the user, and a data formatting means for transmitting the generated plan, message, and report in JSON format. This enables the server to provide an optimal diet plan for each individual user, manage the progress, send supportive messages, generate periodic reports, and suggest alternative plans if the goal is not achieved.

[1770] "User interface means" refers to means that provides an interface for an individual to input information regarding the target weight, the target body shape, the amount of time available, and the exercise environment.

[1771] The "database means" is a database system for storing and managing information input by the user.

[1772] "Algorithmic means" refers to computational means for generating a personalized optimal exercise and diet plan based on stored user information.

[1773] "Communication means" refers to the communication protocols and infrastructure for transmitting the generated exercise and meal plan to the user terminal.

[1774] The "evaluation means" is a means for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[1775] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[1776] The "report generating means" is a means for periodically generating a progress report based on the progress and transmitting the report to the user terminal.

[1777] The "alternative plan generating means" is a means for generating an alternative exercise and meal plan when the goal is not achieved, and transmitting the plan to the user terminal.

[1778] "Communication security measures" are security protocols and techniques for securely communicating user-entered information and progress.

[1779] "Data Format Means" means the data format and means for sending and receiving generated plans, messages, and reports in JSON format.

[1780] In order to implement the present invention, the following means and processes must be utilized: The system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative plan generation means, a communication security means, and a data formatting means.

[1781] User Interface Means

[1782] Users use a smartphone app to input information about their personal goal weight, body shape, available time, and exercise environment (home, gym, etc.). The app was developed using Flutter, allowing users to input information intuitively.

[1783] Database Means

[1784] The entered user information is sent from the device to the server, which then stores it in a MySQL database, including the user ID, target weight, target body shape, available time, and exercise environment.

[1785] Algorithmic means

[1786] The server uses a Python-based algorithm to generate personalized exercise and diet plans based on the user's saved information, such as a plan that combines 30 minutes of aerobic exercise and strength training per day to suit the user's goals and lifestyle.

[1787] communication means

[1788] The generated exercise and meal plan is sent to the user's device in JSON format, and this communication is securely performed using the HTTPS protocol.

[1789] Evaluation methods

[1790] Users record their daily exercise and dietary habits in the app, such as the duration of exercise, calories burned, and the types and calories of food they ingest. This information is then sent from the device to the server, where it is stored in a database and progress is evaluated using an evaluation algorithm implemented in Python.

[1791] Message Generation Method

[1792] The server generates encouraging and supportive messages based on the progress assessment, using NLP techniques and generative AI models (e.g., GPT-3). Generated messages include "You did a great job today!" and "Today may have been difficult, but I'm sure you can do it tomorrow!"

[1793] Report Generation Method

[1794] The server periodically collects the user's progress data and generates a PDF report containing information such as progress, total exercise time, and calorie intake. The report is then sent to the user's device.

[1795] Alternative plan generation methods

[1796] If the user does not reach their goal, the server analyzes the progress data and offers a new approach, for example, generating a new plan with modified exercise content. This plan is also generated in JSON format and sent to the user's device.

[1797] Communications Security Measures

[1798] The HTTPS protocol is used to securely transmit user input information and progress, ensuring data safety and privacy.

[1799] Data Formatting Method

[1800] It is a means of sending and receiving generated exercise and meal plans, messages, and reports in JSON format. Using the JSON format structured data makes it easy to exchange various information.

[1801] Specific examples

[1802] For example, user "C" inputs a goal weight of 60 kg, 40 minutes of exercise per day, and training at home. The device sends the following data to the server: {"Goal weight": "60 kg", "Exercise time": "40 minutes per day", "Environment": "Home"}. The server saves this data and uses an algorithm to generate a plan of "40 minutes of jogging and sit-ups per day" and sends it to the device.

[1803] Example of an input prompt for a generative AI model:

[1804] Generate an optimal diet plan based on user-specified information. Use the following information:

[1805] Target weight: 60kg

[1806] Available time: 40 minutes per day

[1807] Exercise environment: Home

[1808] Please suggest a plan that combines jogging and abdominal exercises.

[1809] In this way, the present invention functions as a system that provides high-level support for users to succeed in dieting.

[1810] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1811] Program processing flow

[1812] Step 1:

[1813] The user opens the app and inputs their target weight, body shape, available time, and exercise environment. The input information is retrieved from the smartphone app's UI.

[1814] input:

[1815] Target weight

[1816] Target body shape

[1817] Time available

[1818] exercise environment

[1819] output:

[1820] User information in JSON format

[1821] Specific behavior:

[1822] User "A" inputs his / her goal weight of 60kg, his / her goal body shape, 40 minutes of exercise per day, and home workouts into the app. The app structures this information in JSON format and generates the following JSON data, for example:

[1823] json

[1824] {

[1825] "Goal Weight": "60kg",

[1826] "Target Body Type": "Slim",

[1827] "Time available": "40 minutes a day",

[1828] "Exercise environment": "Home"

[1829] }

[1830] Step 2:

[1831] The device sends the entered information to the server. This communication is carried out using the HTTPS protocol.

[1832] input:

[1833] User information in JSON format

[1834] output:

[1835] User information sent to the server

[1836] Specific behavior:

[1837] The terminal sends the aforementioned JSON data to the server using the HTTPS protocol. The data received on the server side is

[1838] json

[1839] {

[1840] "Goal Weight": "60kg",

[1841] "Target Body Type": "Slim",

[1842] "Time available": "40 minutes a day",

[1843] "Exercise environment": "Home"

[1844] }

[1845] Step 3:

[1846] The server stores the received information in a database.

[1847] input:

[1848] User information sent to the server

[1849] output:

[1850] User information stored in a database

[1851] Specific behavior:

[1852] The server parses the received JSON data and stores it in a MySQL database. For example, it executes the following SQL statement to store the data:

[1853] sql

[1854] INSERT INTO users (user_id, goal_weight, goal_shape, exercise_time, environment)

[1855] VALUES ("A's ID", "60kg", "Slim", "40 minutes a day", "Home");

[1856] Step 4:

[1857] The server uses an algorithm to generate an optimal diet menu based on the stored user information. This algorithm is implemented in Python.

[1858] input:

[1859] User information stored in a database

[1860] output:

[1861] Diet menu in JSON format

[1862] Specific behavior:

[1863] The server retrieves user information from the MySQL database and uses an algorithm to generate an optimal diet menu, such as "40 minutes of jogging and sit-ups a day." The generated menu is the following JSON data:

[1864] json

[1865] {

[1866] "exercise": "jogging and sit-ups",

[1867] "duration": "40 minutes a day",

[1868] "detailed_plan": ["20 minutes of jogging", "20 minutes of sit-ups"]

[1869] }

[1870] Step 5:

[1871] The server sends the generated diet menu to the terminal.

[1872] input:

[1873] Diet menu in JSON format

[1874] output:

[1875] Diet menu sent to the user's device

[1876] Specific behavior:

[1877] The server sends the JSON data to the user's device using the HTTPS protocol. The generated menu is displayed on the user's device.

[1878] Step 6:

[1879] The user uses the app to record their daily exercise and dietary habits, for example, by entering the duration of exercise, calories burned, and the types and calories of food consumed.

[1880] input:

[1881] Daily exercise and dietary habits

[1882] output:

[1883] Execution status data in JSON format

[1884] Specific behavior:

[1885] User "A" jogs for 20 minutes and does sit-ups for 20 minutes, and records this information in the app. The app generates the following JSON data:

[1886] json

[1887] {

[1888] "jogging": "20 minutes",

[1889] "Sit-ups": "20 minutes"

[1890] }

[1891] Step 7:

[1892] The terminal transmits the execution status data to the server.

[1893] input:

[1894] Execution status data in JSON format

[1895] output:

[1896] Execution status data sent to the server

[1897] Specific behavior:

[1898] The terminal sends the above JSON data to the server. The data received by the server is

[1899] json

[1900] {

[1901] "jogging": "20 minutes",

[1902] "Sit-ups": "20 minutes"

[1903] }

[1904] Step 8:

[1905] The server receives execution status data, stores it in a database, and evaluates the progress. This evaluation is implemented in Python.

[1906] input:

[1907] Execution status data sent to the server

[1908] output:

[1909] Progress evaluation results

[1910] Specific behavior:

[1911] The server stores the received data in a MySQL database and runs a Python script to evaluate progress, generating results such as "Today's achievement rate is 80%."

[1912] Step 9:

[1913] The server generates supportive and encouraging messages based on the evaluation results, using a generative AI model.

[1914] input:

[1915] Progress evaluation results

[1916] output:

[1917] Messages of support or encouragement

[1918] Specific behavior:

[1919] Based on the evaluation results, the server uses a generative AI model to generate messages such as "You worked hard today!" or "You can do better tomorrow!"

[1920] Step 10:

[1921] The server generates a message and sends it to the user's terminal.

[1922] input:

[1923] Messages of support or encouragement

[1924] output:

[1925] Message sent to user device

[1926] Specific behavior:

[1927] The server sends the generated message to the user's device using the HTTPS protocol, and user "A" receives the message in the app.

[1928] Step 11:

[1929] The server periodically aggregates user progress data and generates reports, which are generated using Python and ReportLab.

[1930] input:

[1931] User progress data

[1932] output:

[1933] Progress report in PDF format

[1934] Specific behavior:

[1935] The server will compile your progress data weekly and generate a PDF report containing the following:

[1936] Achievement level: 80%

[1937] Total exercise time: 280 minutes

[1938] Calorie intake trend: Stable

[1939] Step 12:

[1940] The server sends the generated report to the user's terminal.

[1941] input:

[1942] Progress report in PDF format

[1943] output:

[1944] Reports sent to user devices

[1945] Specific behavior:

[1946] The server sends the report in PDF format to the user's device, and user "A" checks the report in the app.

[1947] Step 13:

[1948] The server generates alternative plans as needed and sends them to the user's device, also in JSON format.

[1949] input:

[1950] User history and ratings

[1951] output:

[1952] New exercise and meal plans in JSON format

[1953] Specific behavior:

[1954] If user "A" does not reach his / her goal, the server analyzes past records, generates a new plan such as "20 minutes of brisk walking and plank exercises per day," and sends it to the user's terminal.

[1955] In this way, the system of the present invention uses various means to provide high support for the user's successful dieting.

[1956] (Application example 1)

[1957] 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."

[1958] Conventional diet support systems lack real-time feedback to help users train efficiently toward their set goals. Also, because it is difficult to maintain accurate training form, there is a high risk of injury due to improper form. Furthermore, users often lose motivation and have difficulty achieving their goals because they rely solely on self-evaluation to manage their progress.

[1959] 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.

[1960] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, an interface means for displaying the generated diet menu through smart glasses and providing real-time training assistance, and a motion sensor means for detecting movements during training and displaying instructions for maintaining correct form. This allows the user to receive real-time feedback, train safely with proper form, and effectively diet while maintaining motivation.

[1961] The "user interface means" is an interface for inputting information regarding an individual's target weight, target body shape, available time, and environment.

[1962] The "database means" is a storage system for storing the user information.

[1963] The "algorithm means" is a calculation method for generating an optimal diet menu for each individual based on the user information.

[1964] The "communication means" is a communication device for transmitting the generated diet menu to the user terminal.

[1965] The "evaluation means" is a method for receiving daily exercise and diet records and evaluating the user's progress based on said records.

[1966] The "message generating means" is a device for generating a supportive or encouraging message based on the evaluation means and transmitting the message to the user terminal.

[1967] The "report generating means" is a device for generating a progress report periodically based on the progress and transmitting the report to the user terminal.

[1968] The "alternative menu generating means" is a device for generating an alternative diet menu when the goal is not achieved and transmitting it to the user terminal.

[1969] The "interface means" is an interface for displaying the generated diet menu through smart glasses and providing real-time training assistance.

[1970] The "motion sensor means" is a device that detects movements during training and displays instructions to help maintain correct form.

[1971] To practice this invention, it is first necessary to understand the major elements that make up the system: the system includes a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, an interface means, and a motion sensor means.

[1972] User Interface Means

[1973] Through the smart glasses, users input information about their target weight, target body shape, available time, and exercise environment (home, gym, etc.). This information is input via an interface displayed on the smart glasses' display.

[1974] Database Means

[1975] The entered user information is sent to the server and stored in a database, which includes information such as the user ID, target weight, target body shape, available time, and exercise environment.

[1976] Algorithmic means

[1977] The server is equipped with an algorithm that generates an optimal diet menu based on the user information stored in the database. This algorithm uses TensorFlow, for example, to generate an individually customized diet plan.

[1978] communication means

[1979] The generated diet menu is sent from the server to the smart glasses, where the user can review and follow it.

[1980] Evaluation methods

[1981] Users enter their daily exercise and diet records through the smart glasses. These records are then sent back to the server, where progress is assessed using an assessment tool. The assessment results are quantified to show the degree of achievement and continuity.

[1982] Message Generation Method

[1983] Based on the evaluation results, the server generates a message of encouragement or encouragement and sends it to the smart glasses, thereby maintaining the user's motivation.

[1984] Report Generation Method

[1985] The server periodically aggregates the user's progress data and generates progress reports that are sent to the user so that they can view their progress.

[1986] Alternative Menu Generation Methods

[1987] If the user does not reach their goal, the server will take into account past records and evaluations and generate a new diet menu, which will also be sent to the smart glasses.

[1988] Interface Means

[1989] The smart glasses visually display the generated diet menu and provide real-time assistance during training.

[1990] Motion Sensor Means

[1991] The smart glasses' built-in motion sensors detect movements during training and provide real-time guidance to help maintain proper form.

[1992] Specific examples

[1993] For example, user "A" sets a target weight of 70 kg, 30 minutes of training time per day, and a gym as the exercise environment. A uses smart glasses to input this information. The server receives A's information, generates an optimal diet plan, and sends it to the smart glasses. A trains according to the menu displayed on the smart glasses. During training, a motion sensor checks the form and displays correction instructions as needed. A also records their daily training and meals, which are sent to the server. The server evaluates the data and sends encouraging messages such as "You did a great job today!"

[1994] Using a generative AI model, the following prompt is generated:

[1995] "User name: A

[1996] Target weight: 70kg

[1997] Time available: 30 minutes a day

[1998] Exercise environment: Gym

[1999] This allows users to receive real-time feedback, train safely and effectively, and stay motivated to achieve their goals.

[2000] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2001] Step 1:

[2002] The user inputs information about their target weight, body shape, available time, and exercise environment through the smart glasses interface. The input information is temporarily stored inside the smart glasses and prepared for transmission to the server.

[2003] Input: Goal and environment information input by the user through smart glasses

[2004] Output: Temporarily saved user information

[2005] Step 2:

[2006] The smart glasses send the entered user information to the server, which receives the information and stores it in a database.

[2007] Input: User information sent from smart glasses

[2008] Output: User information stored in the database

[2009] Step 3:

[2010] The server passes the user information stored in the database to an algorithm that generates the optimal diet menu based on the user's lifestyle and goals. This is done using machine learning models such as TensorFlow.

[2011] Input: User information stored in the database

[2012] Output: Generated diet menu

[2013] Step 4:

[2014] The generated diet menu is sent from the server to the smart glasses, which then display it to the user, providing a visual of the training content.

[2015] Input: Diet menu sent from the server

[2016] Output: Diet menu displayed on smart glasses

[2017] Step 5:

[2018] The user performs training according to the display on the smart glasses. The smart glasses' built-in motion sensors detect training movements and provide guidance on maintaining correct form. Incorrect form is pointed out in real time and correction instructions are displayed.

[2019] Input: User training behavior

[2020] Output: Data detected by the motion sensor, correction instructions

[2021] Step 6:

[2022] Users enter their daily training and diet records and send them via smart glasses to a server, which then receives and evaluates their progress data.

[2023] Input: User-entered training and meal logs

[2024] Output: Progress data stored on the server

[2025] Step 7:

[2026] The server analyzes the progress data based on the evaluation method, quantifies the achievement level and continuity, and generates messages of encouragement and support, which are sent to the smart glasses.

[2027] Input: Progress data

[2028] Output: Evaluation results, generated cheering message

[2029] Step 8:

[2030] The server periodically generates and sends progress reports for the user to the smart glasses, allowing the user to view their progress.

[2031] Input: Past progress data

[2032] Output: Generated progress report

[2033] Step 9:

[2034] If the goal is not achieved, the server uses past records and evaluation data to generate an alternative diet menu and transmits it to the smart glasses, where the user can then implement the new menu.

[2035] Input: Historical records and evaluation data

[2036] Output: Alternative diet menu

[2037] The above is a specific process flow for implementing this invention. At each step, data is exchanged between the smart glasses and the server, and training and feedback are effectively carried out to help the user achieve their goals.

[2038] 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.

[2039] To implement the present invention, it is necessary to consider a configuration that combines a conventional system with an emotion engine means. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[2040] User Interface Means

[2041] Users use a smartphone app to input information about their target weight, body shape, available time, and exercise environment, which provides an intuitive interface to facilitate detailed input of user information.

[2042] Database Means

[2043] The input information is sent from the device to the server, which then stores it in a database, including the user ID, target weight, target body shape, available time, and exercise environment.

[2044] Algorithmic means

[2045] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database, which is customized to the user's lifestyle and goals.

[2046] communication means

[2047] The generated diet menu is sent from the server to the user's terminal, and the user can follow the displayed menu to manage their exercise and diet.

[2048] Evaluation methods

[2049] Users record their daily exercise and dietary habits in the app, and the device sends the data to the server. The server stores the data in a database and evaluates the progress using an evaluation tool. The evaluation is a numerical representation of the user's progress toward their goals.

[2050] Message Generation Method

[2051] The server generates encouraging or supportive messages based on the evaluation results, providing the necessary feedback to keep the user motivated.

[2052] Report Generation Method

[2053] The server periodically generates a progress report and sends it to the user's device, which includes information such as progress, total exercise time, and calorie intake.

[2054] Alternative Menu Generation Methods

[2055] If the user does not reach the goal, the server runs an algorithm to generate a new approach and sends an alternative menu to the user's terminal.

[2056] Emotion Engine Means

[2057] The emotion engine recognizes the user's emotional state based on the user's input data. This emotion engine analyzes the user's recorded data and information acquired from the biometric information sensor to determine the user's emotional state. For example, it can analyze the level of stress or satisfaction.

[2058] Specific examples

[2059] User "D" starts the app and inputs information about his / her target weight, target body shape, available time, and exercise environment (home). The input information is sent from the device to the server and stored in a database. The server uses this information to generate an optimal diet menu for D and sends it to D's device. For example, it generates a plan that combines 30 minutes of jogging and abdominal exercises per day.

[2060] Person D records his / her daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates his / her progress and sends him / her messages of encouragement and support. Furthermore, the server recognizes Person D's emotional state using an emotion engine means and sends him / her messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax," further increasing his / her motivation.

[2061] If D does not reach his goal, the server calculates a new approach and generates an alternative diet menu to present to D. This allows D to continue his diet with a new approach.

[2062] Through this series of processes, the system of the present invention also takes into account the user's emotional state and provides individually tailored feedback and support, further increasing the success rate of dieting.

[2063] The processing flow will be explained below.

[2064] Step 1:

[2065] The user starts the smartphone app and inputs information about the target weight, target body shape, available time, and exercise environment (home, gym, etc.) through a user interface.

[2066] Step 2:

[2067] The device converts the input information into JSON format and sends it to the server. The transmitted information includes the user ID, target weight, target body shape, available time, and environmental data.

[2068] Step 3:

[2069] The server validates the received user information and stores it in a database, including a unique ID for each user, as well as target weight, body shape, available time, and exercise environment.

[2070] Step 4:

[2071] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database. This menu is customized by combining elements such as aerobic exercise, strength training, and dietary management.

[2072] Step 5:

[2073] The generated diet menu is sent from the server to the device in JSON format, and the user's device displays an exercise and meal plan based on their daily schedule.

[2074] Step 6:

[2075] Users record their daily exercise and dietary habits in the app, for example by entering the duration of exercise and the calories they consume. The device then sends this data in JSON format to the server.

[2076] Step 7:

[2077] The server stores the received daily record data in a database and evaluates the progress using an evaluation tool, including the progress, achievement rate, and continuation rate of the user toward their goal.

[2078] Step 8:

[2079] Based on the progress evaluation, the server generates messages of encouragement and support to keep the user motivated, such as "You did a great job today!" or "You'll do better tomorrow!"

[2080] Step 9:

[2081] The emotion engine means analyzes the user's input data and the data from the biometric sensor to recognize the user's emotional state, for example, to identify when the user is feeling stressed or has low motivation.

[2082] Step 10:

[2083] The server generates a customized message according to the user's emotional state obtained from the emotion engine means, for example, a message such as "You seem to be feeling a bit stressed today. Take a deep breath and relax."

[2084] Step 11:

[2085] The server generates periodic progress reports and sends them to the user's device. These reports include the level of achievement, the total exercise time, and the trend of calorie intake, allowing the user to check their own progress.

[2086] Step 12:

[2087] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu, which may include changing the exercise routine or revising the meal plan. The generated alternative menu is sent to the device, allowing the user to try a new approach.

[2088] Through this series of steps, the system of the present invention provides a diet plan tailored to the user and provides continuous and personalized support while taking into account their emotional state, thereby increasing the success rate of dieting.

[2089] Example 2

[2090] 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."

[2091] Conventional diet support systems only provide feedback based on the user's physical information and activity data. However, they lack support tailored to the user's motivation and psychological state, resulting in low rates of continuity and success in diet plans. In addition, because they do not take the user's emotional state into account, stress and frustration tend to accumulate, making it difficult to generate optimal diet menus. The objective of this invention is to solve this problem.

[2092] 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.

[2093] In this invention, the server includes input means for inputting information regarding an individual's target weight, target body shape, available time, and environment, storage means for storing the user information, generation means for generating an individually optimized menu based on the user information, transmission means for transmitting the generated menu to the user device, evaluation means for receiving a record of daily progress and evaluating progress based on the record, generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user device, reporting means for periodically generating a progress report based on the progress and transmitting it to the user device, alternative generation means for generating an alternative menu if the target is not achieved and transmitting it to the user device, and recognition means for recognizing the user's emotional state from the input data and biosensor information and providing feedback. This makes it possible to provide individually optimized feedback and support while taking the user's emotional state into consideration, thereby supporting the continuation and success of the diet plan.

[2094] The "input means" is an interface for the user to input information regarding the individual's target weight, target body shape, available time, and environment.

[2095] The "storage means" refers to a function for storing the user information in a database or the like.

[2096] The "generation means" is a function that includes algorithms and processes that create an optimal menu for each user based on the stored user information.

[2097] The "transmission means" refers to a function for transmitting the generated menu or message to the user device.

[2098] The "evaluation means" is a function for receiving records of daily implementation status and evaluating the user's progress based on those records.

[2099] The "generation means" refers to a function for creating cheering messages and the like based on the evaluation means and other data.

[2100] The "reporting means" is a function for periodically generating progress reports based on the progress and transmitting them to the user device.

[2101] The "alternative generation means" refers to a function for generating a new menu and transmitting it to the user device if the target is not achieved.

[2102] The "recognition means" is a function that analyzes the user's emotional state from input data and biosensor information and provides feedback.

[2103] The present invention provides a diet support system that meets the individual needs of users. Below, each element for implementing the present invention and its operation will be described in detail.

[2104] User Interface Means

[2105] Users use a smartphone app to enter information about their target weight, body shape, available time, and exercise environment. The app provides an intuitive interface and is designed to allow users to easily enter information using sliders and checkboxes, allowing users to register their information quickly and accurately.

[2106] Database Means

[2107] The entered information is sent from the terminal to a server, which stores the received information in a database and manages information such as the user's ID, target weight, target body shape, available time, and exercise environment. This database uses a modern database management system (DBMS) to provide fast and reliable data access.

[2108] Algorithmic means

[2109] The server generates an optimal diet menu based on the user's information stored in the database. The algorithm creates a customized menu based on the user's lifestyle and goals. For example, it takes into account the user's individual energy expenditure and preferred food types.

[2110] communication means

[2111] The generated diet menu is sent from the server to the user's device, which then displays the menu to the user as a push notification or in-app message. This allows the user to always check the latest menu information and manage their exercise and diet accordingly.

[2112] Evaluation methods

[2113] Users record their daily exercise and dietary habits in the app. This data is sent from the device to a server, which stores the information in a database. The server evaluates the progress and quantifies how close the user is to achieving their goals. The evaluation results are presented to the user in the form of graphs and statistics.

[2114] Message Generation Method

[2115] The server generates messages of encouragement or support based on the evaluation results. These messages are important as feedback to maintain the user's motivation. The generated messages are sent to the user's device via push notification.

[2116] Report Generation Method

[2117] The server periodically generates progress reports and sends them to the user's device. The reports contain detailed information such as the level of achievement, cumulative exercise time, and calorie intake, and are designed to allow the user to visually check their progress.

[2118] Alternative Menu Generation Methods

[2119] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu, allowing the user to continue with the new approach.

[2120] Emotion Engine Means

[2121] The emotion engine analyzes the user's input data and information from biometric sensors to determine the user's emotional state. Based on this, it provides feedback aimed at reducing stress and increasing motivation. For example, it sends a message such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[2122] Specific examples

[2123] The user launches the smartphone app and inputs their target weight and exercise environment. The input information is sent from the device to the server, which stores it in a database. For example, a plan combining 30 minutes of jogging and sit-ups per day is generated and sent to the user's device.

[2124] Users record their daily exercise and dietary habits in the app, and the data is sent to the server. The server evaluates the progress and generates and sends messages of encouragement and support. It also uses an emotion engine to recognize the user's emotional state and send appropriate messages.

[2125] If the user does not reach the goal, the server calculates a new approach and generates an alternative menu to present to the user. Through this series of processes, the system of the present invention provides individually tailored feedback and support while also taking into account the user's emotional state, increasing the success rate of dieting.

[2126] Example of input prompt for generative AI model

[2127] Here are some examples of prompts to input to a generative AI model:

[2128] "Please provide a detailed explanation of each processing step of a diet support system, including the user interface, database, algorithm, communication, evaluation, message generation, report generation, alternative menu generation, and emotion engine means. The subject should be either the server, terminal, or user, and please also include specific operations in the explanation."

[2129] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2130] Step 1: Enter your user information

[2131] Detailed description: The user launches the smartphone app and inputs information about their target weight, target body shape, available time, and exercise environment.

[2132] Input and Output: Input includes data about the user's goal weight, goal body shape, amount of time available to exercise, and exercise environment. The output is a dataset of this information.

[2133] What it does: The user enters information using sliders and checkboxes within the app. Each time the information is entered, a dataset is generated.

[2134] Step 2: Send and save information

[2135] Specific explanation: The terminal sends the input information to the server, and the server stores the received information in a database.

[2136] Input and Output: Input is the data entered by the user into the terminal, and output is the data stored in the server's database.

[2137] Specific operation: The device sends data to the server over the network, and the server executes an SQL query to store the received data in a database.

[2138] Step 3: Create a diet menu

[2139] Specific explanation: The server generates an optimal diet menu based on the user information stored in the database.

[2140] Input and Output: The input is the user information in the database, and the output is the generated diet menu.

[2141] Specific operation: The server pulls user information from a database, runs an algorithm based on that information, and generates a customized diet menu.

[2142] Step 4: Submit the menu

[2143] Specific explanation: The server sends the generated diet menu to the user's terminal.

[2144] Input and Output: The input is the generated diet menu, and the output is the menu sent to the user's terminal.

[2145] Specific operation: The server pushes the generated diet menu to the user's device, which receives the notification and displays it within the app.

[2146] Step 5: Record the implementation status

[2147] Specifically, users record their daily exercise and dietary habits in the app, and the device sends the data to the server.

[2148] Input and Output: The input is the exercise and diet data recorded by the user, and the output is the performance status data sent to the server.

[2149] Specific operation: Users record their daily exercise time and calorie intake within the app, and when they press the save button, the data is sent to the server.

[2150] Step 6: Evaluate your progress

[2151] Specifically, the server stores the received data in a database and evaluates the progress, which is a numerical representation of the user's progress toward their goal.

[2152] Inputs and Outputs: Inputs are implementation status data and outputs are progress assessment results.

[2153] Specific operation: The server analyzes the implementation status data in the database and calculates the progress using an algorithm.

[2154] Step 7: Generate a message

[2155] Specifically, the server generates messages of encouragement and support based on the progress and sends them to the user's device.

[2156] Input and Output: The input is the progress evaluation result and the output is the generated message.

[2157] Specific operation: The server generates an appropriate message based on the evaluation results and sends it to the user's device as a push notification or in-app message.

[2158] Step 8: Generate a progress report

[2159] Specifically, the server periodically generates progress reports and sends them to the user's terminal.

[2160] Inputs and Outputs: Inputs are implementation data and evaluation results, and outputs are progress reports.

[2161] Specific operation: The server compiles user data at regular intervals, generates a report visually represented as graphs and numbers, and sends it to the user's device.

[2162] Step 9: Generate Alternate Menus

[2163] Specific Description: If the user does not reach the goal, the server calculates a new approach, generates an alternative diet menu, and sends it to the user's terminal.

[2164] Input and Output: The input is the progress assessment results and past records, and the output is the newly generated substitution menu.

[2165] Specific operation: The server reanalyzes the evaluation results and past data, generates a new exercise and meal plan, and presents it to the user.

[2166] Step 10: Emotional state analysis and feedback

[2167] Specific Description: The server uses an emotion engine means to recognize the user's emotional state based on input data and biosensor information, and provides feedback.

[2168] Input and output: The input is the user's recorded data and biometric information, and the output is the emotion recognition results and feedback messages based on them.

[2169] Specific operation: The server analyzes the user's input data and sensor information, runs an algorithm to recognize the emotional state, and generates appropriate feedback messages and sends them to the user's device.

[2170] (Application example 2)

[2171] 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."

[2172] Conventional diet support systems provide optimal menus based on information such as the user's target weight and exercise time, but lack feedback that takes the user's emotional state into consideration. This can lead to problems such as a decrease in user motivation and difficulty in continuing the diet. Therefore, the present invention aims to provide a system that analyzes the user's emotional state and provides optimal meal menus and encouraging messages based on that state.

[2173] 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.

[2174] In this invention, the server includes a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment, a database means for storing the user information, an algorithm means for generating an optimal diet menu for each individual based on the user information, a communication means for transmitting the generated diet menu to a user terminal, an evaluation means for receiving daily exercise and meal records and evaluating the user's progress based on the records, a message generation means for generating a supportive or encouraging message based on the evaluation means and transmitting it to the user terminal, a report generation means for periodically generating a progress report based on the progress and transmitting it to the user terminal, an alternative menu generation means for generating an alternative diet menu if the target is not achieved and transmitting it to the user terminal, and a means for analyzing the user's emotional state using an emotion engine and providing a meal menu and feedback messages based on that state, thereby enabling optimal diet support that takes the user's emotional state into consideration.

[2175] A "personal weight goal" is a body weight goal that a user wishes to achieve.

[2176] The "target body shape" is the ideal body shape or physical condition that the user aims for.

[2177] "Available time" refers to the amount of time a user can devote to dieting and exercise.

[2178] The "environment" refers to the specific location or situation where the user diets or exercises.

[2179] A "user interface means" is a means by which a user inputs information into a system.

[2180] "Database Means" means means for storing and managing user information and records.

[2181] The "algorithm means" is a means for calculating the optimal diet menu based on user information.

[2182] "Communication means" refers to a means for transmitting the generated diet menu and feedback to the user terminal.

[2183] The "evaluation means" is a means for evaluating the progress of the user based on the user's daily exercise and diet records.

[2184] The "message generating means" is a means for generating a supportive or encouraging message based on the evaluation.

[2185] The "report generation means" is a means for creating periodic progress reports based on the user's progress data.

[2186] The "substitute menu generating means" is a means for generating a new diet menu when the user is unable to achieve their goal.

[2187] An "emotion engine" is a means for analyzing a user's emotional state and providing feedback based on that state.

[2188] A "meal menu" is a specific meal plan proposed to suit the user's diet goals.

[2189] "Feedback messages" are encouraging messages or advice provided based on the user's progress or emotional state.

[2190] 1. System Overview

[2191] The present invention is a system that provides an optimal diet menu based on information on an individual's target weight, target body shape, available time, and environment, and provides feedback while taking into account the user's emotional state. The system includes the following main elements: a user interface means, a database means, an algorithm means, a communication means, an evaluation means, a message generation means, a report generation means, an alternative menu generation means, and an emotion engine means.

[2192] 2. Hardware and Software Used

[2193] Hardware: Smartphones, servers (physical or cloud-based)

[2194] software:

[2195] Smartphone application (iOS, Android)

[2196] Application Server:Flask (Python)

[2197] Database: PostgreSQL

[2198] Emotion Engine: Google Cloud Natural Language API

[2199] Communication: HTTP / HTTPS (requests library)

[2200] 3. User Interface Methods

[2201] Users input information about their target weight, body shape, available time, and exercise environment through a smartphone application. This information is designed to be input intuitively. The data entered by the user is sent to a server and stored in a database.

[2202] 4. Algorithmic Means

[2203] The server generates an optimal diet menu based on the user information stored in the database. The algorithm customizes the diet and exercise menu based on the user's lifestyle and goals. The generated menu is then sent to the user's smartphone via communication means.

[2204] 5. Evaluation and Emotion Engine Methods

[2205] The user records daily exercise and diet data in the smartphone application. This data is sent to the server and stored in a database. The evaluation means analyzes the user's progress, and the emotion engine means analyzes the user's emotional state.

[2206] 6. Message Generation and Report Generation Methods

[2207] The server generates supportive and encouraging messages based on the evaluation results and the user's emotional state and sends them to the user's device. It also periodically generates progress reports and sends them to the user's device. For example, if the user is feeling stressed, the server generates a message saying, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[2208] 7. Alternative Menu Generation Methods

[2209] If the user does not achieve the goal, the server generates an alternative diet menu and sends it to the user's terminal. This alternative menu is generated taking into account the user's past records and evaluation results.

[2210] 8. Examples of concrete examples and prompts

[2211] For example, when user "A" uses the app to input his / her target weight and exercise environment, the system suggests an optimal meal menu and exercise plan. A records his / her daily progress and sends the data to the server. The emotion engine analyzes A's emotional state and sends messages such as, "You seem to be feeling a little stressed today. Take a deep breath and relax."

[2212] Example prompt sentence:

[2213] "Emodish is a personalized food delivery service based on the user's diet goals and emotional state. It proposes optimal meal plans based on the user's input of target weight and exercise time, and uses an emotion engine to analyze the user's emotional state and provide appropriate feedback."

[2214] In this way, the system of the present invention can take into account the user's emotional state and provide individually tailored feedback and support, further increasing the success rate of dieting.

[2215] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2216] Step 1:

[2217] Users use a smartphone application to input information about their target weight, body shape, available time, and exercise environment.

[2218] Input: Target weight, target body shape, available time, exercise environment

[2219] Output: User information entered (JSON format)

[2220] Specific behavior: The user enters the required information into the input form and presses the "Submit" button.

[2221] Step 2:

[2222] The entered information is sent from the terminal to the server, and the server stores the received information in a database.

[2223] Input: User information in JSON format

[2224] Output: User information stored in the database

[2225] Specific behavior: The server receives the HTTP request and writes the information to the database.

[2226] Step 3:

[2227] The server uses an algorithm to generate an optimal diet menu based on the user information stored in the database.

[2228] Input: User information stored in the database

[2229] Output: Optimal diet menu

[2230] What it does: The server runs an algorithm to calculate a diet menu based on the user's lifestyle and goals.

[2231] Step 4:

[2232] The generated diet menu is sent from the server to the user's terminal.

[2233] Enter: Optimal Diet Menu

[2234] Output: Diet menu displayed on the user's device

[2235] Specific operation: The server sends a diet menu as an HTTP response, and the user's device receives and displays it.

[2236] Step 5:

[2237] Users record their daily exercise and dietary habits in the app, and the data is sent to a server.

[2238] Input: Daily exercise and dietary habits

[2239] Output: Recorded data stored on the server

[2240] Specific behavior: The user uses the app's recording function and the data they enter is sent to the server.

[2241] Step 6:

[2242] The server stores this in a database and evaluates the progress using an evaluation means.

[2243] Input: Saved recording data

[2244] Output: Evaluation results (progress)

[2245] What happens: The server analyzes the recorded data and calculates the progress towards the goal.

[2246] Step 7:

[2247] The server generates a message of encouragement or support based on the evaluation result and transmits it to the user's terminal.

[2248] Input: Evaluation result

[2249] Output: A message of encouragement or support

[2250] Specific operation: The server uses the generative AI model to create a message and send it to the user's device.

[2251] Step 8:

[2252] The server periodically generates progress reports and sends them to the user's terminal.

[2253] Input: Evaluation results and recorded data

[2254] Output: Progress report

[2255] Specific operation: The server creates a progress report and periodically sends it to the user's terminal.

[2256] Step 9:

[2257] An emotion engine is used to recognize the user's emotional state and provide feedback messages based on that state.

[2258] Input: User recorded data and information from biometric sensors

[2259] Output: Feedback message based on emotion

[2260] Specific operation: The server uses the emotion engine to analyze the emotional state and generates and sends a message accordingly.

[2261] Step 10:

[2262] If the user does not reach the goal, the server calculates a new approach and generates an alternative diet menu to present to the user.

[2263] Input: Past records and evaluation results

[2264] Output: New diet menu

[2265] Specific operation: The server re-runs the algorithm and sends the alternative diet menu to the user's device.

[2266] 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.

[2267] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Intern...

Claims

1. a user interface means for inputting information regarding the individual's target weight, target body shape, available time, and environment; database means for storing said user information; an algorithm means for generating an optimal diet menu for each user based on the user information; A communication means for transmitting the generated diet menu to a user terminal; evaluation means for receiving daily exercise and diet records and evaluating the user's progress based on said records; a message generating means for generating a support message or an encouragement message based on the evaluation means and transmitting the support message or an encouragement message to a user terminal; report generation means for periodically generating a progress report based on the progress and transmitting the report to a user terminal; an alternative menu generating means for generating an alternative diet menu when the goal is not achieved and transmitting the menu to the user terminal; A system including:

2. 2. The system according to claim 1, further comprising conversion means for transmitting input information to a server in said user interface means.

3. 2. The system according to claim 1, wherein said alternative menu generating means includes algorithm means for generating a new diet menu in consideration of the user's past records and evaluations.

Images